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A Final Aha Moment: Try the Crazy Idea When a collaborator offered a neuroma model (one where opioids _____ Keyword Cloud: GPCR online course, early-career scientists, imposter syndrome, GPCR podcast, neuroma model

“We’ve seen these modulators rescue opioid function where it completely fails in neuroma models. .” – Ben Clements By combining chronic pain models with receptor-level pharmacology, Ben is bridging molecule to model, and model to patient. Neuropathic conditions like neuromas often resist standard opioid treatments. collaborations across medicinal chemistry and neuropathic pain research, Ben is bridging molecule to model

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. Unlock "Pharmacologic Models" now

Watch Episode 175 From failed assays to breakthroughs in GPCR modeling , Dr. A professor highlighted Carlsson’s talent in molecular modeling, a skill he hadn’t yet recognized as While others refined lab techniques, he found himself gravitating toward structural models in his spare Predictive GPCR-Ligand Modeling Carlsson's work quickly shifted from curiosity to impact. It's not enough to run simulations or generate models.

GPCRs demanded something different: the integration of modeling, medicinal chemistry, and pharmacology Predictions from modeling inform chemistry. Chemistry fuels assays. Assay data flows back into models. The cycle only works because every part is connected .   His group is trained to explain exactly what a model can predict and where its limits are. He treats modeling as part of a continuum rather than a separate discipline.

Models are the bridge. With a model, you don’t guess. You project. It’s signal—once the model interprets it. Models as Experimental Guides Models don’t just interpret results. They design experiments. Are Models Ever Proven? Here’s the uncomfortable truth: you can never prove a model “right.”

Watch Episode 175 If your model can’t predict the future of GPCR drug discovery, why build it at all? Carlsson’s group integrates modeling with mechanistic pharmacology. For scientists, this is an intellectual challenge: demand more from your models.  The next frontier in GPCR drug discovery isn’t more structures—it’s smarter models. Want to go deeper into GPCR modeling? Dr.

In his work, Serafini emphasizes a phenotype-driven, patient-relevant perspective , where animal models This approach reflects his focus on developing models that behave  like patients before molecular exploration "I'm particularly interested in model development... seeing if we can bring preclinical models much closer Takeaway We don’t need better in vitro data — we need better models of reality. Dr. . ________ Keyword Cloud: GPCR podcast , pain modeling , GPCR online course , translational research

Must-read publications:  β-arrestin2-biased allosteric modulator for pain beyond opioids & GPR3 regulated by a negative allosteric modulator Terry's Corner – Determine GPCR MoA Early (and Right) Early discovery This week’s Terry’s Corner lesson shows how to replace inference with models that disentangle mechanism—so You’ll apply a model-first workflow to classify orthosteric vs. allosteric behavior, stress-test assumptions

Terry's Corner - New Course on Pharmacologic Models The latest Terry’s Corner unlocks clinical forecasting   ✅ Avoid costly errors:  Master vital models to confidently forecast outcomes, before it’s too late

Watch Episode 167 Today’s GPCR scientists don’t want to study one interaction, they want to model the visiting scientists are already expanding this work, bringing in computational layers  like AlphaFold to model

Batman ) and master the Hall model  to decode the thermodynamics behind complex binding behavior . Real-world case studies showing binding-function dissociation and residual signal effects ✅ Tools to model Thermodynamics > Intuition: Why the Hall Cube Matters To untangle complex binding behaviors, you need a model Kenakin introduces the Hall model : a cube mapping allosteric and orthosteric interactions, layered with This lecture gives you the language, models, and mindset  to interpret these systems correctly and act

October 2022 Comparative studies of AlphaFold, RoseTTAFold and Modeller: a case study involving the use Although the overall accuracy of the two non-homology-based modeling methods, AlphaFold and RoseTTAFold for GPCRs with the most widely used template-based software-Modeller. If only looking at each program's top-scored structure, Modeller had the smallest average modeling RMSD 73 cases with the top-scored model, respectively, where no good templates were available for Modeller

vitro and in situ chemical crosslinking, disulfide pattern analysis, and mutation data with molecular modeling to generate experimentally driven full-length models. These models provide insights into the interface, important side-chain interactions, and activation mechanism The models are expected to allow for testable hypotheses about signal transduction and drug development

September 2022 Dynamics of tumor-associated macrophages in a quantitative systems pharmacology model of immunotherapy in triple-negative breast cancer "Quantitative systems pharmacology (QSP) modeling is immuno-suppressive tumor microenvironment, we incorporated the dynamics of TAMs into our previously published QSP model We show that through proper calibration, the model captures the macrophage heterogeneity in the tumor

Changes the Game in Drug Discovery For decades, drug discovery pipelines have relied on the orthosteric model But that model is no longer sufficient. Unexpected activity profiles, SAR that breaks your QSAR model, and missed opportunities to design more You’ll walk away with tools to: Interpret probe-dependent effects Model and anticipate longer equilibration Outdated models can mislead your team, waste your resources, and cost your pipeline months of progress

Enter AlphaFold: Predicting the “Face” of a Receptor When Alessandro began his PhD, structural models of struggling to predict structures from scratch, Alessandro and others could now use AI-generated models “…now you have a plethora of 400 models that you can start with molecular dynamics, docking, virtual By iteratively refining the models with docking and mutagenesis data, they developed predictive pipelines Want to level up your modeling skills?

October 2022 Bell-Evans model and steered molecular dynamics in uncovering the dissociation kinetics approach of combining the data derived from steered molecular dynamics simulations and the Bell-Evans model

Accordingly, in these hiPSC-derived hNPCs and neurons, we observe a shortening of PC. Additionally, we detect a shortening of PC in PINK1-deficient human cellular and mouse models of familial Furthermore, in sPD models, the shortening of PC is accompanied by increased Sonic Hedgehog (SHH) signal

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

August 2022 "The common mechanisms by which members of the G protein-coupled receptor (GPCR) family respond to neurotransmitters in the brain have been well studied. However, it is becoming increasingly clear that GPCRs show great diversity in their intracellular location, interacting partners and effectors, and signaling consequences. Here we will discuss recent studies on the diversity of location, effectors, and signaling of GPCRs, and how these could interact to generate specific spatiotemporal patterns of GPCR signaling in cells." Read more at the source #DrGPCR #GPCR #IndustryNews

But in Melbourne, a quiet experiment challenged that model — and it worked. Funding models rewarded independence, not shared resources. Engineering Collaboration: The Monash Lab Model Traditional academic labs mirror feudal structures. The Monash model flipped that logic: Shared infrastructure, not duplicated equipment Centralized core What Changed After This Data The pooled funding model turned the lab into a magnet: postdocs, visiting

analysis of a series of GPCRs whose activity has been shown to affect the lifespan of animal and human models

regulated by membrane potential in vitro, but whether the voltage dependence of GPCRs contributes to neuronal Here we show that muscarinic GPCR mediated neuronal potentiation in vivo is voltage dependent. the voltage dependency of GPCRs by demonstrating crucial involvement of GPCR voltage dependence in neuronal Thus, this study suggests that GPCR voltage dependency plays a role in many diverse neuronal functions

Neuronal Gα subunits required for the control of response to polystyrene nanoparticles in the range of μg/L in C. elegans The aim of this study was to identify Gα proteins mediating function of neuronal Caenorhabditis elegans was used as an animal model, and both gene expression and functional analysis Among these 7 Gα genes, only neuronal RNAi knockdown of gsa-1, gpa-10, and goa-1 affected toxicity of of GOA-1, some neuronal GPCRs (such as DCAR-1, DOP-2, NPR-9, NPR-8, and DAF-37) functioned upstream

August 2022 GPR3 expression in retinal ganglion cells contributes to neuron survival and accelerates The axonal degeneration that occurs before retinal ganglion neuronal loss is suggested to be involved Our earlier reports suggested that GPR3 enhances both neurite outgrowth and neuronal survival. However, the potential role of GPR3 in axonal regeneration after neuronal injury has not been elucidated and neuronal survival.

receptors (GPCRs), including the parathyroid hormone 1 receptor (PTH1R), a class B GPCR and an important modulator activation of PTH1R and its downstream signaling, we describe here that RAMP2 acts as a specific allosteric modulator Moreover, RAMP2 modulates PTH1R downstream signaling in an agonist-dependent manner, most notably increasing Employing homology modeling, we describe the putative structural molecular basis underlying our functional of RAMPs in the activation and signaling of a GPCR that may provide a new venue for highly specific modulation

October 2022 "Over three decades of research have provided thorough insights into G protein-coupled receptor (GPCR) regulation. In a recent issue of Molecular Cell, Fonseca et al. identified a previously overlooked desensitization mechanism. Agonist activation of the β2-adrenoceptor (β2AR) causes its S-nitrosylation that is required for the receptor to internalize and desensitize. Eliminating β2AR S-nitrosylation by mutation of C265 augments β2AR protein kinase A signaling, enables β2AR nitric oxide (NO) signaling, renders mice resistant to bronchoconstriction, and protects mice from allergen-induced asthma." Read more at the source #DrGPCR #GPCR #IndustryNews

We report that arrestin-3 modulates Fgr activity with a hallmark bell-shaped concentration-dependence interaction, we determined the crystal structure of the Fgr SH3 domain at 1.9 Å resolution and developed a model This model suggests that Fgr interacts with arrestin-3 at multiple sites and is consistent with the locations

Latrophilin-1 drives neuron morphogenesis and shapes chemo- and mechanosensation-dependent behavior in Detailed expression and RNA-Seq analyses revealed specific LAT-1-positive neurons and first insights into the genetic network that is modulated by the receptor function. We conclude that 7TM-independent functions of Latrophilins are essential for neuronal physiology, possibly