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Congrats to: Ya-Tzu Li , our notable contributor, for her superb undergrad paper along with Hao-Jen Hsu , Chun-Chun Chang , et al.   Drugs like Ozempic will change the world GPCR Events, Meetings, and Webinars November 5 - 7, 2024 | 16th

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

allosteric modulators with built-in selectivity and context sensitivity Why GPCR Allosteric Thinking Changes Ligands don’t just “bind”—they change  the receptor. These changes can alter how the receptor talks to G proteins, arrestins, or other receptors. muscarinic receptors, CCR5 chemokine programs, and NMDA receptors, where ligand context fundamentally changes But without understanding how GPCR state changes  influence that affinity—or vice versa—drug discovery

April 2022 Sosei Heptares Confirms Senior Leadership Changes to Drive the Company Through the Next Stage Sosei Group Corporation (“the Company”; TSE: 4565) today confirms that a series of Executive Management changes

Obesity-induced changes in human islet G protein-coupled receptor expression: Implications for metabolic

⚠️Mark your calendar for the Dr. GPCR Summit 2022 held between Oct. 10 - 16, it's FREE! Join the #GPCR movement by signing up now! ➡️ https://bit.ly/3cKMXlw #gpcr #drgpcr

publication-quality, high-impact, and strategically focused This approach allowed him to avoid the experimental churn

modulators (NAMs), that fully or partially dampen the receptor's functional response to the ligand (Wold, Chen or more of the following pharmacological characteristics: 1) affinity modulation where the resulting change substantial doses of allosteric modulators with a diminished risk of target-related toxicity (Wold, Chen

Adapted from: Zhang Y, Tang H, Chen W, Zhang J. is most effective at studying interactions between large proteins and small ligands thanks to this change

This process is a binding event that facilitates a change in the shape of a macromolecule which impacts post-translational modification, or protein interactions, allowing proteins to sense and respond to changes structure, its molecular interactions with various ligands and canonical Gαq transducer, and conformational changes González-Maeso J, Weisstaub NV, Zhou M, Chan P, Ivic L, Ang R, et al. Teng X, Chen S, Wang Q, Chen Z, Wang X, Huang N, et al.

Following extracellular stimulus detection, receptor activation initiates conformational changes, exposing F et al. 2021, Chen, H. et al. 2022). fluorescence microscopy assays employ conformation-selective probes for monitoring activation-induced changes not all receptors recruit both isoforms equally and arrestins can undergo different conformational changes Changes in the availability of regulatory proteins like GRKs can impact GPCR phosphorylation and subsequent

Through developing a high-resolution method, Hao Chen et al. directly visualized the fusion of vesicles Zhang, A.J.M. Molina, T.C. Südhof, and R.C. Malenka. 2013. Chen, X. Zhang, and L. Ma. 2008.

Hauser Calcineurin-fusion facilitates cryo-EM structure determination of a Family A GPCR Jun Xu , Geng Chen Ramona Birke , Joshua Levitz , Ben Jones , Johannes Broichhagen Design of allosteric modulators that change This change is all about keeping our community strong and delivering top-notch content. the discovery of antibodies, which recognized native receptor Design of allosteric modulators that change predicted by combinatorial computational strategy Uncovering conserved networks and global conformational changes

Upon activation, GPCRs have conformational changes that allow the coupling and subsequent activation Liu-Chen, and J.R.

structural perspective, the -4 position of αH5 was key for the selectivity of G-protein coupling, since the change , Z., Liu, C., Li, X., Zhu, X., Wang, N., Xu, Z., Xia, R., Liang, J., Duan, Y., Yin, H., Xiong, Y., Zhang , A., Guo, C., Chen, Z., Huang, Z., & He, Y. (2022).

the lipid composition of intracellular membranes may influence GPCR dynamics and signaling outcomes, changing Pharmaceuticals (Basel, Switzerland), 14(5), 439. https://doi.org/10.3390/ph14050439 Chen, K. Z., Wilderman, A., Katakia, T., McCann, T., Yokouchi, H., Zhang, L., Corriden, R., Liu, D., Feigin, M

Fluorescence Anisotropy and BBV – The theory behind the assays FA is based on measuring the change in Figure 1.Time course of FA change caused by CELT-419 binding to D3 receptor on the BBV particles. The insert shows the Log(IC50) ± SE change in time of corresponding displacement curves. The Log(IC50) change in time was fitted with equation  3  and k given is the weighted average from 3  Change in FA level was measured after incubation of 0.5 nM CELT-419, 1 μL BBV/well (CD3R = 0.7 nM), and

al. 2012, Scurci, Akondi et al. 2021, Verhallen, Lackman et al. 2023), which provide extra negative charges Conformational changes between inactive and active states are facilitated by a "microswitch network" inverse agonist (maraviroc) (Tan, Zhu et al. 2013, Zheng, Han et al. 2017, Isaikina, Tsai et al. 2021, Zhang , Chen et al. 2021). , exhibits bias toward G-protein signaling, which has been structurally related to a conformational change

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 —Alessandro Nicoli This perspective changed everything.

Cambridge Fellowship  — Precision meets scale Leadership at MIPS  — Turning questions into impact What Changed She built on chance moments with deliberate moves—grants pursued, labs chosen, collaborations built. Why GPCR Spatial Signaling Is Changing Drug Discovery Today, Michelle leads the Spatial Organization laboratory, asking a deceptively simple question: where  do GPCR signals happen—and how does location change

This wasn’t just a clever idea on paper — it changed how science happened, day to day. This changed not just what got funded, but what was possible . What Changed After This Data The pooled funding model turned the lab into a magnet: postdocs, visiting Culture as Infrastructure: How Trust Was Built Collaboration at this scale doesn’t happen by chance.

It’s a chance to stand shoulder-to-shoulder with peers from across the globe and the Boston biotech scene America, NIS delivers cutting-edge imaging and analysis that accelerates the discovery of new and life-changing Register Now 👉 Bring a colleague you trust . 👉 Don’t miss the chance to be part of the conversations

We are closely monitoring any regulation changes from both Boston and Massachusetts with regard to in-person If there are any changes made that will impact our ability to hold the event in-person, we will notify Don't miss the chance to present your innovative research at this year's conference.

While her work there focused on immunological changes in pregnancy—not addiction—it was a valuable chapter Catherine's experience serves as a reminder that it is never too late to change direction and pursue Embracing Change and Uncertainty Change can be daunting, especially when it involves stepping away from illustrates the power of following one's passion and the importance of being adaptable in the face of change Catherine's experience serves as an inspiration for anyone considering a career change or seeking to

And that shift changed everything. This accidental tool changed that. Collaboration, Chemistry, and the Pivot That Changed the Project Goal:  Develop a photo-switchable GPCR What Changed After This Data This imaging tool is now being used to: Re-evaluate where GLP-1 and GIP

These probes shift brightness and fluorescence lifetime as pH changes. “You’re not changing the spectrum. You’re just changing how bright it is—and how long it glows,” said Dr. Eric Trinquet. To hear the full story of how pHSense came to life—and why the GLP-1 data changed everything— 🎧 Listen

Furthermore, image-based data provide an additional check against off-target cytotoxicity or morphological changes Notably, no compound displayed toxicity or morphological changes at this concentration, supporting the Ki values were then calculated using the Cheng–Prusoff equation, with CELT-331 parameters fully reported evaluate affinity jumps between analogues, image data can help resolve questions such as: Is the signal change

These receptors respond to a variety of signals by undergoing structural changes that activate internal brief sequential intervals following GTP addition, the research team identified the conformational changes The captured structures reveal a dynamic of conformational changes initiated by the binding of an agonist This early interaction sets the stage for a cascade of significant conformational changes. Concurrently, the α1 helix extends, propagating structural changes throughout the G protein.

Kenakin’s latest lecture delivers a game-changing framework for teams grappling with the gap between This lecture is a guide to understanding why intracellular drug access changes everything: from target scaffold permeability using modern, cost-effective pharmacokinetic assays   Why Intracellular GPCR Drugs Change

In this eye-opening module, Terry Kenakin explores a concept that could change how you interpret pharmacological