Structure-Independent Peptide Binder Design via Generative Language Models

Explore cutting-edge approaches to peptide binder design using generative language models in this hour-long conference talk by Pranam Chatterjee from Valence Labs. Discover how protein language model embeddings can be leveraged to design target-specific peptides without relying on 3D structures, addressing challenges in targeting "undruggable" and intrinsically disordered proteins. Learn about novel algorithms for selecting high-affinity peptides, developing selective peptide discriminators, and generating binding peptides de novo. Gain insights into applications ranging from Cas9-PAM engineering and transcription factor-mediated cell engineering to COVID-19 diagnostics and protein targeting. The talk concludes with a Q&A session, providing an opportunity to delve deeper into this promising field of computational biology and drug discovery.