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March 2022 Crinetics Pharmaceuticals Expands Executive Team With Appointment Of James Hassard As Chief therapeutics for rare endocrine diseases and endocrine-related tumors, today announced the appointment of James Hassard as chief commercial officer. Hassard is a commercial leader with more than three decades of experience leading sales and marketing

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

Biology, Vlaams Instituut Biotechnologie, at the Vrije Universiteit Brusle, Brussels, Belgium, has been named

then moved to the UK, where he did a post-doctoral fellowship in University College London with Sir James

University School of Medicine in 1975 and then returned to join Duke’s faculty, where he remained as a James

University School of Medicine in 1975 and then returned to join Duke’s faculty, where he remained as a James