To Design Scalable Free Energy Perturbation Networks, Optimal Is Not Enough.

ABSTRACT: Drug discovery is accelerated with computational methods such as alchemical simulations to estimate ligand affinities. In particular, relative binding free energy (RBFE) simulations are beneficial for lead optimization. To use RBFE simulations to compare prospective ligands in silico, researchers first plan the simulation experiment, using graphs where nodes represent ligands and graph edges represent alchemical transformations between ligands. Recent work demonstrated that optimizing the statistical architecture of these perturbation graphs improves the accuracy of the predicted changes in the free energy of ligand binding. Therefore, to improve the success rate of computational drug discovery, we present the open-source software package High Information Mapper (HiMap)─a new take o

SUBMITTER: Pitman M 

PROVIDER: S-EPMC10547263 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature