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Explore a groundbreaking approach to generating protein structural ensembles in this 57-minute conference talk by Bowen Jing from Valence Labs. Dive into the innovative combination of AlphaFold and flow matching techniques for modeling protein conformational landscapes. Learn how AlphaFlow and ESMFlow, sequence-conditioned generative models, outperform traditional methods in precision and diversity when trained on the Protein Data Bank. Discover how these models accurately capture conformational flexibility and ensemble properties for unseen proteins when trained on all-atom molecular dynamics simulations. Gain insights into the potential of this method as a faster alternative to expensive physics-based simulations for diversifying static protein structures. The talk covers background information, flow matching with AlphaFold, evaluation on PDB ensembles, assessment of molecular dynamics ensembles, and concludes with a discussion on MD ensembles.
