TwoFold: highly accurate structure and affinity prediction for protein-ligand complexes from sequences
DescriptionWe describe our development of ab initio protein-ligand binding pose prediction models based on transformers and binding affinity prediction models based on the neural tangent kernel (NTK). Folding both protein and ligand, the TwoFold models achieve efficient and quality predictions matching state-of-the-art implementations while additionally reconstructing protein structures. NTK and Gaussian Process models are demonstrated to be a worthy use of HPC resources for AI, and the advantages of adapting highly-optimized linear solver benchmarking codes to solve the large dense linear systems required by these models are shown.
Authors
Event Type
ACM Gordon Bell COVID Finalist
ACM Gordon Bell Finalist
Awards Presentation
TimeWednesday, 16 November 202211:30am - 12pm CST
LocationC144-145
Recorded
Awards
TP