RosettaAMRLD: A Reaction-Driven Approach for Structure-Based Drug Design from Combinatorial Libraries with Monte Carlo Metropolis Algorithms.

ABSTRACT: The Rosetta automated Monte Carlo reaction-based ligand design (RosettaAMRLD) integrates a Monte Carlo Metropolis (MCM) algorithm and reaction-driven molecule proposal to enhance structure-based de novo drug discovery. By leveraging combinatorial ultralarge libraries, RosettaAMRLD ensures synthetic accessibility, optimizing protein-ligand interactions while efficiently sampling accessible chemical space. Importantly, RosettaAMRLD can be initiated without a known binder, broadening its applicability to novel pharmaceutical targets. We applied RosettaAMRLD to three protein classes typically targeted by drugs, demonstrating its ability to generate novel, synthetically accessible ligands with active-like binding poses. Benchmark results show that RosettaAMRLD can propose diverse ligands

SUBMITTER: Tang Y 

PROVIDER: S-EPMC12199295 | biostudies-literature | 2025 Jun

REPOSITORIES: biostudies-literature