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Introducing ligand GA, a genetic algorithm molecular tool for automated protein inhibitor design.

ABSTRACT: Ligand GA is introduced in this work and approaches the problem of finding small molecules inhibiting protein functions by using the protein site to find close to optimal or optimal small molecule binders. Genetic algorithms (GA) are an effective means for approximating or solving computationally hard mathematics problems with large search spaces such as this one. The algorithm is designed to include constraints on the generated molecules from ADME restriction, localization in a binding site, specified hydrogen bond requirements, toxicity prevention from multiple proteins, sub-structure restrictions, and database inclusion. This algorithm and work is in the context of computational modeling, ligand design and docking to protein sites.

SUBMITTER: Chalmers G

PROVIDER: S-EPMC9719503 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature

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Introducing ligand GA, a genetic algorithm molecular tool for automated protein inhibitor design.

Chalmers Gordon G

Scientific reports 20221203 1

Ligand GA is introduced in this work and approaches the problem of finding small molecules inhibiting protein functions by using the protein site to find close to optimal or optimal small molecule binders. Genetic algorithms (GA) are an effective means for approximating or solving computationally hard mathematics problems with large search spaces such as this one. The algorithm is designed to include constraints on the generated molecules from ADME restriction, localization in a binding site, sp ...[more]

PMID: 36463310

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Dataset Information

Introducing ligand GA, a genetic algorithm molecular tool for automated protein inhibitor design.

Publications

Introducing ligand GA, a genetic algorithm molecular tool for automated protein inhibitor design.

Similar Datasets

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