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Kenakin’s latest lecture delivers a wake-up call for pharmacologists interpreting allosteric binding data. If you’re applying orthosteric logic to modulator-driven systems, you’re likely misreading your assays—and potentially misclassifying your leads. This lesson helps you reframe how you interpret allosteric interactions —not as simple ligand displacement, but as transformations in receptor identity . You’ll learn how to recognize these shifts using vivid analogies (like Bruce Wayne vs. Batman ) and master the Hall model  to decode the thermodynamics behind complex binding behavior . If your project involves GPCRs , functional selectivity , or non-traditional ligands , this session is essential. In This Session, You’ll Gain: ✅ A clear explanation of why allosteric modulators don’t displace ligands—they change the protein species itself ✅ Real-world case studies showing binding-function dissociation and residual signal effects ✅ Tools to model binding with cooperativity factors (α, β, γ, σ) using the Hall allosteric cube The Allosteric Shift: When Receptors Become Something New In orthosteric pharmacology, a ligand is either on or off the receptor. More concentration = more competition = displacement. But in allosteric systems , adding a modulator doesn’t push another molecule off—it transforms the receptor  into a different version of itself. This isn’t just semantic. It redefines how we interpret radioligand curves , shifts in signal, and the meaning of “inhibition.” You’re no longer tracking the same protein species—and that changes everything. Kenakin shows how even small cooperativity values (like α = 0.1) cap the shift in signal . No matter how much non-radioactive ligand you add, the binding curve levels off —because the receptor’s affinity state is redefined . Binding vs. Function: Two Different Worlds One of the most common—and dangerous—mistakes in allosteric pharmacology is expecting binding and function to match . Kenakin lays out why this is flawed. Binding assays  report on one set of receptor states. Functional assays  track another. When a PAM increases radioligand binding but suppresses functional response, it’s not broken pharmacology—it’s biology working as designed . This lesson shows how to read these patterns correctly —and how to avoid false conclusions in your lead prioritization. Thermodynamics > Intuition: Why the Hall Cube Matters To untangle complex binding behaviors, you need a model grounded in thermodynamics . Kenakin introduces the Hall model : a cube mapping allosteric and orthosteric interactions, layered with G protein binding. Each face of the cube is governed by a cooperativity constant : α:  Modulator’s effect on radioligand binding σ:  Modulator’s effect on G protein coupling (efficacy) γ:  G protein’s effect on radioligand binding (efficacy of A) β:  Dual cooperativity—how ternary complexes influence each other This framework explains partial signals , paradoxical responses , and the persistence of radiolabel  even in “displaced” systems. The G Protein Bottleneck: Why Stoichiometry Matters In a standout case study, Kenakin shows how G protein availability  determines whether you see “displacement” at all. A strong agonist, fails to reduce binding of a labeled NAM—not because of irreversibility, but because there isn’t enough G protein in the system to form the species that would lower the signal. Switch cell lines. Add G protein. Suddenly, the agonist works . The takeaway:  what looks like pharmacology failure may be a systems problem . This insight could prevent wasted effort and reveal the true nature  of your compound. Allosteric Binding Is a Different Game. Learn the Rules. If you’re still using orthosteric assumptions to interpret allosteric binding data, you're likely missing critical insights—or mislabeling your drug’s profile. This lecture gives you the language, models, and mindset  to interpret these systems correctly and act with confidence  in the lab. Kenakin doesn’t just challenge assumptions. He gives you the tools to replace them . Unlock “Allosteric Binding” Now Only in Terry’s Corner Why Terry’s Corner Drug discovery isn’t slowing down—and neither can you.  Terry’s Corner is built for scientists who want to move faster , think sharper , and make smarter decisions  in early discovery. As a member, you’ll get: Weekly expert-led lectures from Dr. Terry Kenakin An always-growing library of on-demand pharmacology insights The ability to vote on or suggest future topics Access to a community of fellow scientists solving the same problems From hit-to-lead to translational strategy, this is where 40 years of pharmacological insight meets the questions you’re asking right now. Don’t just keep up, get ahead. 🟢 40 years of expertise at your fingertips:   Explore the complete library ➤ ✳️ Want to know what’s inside?   Read the latest articles ➤ Stay sharp between lectures.  Subscribe to The Kenakin Brief today ➤ #AllostericPharmacology #GPCR #BindingVsFunction #ReceptorPharmacology #DrugDiscoveryTools #HallModel #Allostery #PharmacologicalModels #AllostericBinding

GPCRs pose a critical challenge in drug discovery: a vast therapeutic potential with many targets yet to be explored.  35% of FDA-approved drugs target GPCRs, showing their importance in numerous physiological processes. However, over half of non-sensory GPCRs do not have drugs available in the clinic, opening the door to groundbreaking treatments for various diseases.   In order to fast-track these advancements, an improvement in tools for their study must happen. Thus we propose the use of fluorescent probes in GPCR screening assays due to their numerous advantages over traditional techniques like radioligands.   The advantages of Fluorescent Probes in GPCR assays over other methods Fluorescent ligands are made by choosing an adequate pharmacophore with the desired affinity and/or functional activity, that is modified to introduce a linked and then conjugated with a fluorescent ligand. These probes facilitate localization of receptors, tracking of their internalization and are also safer alternatives to radioligand binding assays. They can also further pharmacological and structural studies, as they can be used to determine receptor activation dynamics, ligand binding geometry and receptor interactions.   The traditional binding assays for GPCRs use radioligands, whose limitations, especially safety concerns, low temporal resolution and the need for specialized facilities including disposal, mean their use should be reduced in favor of more accessible and safer alternatives, such as fluorescent ligands. On the other hand, fluorescent ligands have a superior safety and environmental profile. They are easier to handle and store, which also lowers outsourcing.   Fluorescent ligands provide real-time data on receptor activation, ligand binding and downstream signaling using live-imaging modalities. This means fluorescent probes enable a dynamic observation of GPCRs. For example, in Figure 1A, the dual A2B/A3 adenosine receptor fluorescent antagonist (CELT-327) was added to HCT116 cells (colon cancer cell line), detectable fluorescence starting at 1minute after addition. The fluorescence plateaus after approximately 10minutes. It can be appreciated how fast the ligand diffuses and is distributed homogeneously within monolayers, staining both apicobasal and lateral membranes (Figure 1B). Figure 1. Real-time dynamic labeling of A 2B AR. A) Representative confocal images of HCT116 cells pre-stained with CellTracker Green (lower panels) and labeled in real-time with CELT-327 250 nM, added at timepoint 0 (upper panels). Scale bars: 50 μm. B) Orthogonal projections on a selected area of images in A. Scale bar: 20 μm. C) Quantification of CELT-327 average fluorescence intensity over time. The Challenges Fluorescent Probes Face There are several challenges fluorescent ligands face for their use as tools. 1.        Photobleaching . This happens when prolonged exposure to light in the excitation range causes the emission signal to decrease over time. This can lower the quality of long-term imaging studies but can be fixed by using stable fluorescent tags or specialized imaging techniques. The combination of the correct linker and dye can offer better photostability, maintaining signal integrity for longer. 2.        Spectral Overlap.  The cells’ autofluorescence and the background noise from other dyes present in the experiment can interfere with measurements. This can be fixed by using fluorescent dyes that emit at longer wavelengths, where fluorescence from the cell components is minimal, as well as expanding the working range for imaging in vivo . Confocal microscopy is a technique that can be used to mitigate this issue. At Celtarys, we focus on developing fluorescent tools that keep minimal background signal even without washing before cell visualization (Figure 2). Our portfolio also includes all kinds of dyes, such as pharmacophores conjugated to near-infrared fluorophores ( CELT-075 hD2 dopamine receptor fluorescent antagonist and CELT-095 hM1/M2 muscarinic receptor fluorescent antagonist). Our proprietary conjugation technology also facilitates the synthesis of different linker sizes and types, making it easier to find the adequate probe for a certain technique and reduce these issues. Another issue, that is present in all probes but can sometimes be stronger in fluorescent ligands, is non-specific binding. The dyes might have charges or be so hydrophilic/hydrophobic that they bind to intracellular structures. Thus, rational design using efficient synthetic strategies is needed to make these probes as specific as possible. Figure 2. Representative confocal images of co-cultures of HCT116 cells and human primary CAFs. The dashed line represents the frontier between both cell types. CAFs are labeled with CellTracker (Green), and cocultures are labeled with CELT-327 250 nM. Scale bar 100 μm.     Protocols for GPCR assays using Fluorescent Probes The preparation of the cellular system is the most common starting point for employing fluorescent probes in GPCR assays. Cells expressing or over-expressing the receptor of interest are cultured, preserving their physiological characteristics. Cell fragments (such as membranes) can also be used for some assays, reducing the possibility of non-specific binding. Once the cells are ready, the fluorescent ligand is added, and the cells are incubated with it for a short time. For visualization purposes, cells can be co-stained with a green live-cell dye (Calcein) or Hoechst. For fixed cell preparations, DAPI (4′,6-diamidino-2-phenylindole), a DNA-specific fluorescent probe, can be used. After incubation, cells are observed using a confocal microscope. In competition binding assays, another ligand is introduced in the medium to displace the fluorescent ligand, and the decrease in fluorescence as the concentration of the competitor is increased is the one used to obtain an affinity constant. Celtarys’ protocol section includes detailed protocols for diverse applications and fluorescent ligands.   Contact us  if you have any questions about our fluorescent ligands. Our scientific team can guide you choose or design the right fluorescent ligand for your research.   References Barbazán J, Majellaro M, Martínez AL, Brea JM, Sotelo E, Abal M. Identification of A2BAR as a potential target in colorectal cancer using novel fluorescent GPCR ligands. Biomed Pharmacother. 2022 Sep;153:113408. doi: 10.1016/j.biopha.2022.113408. Casadó V, Casadó-Anguera V. What are the current trends in G protein-coupled receptor targeted drug discovery? Expert Opin Drug Discov. 2023 Jul-Dec;18(8):815-820. doi: 10.1080/17460441.2023.2216014. Ciruela F, Jacobson KA, Fernández-Dueñas V. Portraying G protein-coupled receptors with fluorescent ligands. ACS Chem Biol. 2014 Sep 19;9(9):1918-28. doi: 10.1021/cb5004042.  Soave M, Briddon SJ, Hill SJ, Stoddart LA. Fluorescent ligands: Bringing light to emerging GPCR paradigms. Br J Pharmacol. 2020 Mar;177(5):978-991. doi: 10.1111/bph.14953. Sridharan R, Zuber J, Connelly SM, Mathew E, Dumont ME. Fluorescent approaches for understanding interactions of ligands with G protein coupled receptors. Biochim Biophys Acta. 2014 Jan;1838(1 Pt A):15-33. doi: 10.1016/j.bbamem.2013.09.005.

Our CSO, Maria, has recently traveled to the US to attend the ACSMEDI-EFMC Medicinal Chemistry Frontiers 2025 , a conference organized by both the EFMC and the ACSMEDI, in an effort to share the most novel medicinal chemistry advancements in both the US and Europe. This joint effort by both associations is repeated every year, with 2026’s being in Dublin, Ireland. The conference, chaired by Prof. Terry W. Moore, was most definitely a success. The venue was the UIC Student Center East, and Chicago is a great choice for a city, Maria found it very cozy. The conference had just enough attendees – enough for a great variety of scientific content and having the opportunity of meeting and networking with basically most of the participants. Here you can find the full program . Figure 1. UIC Student Center East. There were several sections, among them one specific for GPCRs. Sometimes when you’re in the field you forget the importance GPCRs holds in drug development as a whole, and how each and every finding can contribute towards better care for the patients. Another section was dedicated to Chemistry Tools, highlighting their importance. After all, a good tool makes a good assay, and a good assay improves research capacity. All of the talks were fantastic, but Maria would love to highlight these three: -            First, Prof. Ingo Hartung’s opening. This talk gave a general idea of what goes into designing small molecule drugs, using state-of-the-art examples such as PROTACs. -            Dr. Wendy Young’s talk, during session 3 on day 2, was also incredible. She gave us an overview of the drugs she has participated in developing throughout her career, highlighting her experience in the field as a woman, a topic which is still very relevant today. -            Dr. Katerina Leftheris’ talk, which talked about new and innovative technologies used to overcome peptides limitations as drugs. She has a lot of experience working for bigger businesses which she now shares as an advisor for startups. Several of the drugs shown throughout the conference are starting their clinical trials. Also, there was a great balance between academic and industrial talks. Wednesday was a key day for Maria, as she got to participate in a panel discussion alongside Dr. Katerina Leftheris, Prof. Brian K. Shoichet, Dr. Luc Van Hijfte and Dr. Wendy Young. Sharing the round table discussion with these excellent scientists felt like a dream come true, and Maria enjoyed giving advice to those who are starting their careers in the scientific field. Figure 2. Maria alongside the other panelists during Wednesday's panel discussion. Session 4 on Wednesday was dedicated to GPCRs. The talks given targeted both traditional GPCRs such as the serotoninergic receptor 5HT1A, but also newer targets like GPR88. Session 8 on Thursday was Maria’s turn to give a talk. This Chemistry Tools session was more industry focused than those before, and Maria shared the floor with researchers such as Dr. Amanda Dombrowski from Abbvie, Dr. Charles Yeung from Merck and Dr. Rico Gerup Petersen from Vipergen APS. Finally, during Session 9 Prof. Xiaoyu Zhang showed great insight into new ligands for new E3 ligases for PROTAC development. This was a very enriching experience for Maria, not only did she have a chance to share Celtarys’ technology and innovative probes, but she got to help others as a panelist. She also took the chance to do some sightseeing in Chicago . Now back in Europe, all she can think about is next year’s date, in Dublin, where she is sure she will have an equally amazing experience!

If you’ve read our previous post, you probably know what CELT-335 is and its high affinity for the cannabinoid 1 receptor (CB1R). During that project we tested its validity as a fluorescent probe for Tag-lite® assays, where we used a set of 7 cannabinoid ligands (both natural and synthetic) to validate and optimize the assay. Because Tag-lite® is based on FRET, we have collaborated with BMG Labtech to develop an application note where CELT-335 is used to differentiate binding of THC derivatives to CB1R. Introduction Cannabinoid receptors are GPCRs, and two main types exist, CB1R and CB2R. CB1R are mainly found in the central nervous system (CNS) and the brain. They regulate mood, memory, appetite and motor function. CB2R are located primarily in the immune system and peripheral tissues, where they modulate inflammation and immune response. Cannabinoids have the potential to treat a variety of diseases, including neurological and metabolic conditions. This interest has been driving efforts to understand their pharmacology since the 1980s. It has been proven that when different ligands bind to the receptors the effects are different depending on which signaling pathway is activated, which is called ‘bias signaling’. The bias depends on the agonist’s structure as well as the state of the cannabinoid receptor (whether it’s monomeric or heteomeric). Here, the PHERAstart FSX microplate reader was used to differentiate binding of natural cannabinoids to CB1R based on TR-FRET assays. In this case, Terbium is used as donor and CELT-335 fluorescent ligand is used as acceptor. Figure 1.Combinational optical spectra of terbium (Tb) and CELT-335: The terbium (donor) emission spectrum overlaps with the CELT-335 (acceptor) excitation spectrum. CELT-335 was successfully used in assays to determine the pharmacological properties of Δ9-tetrahydrocannabinol (Δ9-THC), Δ9-tetrahydrocannabinolic acid (Δ9-THCA) and Δ9-tetrahydrocannabivarin (Δ9-THCV) when binding to CB1R. Assay Principle CELT-335 is a fluorescently labelled full agonist, which binds to the orthosteric site of the human CBRs. It bears a hydrophilic fluorophore compatible with the terbium donor in TR-FRET assays. It binds to the receptor, which is labelled with Tb. When this happens the proximity between donor and acceptor is sufficient for a transmission of energy to occur between the Tb and fluorophore, which will emit at 665nm. Figure 2.Assay Principle: TR-FRET assay using CELT-335, a dual (CB1/CB2) fluorescent ligand that serves as a TR-FERT acceptor. Results and Discussion The TR-FRET assay performed in living HEK-293 T cells expressing CB1R using CELT-335 as acceptor provides a sensitive and robust measurement for competition binding experiments. The curves were obtained using 100nM of probe and increasing concentrations of Δ9-THC, Δ9-THCA and Δ9-THCV (0 – 10 μM). Competition was similar for Δ9-THC and Δ9-THCV, but considerably lower for Δ9-THCA. The data obtained is comparable to those reported in radioligand binding assays (Table 1). Figure 3.TR-FRET competition assay between CELT-335 (TR-FRET acceptor) and Δ9-THC, Δ9-THCA and                     Δ9-THCV.Data represent the mean ± SEM (n = 5 in triplicates) Table 1. Comparison of binding affi nities using radioligand binding or TR-FRET assays. Radioligand binding data are from [2,3]. Conclusion CELT-335 is a functional TR-FRET acceptor which can be coupled with Tb as donor. It has shown high affinity for the CB1R, and the binding affinity values obtained for natural cannabinoids and their derivatives are comparable values to those reported in literature [2,3]. These assays probide a reliable way to measure binding affinities for CB1R in live cells and the PHERAstar FSX is the ideal microplate reader for characterizing the GPCR-ligand interactions. If you want to check out the Materials and Methods section as well as the application note, here is the link to our website ! If you are interested in our ligands or technology, feel free to contact me anytime. References 1. Raïch I et al. , Similarities and differences upon binding of naturally occurring Δ9-tetrahydrocannabinolderivatives to cannabinoid CB1 and CB2 receptors, Pharmacological Research (2021) 174: 105970, doi: 10.1016/j.phrs.2021.105970 2. Zagzoog A et al ., In vitro and in vivo pharmacological activity of minor cannabinoids isolated from Cannabis   sativa , Scientifi c Reports (2020) 10(1):20405. doi: 10.1038/s41598-020-77175-y 3. Palomares B et al. , Δ9-Tetrahydrocannabinolic acid alleviates collagen-induced arthritis: Role of PPARγ and CB1 receptors, British Journal of Pharmacology (2020) 177(17): 4034-4054. doi: 10.1111/bph.15155.

1.     Introduction 1.1 The Endocannabinoid System The Endocannabinoid System (ECS) is composed of the Cannabinoid Receptors 1 and 2 (CB1R and CB2R) and the endocannabinoids (endogenous ligands such as 2-arachidonoylglycerol and anandamide) as well as metabolic enzymes. It is involved in several pathophysiological processes such as Parkinson’s disease, depression, addiction, eating disorders and has synergistic effects with anticancer agents.[1–3] These insights highlight the potential in modulating the ECS to fulfill unmet medical needs. New scaffolds modulating the CBRs in both the orthosteric and allosteric sites have been developed, supported by resolved crystal structures of both CBRs.[4–8] A key challenge in CBR modulator development is separating the therapeutic effects from the side effects, especially the psychotropic effects CB1R causes in the Central Nervous System. This can be appreciated when talking about SCRAs (Synthetic Cannabinoid Agonists), as one of the series developed by Pfizer, including CP5594, gave rise to a new class of abused psychoactive substances, thanks to their higher potency in the CB1R. [9,10] 1.2 Novel fluorescent strategies for CBR binding affinity assays Thus, the need for novel, robust and cost-effective methodologies for screening compound libraries targeting the CBRs becomes key for identifying drugs with a clinical profile. The most used probe right now is the radioactive CP-55940, [3H-CP-55940].[11] Figure 1. Chemical structure of [3H-CP-55940]. Selective fluorescent CB1R ligands have been validated for flow cytometry [12], and selective CB2R probes have been validates in TR-FRET[13], as well as receptor visualization in living cells[14], mice[15], and zebrafish[13]. Homogeneous Time-Resolved Fluorescence (HTRF) is a TR-FRET-based assay[16] conducted in homogeneous conditions, using lanthanide (europium, terbium) as donors.[17] Lanthanides provide unique advantages as donors, since they have extended fluorescence duration, enable delayed emission readings, have narrow bands and high stokes shift, which prevent cross-excitation and cross-emission phenomena.[18] Thus, they reduce background noise, improving both the signal-to-noise ratio and the sensitivity of the assays. [18–20] Several strategies can be used to attach donor fluorophores to the target, among them antibodies bearing the donor. GPCRs are not suitable for antibody use due to steric hindrance and reverse binding, thus, other strategies must be applied. Among them, we have chosen the SNAP-tag, a suicide enzyme technology. The SNAP-tag is an engineered mutant of O5-alkylguanine-DNA alkyltransferase (AGT) that reacts specifically with O6-benzylguanine (BG) derivatives. This modification is small enough to not affect GPCR expression or activity.[21–23] The Tag-lite® binding assay combines the HTRF detection method with the SNAP-tag. It has been applied to different GPCR binding assays, such as CXCR4, opioid receptors, CCK1 and CCK2. We have previously used this technology using CELT-335, a dual hCB1/hCB2 fluorescent ligand, which was validated in CB1R as a binding assay probe with three natural CBR ligands. Herein we report the first example of a Tag-lite® binding assay for both CBs using CELT-335, which exhibits a high specific binding (signal-to-noise ratio), and FERT signal, providing a reliable, robust and cost-effective alternative for CB1R and CB2R screening campaigns.[24] 2.     Results 2.1  CELT-335 Binding at CB1 and CB2 Receptors The first step for the development of the assay is to obtain a fluorescent ligand suitable for the Tag-lite® binding assays. In this case, CELT-335 exhibits exc and em at 650nm and 673nm, which are compatible with the lanthanide Terbium. Their binding affinity was assessed through radioligand binding, showing a nanomolar affinity for both CBRs, with it being 6-fold higher for CB2R. Table 1. Comparison of CELT-335 affinity for CB1 and CB2 receptors measured by competition radioligand binding assay (Ki) and saturation Tag-lite® binding assay (Kd).   1  Competition radioligand binding assay.  2  Saturation assay by Tag-lite® binding assay.  3  Displacement of specific [3H]-CP55940 binding in human HEK-CB1 cells expressed as Ki ± SEM in nM (n = 3) or percentage displacement of specific binding at a concentration of 1 μM (n = 2).  4  Displacement of specific [3H]-CP55940 binding in human HEK-CB2 cells expressed as pKi ± SEM in nM (n = 3) or percentage displacement of specific binding at a concentration of 1 μM (n = 2).  5  pKd calculated through saturation of CELT-335 in human HEK-293T cells transiently expressing Tb-labeled SNAP-CB1R.  6  Kd calculated through saturation of CELT-335 in human HEK-293T cells transiently expressing Tb-labeled SNAP-CB2R. In the saturation experiments, specific binding was also checked, employing appropriate competitors (Figure 2). The high affinity of CELT-335 for CB1R was maintained in the Tag-lite® assay (Ki=44.8nM in radioligand assay and Kd= 42nM in Tag-lite®). Figure 2.   Saturation assays using CELT-335. Specific binding is shown, obtained from total binding and unspecific binding ( a ) CB1R expressing adherent HEK-293T cells and unspecific binding measurement (specific binding measured using CP55490 at 10 μM concentration) ( b ) CB2R expressing adherent HEK-293T cells and unspecific binding measurement (specific binding measured using GW405833 at 10 μM concentration). Data represent the mean ± SEM (n = 3 in triplicates). 2.2 CELT-335 HTRF assay validation in hCB1R Expressing adherent Cells. To validate the potential of CELT-335 as a probe, seven reference compounds were selected. Table 2. Comparison of affinity data for CB1 receptor of the set of reference compounds obtained through the radioligand competition binding assay and CB1 competition binding assays with Tag-lite® technology using CELT-335. Values represent the mean ± SEM of triplicate determinations. Reference is not indicated for those compounds whose affinity through the radioligand binding assay was measured experimentally following published protocols.[14] Figure 3. Chemical structures and functional activity of the reference compounds used for CELT-335 validation in Taglite® binding assays. Using these results as a starting point, the Tag-lite® binding assay was developed. In Figure 4 coherent and well-defined sigmoidal concentration/response curves can be found for all seven molecules tested, and their pKi values compared to literature data in Table 2 . Figure 4.   Competition experiments of binding of fluorescent ligand CELT-335 to living HEK-293 T cells expressing the SNAP-CB1R. Tb labelling was performed as described in Materials and Methods. Tag-Lite® competition binding curves were obtained by using 100 nM of CELT-335 and increasing concentrations of compounds tested (0–10 μM). HTRF Ratio = 665 nm acceptor signal/620 nm donor signal × 10,000; the percentage is calculated by taking the highest value as 100%. Data represent the mean ± SEM (n = 5 in triplicates). ( a ) concentration/response curves obtained for agonists; ( b ) concentration/response curves obtained for the antagonists. 2.3  CELT-335 HTRF Assay Validation in hCB2R Expresing adherent cells The Kd obtained through the Tag-lite® saturation binding assay at the CB2R is 24.2nM, confirming the one observed in radioligand assay, while maintaining the appropriate properties for the HTRF signal. Thus, the same set of compounds used for CB1R competition assays was used in CB2R. Table 3. Comparison of affinity data for CB1 receptor of the set of reference compounds obtained through the radioligand competition binding assay and CB1 competition binding assays with Tag-lite® technology using CELT-335.   Values represent the mean ±SEM of triplicate determinations. Reference is not indicated for those compounds whose affinity through the radioligand binding assay was measured experimentally following published protocols.[14] Figure 5.   Competition experiments of binding of fluorescent ligand CELT-335 to living HEK-293 T cells expressing the SNAP-CB2R. Tb labelling was performed as described in Materials and Methods. Competition binding curves were obtained through Tag-lite® technology using 10 nM of CELT-335 and increasing concentrations of compounds tested (0–10 μM). HTRF Ratio = 665 nm acceptor signal/620 nm donor signal × 10,000; the percentage is calculated by taking the highest value as 100%. Data represent the mean ± SEM (n = 5 in triplicates). ( a ) concentration/response curves obtained for agonists; ( b ) concentration/response curves obtained for the antagonists. 3.       Discussion The saturation experiments revealed a lower 2-fold difference in the Kd for each CBR receptor, which was originally 6-fold in the radioligand binding assays, while keeping an excellent FRET signal. High specific binding was observed by measuring 10uM concentrations of the appropriate competitors (CP55490 and GW405833 for CB1R and CB2R). To fully optimize the Tag-lite assays, the concentration of probe was based on the Kd obtained for each receptor, 1 00nM for CB1R and 10nM for CB2R . The curves obtained using this concentration of probe in the Tag-lite® assays are reproducible sigmoidal concentratio/response curves and the affinity data obtained (Ki) has a high correlation to those obtained through tradional radioligand binding assays. Figure 6.   Schematic representation of the high correlation between reference compounds affinity data obtained through radioligand binding assays and the Tag-lite® binding assay developed in this work. ( a ) CB1R binding affinities; ( b ) CB2R binding affinities. The set of reference compounds were chosen to provide the highest diversification in affinity, selectivity, functional acitvity and chemical structure. A graphic highlighting these differences can be found in Figure 7 . Figure 7. Chemical structures, selectivity (radioligand binding assays Ki), and functional activity (blue for antagonists and red for agonists) of the reference compounds used for CELT-335 validation in Tag-lite® competition binding assays. CELT-335 proved itself as a good competitor for both synthetic and naturally derived cannabinoid ligands, both agonists and antagonists. It highlights the difference in affinity of compounds such as SCRAs and other synthetic cannabinoids. Furthermore, the affinity trend is similar to those obtained in literature and t raditional radioligand binding assays . Indeed, the difference is lower than 1pKi value between both experiments. For further validation, a larger range of compounds will be tested, including screening chemical libraries with even more diversity in chemical structures and affinities for other receptors. If you want to read the materials and methods section check out the link  to the full article. If you have any questions about CELT-335 or the assays themselves, feel free to contact me! References (1)         Ajalin, R. M.; Al‐Abdulrasul, H.; Tuisku, J. M.; Hirvonen, J. E. S.; Vahlberg, T.; Lahdenpohja, S.; Rinne, J. O.; Brück, A. E. Cannabinoid Receptor Type 1 in Parkinson’s Disease: A Positron Emission Tomography Study with [ 18 F  ] FMPEP ‐  d 2. Movement Disorders   2022 , 37  (8), 1673–1682. https://doi.org/10.1002/mds.29117 . (2)         Kibret, B. G.; Ishiguro, H.; Horiuchi, Y.; Onaivi, E. S. New Insights and Potential Therapeutic Targeting of CB2 Cannabinoid Receptors in CNS Disorders. IJMS 2022 , 23  (2), 975. https://doi.org/10.3390/ijms23020975 . (3)         Hinz, B.; Ramer, R. Cannabinoids as Anticancer Drugs: Current Status of Preclinical Research. Br J Cancer   2022 , 127  (1), 1–13. https://doi.org/10.1038/s41416-022-01727-4 . (4)         Hua, T.; Vemuri, K.; Pu, M.; Qu, L.; Han, G. W.; Wu, Y.; Zhao, S.; Shui, W.; Li, S.; Korde, A.; Laprairie, R. B.; Stahl, E. L.; Ho, J.-H.; Zvonok, N.; Zhou, H.; Kufareva, I.; Wu, B.; Zhao, Q.; Hanson, M. A.; Bohn, L. M.; Makriyannis, A.; Stevens, R. C.; Liu, Z.-J. Crystal Structure of the Human Cannabinoid Receptor CB1. Cell   2016 , 167  (3), 750-762.e14. https://doi.org/10.1016/j.cell.2016.10.004 . (5)         Li, X.; Hua, T.; Vemuri, K.; Ho, J.-H.; Wu, Y.; Wu, L.; Popov, P.; Benchama, O.; Zvonok, N.; Locke, K.; Qu, L.; Han, G. W.; Iyer, M. R.; Cinar, R.; Coffey, N. J.; Wang, J.; Wu, M.; Katritch, V.; Zhao, S.; Kunos, G.; Bohn, L. M.; Makriyannis, A.; Stevens, R. C.; Liu, Z.-J. Crystal Structure of the Human Cannabinoid Receptor CB2. Cell   2019 , 176  (3), 459-467.e13. https://doi.org/10.1016/j.cell.2018.12.011 . (6)         An, D.; Peigneur, S.; Hendrickx, L. A.; Tytgat, J. Targeting Cannabinoid Receptors: Current Status and Prospects of Natural Products. IJMS   2020 , 21 (14), 5064. https://doi.org/10.3390/ijms21145064 . (7)         Lu, D.; Immadi, S. S.; Wu, Z.; Kendall, D. A. Translational Potential of Allosteric Modulators Targeting the Cannabinoid CB1 Receptor. Acta Pharmacol Sin   2019 , 40  (3), 324–335. https://doi.org/10.1038/s41401-018-0164-x . (8)         Gado, F.; Di Cesare Mannelli, L.; Lucarini, E.; Bertini, S.; Cappelli, E.; Digiacomo, M.; Stevenson, L. A.; Macchia, M.; Tuccinardi, T.; Ghelardini, C.; Pertwee, R. G.; Manera, C. Identification of the First Synthetic Allosteric Modulator of the CB2 Receptors and Evidence of Its Efficacy for Neuropathic Pain Relief. J. Med. Chem.   2019 , 62  (1), 276–287. https://doi.org/10.1021/acs.jmedchem.8b00368 . (9)         Adams, A. J.; Banister, S. D.; Irizarry, L.; Trecki, J.; Schwartz, M.; Gerona, R. “Zombie” Outbreak Caused by the Synthetic Cannabinoid AMB-FUBINACA in New York. N Engl J Med   2017 , 376  (3), 235–242. https://doi.org/10.1056/NEJMoa1610300 . (10)      Rosado, T.; Gonçalves ,Joana; Luís ,Ângelo; Malaca ,Sara; Soares ,Sofia; Vieira ,Duarte Nuno; Barroso ,Mário; and Gallardo, E. Synthetic Cannabinoids in Biological Specimens: A Review of Current Analytical Methods and Sample Preparation Techniques. Bioanalysis   2018 , 10  (19), 1609–1623. https://doi.org/10.4155/bio-2018-0150 . (11)      Showalter, V. M.; Compton, D. R.; Martin, B. R.; Abood, M. E. 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Understanding receptor-ligand interaction is key in drug discovery and biomedical research. Radioligands have been used to study GPCRs for decades, but with the advances in the fluorescence field, assays have shifted towards fluorescent-approaches, thanks to their versatility, safety and precision. What Are the Benefits of Radioligands?   They are ligands labeled with radioactive isotopes which can be used in binding assays to quantify other ligands’ interaction with the receptor. One of the atoms in the original molecule is replaced by a radionuclide, which emits radiation. Some examples are tritium (3H) and 125Iodine (125I), 14Carbon (14C), 35Sulfur (35S), and 32Phosphorous (32P). Besides binding assays, they can also be used to study receptor density, binding sites and ligand kinetics in biological systems. They have several advantages, such as the minimal chemical modifications in the original ligand, high sensitivity and their extensive and successful use throughout decades. Tritium (3H) labeled ligands are usually chemically identical to the original, because tritium will usually substitute hydrogen atoms. The problem is their long half-life, which results in lower detection efficiency. Another common radioactive atom, 125I, with a higher specific activity, but a shorter half-life (60 days), which complicates storage, besides changing the chemical structure of the ligand, as it is generally introduced into aromatic rings. While their high specificity and extensive experience working with them, other drawbacks include radiation exposure, disposal costs and regulatory requirements for working with them. Handling of radioligands must be done by trained users in specific facilities and using specific equipment. Thus, it’s frequently outsourced to academic groups or companies who have everything set-up.   Radioligands vs. Fluorescent Probes: Differences in Binding Assays Fluorescent ligands are a type of fluorescent probes that offer an alternative to radioligands in binding assays. They combine the desired functional activity of the original ligand, by conjugating it to a fluorescent dye (Figure 1). This can be done with agonists, antagonists, reverse agonists in the case of GPCRs. Figure 1. General structure of a fluorescent ligand. Strategic placement of the linker in the pharmacophore and its optimization ensure access to the binding site with minimal unspecific interactions, while also tuning the pharmacological, physicochemical and photophysical properties of the conjugated ligands. Traditional radioligand protocols rely on filtration assay or on scintillation proximity technologies to measure ligand binding. On the other hand, fluorescence signals can be easily monitored through confocal microscopy, plate readers, fluorescence polarization and flow cytometry, proving more versatile. Fluorescent ligands can be used at a broader range of concentration without losing accuracy, as well as detect different receptor conformation states. Ease of handling is the other key difference, because fluorescent compounds do not require regulatory compliance, specific disposal methods and dedicated facilities, making them much easier to implement in any lab. Fluorescent Probes and Radioligands: When should you use one or the other? The choice between these two depends on the results needed – but in case they are similar, fluorescent probes provide a safer and more accessible alternative. -            Quantitative cell binding studies : Radioligands have superior precision when accounting for ligand-receptor interactions, particularly in pharmacokinetic and receptor occupancy studies. However, fluorescent ligands can be used as well as a safer and more accessible alternative. -            Live-cell imaging:  Fluorescent ligands can be used to study cellular and tissue location of a receptor. They are useful tools to visualize receptors in native or transfected cells, whether living or fixed. This is complimentary with other applications, and essential in our understanding of signaling pathways. Figure 2. Representative images of non-fixed HCTT116 colorectal tumor cells co-stained with hA2B-A3 adenosine receptor fluorescent antagonist (Celt-327) and Calcein. Images were taken 2 min after the addition of Celt-327 to the medium. -            Fluorescent probe design for specific targets:  Not all targets have available high-affinity radioligands, but with the development of potent fluorescent probes, this gap can filled in a timely and safe manner. If you are curious about fluorescent probes, fluorescent probe design or GPCR tools, feel free to contact us! References Flanagan CA. GPCR-radioligand binding assays. Methods Cell Biol. 2016;132:191-215. doi: 10.1016/bs.mcb.2015.11.004.  Soave M, Briddon SJ, Hill SJ, Stoddart LA. Fluorescent ligands: Bringing light to emerging GPCR paradigms. Br J Pharmacol. 2020 Mar;177(5):978-991. doi: 10.1111/bph.14953. Stoddart LA, Kilpatrick LE, Briddon SJ, Hill SJ. Probing the pharmacology of G protein-coupled receptors with fluorescent ligands. Neuropharmacology. 2015 Nov;98:48-57. doi: 10.1016/j.neuropharm.2015.04.033.

1.       Introduction Dopamine receptors are G-protein-coupled receptors (GPCRs), which have 5 subtypes -D1-5. The dysfunction of these receptors has been linked to the development of many serious pathologies, like depression, schizophrenia and Parkinson’s disease. [1,2] Several dopamine ligands have been approved as drugs, however they often have serious side effects and too low or temporary therapeutic effects.[3,4] Since dopaminergic signaling is very complex, there’s a need to increase and modernize the assays to study this system. Thus, developing assays for commercially available probes such as CELT-419 would facilitate research into these receptors. Understanding binding kinetics is a key step for a more mechanistic and systematic understanding of the ligands’ action. Thus, fluorescence polarization assays and other fluorescence-based methods that allow for kinetic measurements should reduce this knowledge gap. Fluorescence anisotropy (FA) assay has been used to study the ligand binding kinetics of many GPCRs.[5–7]  2.       Fluorescence Anisotropy and BBV – The theory behind the assays FA is based on measuring the change in rotational freedom of the fluorescent label upon receptor binding, thus does not require the physical separation of the bound and free ligand. Moreover, due to the ratiometric nature of the assay, the FA signal depends on the concentration of both the free and the receptor-bound fluorescent ligand. Therefore, FA requires sufficient receptor concentration to achieve free achieve depletion of free fluorescent ligand. Budded baculoviruses (BBV) have a high receptor concentration as well as being homogenous in size, which makes them a good receptor source for a FA assay.8 It must be considered that the BBVs are nanoparticles covered with Sf9 cell membranes different from mammalian membranes,[9] which can affect receptors’ properties.[10,11] BBVs also lack downstream signaling components, which can be an advantage or disadvantage depending on the purpose of the assay. Thus, in order to complete the studies, quantitative live cell microscopy assay relies on cell segmentation from the bright-field channel while quantifying ligand binding from the fluorescent channel.[7] 3.       Probe characterization and assay development and validation 3.1  Characterization of CELT-419 in radioligand binding assay To determine the affinity CELT-419 has for D3R, and prove it has enough affinity for FA assays, the radioligand binding method was used. The IC50 ± SEM value for CELT-419 binding to D3 receptor was determined to be 30.1 ± 1.7 nM corresponding to apparent Ki ± SEM = 15.7 ± 0.9 nM according to the Cheng-Prusoff model.[12] However, CELT-419 binds also to the D2 receptor in a similar affinity range (IC50 ± SEM = 78 ± 6 nM; Ki ± SEM = 44 ± 3 nM), while the affinity to D4 receptor is significantly worse (12% displacement at 10 μM). 3.2   Kinetic and equilibrium properties of CELT-419 to D3R in BBVs FA assay, the ligand must have a suitable fluorescent label to obtain good-quality results. The possibility to monitor the process kinetics is useful from multiple points of view – practically, it can be used to determine the time to reach equilibrium and, more fundamentally, to determine the kinetic parameters of the ligand binding. Using the FA method, CELT-419 binding affinity and kinetics were determined using budded baculovirus particles (BBV) that display the D3 receptors on their membrane. Figure 1 shows that CELT-419 binds reversibly to the D3 receptor, and there is a large difference between total and non-specific binding resulting in a high signal-to-noise-ratio and stable signal over several hours. Figure 1.Time course of FA change caused by CELT-419 binding to D3 receptor on the BBV particles. The reaction was initiated by the addition of 1 μL D3 receptor displaying BBVs (CD3R = 0.7 nM) to 0.5 nM CELT-419 in the absence (blue circles) or presence (black squares)   of 50 μM Spiperone, or solution without BBVs (orange diamonds). After 90 min (indicated with an arrow), the measurement was paused, and dissociation was initiated by the addition of 333 μM Spiperone (open light blue circles). An equivalent volume of assay buffer was added to association controls (filled dark blue circles). A representative experiment of at least three independent experiments is shown. The model obtained by global analysis of kinetic data suggests that 8 ± 4% of CELT-419 is non-specifically bound. Saturation binding experiments with high-quality results (Figure 2) enabled the calculation of the binding affinity constant Kd ± SEM of 0.42 ± 0.04 nM and receptor concentration in the BBV stock preparation Rstock ± SEM of 20 ± 4 nM. Figure 2. Binding curves of CELT-419 binding to D3 receptors in BBVs. FA of 3 nM (orange squares) or 0.5 nM (blue circles) CELT-419 were measured after 2 h incubation with different amounts of D3 receptor displaying BBVs. Non-specific binding (NS, open symbols) was determined in the presence and total binding (T, filled symbols) in absence of 50 μM Spiperone. The displayed fit, the concentration of D3 receptor binding sites and the Kd values were calculated post hoc from the results of these experiments using the model described in Veiksina et al., 2014 .13 Kd ± SEM is the weighted average of three independent experiments performed in duplicates. Representative experiment performed in duplicates is shown, with both duplicates displayed. 3.3  FA competition binding assay with BBVs CELT-419 has the properties required for measuring affinities of unlabeled ligands: good affinity, high signal-to-noise ratio and stable FA signal during its binding to the D3Rs present in the BBVs. The speed of reaching the binding equilibrium is key for this assay, which can be monitored over time until the values stabilize. To validate that the developed assay is suitable for measuring the K i of different ligands, competition binding measurements were carried out using CELT-419. The assay shows a high signal level with DELTAFA+-SD between total and non-specific points of 0.12+-0.02 (n=26) anisotropy units. The estimated Z’ of the assay is 0.71, which is sufficient for HTS standards. Figure 3.   Displacement of CELT-419 by different concentrations of Butaclamol  (A)  and PL-384  (B)  at different time points. The final concentration of CELT-419 was 0.5 nM and 1 μL BBV/well (CD3R = 0.7 nM) was used. The insert shows the Log(IC50) ± SE change in time of corresponding displacement curves. Data from a single representative experiment performed in duplicate is shown. The Log(IC50) change in time was fitted with equation  3  and k given is the weighted average from 3  (A)  or 4  (B)  experiments with weighted SD The Ki values were calculated based on the IC50 values, receptor concentration and Kd of CELT-419 as described in Veiksina et al., 2014, considering the ligand depletion effect during FA assay. Overall the determined affinities agree well with the affinities from previous studies.[13] Besides traditional dopaminergic ligands, the affinities of the P-165 (CELT-419 pharmacophore), and PL-384 (pharmacophore + linker of CELT-419), were also determined to understand any effects the fluorescent moiety may have on the binding properties of the ligand. No substantial differences were found between them and the reporter. Figure 4.    Displacement of CELT-419 binding to D3 receptor by different dopaminergic ligands. Change in FA level was measured after incubation of 0.5 nM CELT-419, 1 μL BBV/well (CD3R = 0.7 nM), and different concentrations of corresponding dopaminergic ligands for 180 min. The FA values were normalized by taking the average FA value of C = 0 points as 100% and the average FA value of the highest used concentration points as 0%. Data of a representative experiment from at least three independent experiments, performed in duplicates, is shown with both replicates displayed. pKi values are calculated as described in Veiksina et al., 2014 , and presented as mean ± SD of n independent experiments.[13] Due to the relatively slow kinetics of PL-384 compared to CELT-419 (Figure 3B), it was possible to determine the kinetic parameters of PL-384 binding to D3 receptors from competition binding experiment data by global systems biology analysis (Figure 5). The results suggest that adding the linker to the pharmacophore slows down both association and dissociation kinetics, but further addition of the fluorescent label to the structure does not have any further effects. Altogether, these aspects hint that the linker design and strategy can provide options for the tuning of the final ligand’s kinetic properties. Miniaturization is key for HTS application, so achieving good Z’ values for GPCR ligand binding assays using a 384-well plate. In this case, the Z’ value is high enough, proving that the change does not deteriorate the assay during the 3-5h experiments performed. 3.4  Quantitative live-cell microscopy with CELT-419 New robust fluorescent ligands and sophisticated microscopy systems have opened possibilities to perform more high-quality and automated measurements and, therefore, allows HTS compatible quantitative ligand binding experiments in live cells. Since BBVs lack downstream signaling, doing a quantitative lice-cell assay using the same ligand would provide more information and alternatives for binding assays. Therefore, CELT-419, which worked well in FA assays, was also tested with live HEK293-D3R cells. CELT-419 binding to D3 receptors in cells can be clearly visualized with fluorescence imaging. The signal is highly specific as no binding can be seen in the presence of 10 μM Spiperone nor in cells not expressing the D3 receptor. CELT-419 localizes mainly to the cell contour corresponding to receptor-ligand binding in cell membranes. These results indicate that CELT-419 is suitable for live-cell assay with automated microscopy. Figure 5.   Fluorescence and bright-field images of total (left panels) and non-specific binding (central panels) of CELT-419 to live HEK293-D3R cells and to SKOV3 cells without D3 receptors (right panels). HEK293-D3R cells in DMEM medium with added 9% FBS and antibiotic antimycotic solution were incubated with 2 nM CELT-419 in the absence (total binding) or presence (non-specific binding) of 10 μM Spiperone for 2 h in 5% CO2 and at 37 °C. The number of seeded cells per well was 20,000. For negative control, SKOV3 cells without D3 receptors seeded at 30,000 cells per well were used with 2 nM CELT-419. The contrast of fluorescence and bright-field images was enhanced for presentation purposes only, the same lookup table was used for all images of the same imaging mode. The scale bar corresponds to 10 μm. As the next step, the cells were incubated with different concentrations of CELT-419 to determine its affinity for D3 receptors in a live cell system. The Kd ± SEM of 0.38 ± 0.14 nM determined from the saturation binding curve (Figure 7) is in good agreement with the affinity obtained from the FA assay. Figure 6.   Saturation binding of CELT-419 binding to D3 receptors on live HEK293-D3R cells. The HEK293-D3R cells (20,000 cells per well) were incubated with CELT-419 (twofold serial dilutions up to 4 nM) for 4.3 h. Non-specific binding (orange triangles) was measured in the presence of 10 μM Spiperone. The background-corrected fluorescence intensities of cells were determined with the cell detection and image quantification software as described in Materials and methods and are presented as individual replicates from a representative experiment of three independent experiments performed in duplicates. Every point corresponds to the difference between the average pixel intensity of a cell and the average pixel intensity of the background. The average pixel intensities of each point were calculated from four images from different fields of view obtained from a single well. The calculated Kd value is given as mean ± SEM of three independent experiments. Also, competition experiments were carried out to demonstrate the versatility of this system (Figure 8) Dopamine (agonist) as well as Spiperone (antagonist) caused concentration-dependent displacement of CELT-419 to live HEK293-D3R cells. The affinities of these ligands in live cells were higher than in FA assay, but this can be caused by difference in cell membrane composition and downstream signaling systems of the targets. As it is shown before dopamine receptors ligands can achieve higher affinity if G-proteins are coupled to the receptor.[14] Figure 7.   Inhibition of CELT-419 binding to live HEK-D3R cells by dopaminergic receptor ligands. The HEK293-D3R cells (40,000 cells/well) were incubated with 1 nM CELT-419 and different concentrations of Dopamine or Spiperone for 180 min as described in Materials and methods. The background-corrected fluorescence intensities of cells were determined with the cell detection and image quantification software as described in Materials and methods and are presented as individual replicates from a representative experiment of three independent experiments performed in duplicates. Every point corresponds to the difference between the average pixel intensity of a cell and the average pixel intensity of the background. The average pixel intensities of each point were calculated from four images from different fields of view obtained from a single well. 4.       Conclusions and future perspective As can be seen from all the data from this study, CELT-419 is a high-affinity ligand with good kinetic properties, which showed similar results both in FA assay with BBVs and quantitative live-cell fluorescence microscopy. Therefore, both assays can be used for fundamental D3 receptor-ligand binding studies as well as for drug screening purposes. The use of CELT-419 as a fluorescent ligand is not limited by the methods used in this study. Several fluorescence ligands that performed well in either FA or live-cell assays have been confirmed to work well also, for example, in both live-cell and BBVbased TIRF microscopy assays, nanoBRET method and flow cytometry. 15–17In addition, this ligand may be suitable for some superresolution microscopy methods such as photoactivated localization microscopy (PALM) or other single-molecule localization microscopy (SMLM). 18,19However, the Cy3B label of CELT-419, which fits well for FA and live-cell microscopy measurements, is not the best choice for all assays. For example, some assays benefit from using a more red-shifted fluorescent label or a combination of multiple labels in a single study. For example, a Cy5-labelled fluorescent ligand with the same pharmacophore is available from Celtarys Research (CELT-241) which may be more suitable for tissue labelling and imagining due to lower autofluorescence. Altogether, the development of similar probes for other GPCRs and further development of measurement methods can increase the quality and quantity of both fundamental receptor research and high-throughput drug screening. If you are curious about the material and methods or want more information, here is the published article: Frontiers | Fluorescence based HTS-compatible ligand binding assays for dopamine D3 receptors in baculovirus preparations and live cells References (1)         Leggio, G. M.; Bucolo, C.; Platania, C. B. M.; Salomone, S.; Drago, F. Current Drug Treatments Targeting Dopamine D3 Receptor. Pharmacology & Therapeutics   2016 , 165 , 164–177. https://doi.org/10.1016/j.pharmthera.2016.06.007 . (2)         Sokoloff, P.; Le Foll, B. The Dopamine D3 Receptor, a Quarter Century Later. Eur J of Neuroscience   2017 , 45  (1), 2–19. https://doi.org/10.1111/ejn.13390 . (3)         Borovac, J. A. Side Effects of a Dopamine Agonist Therapy for Parkinson’s Disease: A Mini-Review of Clinical Pharmacology. 2006 . (4)         Garcia-Borreguero, D.; Silber, M. H.; Winkelman, J. W.; Högl, B.; Bainbridge, J.; Buchfuhrer, M.; Hadjigeorgiou, G.; Inoue, Y.; Manconi, M.; Oertel, W.; Ondo, W.; Winkelmann, J.; Allen, R. P. Guidelines for the First-Line Treatment of Restless Legs Syndrome/Willis–Ekbom Disease, Prevention and Treatment of Dopaminergic Augmentation: A Combined Task Force of the IRLSSG, EURLSSG, and the RLS-Foundation. Sleep Medicine   2016 , 21 , 1–11. https://doi.org/10.1016/j.sleep.2016.01.017 . (5)         Tõntson, L.; Kopanchuk, S.; Rinken, A. Characterization of 5-HT1A Receptors and Their Complexes with G-Proteins in Budded Baculovirus Particles Using Fluorescence Anisotropy of Bodipy-FL-NAN-190. Neurochemistry International   2014 , 67 , 32–38. https://doi.org/10.1016/j.neuint.2014.01.012 . (6)         Link, R.; Veiksina, S.; Rinken, A.; Kopanchuk, S. Characterization of Ligand Binding to Melanocortin 4 Receptors Using Fluorescent Peptides with Improved Kinetic Properties. European Journal of Pharmacology   2017 , 799 , 58–66. https://doi.org/10.1016/j.ejphar.2017.01.040 . (7)         Allikalt, A.; Kopanchuk, S.; Rinken, A. Implementation of Fluorescence Anisotropy-Based Assay for the Characterization of Ligand Binding to Dopamine D1 Receptors. European Journal of Pharmacology   2018 , 839 , 40–46. https://doi.org/10.1016/j.ejphar.2018.09.008 . (8)         Rinken, A.; Lavogina, D.; Kopanchuk, S. Assays with Detection of Fluorescence Anisotropy: Challenges and Possibilities for Characterizing Ligand Binding to GPCRs. Trends in Pharmacological Sciences   2018 , 39  (2), 187–199. https://doi.org/10.1016/j.tips.2017.10.004 . (9)         Marheineke, K.; Grünewald, S.; Christie, W.; Reiländer, H. Lipid Composition of Spodoptera Frugiperda  (Sf9) and Trichoplusia Ni  (Tn) Insect Cells Used for Baculovirus Infection. FEBS Letters   1998 , 441  (1), 49–52. https://doi.org/10.1016/S0014-5793(98)01523-3 . (10)      Harikumar, K. G.; Puri, V.; Singh, R. D.; Hanada, K.; Pagano, R. E.; Miller, L. J. Differential Effects of Modification of Membrane Cholesterol and Sphingolipids on the Conformation, Function, and Trafficking of the G Protein-Coupled Cholecystokinin Receptor. Journal of Biological Chemistry   2005 , 280 (3), 2176–2185. https://doi.org/10.1074/jbc.M410385200 . (11)      Mondal, S.; Khelashvili, G.; Johner, N.; Weinstein, H. How the Dynamic Properties and Functional Mechanisms of GPCRs Are Modulated by Their Coupling to the Membrane Environment. In G Protein-Coupled Receptors - Modeling and Simulation ; Filizola, M., Ed.; Springer Netherlands: Dordrecht, 2014; pp 55–74. https://doi.org/10.1007/978-94-007-7423-0_4 . (12)      Yung-Chi, C.; Prusoff, W. H. Relationship between the Inhibition Constant (KI) and the Concentration of Inhibitor Which Causes 50 per Cent Inhibition (I50) of an Enzymatic Reaction. Biochemical Pharmacology   1973 , 22 (23), 3099–3108. https://doi.org/10.1016/0006-2952(73)90196-2 . (13)      Veiksina, S.; Kopanchuk, S.; Rinken, A. Budded Baculoviruses as a Tool for a Homogeneous Fluorescence Anisotropy-Based Assay of Ligand Binding to G Protein-Coupled Receptors: The Case of Melanocortin 4 Receptors. Biochimica et Biophysica Acta (BBA) - Biomembranes   2014 , 1838  (1), 372–381. https://doi.org/10.1016/j.bbamem.2013.09.015 . (14)      Rinken, A.; Terasmaa, A.; Raidaru, G.; Fuxe, K. D2 Dopamine Receptor-G Protein Coupling. Cross-Regulation of Agonist and Guanosine Nucleotide Binding Sites. Neuroscience Letters   2001 , 302  (1), 5–8. https://doi.org/10.1016/S0304-3940(01)01568-3 . (15)      Grätz, L.; Tropmann, K.; Bresinsky, M.; Müller, C.; Bernhardt, G.; Pockes, S. OPEN NanoBRET Binding Assay. Scientific Reports . (16)      Laasfeld, T.; Ehrminger, R.; Tahk, M.-J.; Veiksina, S.; Kõlvart, K. R.; Min, M.; Kopanchuk, S.; Rinken, A. Budded Baculoviruses as a Receptor Display System to Quantify Ligand Binding with TIRF Microscopy. Nanoscale   2021 , 13 (4), 2436–2447. https://doi.org/10.1039/D0NR06737G . (17)      Müller, C.; Gleixner, J.; Tahk, M.-J.; Kopanchuk, S.; Laasfeld, T.; Weinhart, M.; Schollmeyer, D.; Betschart, M. U.; Lüdeke, S.; Koch, P.; Rinken, A.; Keller, M. Structure-Based Design of High-Affinity Fluorescent Probes for the Neuropeptide Y Y1 Receptor. J. Med. Chem.   2022 , 65  (6), 4832–4853. https://doi.org/10.1021/acs.jmedchem.1c02033 . (18)      Dempsey, G. T.; Vaughan, J. C.; Chen, K. H.; Bates, M.; Zhuang, X. Evaluation of Fluorophores for Optimal Performance in Localization-Based Super-Resolution Imaging. Nature Methods   2011 , 8  (12), 1027–1036. https://doi.org/10.1038/nmeth.1768 . (19)      Schueder, F.; Stein, J.; Stehr, F.; Auer, A.; Sperl, B.; Strauss, M. T.; Schwille, P.; Jungmann, R. An Order of Magnitude Faster DNA-PAINT Imaging by Optimized Sequence Design and Buffer Conditions. Nature Methods   2019 , 16 (11), 1101–1104. https://doi.org/10.1038/s41592-019-0584-7 .

Hello Dr.GPCR readers! This is Lucía from the Celtarys Research chemistry team.  For our very first post in this ecosystem, we wanted to highlight a huge part of our work at Celtarys Research: conjugation strategies. You can check what we do here on our website!   Conjugation strategies for small molecules are very versatile! In this case, we would like to focus on the synthesis of fluorescent probes. Traditionally, the most reliable and commonly used method is the amide coupling  using acid and amine .[ 1 ] This method has several advantages: it is usually very robust, good yields, reagents are found in most chem labs (like HATU, HoBT, EDCI etc.). Still, there are some downsides, such as the byproduct obtained by the O-acylisourea rearranging intramolecularly into the N-acylurea.[ 2]     NHS ester amide coupling  is the most suited for bioconjugation with proteins, DNA, etc, thanks to its reaction with the free amino groups present in these biomolecules. NHS esters are not very stable even in aqueous environment but they only need a slightly basic medium for the reaction to work, so they have to be used quickly and stored correctly. Not only do they work in aqueous medium, but also in aprotic solvents like DMF, where you will need to add a base such as TEA. [ 3]     Maleimide  conjugation with thiols  present Cys residues. This conjugation is very useful for tagging biomolecules and can also be used to develop fluorescent probes with small molecules. Its biggest advantage is the presence of Cys residues in proteins, although sometimes S-S bridge reduction is needed, and how quickly the reaction takes place. The biggest detractor? It’s reversible under non-reducing conditions. [ 4]     Other strategies include click chemistry,  more specifically, the CuAAC (Cu(I)- catalyzed azide-alkyne 1,3-dipolar cycloaddition), which is a very robust conjugation strategy to obtain linkers with a rigid moiety (the triazol). But it also presents some issues, such as synthesizing the as the presence of the copper catalyst, which has to be removed completely, otherwise it can quelate biomolecules or induce cell toxicity. [ 5]     At Celtarys’ we have our conjugation strategy - our own proprietary technology- which bypasses some of the issues seen before. There’s no need for any catalysts; all reagents will be incorporated in the structure of the final compound. The reaction is convergent, efficient and robust. Thanks to the unique linker structure we obtain, which can be divided into three differentiated parts, we can modify the rigidity of the linker as well as the physicochemical properties of the whole probe. This property comes from the wide chemical space this reaction can access – we can substitute one reagent and make an unprecedented combination, also using commercially available precursor, which improves the performance of the probes.  It also poses some disadvantages – just like acid-amine amide coupling, some byproducts are obtained during the synthesis. However, these are usually easily removable. Besides, it’s an eco-friendlier method, which always helps future-proof our probes!  References   (1) Brown, D. G.; Boström, J. Analysis of Past and Present Synthetic Methodologies on Medicinal Chemistry: Where Have All the New Reactions Gone?: Miniperspective. J. Med. Chem.   2016 , 59  (10), 4443–4458. https://doi.org/10.1021/acs.jmedchem.5b01409 .   (2) Sam, S.; Touahir, L.; Salvador Andresa, J.; Allongue, P.; Chazalviel, J.-N.; Gouget-Laemmel, A. C.; Henry De Villeneuve, C.; Moraillon, A.; Ozanam, F.; Gabouze, N.; Djebbar, S. Semiquantitative Study of the EDC/NHS Activation of Acid Terminal Groups at Modified Porous Silicon Surfaces. Langmuir   2010 , 26  (2), 809–814. https://doi.org/10.1021/la902220a .   (3) Fan, J.; Toth, I.; Stephenson, R. J. Chapter Three - Bioconjugated Materials in the Development of Subunit Vaccines. In Comprehensive Analytical Chemistry ; Verma, S. K., Das, A. K., Eds.; Elsevier, 2023; Vol. 103, pp 59–103. https://doi.org/10.1016/bs.coac.2023.02.005 .   (4) Fontaine, S. D.; Reid, R.; Robinson, L.; Ashley, G. W.; Santi, D. V. Long-Term Stabilization of Maleimide–Thiol Conjugates. Bioconjugate Chem.   2015 , 26  (1), 145–152. https://doi.org/10.1021/bc5005262 .   (5) Meldal, M.; Tornøe, C. W. Cu-Catalyzed Azide−Alkyne Cycloaddition. Chem. Rev.   2008 , 108  (8), 2952–3015. https://doi.org/10.1021/cr0783479 .

Tackling the GPCR Imprecision Problem: Strategic Planning for Sustainable Progress in Complex Systems. In the high-stakes world of GPCR drug discovery , breakthrough science isn't enough. You can have the most brilliant minds and cutting-edge assays, but if your science isn't continuously integrated with your GPCR operational strategy and investment goals, even the most promising program can falter. This fundamental disconnect between the lab and the boardroom  is precisely where programs get stuck—not because of bad science, but because companies find themselves throwing more money and people at problems that could be solved with better systems. This reactive approach, driven by a "go fast" mindset, burns through precious capital and time, leaving both scientific teams and investors frustrated. Companies find themselves throwing more money and people at problems that could be solved with better systems . This reactive approach, driven by the prevailing wisdom of "going fast" and focusing only on the science, burns through precious capital and time, leaving both scientific teams and investors frustrated. This belief that we don't have time to build better systems is a costly miscalculation. It reminds me of a conversation I recently overheard: my oldest child complaining about having to do 'everything at the same time ,' only for the youngest to wisely respond, 'No, you just need to do one thing at a time .' This simple truth applies profoundly to the "go fast" culture in biotech. We believe we don't have time to build better systems, but in reality, our most brilliant and expensive minds are stuck with low-impact tasks due to a lack of systems thinking . My perspective on this challenge is shaped not by a 40-year journey at the bench, but by an expertise in systems thinking  and operational discipline . My work isn't just  about the latest and best assay; it's about the framework that ensures the right assay data leads to the right decision. This is the critical piece that often gets lost in the "go fast" culture—the integration of science with strategy and flawless execution. I’ve lived this firsthand, not just in theory, but by building these systems from the ground up. I understand that embracing a systematic approach can feel daunting, especially with the pressure to move quickly. At Dr. GPCR, we recognized this core problem. Our Chief Brainstorm Officer, Attila Foris , is building a system so transparent that anyone joining the company can integrate seamlessly. Every time a problem arises, we trace it back to its root cause, implementing changes that prevent its recurrence. This iterative process of continuous, planned improvement ensures you're always addressing the next critical area. This is the essence of de-risking GPCR programs through operational excellence. This kind of continuous improvement doesn't happen organically; it demands intentional planning and a systematic approach, ensuring every step forward is strategic and sustainable. The Role of Systems Thinking in GPCR Drug Discovery Systems thinking is the intentional practice of seeing the entire GPCR program as a single, interconnected entity. It's the opposite of a reactive approach, where problems are solved in isolation. It’s the fundamental framework for building your Precision Blueprint , ensuring every scientific detail, operational process, and strategic decision aligns to create a seamless, predictable pathway to success. What You'll Learn in This Series Over the next five bi-weekly installments, " The GPCR Precision Blueprint " series will unpack how to bridge this critical gap. I'll show you how to transform your drug discovery process from a series of disconnected efforts into a seamless, predictable, and de-risked pathway. Part 1: The GPCR Imprecision Problem : I'll reveal why reliance on hiring more people over investing in robust systems thinking  is a multi-million dollar mistake. We'll look at how overlooked operational details, such as misaligned data from diverse GPCR assay types or communication gaps in cross-functional collaboration , lead to critical costs. Part 2: The Data Disconnect : Discover how fragmented, unmanaged GPCR data  cripples scientific progress and strategic decision-making. Learn how to build an integrated data pipeline  that transforms this chaos into a strategic asset. Part 3: The Financial Friction : Explore how a lack of precise alignment between GPCR scientific milestones  and financial realities creates significant risk. Learn to tie your program's progress directly to your funding runway, incorporating crucial early commercial and medical foresight. Part 4: The Investor Imperative : Understand what investors truly prioritize beyond just great science. Learn to translate your program’s internal operational precision into a compelling, de-risked narrative  that builds confidence and secures critical venture capital . Part 5: Your Precision Blueprint : I'll tie it all together, providing a concise, actionable guide for implementing this holistic approach within your own GPCR operational strategy , emphasizing that precision is a continuous, intentional journey towards predictable success. The GPCR Precision Blueprint is more than a concept. If you're ready to move beyond the articles and build these systems for your own GPCR program, let's connect. I work with biotechs, VCs, and CROs to implement the framework that ensures every step forward is strategic and sustainable, offering precision scientific and operational guidance  to accelerate discovery . 🚀 Book your free 30-minute strategy call Let’s unlock the momentum your GPCR program needs. 👉 https://calendly.com/drgpcr/yamina-corner Or explore how we can work together: 👉 Yamina.org

As a valued Dr. GPCR Ecosystem Member, you've been with us as we've laid the groundwork for something truly special. Today, we're thrilled to announce that Terry's Corner is officially live !   This new learning hub is your go-to space to revisit core pharmacology concepts, master new ones, and sharpen your thinking to directly advance your drug discovery program.   What's inside Terry's Corner?  We're launching with 10 on-demand lessons , each featuring:   A short, focused video A concise written summary with key takeaways Handpicked references by Dr. Kenakin himself for deeper dives   A new lesson will drop every Tuesday, ensuring fresh insights are always available. This isn't just another lecture series; it's a practical tool designed to help you recognize and build better frameworks.   Your Exclusive Premium Member Benefit:   As a thank you for your continued support of the Dr. GPCR Ecosystem, we're giving Dr. GPCR Premium Members a significantly reduced access  to Terry's Corner for a limited time.   The private discount code will be sent to your inbox this Thursday . Keep an eye out for it!   In the meantime, you can get a sneak peek by exploring Terry's Articles , which offer complementary insights to the new lessons.   No filler. No fluff. Just the thinking and tools drug discovery demands. Explore Terry's Corner Better decisions start with better pharmacology. We're excited for you to dive in.   Warmest Regards, The Dr. GPCR Team & Terry’s Desk

Unlocking the Puzzle: The Importance of Precision in GPCR Programs and the Hidden Costs of Overlooking Details. A GPCR program can have world-class science, top-tier talent, and millions in funding — and still fail. Not because the science is wrong. Not because the people aren’t brilliant. But because the program is run on duct tape and heroics instead of precision. Your program isn’t slipping because of bad science — it’s bleeding money because your systems were broken before the first experiment ran. And every time your Head of Biology spends each night copy-pasting data instead of thinking about the next experiment, your program is bleeding six figures in lost time and wasted salaries. Brilliant minds doing low impact work is not a strategy. It’s a slow-motion car crash. Hiring Won’t Save Your GPCR Drug Discovery Program When a drug discovery program stalls, the default reflex is always the same: hire more people. Bring in a computational chemist. Add a data scientist. Surely more hands will move the needle. But here’s the reality: even ultra-specialized experts can’t fix systemic dysfunction in their spare time. They’re hired for science, not for building operational scaffolding. And when you chain your highest-paid scientists to repetitive admin work, you’re not solving problems — you’re multiplying them. Every two-week delay in a DMTA cycle can burn through hundreds of thousands in salaries and overhead. That’s not a hiccup. That’s a hemorrhage. Bad Data Management Is Undermining Your GPCR Drug Discovery Team The real problem isn’t competence. It’s the absence of operational precision. Even flawless experiments collapse under sloppy systems. A few familiar failure points: Fragmented Data: GPCR programs spew data across files, folders, and inboxes. Without a unified drug discovery data management  pipeline, teams waste hours cleaning, reconciling, and integrating before they can even think about analysis. A good ELN that pipes instrument outputs into a central hub — where QC, analysis, consumption and consolidation across assays — isn’t a luxury. It’s oxygen. Undefined Protocols: “We’ll figure it out” is not a workflow. Without clear rules of engagement, communication becomes chaos, progress gets lost in Slack threads, and insights die in inboxes. Ambiguous Decision Gates: Molecules advance or stall based on vibes, not criteria. That leads to premature investment in weak scaffolds or endless tinkering with dead ends. These aren’t minor oversights. They’re cracks in the foundation. And cracks don’t stay small for long. Build Precision Systems for GPCR Drug Discovery The only way out for GPCR drug discovery programs isn’t more people or shinier assays. It’s a deliberate blueprint for precision. This doesn’t mean an overnight overhaul. It means a commitment to continuous improvement — starting with the highest-friction gaps and working upward. Plan, fix at the root, and stop fighting the same fire every week. The payoff? Progress that’s predictable, not reactive. The Hidden Costs of Poor Drug Discovery Data Management Stop pretending more hires or new assays will save you. They won’t. Every DMTA cycle lost to fragmented data and sloppy processes costs your company hundreds of thousands of dollars. That’s not “part of the process.” That’s a chaos tax — and you’re paying it in cash, time, and morale. If you want your program to survive, you need a Blueprint for Precision. Not next quarter. Not after the next fire drill. Now. Because the truth is harsh: in drug discovery, you don’t run out of science. You run out of money. And if your systems aren’t built for precision, you’ll run out fast. 👉 In Part 2, we’ll expose exactly how fragmented data cripples GPCR programs — and how to fix it before it sinks yours. And if you’re already seeing the cracks? Don’t wait for Part 2. Reach out. Let’s build the systems now, before the next delay burns another half a million. 🚀 Book your free 30-minute precision audit — before your next DMTA cycle costs another $200K Let’s unlock the momentum your GPCR program needs. 👉 https://calendly.com/drgpcr/yamina-corner Or explore how we can work together: 👉   Yamina.org

Understanding the Connection Between Residence Time and Drug Efficacy: The Importance of Moving Beyond In Vitro Potency. Kenakin’s latest lecture delivers a paradigm shift for pharmacologists working on drugs where in vitro potency fails to predict clinical outcomes . If your lead compounds look perfect on paper but disappoint in vivo, residence time may be the missing piece. This course redefines what makes a drug “effective,” arguing that kinetic persistence (not binding affinity) determines real-world success . From restricted tissue diffusion to PK–PD dissociation, Kenakin equips you with the kinetic models and biological context needed to design drugs that actually work where it matters: in the body. In This Session, You’ll Gain: ✅ Modeling tools to understand how restricted diffusion  in tissues like tumors slows offset and improves therapeutic window ✅ Examples of how rebinding in dense receptor environments  amplifies target occupancy, even post-clearance ✅ Insight into why half-life can be misleading  when volume of distribution hides the drug from its target When Potency Isn’t Enough Drug discovery teams are trained to chase nanomolar potency. But this metric assumes equilibrium, and equilibrium doesn’t exist in vivo. Concentrations rise and fall. Clearance happens. And drugs only work when they’re bound. Kenakin walks through cases where two equipotent ligands produce radically different clinical outcomes , not because of potency, but because of how long they stay on target. In a world of fluctuating drug levels, residence time becomes the true predictor of effect. Diffusion, Rebinding, and Receptor Density: The In Vivo Edge This lecture shows how tissue architecture alters drug action . In structured, diffusion-restricted environments (e.g. brain, tumors), drugs don't just leave slowly; they often rebind . And when receptors are dense (like GPCRs on membranes), this rebinding hits the collisional limit , where every molecular encounter leads to binding. The result? Drugs with poor pharmacokinetics can outperform flashier compounds by exploiting kinetic environments  that weren’t visible in vitro assays. PK–PD Dissociation: When Clearance Doesn’t Mean It’s Over The lecture’s standout example: Aplaviroc, an allosteric CCR5 inhibitor with rapid systemic clearance—yet near-permanent occupancy at its target. The takeaway is clear: fast clearance does not necessarily mean loss of efficacy  when binding offset is slow. This has implications for everything from dosing frequency  to resistance barriers  in infectious disease and oncology. Why Half-Life Can Lie to You Most teams use systemic half-life as a proxy for action. But as Kenakin shows, t½ is a surface metric —a combination of clearance and volume of distribution. A drug hiding in fat tissue may stay in the body for days, but if it never reaches the target site, the therapeutic effect is zero. He breaks down how to distinguish between true target persistence vs. sequestration, with clear takeaways for decision-making in lead optimization and formulation. Rebuild Your Metrics. Redefine Your Pipeline If your development program is built around potency alone, you may be leaving high-value compounds behind. Residence time provides a second dimension of drug evaluation , one that explains results in animal models, informs clinical translation, and helps teams avoid late-stage surprises. Kenakin offers not just theory, but tools to model, predict, and validate this behavior early. Unlock “Target Residence Time” Now Only in Terry’s Corner Why Terry’s Corner In a world where drug discovery is evolving faster than most can track, Terry’s Corner is your shortcut to staying ahead . Here’s what members get: Weekly deep dives from Dr. Terry Kenakin Monthly Ask‑Me‑Anything sessions with live Q&A An expanding on‑demand library for novices to expert drug hunters Influence over future topics Access to the study group Whether you’re in hit-to-lead, lead optimization, or clinical pharmacology strategy, this is where 40 years of kinetic expertise meet the real questions you’re asking in the lab. Don’t just keep pace—outpace the field. 🟢 40 years of expertise at your fingertips: Explore the complete library ➤ ✳️ Want to know what’s inside? Read the latest articles ➤ Stay sharp between lectures. Subscribe to The Kenakin Brief today ➤ #TargetResidenceTime #DrugBindingKinetics #PKPDdissociation #ReceptorPharmacology #InVivoPharmacology #KineticPharmacology #LeadOptimization #Pharmacokinetics #Pharmacodynamics #TissueDiffusion #DrugRebinding #ResidenceTimeMatters

Watch Episode 171 Mentoring in science is more than supervising—it’s about shaping the next generation. In this podcast episode , Alessandro Nicoli shares how becoming the first PhD student in a new lab shaped his view of leadership, teamwork, and scientific growth. Starting From Zero: Growing With a Mentor When Alessandro joined Prof. Antonella Di Pizio’s lab , there was almost nothing—no team, no culture, not even proper desks. But that experience gave him a unique sense of ownership. As the lab grew, so did his responsibilities: from building computational models of GPCRs to guiding interns, master’s students, and even giving lectures . “I remember my first day—we were even sharing the desk. Over the years you see the lab establishing, and for both of us, of course, growing.”  —Alessandro Nicoli Delegating Is a Process Learning to delegate was not easy. Alessandro admits he struggled at first with handing over parts of his projects, fearing mistakes. “It’s a process that is still going on. At the start it was difficult, because you see all these projects and you think, ah, I don’t know… but then with time, of course, it’s a lot of investment.”  —Alessandro Nicoli He discovered that investing time in people pays off. Mistakes are part of learning—and guiding students through them is more valuable than doing everything alone. Leadership as Shared Growth For Alessandro, mentorship is not about control but about growing together . Students bring fresh perspectives, and in teaching them, he also sharpens his own skills. “You can guide them to learn the technique and go over it. But at the same time, you pass the same struggle before… you shape the new generation too.”  —Alessandro Nicoli This two-way growth has turned mentoring into one of his favorite parts of PhD life. Ready to mentor—or to be mentored? Join the GPCR scientist network and connect with peers shaping the next wave of discovery. ________ Keyword Cloud: #Mentoring #ScienceLeadership #PhDmentorship #GPCR #PhDlife #AcademicLeadership #LabCulture #TrainingScientists

Elevate Your GPCR Science with Essential Frameworks for Precision Drug Discovery: An Insight into Advanced Strategies for Targeted Therapeutics. Welcome back GPCR lovers, In pharmacology, the wrong interpretation of antagonist behavior can derail your conclusions, your experiments, and even your program’s credibility. That’s why mastering competitive vs non-competitive antagonism isn’t optional — it’s essential for accurate, defensible science. This week, Terry’s Corner takes you beyond curve shapes into the kinetic and mechanistic realities that separate surface-level analysis from true expertise. Breakthroughs this week: FFA4 receptor signaling controls lipolysis at lipid droplets; novel atypical GPCR-arrestin complexes; Lilly's oral GLP-1, orforglipron, delivers weight loss of up to an average of 27.3 lbs in first of two pivotal Phase 3 trials in adults with obesity. 🔍 This Week in Premium: Sneak Peek A quick look at the curated intelligence our Premium members are using to stay ahead this week: Industry insights:  The latest on how AI is being used to unlock elusive GPCR targets, financial results from Neurocrine Biosciences, and a deep dive into Crinetics Pharmaceuticals’ oral acromegaly drug. We’re also tracking major pipeline clearouts and the competitive landscape for oral GLP-1 drugs. Upcoming events:  An exclusive preview of the “neuroGPCR: G protein coupled receptor signaling in its physiological cellular context” symposium and our featured talk at the upcoming Discovery on Target 2025 conference. Career opportunities:  A curated list of new positions, including a Research Associate, a Senior Research Scientist, and a Post-doctoral Researcher position focused on GPCRs and Mitochondria. Must-read publications:  New insights on RGS protein modulation, GRK2-biased β₂AR signaling, and the distinct role of GRK3 in platelet activation. We’ve also highlighted the latest research on non-canonical internalization mechanisms of mGlu receptors and the intrinsic signaling bias of GPR52. Terry's Corner - Demystifying Antagonism: The Key to Precision Drug Discovery Understanding the nuances of competitive versus non-competitive antagonism is a cornerstone of effective drug discovery. Without a solid grasp of these concepts, scientists risk misinterpreting critical data, leading to flawed decisions and wasted resources. This week in Terry’s Corner , we go beyond the dose-response curves to explore the kinetic and pharmacologic signatures of antagonism. Dr. Kenakin’s expert guidance provides a clear framework for distinguishing these mechanisms and avoiding common pitfalls that can derail a program. Don't let misconceptions about receptor binding kinetics slow your progress—gain the clarity you need to move forward with confidence. Solve the problem of misinterpreting your data by understanding how slow-offset kinetics can mimic classical patterns, leading to incorrect mechanistic assignments. Gain a competitive edge by asking the right questions about binding kinetics and experimental constraints, ensuring your analysis is robust and your decisions are sound. Avoid the professional threat of flawed data interpretations that can lead to costly dead ends and missed opportunities in your drug discovery program. Premium Members get 50%+ discount when they join Terry’s Corner. Sharpen your discovery decisions ➤ Yamina's Consulting Corner - Building Your GPCR Program for Breakthroughs, Not Breakdowns In the fast-paced world of GPCR drug discovery, the "go fast" mindset can often lead to costly breakdowns. Yamina’s Corner tackles the critical disconnect between brilliant science and operational strategy, revealing why throwing more money and people at a problem is a multi-million dollar mistake. This week, we introduce a new series, "The GPCR Precision Blueprint," which provides a systematic framework to ensure your science, strategy, and execution are seamlessly aligned. Learn how to transform your program from a series of disconnected efforts into a predictable, de-risked pathway to success. Solve the problem of a fragmented approach by learning how to build a unified system where every scientific detail and strategic decision aligns. Gain a competitive edge by transforming your GPCR data from chaos into a strategic asset, enabling faster, more confident decision-making. Avoid the professional threat of financial friction and missed investment opportunities by learning to translate operational precision into a compelling narrative for stakeholders. Three takeaways from this week’s feature: Stop firefighting:  Learn why solving isolated problems burns capital without fixing root causes. Bridge science and strategy:  Ensure data and decision-making align with funding and milestones. Build predictable success:  Use a repeatable improvement framework to turn operational chaos into precision execution. Read the full article here ➤ Insights from the Field: The Next Wave of GPCR Drug Discovery The 20th annual GPCR-Based Drug Discovery conference is where the future of GPCR therapies will be defined. If you’re not there, you’re missing out on the next wave of allosteric modulators, biased ligands, and computational targeting. This event is a critical opportunity to stay informed, but the real advantage lies in applying these insights to your work. Our weekly curated news and expert frameworks provide the actionable intelligence you need to make sense of these trends and integrate them into your own research. Solve the problem of information overload by getting a curated summary of the key talks and discussions from the event. Gain a competitive edge by staying on top of the latest breakthroughs in allostery, biased signaling, and computational pharmacology. Avoid the professional threat of falling behind your peers by accessing the same insights that are driving the next generation of drug discovery. Register and join your colleagues in September ➤ Why Dr. GPCR Premium Membership Gives You an Edge In a world filled with noise, Dr. GPCR Premium Membership delivers curated, noise-free intelligence every week. We provide deep-dive expert lessons, classified industry news, priority event alerts, job opportunities, and insider commentary—all designed to help you move faster, smarter, and with greater confidence. This isn’t just information; it’s a strategic framework for your career. Our content is meticulously vetted and organized to provide clarity and actionable insights that you can apply immediately to your work, helping you avoid costly missteps and capitalize on emerging opportunities. FAQ 🔹 What’s included? The complete Weekly News digest, curated jobs, upcoming events, classified GPCR publications, exclusive on-demand expert frameworks, and member-only discounts. 🔹 Who is it for? GPCR scientists, translational pharmacologists, biotech drug discovery teams, and decision-makers who need fast, curated, career-relevant intelligence to stay ahead. 🔹 Why now? The pace of GPCR innovation is accelerating. Those acting on the right signals today will shape tomorrow’s breakthroughs—and avoid delays others won’t see coming. Don’t Fall Behind—Access the Edge You Need 👉 Become a Premium Member Today ➤ Already a Premium Member? 👉 Access this week’s full Premium Edition here ➤ Hear What Our Members Are Saying “The content had enough depth to satisfy the hunger for theory while being full of practical knowledge.” - DrGPCR University Course Attendee Get a competitive advantage—Join Dr. GPCR Premium Today The breakthroughs are happening now, and the decisions you make today will determine your professional trajectory. Don’t wait for others to lead the way. Join the community of informed, empowered GPCR professionals who are shaping the future of drug discovery. Gain the insights, tools, and connections you need to excel in your field and make your mark. Keywords: GPCR, drug discovery, pharmacology, antagonism, competitive, non-competitive, Terry's Corner, Yamina's Corner, biotech, systems thinking, signal transduction, operational excellence, drug development, pharmaceutical, scientific career Hashtags: #DrGPCR #GPCR #DrugDiscovery #Pharmacology #Biotech #GPCRNews #Science #DrugDevelopment

In GPCR drug discovery, a single mistaken assumption can derail an entire program. When pharmacologists misinterpret how an antagonist interacts with its receptor, the consequences ripple across assay development, SAR interpretation, and clinical translation. This week in Terry’s Corner, Dr. Terry Kenakin reframes one of pharmacology’s most foundational ideas: the difference between competitive and non-competitive antagonism. It’s a practical, kinetic problem with real implications for compound evaluation and mechanism-of-action (MOA) studies. Why Misreading Antagonism Delays GPCR Drug Discovery If a dose-response curve shifts to the right, you might call it competitive antagonism. If the maximal response drops, non-competitive seems like the obvious answer. But Terry explains why those assumptions don’t always hold. The real story lies in the rate at which antagonists bind and unbind . Fast offset kinetics allow agonists to outcompete and restore full activity—hallmarks of competitive behavior. But if the antagonist binds tightly and dissociates slowly, the receptor remains blocked, even at high agonist concentrations. This mimics non-competitive behavior, even if the antagonist occupies the orthosteric site. In other words, you can’t diagnose mechanism from curve shape alone . Inside the Lesson: Antagonist Behavior by the Numbers Terry walks through both the pharmacologic and kinetic signatures of antagonism and explains why: Orthosteric antagonism  blocks the receptor completely via steric hindrance, unlike partial allosteric inhibition. Competitive antagonism  occurs when agonist and antagonist re-equilibrate rapidly during the experiment. DR curves shift to the right with no loss of maximal effect. Non-competitive antagonism  results from slow offset kinetics . Antagonist “hogs” the receptor, depressing the response, even if more agonist is added. Schild and Gaddum equations  offer early frameworks for quantifying these effects but modern curve-fitting provides more accurate assessments. Common misconceptions  arise when irreversible binding, receptor reserve, or allosteric effects mimic classical patterns —leading scientists to assign the wrong mechanism. This lecture helps you not only understand these differences, but also know when and why they matter. Beyond the Curve: Questions This Lesson Helps You Answer This lesson pushes you to go deeper than surface-level interpretations and ask the questions that truly shape mechanistic understanding. How do the binding kinetics  of an antagonist influence what we actually observe in a dose-response experiment? Why is competitive antagonism  considered reversible and surmountable, while non-competitive antagonism  often results in persistent receptor blockade? Terry also explores the experimental constraints —like timing and equilibrium—that determine whether you can confidently assign mechanism. He challenges the idea that curve shape alone is diagnostic, pointing out how features like receptor reserve  or irreversible binding  can mislead interpretation. And through historical context, he explains how the classic models of Schild and Gaddum  continue to inform modern analysis, while also highlighting the need for contemporary curve-fitting methods in a post-linear era. Unlock “Competitive Antagonism” Now Only in Terry’s Corner Why Terry’s Corner For discovery-phase teams, time is the scarcest resource. Misinterpreted mechanisms delay decision-making and weaken downstream results. Terry’s Corner  is built to help you avoid those traps. Each subscription includes: Weekly deep dives from Dr. Terry Kenakin Monthly Ask‑Me‑Anything sessions with live Q&A An expanding on‑demand library for novices to expert drug hunters Influence over upcoming topics Who it’s for:  drug discovery teams, pharmacologists refining their toolkit, and scientists who need trusted, curated insights to keep pipelines moving efficiently. Why now:  GPCR research is accelerating—and the projects that succeed will be those built on clear, accurate models of receptor behavior. 40 years of expertise at your fingertips:   Explore the complete library ➤ Want to know what’s inside?   Read the latest articles ➤ Not ready for full membership? Start by challenging your assumptions. Consider this: Two dose-response curves, side by side. One shifts neatly to the right without dropping the maximum. The other shows a clear depression in maximal effect. You’d be tempted to label the first “competitive” and the second “non-competitive.” But Terry cautions: “These patterns are consistent with, but not proof of, mechanism. The real determinant lies in the kinetics of antagonist binding and unbinding.” This is the kind of insight that makes the difference between a dead-end program and a well-informed decision. The stakes are too high to rely on assumptions. If you want to avoid costly misinterpretations and strengthen your pharmacology toolkit, Terry’s Corner is your edge. Keep yourself and your team updated on the newest releases. Subscribe to The Kenakin Brief today  ➤   #GPCRantagonism #CompetitiveAntagonists #NonCompetitiveAntagonists #DoseResponseCurve #Pharmacology #SchildEquation #AntagonistAffinity #Kinetics #DrugReceptorInteractions #GPCRblockade

Watch Episode 171 What happens when your protein has no known ligands, no structure, and very little data? For most researchers, that’s a dead end. For Alessandro Nicoli, it’s an opportunity. In this post, we explore how computational tools—especially AlphaFold —are helping crack the mystery of olfactory GPCRs , one of the most elusive receptor families in the human body. The Problem: Hundreds of Receptors, Almost No Ligands Alessandro’s work focuses on olfactory GPCRs—nearly 400 distinct receptors that play key roles in smell but remain largely uncharacterized . Most have only one known ligand, if any. Their structures are hard to determine experimentally due to poor expression and the volatility of odorant molecules. That’s where computational chemistry steps in. Enter AlphaFold: Predicting the “Face” of a Receptor When Alessandro began his PhD, structural models of olfactory GPCRs were essentially nonexistent. The main challenge was simple but daunting: “The challenge was to get a face to those proteins—the structure. AlphaFold has, of course, as we know, revolutionized the world.”  —Alessandro Nicoli For the first time, researchers had a reliable set of predicted structures to work from. That meant simulations, ligand screening, and experimental design could move forward with confidence. “When they released the first structure of the odorant receptors… AlphaFold already had it, without any prior information, and the match was very close to experimental error.”  —Alessandro Nicoli A New Era of GPCR Research AlphaFold didn’t just fill a gap—it shifted the focus of computational biology. Instead of struggling to predict structures from scratch, Alessandro and others could now use AI-generated models as starting points  for deeper questions. “…now you have a plethora of 400 models that you can start with molecular dynamics, docking, virtual screening.”  —Alessandro Nicoli The result? More accurate hypotheses, faster ligand discovery, and new strategies to tackle one of biology’s most complex receptor families. From Prediction to Discovery One of Alessandro’s projects focused on receptor R5VK1 , where his team tested computational models against a set of experimentally validated active and inactive ligands. By iteratively refining the models with docking and mutagenesis data, they developed predictive pipelines that can help identify new odorant ligands . This case study highlights why computational chemistry is no longer a side tool—it’s a driver of discovery , especially when experimental data is scarce. Want to level up your modeling skills? Start with our GPCR training program and get hands-on with virtual tools shaping the future of drug discovery. ________ Keyword Cloud: # AlphaFold #GPCRdata #DrugDiscovery #OlfactoryReceptors #StructuralBiology #ArtificialIntelligence #MolecularDynamics #ComputationalBiology #MolecularModeling

Kenakin’s Emerging Drug Hunter  lecture delivers exclusive, cutting-edge insights that help you move beyond outdated assumptions and equip your team to interpret data with clarity and confidence.   In this session, you’ll gain:   ✅ A framework for understanding when apparent multiple affinities really matter—and when they don’t ✅ Guidance on extracting meaningful information from binding experiments that advance your work efficiently ✅ Clarity that helps you move from assay to decision faster, with fewer false starts   This isn’t textbook material—it’s real-world expertise designed to help you optimize faster and more effectively.     Move Faster, Smarter, and with Confidence   When you understand what your assays are truly showing you, you eliminate wasted effort and focus only on compounds with genuine potential.   Every day spent misunderstanding the meaning of apparent affinity differences can slow your project’s path to key milestones.   This is about accelerating your path from discovery to clinic, without wasted cycles or missteps.     Why the Myth of High and Low Affinity Binding Sites Could Be Slowing Your Pipeline   If you’re working in drug discovery, you know the pressure: timelines are tight, resources finite, and decisions must be fast and informed. Yet some assumptions still shaping pharmacology workflows haven’t evolved as fast as today’s science.   One of the most persistent misconceptions? The interpretation of high and low affinity binding sites  on GPCRs.   At first glance, when a ligand appears to bind at two different affinities in the same system, it seems logical to assume two distinct sites. But as Terry Kenakin reveals, this interpretation can be misleading, and sticking with it could slow your path to an optimized candidate.   High and Low Affinity: What’s Really Going On? It’s common to observe two apparent affinities for a ligand under certain experimental conditions. But are these differences really pointing to two physical sites?   Kenakin challenges this assumption and shows that what you’re seeing may reflect something entirely different.   In many systems, a ligand may appear to bind with very high affinity when it facilitates formation of ligand-receptor-G protein complexes —an observation that creates the illusion of multiple sites.   But this doesn’t necessarily reflect what’s happening in a physiological context, and misunderstanding this can introduce inefficiency into your decision-making process.   Are You Using Models That Slow You Down?   The analytical tools that shaped traditional affinity analysis were designed for simpler systems. Without appreciating their limitations, it’s easy to misinterpret affinity values, potentially leading to inefficient workflows.   Misunderstandings at this level can delay optimization cycles, result in wasted SAR iterations, or cause programs to focus on leads that won’t deliver—ultimately slowing your program’s forward momentum. Don’t let outdated interpretations slow your next program. Join Now — Access Immediate, Actionable Insight   You’ll gain the insight needed to:   Interpret complex binding data correctly Separate what matters from what misleads Make confident, efficient decisions that keep your pipeline moving forward, toward your next milestone. Unlock “Rethinking Affinity” Now Only in Terry's Corner _____ #GPCR #BindingAffinity #Pharmacology #DrugDiscovery #LeadOptimization #TerryKenakin #EmergingDrugHunter #EfficientDiscovery #PipelineAcceleration

Kenakin’s latest lecture delivers high-impact insight crafted for teams navigating the complex behaviors of GPCR-targeting compounds, especially when potency alone doesn’t explain outcomes. This lecture is a roadmap for understanding why two drugs with similar affinity may behave completely differently , and how the secret lies in receptor conformational dynamics , probe dependence , and cryptic binding sites . In this session, you’ll gain: ✅ A deeper understanding of how every ligand alters receptor conformation—and why this can’t be ignored  ✅ Practical examples of how probe dependence  alters efficacy, selectivity, and SAR interpretation  ✅ Insight into cryptic binding sites  and why some drugs need hours—not minutes—to equilibrate  ✅ A framework for designing or troubleshooting allosteric modulators with built-in selectivity and context sensitivity Why GPCR Allosteric Thinking Changes the Game in Drug Discovery For decades, drug discovery pipelines have relied on the orthosteric model: one ligand, one site, one outcome. But that model is no longer sufficient. As Kenakin explains, all GPCR signaling is allosteric , and pretending otherwise introduces risk at every stage of the pipeline. Ligands don’t just “bind”—they change  the receptor. These changes can alter how the receptor talks to G proteins, arrestins, or other receptors. The consequences? Unexpected activity profiles, SAR that breaks your QSAR model, and missed opportunities to design more efficient ligands from the start. If you’re still treating GPCRs as passive targets, your screening filters may be blind to key liabilities or falsely disqualifying promising candidates. Cryptic Sites, Longer Onset: Why Some Drugs Work Differently in Cells Than in Assays One of the most actionable takeaways from this lecture is how cryptic binding pockets —sites that only exist briefly in certain receptor states—can drastically alter the pharmacokinetics of an allosteric drug. These sites don’t behave like traditional active sites. Ligands may take hours to equilibrate , even when they look potent on paper. This has direct implications for: Assay timing and readout design Misclassification of lead candidates Underestimation of in vivo potency Kenakin explains why recognizing this phenomenon early can prevent costly misreads and wasted SAR cycles. What If the Same Site Behaves Differently Depending on the Ligand? (It Often Does) A central concept explored here is probe dependence : the idea that the effect of an allosteric modulator depends entirely on the probe it interacts with. The same modulator might enhance  one probe and inhibit  another, at the same site . This unpredictability isn’t chaos—it’s structure-driven , and when properly understood, it becomes a powerful design tool. You’ll see how this manifests in real data from muscarinic receptors, CCR5 chemokine programs, and NMDA receptors, where ligand context fundamentally changes modulator behavior. Why “Affinity Alone” Isn’t Enough—Again Just like binding kinetics require us to go beyond static Kd values, allostery demands that we go beyond “one-drug, one-outcome” logic. Affinity tells part of the story. But without understanding how GPCR state changes  influence that affinity—or vice versa—drug discovery becomes guesswork. In this lecture, Kenakin lays out why no ligand binds without altering receptor conformation , and how that physical truth underpins allosteric design, signal bias, and functional selectivity. Design with Intelligence, Not Assumptions Whether you're aiming to discover PAMs, NAMs, or bias-selective modulators, the principles in this lecture equip you to design ligands that not only bind, but bind with purpose —selectively, contextually, and predictably. You’ll walk away with tools to: Interpret probe-dependent effects Model and anticipate longer equilibration times Recognize when your data reflects true receptor behavior—and when it doesn’t Use allostery as a deliberate strategy, not a confounding variable GPCRs Are Dynamic. Your Strategy Should Be Too. Outdated models can mislead your team, waste your resources, and cost your pipeline months of progress. Terry’s Pharmacology Corner  delivers trusted, razor-sharp insight to help drug discovery professionals like you stay ahead of the science and the competition. If you’re ready to stop guessing and start optimizing, this lecture is your next step. Unlock “GPCRs as Allosteric Machines” Now Only in Terry’s Corner Why Terry’s Corner Terry’s Pharmacology Corner  is your trusted, expert-led guide through the evolving landscape of GPCR science. Subscribers gain access to: Weekly lessons by Dr. Terry Kenakin Monthly Ask-Me-Anything sessions A growing, curated on-demand library Opportunities to shape future topics Built for discovery-phase teams, pharmacologists refining their methods, and decision-makers navigating fast timelines, it’s the go-to resource for reliable insight. Why now? Because the pace of innovation is accelerating. Scientists acting on today’s insight will shape tomorrow’s breakthroughs. 40 years of expertise at your fingertips: Explore the complete library ➤ Or get a sneak peek of what’s inside: Read the latest articles ➤ ______ #GPCR #AllostericPharmacology #DrugDiscovery #MedicinalChemistry #ProbeDependence #CrypticBindingSites #ReceptorDynamics #BiasedSignaling

Kenakin’s latest lecture delivers a game-changing framework for teams grappling with the gap between in vitro potency and in vivo performance, especially when target engagement doesn't explain clinical outcomes. This lecture is a guide to understanding why intracellular drug access changes everything: from target residence time to diffusion-driven pharmacodynamics and the discovery of previously untargetable sites. In this session, you’ll gain: ✅ A clear breakdown of how intracellular vs. extracellular receptor access alters diffusion, offset kinetics, and rebinding ✅ Real-world examples of how residence time—not potency—predicts therapeutic coverage ✅ Insight into cryptic intracellular GPCR sites, including allosteric modulators only accessible from inside the cell ✅ Tools for evaluating scaffold permeability using modern, cost-effective pharmacokinetic assays   Why Intracellular GPCR Drugs Change the Game For decades, drug design has treated GPCRs as surface targets. And while that strategy has yielded enormous success, it ignores a powerful reality: the cytosol is a restricted diffusion compartment. Once a ligand crosses into this intracellular space, it behaves differently, often much more favorably. Offset slows. Rebinding becomes possible. And intracellular targets, including allosteric sites unreachable from the extracellular side, become available. In this protected environment, pharmacokinetics can decouple from plasma clearance. You get longer activity with shorter exposure—a dream scenario for drug designers. Kenakin walks you through the science, the data, and the practical methods for making it happen.   Restricted Diffusion, Rebinding, and Residence Time: The Hidden Variables One of the most actionable takeaways from this lecture is how intracellular environments create the conditions for kinetic persistence. This isn’t just theoretical—Kenakin shows data from risperidone, comparing offset rates in open compartments vs. restricted ones like the brain. When a drug rebounds after dissociating—something only possible in a diffusion-limited space—it can maintain target occupancy long after systemic levels drop. These aren’t small differences. They’re the reason two equipotent drugs may perform very differently in vivo. You’ll learn how to recognize and harness this in your own programs.   Same Affinity, Different Outcomes: Why Residence Time Matters More Two ligands. Identical in vitro affinity. One with rapid offset, the other with slow offset. In a traditional assay, they look the same. But in vivo? The slow-offset compound stays on target longer, maintains therapeutic effect as concentrations drop, and achieves better real-world outcomes. Kenakin shows how this plays out in model systems and clinical data—and why residence time should be a first-class design parameter, not an afterthought.   New Tools for Getting Drugs Inside Cells All of this hinges on a simple question: can your compound get inside the cell? The good news: we now have reliable, low-cost assays to find out —Kenakin walks through the essential methods to assess intracellular access and permeability. He also reviews key scaffold properties that determine success, offering practical tips for design teams to tune drug-like balance between lipid and aqueous environments.   GPCRs Aren’t Just Surface Receptors Anymore From β2-adrenoreceptors to CCRs and dopamine receptors, multiple GPCRs now have validated intracellular  allosteric sites. And while orthosteric ligands may never reach them, properly designed intracellular drugs can. This opens up a new pharmacological space—and a reason to revisit “failed” targets with fresh eyes. If your pipeline is built only around extracellular engagement, you might be leaving opportunities untapped. Persistent binding isn’t just about longer half-lives—it’s about smarter pharmacology. Intracellular access transforms the kinetic profile of your drug, which may be the difference between success and failure. Unlock “Intracellular Drugs” Now Only in Terry’s Corner   Why Terry’s Corner In a world where GPCR science moves faster than most teams can track, Terry’s Corner is your shortcut to clarity. Here ’s what members get: Weekly deep dives from Dr. Terry Kenakin Monthly Ask‑Me‑Anything sessions with live Q&A An expanding on‑demand library of past lessons Influence over upcoming topics Whether you’re in discovery, refining SAR, or steering strategy, this is the one place where 40 years of GPCR experience  is distilled into practical insight. Don’t just keep pace, stay ahead. 40 years of expertise at your fingertips: Explore the complete library ➤ Want to know what’s inside? Read the latest articles ➤ Not ready for full membership? Stay ahead with The Kenakin Brief  — a concise, science‑first email update with the latest insights in GPCR pharmacology and drug discovery. Quick reads. Clear takeaways. Always one step ahead. Subscribe to The Kenakin Brief today  ➤ #GPCRs #IntracellularDrugs #DiffusionBarriers #DrugResidenceTime #AllostericModulation #CytosolicKinetics #PK #PD #CellPermeabilityAssays #PAMPA #Caco2 #TherapeuticKinetics

Kenakin’s latest   lecture delivers exclusive, real-world insight designed to equip you to move beyond surface-level affinity data and make faster, more confident decisions in your drug discovery pipeline. In this session, you’ll gain: ✅ A practical framework for understanding when a drug’s rate of binding onset and offset matter most for in vivo success, and when static equilibrium affinity won’t tell the full story ✅ Guidance on interpreting kinetic binding experiments that enable operational clarity and avoid wasted effort ✅ The ability to reduce cycle times by recognizing when your data truly reflects equilibrium—and when it doesn’t This is practical kinetic expertise—crafted to help drug hunters reduce wasted effort and move faster from data to decision. Why Faster, Smarter Decisions Require More Than Kd In drug discovery today, the clock is always ticking . Your pipeline depends on early, well-informed decisions that move promising candidates forward while de-prioritizing those unlikely to succeed. Yet most discovery teams still rely on classic affinity metrics alone, often overlooking how kinetic profiles  (onset and offset rates) fundamentally shape how a drug behaves in vivo. Two compounds can show identical affinities on paper, but their biological outcomes can differ dramatically if their kinetic profiles diverge. Every day spent misunderstanding what your assays are truly showing you can lead to costly missteps—wasted SAR iterations, false positives, and slower time-to-milestone. Kenakin’s kinetic insights help you translate assay readouts into actionable knowledge that keeps your programs focused and moving efficiently toward clinical relevance . Why the Myth of “Potency = Affinity” Could Be Slowing Your Pipeline Many workflows still operate on the assumption that equilibrium potency (Kd) alone is sufficient to predict in vivo efficacy. But as Kenakin shows in this lecture, the reality is more nuanced, and mastering drug binding kinetics is essential for pipeline efficiency: How fast a ligand binds (k₁) and how long it stays bound (k₂)  can alter therapeutic profiles dramatically, even if two candidates share the same affinity at equilibrium. Competitive conditions —such as the presence of endogenous ligands— change kinetic behavior , and ignoring this can lead to wrong prioritization decisions. Kinetic measurements reveal hidden liabilities or advantages that static affinity numbers cannot. Understanding these dynamics empowers drug hunters to separate what matters from what misleads , cutting through noise to focus only on compounds with genuine in vivo promise. Kinetics Reveal What Static Numbers Can’t If your workflow stops at “potency = Kd,” you’re missing a critical layer of actionable insight. Kenakin’s lecture guides you through key questions that should shape your decision-making process: Are you measuring equilibrium, or could early-time-point artifacts be skewing your interpretation? How do competing ligands slow or alter binding rates, and what does this tell you about real-world pharmacology? When does onset rate dictate therapeutic onset, and when does offset rate predict duration? These aren’t theoretical questions—they directly impact your ability to advance the best candidates faster, while eliminating wasted cycles on compounds that look good on paper  but won’t deliver. Don’t Let Outdated Models Slow Your Next Program The analytical tools that shaped traditional affinity assays were built for simpler systems. Without appreciating their limitations, it’s easy to misinterpret key kinetic signals that matter for decision-making in modern drug discovery. Missteps at this level can delay optimization, generate unnecessary SAR work, or cause your team to miss subtle but critical liabilities—all of which slow your pipeline’s forward momentum. Dr. Kenakin gives you clear, practical guidance on when to look deeper and how to extract meaningful, operational insight from your kinetic data. Reach key milestones sooner, with fewer false starts. You’ll gain clarity that accelerates your path from discovery to clinic: Know when your assays truly reflect binding equilibrium Interpret competition experiments with confidence Recognize how kinetic rate constants can reveal hidden liabilities, or identify true best-in-class candidates faster Unlock “Drug Binding Kinetics” Now Only in Terry’s Corner   ______ #DrugDiscovery #Pharmacology #DrugKinetics #PipelineEfficiency #PharmaInnovation #GPCR #BindingKinetics #MedicinalChemistry #LeadOptimization

Hi GPCR Fanatics,   This week’s insights will help you avoid wasted time, poor forecasts, and stalled programs. Let’s get you moving with confidence. 🔍 Quick Wins This Week 🔹 Tell us what matters → News Survey Your 1-minute feedback shapes what we spotlight next week. Help us help you. 🔹 Elevate your strategy → Building clarity in GPCR drug discovery Even the strongest GPCR programs stall—not from bad data, but from buried decisions; Yamina's Corner helps teams cut through the noise and build clarity that drives action. 🔹 Innovate faster → Celtarys’s newest GPCR tools Explore new screening tools purpose-built for speed and signal specificity. 🔹 Spot the opportunity → Why Catalio is betting big when others pull back Amid biotech slowdowns, Catalio’s contrarian investments offer insight into what’s next. Terry's Corner - New Course on Pharmacologic Models The latest Terry’s Corner unlocks clinical forecasting tools few scientists truly master.   ✅ Avoid costly errors:  Master vital models to confidently forecast outcomes, before it’s too late. ✅ Future-proof your career: Conquer complex laws and understand where receptor theory is going next. ✅ Premium Members:  Access your exclusive discount in the full newsletter   Secure Your Access Now ➤ 🗣️ “Thank you for bringing this (Principles of Pharmacology I) course with Dr. Kenakin. I wish Dr. GPCR the best for the sake of promoting more educational opportunities that are sorely needed in the field” — Dr. GPCR University Learner Dr. GPCR Podcast - Surviving Discovery’s Gauntlet Dr. Sokhom Pin delivers brutally honest insights.   Break stagnation:  Apply lessons from BMS, Novartis, Cerevel & more. Find your edge:  Dodge the traps that derail real drug discovery careers.   Listen Now – Real Lessons from a GPCR Expert ➤ The future of GPCR isn’t waiting. Get ahead, stay relevant, and lead—starting today.   The Dr. GPCR Team Read Full Edition ➤

Welcome GPCR Fans,   In GPCR-targeted drug discovery, precision isn’t optional—it’s a requirement. But precision isn’t just about clean data; it’s about interpreting what that data means. Subtle misinterpretation can quietly derail projects, slow timelines, and waste scarce resources. That’s why this week at Dr. GPCR , we’re focusing on the hidden risks that undermine progress and how the right frameworks can keep your pipeline moving forward. This is a preview of what Premium Members access every week: industry insights, event updates, jobs, and classified publications—curated for scientists who need fast, actionable intelligence. 🔍 This Week in Premium: Sneak Peek Dr. GPCR Premium Members this week gain curated, early access to: Industry insights : GPCRs and mRNA in drug discovery; new strategies for inflammatory disease treatment; growth strategies from Tectonic Therapeutics Upcoming events : Lab-in-the-Loop AI-powered hit discovery (July 29); 5th Transatlantic GPCR Symposium (Sept 3–4); neuroGPCR Symposium (Sept 17) Career opportunities : Lead/Senior Researcher at St. Jude; Postdoctoral Fellow at University of Copenhagen; PhD in proteomics and GPCR signaling in cancer at CRCM Must-read publications : AlphaFold3 benchmarking for GPCRs; new structural insights into peptide ligand activation All curated for speed, relevance, and immediate application—only for Premium Members. Terry’s Corner: Rethinking Affinity, A Critical Edge for Drug Hunters One of the most persistent misconceptions in pharmacology workflows? The interpretation of high and low affinity binding sites on GPCRs. At first glance, when a ligand binds at two different affinities in the same system, it seems logical to assume two distinct sites. But Terry Kenakin’s new Emerging Drug Hunter lecture reveals why this assumption can mislead even experienced teams . What’s Really Going On? Under certain experimental conditions, what appears to be a second high-affinity site may simply reflect kinetic factors—such as ligand-receptor-G protein complex formation—creating the illusion of multiple sites that aren’t physiologically relevant. This misunderstanding leads to: Inefficient structure-activity relationship (SAR) cycles Wasted optimization efforts Focus on leads that fail later in development In this exclusive session, Kenakin gives you the frameworks needed to interpret data correctly, eliminate wasted effort, and accelerate confident decisions. 🔒 Available only in Terry’s Corner - Premium Members get an exclusive discount Secure Your Access To Terry's Corner ➤ Why the Myth of Multiple Affinity Sites Slows You Down Traditional models that shaped affinity analysis were designed for simpler systems. If you’re not accounting for their limitations today, your team risks costly misinterpretations that delay optimization cycles and waste resources. Kenakin shows exactly how to separate what matters from what misleads—practical, real-world expertise designed to help teams move faster, smarter, and with greater confidence. Every day spent misunderstanding apparent affinity differences delays key milestones. 🗣️ “Thank you for bringing this (Principles of Pharmacology I) course with Dr. Kenakin. I wish Dr. GPCR the best for the sake of promoting more educational opportunities that are sorely needed in the field” — Dr. GPCR University Learner Celtarys Research Recap: Medicinal Chemistry Highlights You May Have Missed The pace of innovation in medicinal chemistry is accelerating—and if you missed this year’s ACSMEDI-EFMC Medicinal Chemistry Frontiers 2025 , you’re already behind. At this international meeting, leaders shared next-gen strategies shaping modern drug discovery: Prof. Ingo Hartung : State-of-the-art design of small molecule drugs, including PROTACs Dr. Wendy Young : Career insights and lessons from a leader in drug development and a champion for women in science Dr. Katerina Leftheris : New technologies overcoming peptide limitations with insights from both pharma and startup environments Read Maria Majellaro's Full Recap ➤ Lab Leadership Without Ego: A Model for R&D Success Scientific rigor doesn’t thrive in cultures defined by micromanagement or burnout. At Alkermes, Sokhom Pin built an in vitro pharmacology group from scratch—not just a lab, but a culture that encouraged curiosity, empowered people, and supported balance while delivering results. His leadership principles: Hire for attitude and team fit—not just credentials Design workflows that enable curiosity-driven research Support work-life balance without compromising scientific excellence His approach didn’t just create a productive lab—it accelerated outcomes and laid the cultural foundation for the next generation of biotech innovation. Get The Full Story ➤ Why Dr. GPCR Premium Membership Gives You an Edge Dr. GPCR Premium is designed for scientists who need the right intelligence, fast—without noise, distractions, or delays. Every week, members get: A full edition of GPCR Weekly News : jobs, events, papers, industry updates Exclusive discounts on Terry’s Corner  digital pharmacology courses Priority access to insights from major conferences, emerging research, and expert commentary Whether you’re a pharmacologist, biotech scientist, or team leader, Dr. GPCR Premium gives you an edge in a fast-moving field. FAQ: What’s Included, Who It’s For, Why Now What’s included? The complete Weekly News digest, jobs, upcoming events, classified industry intelligence, Courses, & Conference Presentations. Who is it for? Scientists, drug discovery teams, and pharmacologists who need curated, career-relevant updates. Why now? The field is evolving rapidly. Those acting on the right insights now will define the next wave of discovery. Don’t Fall Behind—Access the Edge You Need 👉 Access all the news and upcoming events ➤ Already a Premium Member? Access this week’s full Premium Edition here ➤ Hashtags: #GPCR #DrGPCR #BindingAffinity #Pharmacology #DrugDiscovery #LeadOptimization #TerryKenakin #EmergingDrugHunter #EfficientDiscovery #PipelineAcceleration

Masterclass on GPCR Allostery: Unveiling Techniques to Decode Drug Behavior – July 31st, 2025. Welcome back GPCR fans, If your drug discovery strategy still relies on static GPCR models, you’re already behind. Allostery isn’t just an advanced concept—it’s essential to understanding efficacy, ligand bias, and receptor behavior in real-world systems. That’s exactly what Terry’s Corner delivers this week: high-impact insight into GPCR allostery, crafted for pharmacologists and biotech scientists who need to translate mechanistic nuance into better decision-making. 🔍 This Week in Premium: Sneak Peek Industry insights:  Strategic biotech alliances (Chemspace/Enamine, Superluminal Medicines), Novartis financial leadership shakeup, and next-gen GPCR targeting platforms reshaping immunotherapy pipelines. Upcoming events:  GPCR-UK Network Meeting, neuroGPCR symposium, and Transatlantic ECI GPCR event—where discovery and collaboration intersect. Career opportunities:  Exclusive pharma and academic listings you won’t find on job boards—curated for translational scientists and GPCR specialists. Must-read publications:  CXCL12 dimer impact on AML migration, mechanosensitive behavior in GPCRs, and in vivo APLNR biosensor imaging. Terry's Corner : Stop Chasing Affinity and Start Reading the System In this week’s cornerstone Terry’s Corner lecture, Dr. Terry Kenakin reframes GPCRs as dynamic, allosteric sensors—far from static binding sites. This is the lens that lets scientists anticipate drug effects, decode kinetic behavior, and optimize probe-dependent signaling. What you’ll learn: Reveal cryptic binding sites and time-dependent interactions.  Some drugs take hours to reach equilibrium—not because of poor design, but because the system is fluid. Learn how to decode that fluidity. Exploit probe dependence to shape precision pharmacology.  Want to avoid off-target effects? Understand how GPCRs react differently depending on the probe. Map dynamic receptor behavior to real-time decision-making.  Allostery is not passive—it’s predictive. Leverage this model to stay ahead of therapeutic complexity. To stay in the know on upcoming courses and AMA session, get the complementary Kenakin Brief , the weekly newsletter delivered directly to your inbox. Sharpen your discovery decisions ➤ GPCR Signal Transduction Call for Papers: Define What Comes Next Volume I was just the beginning with over 28K reads. As the GPCR field surges forward—from ligand bias to signaling diversity—the guest editors Dr. Lauren Slosky, Stuart Maudsley and Yamina Berchiche invite your insights for Volume II. This is a chance to shape the next scientific consensus on how GPCRs work, signal, and fail. Why this matters: Secure your voice in the next chapter of GPCR science.  Your work belongs in the core conversation—not buried in supplementary files. Position your research for maximum visibility.  This is where funders, peers, and biotech scouts are watching. Contribute to an evolving field still rich with firsts.  Volume II isn’t about repetition—it’s about redefining signal transduction. 📝 Manuscript summary deadline: 23 Sept 2025 📄 Submission deadline: 11 Jan 2026 Submit to Volume II ➤ Discovery On Target: Where the Next Decade of GPCR Drugs Begins If you’re not attending the GPCR-focused sessions at Discovery On Target 2025, you’re missing where the field is headed. It’s the 20th anniversary—and the spotlight is squarely on kinetic modeling, allosteric frameworks, and targeting the “undruggable.” 🔥 Featured:  Dr. Terry Kenakin on “The Kinetics of Allostery: The Added Benefits of Allosteric Function.” Why you need to be there: Learn how kinetic nuance shapes ligand design.  Don’t just measure residence—understand it. Access peer insights on allosteric modulators and biased ligands. Join the conversation on computational targeting and next-gen selectivity. Register for Discovery On Target ➤ What our community is saying “I enjoy the breadth of questioning that goes beyond just the science, and reveals a bit about the scientists as individuals/mentors/people.” — Dr. GPCR Podcast Listener Why Dr. GPCR Premium Membership Gives You an Edge Premium delivers curated, noise-free intelligence every week: deep-dive expert lectures, classified industry news, priority event alerts, job opportunities, and insider commentary—designed to help you move faster, smarter. If you work on GPCRs across translational pharmacology, drug development, or molecular pharmacology, this is your decision advantage. Our Premium Members don’t have to chase signals—they act on them. FAQ: What You Get with Dr. GPCR Premium 🔹 What’s included? 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Exploring Intracellular Targets: Bridging the Gap Between In Vitro and In Vivo GPCR Research - August 7th, 2025. Welcome back GPCR fans, The pace of GPCR innovation is accelerating at a rate that can be difficult to keep up with. For drug discovery teams and scientists, staying ahead requires more than just reading papers—it demands access to the right frameworks and expert insights that separate the noise from the signal. That’s exactly what Terry’s Corner delivers every week: practical tools from Dr. Terry Kenakin to elevate your science and sharpen your decisions. Breakthroughs this week: Glucagon-like Peptide-1 Receptor (GLP-1R) Signaling; Proximity-Dependent Proteomics; Multicolored sequential resonance energy transfer. 🔍 This Week in Premium: Sneak Peek Don't miss the key insights and opportunities that are shaping the future of GPCR research and drug discovery right now. This week's Premium content offers a curated look at what's moving the industry and scientific community forward. Industry insights:  Crinetics' Palsonify gains momentum in acromegaly, a key indicator for pipeline expansion; Septerna's chart signals upward expansion; and a look at how chronic diseases are driving growth in the global GPCR targeting market. Upcoming events:  Get details on the "neuroGPCR" symposium focusing on receptor signaling and a platform for unlocking "undruggable" targets with AI-powered hit discovery. Career opportunities:  New openings for a postdoctoral research position in GPCR biochemistry and biophysics and a research associate/scientist in in vitro pharmacology. Must-read publications:  A deep dive into proximity-dependent proteomics of adenylyl cyclase isoforms, a case for functionally Gs protein-selective GPCRs, and new methods for detecting simultaneous ligand binding. Terry's Corner : Unlock the Power of Intracellular GPCR Drugs For years, GPCR drug discovery has focused on targets at the cell surface. But what if the most significant opportunities lie just inside the cell membrane? This week Dr. Terry Kenakin delivers a game-changing framework for teams grappling with the gap between in vitro potency and in vivo performance. His latest lecture is a guide to understanding why intracellular drug access changes everything—from target residence time and rebinding kinetics to the discovery of previously untargetable sites. Solve the in vitro/in vivo disconnect:  Understand why traditional potency measurements often fail to predict clinical success and learn how intracellular kinetics can provide the missing link. Gain a competitive edge:  Learn to leverage restricted diffusion and rebinding to create drugs with longer therapeutic coverage, even with shorter systemic exposure. Avoid missed opportunities:  Discover how to identify and target cryptic intracellular allosteric sites, opening up new avenues for "failed" or under-studied GPCRs. To stay in the know on upcoming courses and AMA session, get the complementary Kenakin Brief , the weekly newsletter delivered directly to your inbox. Sharpen your discovery decisions ➤ Dr. GPCR Podcast : The Future of GPCR Drug Discovery with Molecular Modeling The field of GPCR research is being transformed by the accessibility of computational tools. In this week's Dr. GPCR Podcast, we sit down with Alessandro Nicoli, from the Technical University of Munich, to discuss his work on olfactory receptors. He shares his journey into computational chemistry and offers a compelling look at how tools like AlphaFold are providing new starting points for drug discovery. Learn how his research aims to develop models that can distinguish between active and inactive ligands, paving the way for computational ligand discovery even where experimental data is scarce. Harness the power of AI:  Discover how breakthroughs like AlphaFold are making previously "undruggable" targets, like olfactory receptors, accessible for computational analysis. Bridge the gap between disciplines:  Get practical advice from a computational expert on how wet-lab scientists can integrate computational tools like Python and Talktorials into their work. Learn from a pioneer:  Hear how mentorship and team science are fueling innovation in the field and providing a path for the next generation of GPCR scientists. Expand your computational toolkit ➤ Call for Papers: GPCRs: Signal Transduction, Volume II Building on the success of its first volume, the research topic "GPCRs: Signal Transduction: Volume II" is now open for submissions. This is a critical opportunity for the scientific community to come together and share new findings on how GPCRs regulate bodily functions, health, and disease. This research topic is designed to stimulate discussion and fuel the scientific direction of future GPCR research within the field of Cellular Biochemistry. Amplify your research:  Contribute to a high-impact collection of work that will shape the future of GPCR signaling studies. Connect with experts:  Join a community of like-minded field-experts dedicated to improving our collective understanding of GPCRs in human health. Stay ahead of the curve:  Showcase your latest findings on the essential role GPCRs play in disease and their function as important drug targets. Discover the research topic ➤ Why Dr. GPCR Premium Membership Gives You an Edge Staying at the forefront of GPCR science is not just a goal—it’s a necessity. The right information at the right time can mean the difference between a breakthrough and a dead end. Dr. GPCR Premium Membership delivers curated, noise-free intelligence every week: deep-dive expert lectures, classified industry news, priority event alerts, job opportunities, and insider commentary—designed to help you move faster, smarter, and with greater confidence. This isn’t just a newsletter; it's a strategic tool for your career and your science. “The best pharmacology teacher (Dr. Kenakin) teaming up with the best GPCR community platform to help train and inspire the next generation of scientists. Also super-valuable for those of us learning how to teach pharmacology” — Dr. GPCR Course Attendee FAQ: What You Get with Dr. GPCR Premium What’s included?  The complete Weekly News digest, curated jobs, upcoming events, classified GPCR publications, exclusive on-demand expert-led courses, and member-only discounts. Who is it for?  GPCR scientists, translational pharmacologists, biotech drug discovery teams, and decision-makers who need fast, curated, career-relevant intelligence to stay ahead. Why now?  The pace of GPCR innovation is accelerating. Those acting on the right signals today will shape tomorrow’s breakthroughs—and avoid delays others won’t see coming. Don’t Fall Behind—Access the Edge You Need 👉 Access all the news and upcoming events ➤ 👉 Already a Premium Member?  Read the Full Edition here ➤ The field of GPCRs is dynamic and competitive. To succeed, you need to move beyond standard approaches and adopt the frameworks that are driving real innovation. Dr. GPCR Premium Membership gives you direct access to the experts and insights that can redefine your work. Don’t wait for others to lead—become a Premium Member today and access the intelligence that will power your next breakthrough.

Watch Episode 171 Some careers are planned. Alessandro Nicoli’s wasn’t. Born near Venice and trained as a pharmaceutical chemist, Alessandro never imagined himself working at the cutting edge of computational GPCR research. But one academic spark—and the right mentor—changed his trajectory forever. In this blog post, we dive into his story of scientific curiosity, chance opportunities, and the unlikely road that led him to the Technical University of Munich. The Early Days: Molecules and Mentors Alessandro began his academic life studying pharmaceutical chemistry at the University of Padua. While fascinated by organic chemistry and the idea of “building molecules,” he didn’t see the big picture—until he encountered Prof. Moro , a medicinal chemist who introduced him to the interplay between molecular structure and biological function. “It was not just a molecule—it was a partner interacting with a protein or DNA… that opened a new world.” —Alessandro Nicoli This perspective changed everything. Suddenly, chemistry wasn’t just synthetic—it was strategic. He began exploring how small modifications could radically alter biological outcomes, an insight that later fueled his move toward computational research. Falling for Computational Chemistry Alessandro’s master’s thesis brought him face to face with his “second academic love”: computational chemistry . Studying cancer-related proteins (BCL2 family), he combined NMR and molecular docking to explore drug candidates. The realization that he could ask—and answer—complex biological questions with a computer sealed the deal. “Doing every day the results, I was getting in love with the topic and decided—yeah, I want to do this in my life.” —Alessandro Nicoli After graduation, a serendipitous email from Prof. Moro led him to an opportunity in Prof. Antonella Di Pizio’s lab  in Munich. Within weeks, he moved to Germany and became her first PhD student—helping build a lab from the ground up. From Empty Lab to GPCR Discovery Starting in an empty lab with just a shared desk, Alessandro and Antonella began their mission: to computationally study olfactory GPCRs , a massively under-characterized group of receptors. With hundreds of subtypes and limited ligand data, olfactory GPCRs represent a high-risk, high-reward challenge —perfect for a PhD built on curiosity and courage. “Choosing one specific receptor is difficult… they’re unique because they can bind many different molecules. Let’s embrace the challenge to study all of them.”  —Alessandro Nicoli Want to explore computational GPCR science yourself? Explore the   GPCR University  or enroll in Terry's Corner for GPCR Courses led by Dr. Terry Kenakin. ________ Keyword Cloud: #GPCRresearch #DrugDiscovery #ComputationalChemistry #MolecularModeling #MolecularDynamics #AlphaFold #StructuralBiology #InSilicoBiology

Watch Episode 170 Thinking Differently Pain research has long followed a familiar route: from molecule, to cell, to animal, to human. But as Dr. Alex Serafini  explains, this conventional bottom-up approach often fails to deliver therapies that truly help patients, especially in the pain field. In his work, Serafini emphasizes a phenotype-driven, patient-relevant perspective , where animal models closely mirror human experience before mechanistic reductionism begins. This approach reflects his focus on developing models that behave  like patients before molecular exploration takes over. "I'm particularly interested in model development... seeing if we can bring preclinical models much closer to the actual human experience than what we're using now." Learning from COVID-19 One striking example came from his COVID-19 work during his PhD. Rather than starting with a molecular hypothesis, Serafini’s team noticed that hamsters infected with SARS-CoV-2 exhibited persistent pain-like behaviors . This observation triggered deep RNA-seq profiling and new hypotheses. This patient-centric and behavior-first approach uncovered robust gene expression signatures  linked to pain, without being constrained by pre-existing assumptions about which molecular players to interrogate. Why This Approach Matters In pain research, bottom-up approaches often fail to translate. Drugs that look great in vitro fall apart in humans. By starting with phenotype-first studies , Serafini’s approach offers a translational lens more tightly aligned with clinical realities. He also integrates concepts like sex differences , epigenetic inheritance , and neuroimmune crosstalk  — factors often absent in reductionist models. This allows him to see how inflammation, cognition, and pain circuits overlap , and how GPCRs might serve as more responsive therapeutic nodes. A Call for Patient-First Science Serafini’s strategy isn’t just about method — it’s about mindset. It asks researchers to consider the entire ecosystem: from patient to molecule , not just the other way around. And it challenges the GPCR community to use its tools not just to explain, but to intervene. Takeaway We don’t need better in vitro data — we need better models of reality. Dr. Alex Serafini makes the case for building pain research from the clinic down, not the bench up. ________ Keyword Cloud: GPCR podcast , pain modeling , GPCR online course , translational research , neuroimmune signaling .

Imagine testing a molecule, seeing no response, and shelving it. But what if your system just wasn't sensitive enough  to see what it was really doing? In this eye-opening module, Terry Kenakin explores a concept that could change how you interpret pharmacological data: the interplay between intrinsic efficacy and system sensitivity. It’s not just about what your molecule does —it’s also about how capable your system is at showing it. Through powerful analogies (think batteries and balance scales), Terry reveals why different tissues—and even different assays—can paint totally different pictures of the same  compound. The result? Misinterpreted potency. Missed opportunities. And potential drug candidates left behind. From oxymetazoline to oxotremorine, discover how drugs can show up as full agonists in one system and antagonists  in another. If you're an emerging drug hunter, this lesson is your bridge from data confusion to predictive clarity. 👉 Dive into Terry’s Vault and see agonism like never before Unlock "Agonism & Sensitivity" now

Imagine running a calcium assay and discovering your compound shows only weak activity. What if that result wasn’t telling you the whole story? In this foundational lesson, Terry Kenakin dives deep into a widely used, often misunderstood tool in early drug discovery: the calcium assay. Revered for its convenience, the FLIPR assay provides rapid insights into receptor activity. But its speed comes with a cost. You’ll learn why calcium signals are inherently transient—giving rise to a “hemi-equilibrium” window that can significantly distort your understanding of drug potency. Through real-world examples (like 5-HT2A and CCR5 agonists), Terry shows how slow-onset agonists can be drastically underestimated—potentially leading promising leads to be dismissed too early. Why does this matter? Because when true pharmacological profiling is essential—like detecting partial or inverse agonism—calcium assays just don’t deliver. If you're starting out in pharmacology, this lesson gives you the interpretive tools to ask smarter questions, avoid missteps, and use calcium assays with strategic clarity. 📍 Foundational Level | Calcium Assays 📚 Part of Terry Kenakin’s Pharmacology Vault 👉 Curious what else you've been missing? Unlock "Calcium Assays" now

Imagine you're navigating a vast terrain—not on foot, but through the shape-shifting world of GPCRs. What if the static models we've relied on for decades have been hiding the truth? In this exclusive Expert Drug Hunter lesson, Terry Kenakin dismantles 100 years of receptor theory and introduces you to a dynamic new framework: Molecular Dynamics. Discover how receptors actually behave, how ligands uniquely sculpt their function, and how cryptic allosteric sites are quietly reshaping the frontier of drug discovery. This isn’t just theory, it’s a practical revolution. With the right lens, you’ll see why efficacy is more than signal strength: it's a fingerprint of conformational selection. 📍 Ready to think beyond the textbook? Step into Terry’s Vault and explore “Molecular Dynamics”—where expert drug hunters forge the future. 🔓 Access the Vault. Understand the Movement. Unlock “Molecular Dynamics” Now

Are you ready to truly understand how pharmacologists predict whole-body drug response from a single experiment?   Terry Kenakin’s newest foundational lesson in Terry's Corner  cuts straight to it:   Why models are vital for translating lab data into clinical forecasts The 4 types of pharmacologic models (and when to use each) The truth about linear models: useful or misleading? How the Mass Action Law underpins nearly every model Future of Receptor Theory: Linkage vs. Probability Models   This is practical drug development expertise from Terry’s 40+ years of experience.   Beyond the lessons, Terry's Corner  is your exclusive gateway. Ecosystem Premium Members: Look for significant savings on this and other resources in your weekly Dr. GPCR News.   Elevate your pharmacology expertise. Unlock "Pharmacologic Models" now