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Dr. GPCR PodcastAuthor: Dr. Yamina Berchiche
We bring you closer to dedicated scientists who work tirelessly to help understand GPCR pathophysiology. Language: en Genres: Life Sciences, Science Contact email: Get it Feed URL: Get it iTunes ID: Get it Trailer: |
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Can Simulations Predict GPCR Ligand Bias?
Episode 183
Tuesday, 17 March, 2026
How does ligand binding at the extracellular pocket of a GPCR reshape signaling on the intracellular side?Biased agonism is often measured through pathway activation assays, but the structural origin of ligand bias remains difficult to trace. Can molecular simulations reveal the communication routes that link ligand binding to G protein or arrestin signaling?In this conversation, computational biologist Anita Niveda explores how molecular dynamics and network analysis can map allosteric communication within GPCRs—revealing how microscopic structural pathways relate to macroscopic signaling outcomes. From discovering bioinformatics as an undergraduate to developing computational methods for quantifying ligand bias, the discussion moves through the scientific thinking behind modeling receptor signaling, collaborations between academia and industry, and how computational tools are becoming predictive instruments in drug discovery.Key Topics in This EpisodeHow molecular dynamics simulations reveal communication pathways connecting ligand binding sites to G protein or arrestin interfacesWhy mapping allosteric communication networks helps explain biased agonism in GPCR signalingWhat computational strategies can quantify ligand bias directly from receptor structuresHow receptor subtype selectivity emerges from subtle structural and dynamic differences in binding pocketsWhy academic–industry collaborations can accelerate method development in receptor pharmacologyWhat career decisions shape the path from computational biology training to drug discovery rolesTimestamps0:00 A structural question behind ligand bias1:30 Introduction and scientific background3:40 Discovering bioinformatics and computational biology7:30 First encounters with GPCR structural biology9:40 Finding and choosing a postdoctoral lab16:40 Entering GPCR research and allosteric communication18:20 Quantifying ligand bias using simulations20:00 Mapping signaling pathways through receptor residues23:30 Academic–industry collaboration with Boehringer Ingelheim27:00 Moving from academia to industry research35:00 Interviewing and transitioning into biotech45:00 Aha moments in computational GPCR research50:00 The diversity of GPCR families and signaling biologyKeywords: GPCR podcast, GPCR signaling, biased agonism, drug discovery, receptor pharmacology
