Accurate Binding Free Energy Method from End-State MD Simulations.

ABSTRACT: Herein, we introduce a new strategy to estimate binding free energies using end-state molecular dynamics simulation trajectories. The method is adopted from linear interaction energy (LIE) and ANI-2x neural network potentials (machine learning) for the atomic simulation environment (ASE). It predicts the single-point interaction energies between ligand-protein and ligand-solvent pairs at the accuracy of the wb97x/6-31G* level for the conformational space that is sampled by molecular dynamics (MD) simulations. Our results on 54 protein-ligand complexes show that the method can be accurate and have a correlation of R = 0.87-0.88 to the experimental binding free energies, outperforming current end-state methods with reduced computational cost. The method also allows us to compare BFEs

SUBMITTER: Akkus E 

PROVIDER: S-EPMC9472276 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature