Ultra-large library screening with an evolutionary algorithm in Rosetta (REvoLd).

ABSTRACT: Ultra-large make-on-demand compound libraries now contain billions of readily available compounds. This represents a golden opportunity for in-silico drug discovery. One challenge, however, is the time and computational cost of an exhaustive screen of such large libraries when receptor flexibility is taken into account. We propose an evolutionary algorithm to search combinatorial make-on-demand chemical space efficiently without enumerating all molecules. We exploit the feature of make-on-demand compound libraries, namely that they are constructed from lists of substrates and chemical reactions. Our algorithm RosettaEvolutionaryLigand (REvoLd) explores the vast search space of combinatorial libraries for protein-ligand docking with full ligand and receptor flexibility through RosettaLigand

SUBMITTER: Eisenhuth P 

PROVIDER: S-EPMC12594993 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature