Cited by 193Computational Drug Discovery MethodsChemical Synthesis and AnalysisSynthesis and Characterization of Heterocyclic Compounds

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Modeling the expansion of virtual screening libraries

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Lyu, Jiankun, Irwin, John J., Shoichet, Brian K.·2023·Nature Chemical Biology

DOI 10.1038/s41589-022-01234-wPMC PMC10243288

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Abstract

Recently, 'tangible' virtual libraries have made billions of molecules readily available. Prioritizing these molecules for synthesis and testing demands computational approaches, such as docking. Their success may depend on library diversity, their similarity to bio-like molecules and how receptor fit and artifacts change with library size. We compared a library of 3 million 'in-stock' molecules with billion-plus tangible libraries. The bias toward bio-like molecules in the tangible library decreases 19,000-fold versus those 'in-stock'. Similarly, thousands of high-ranking molecules, including experimental actives, from five ultra-large-library docking campaigns are also dissimilar to bio-like molecules. Meanwhile, better-fitting molecules are found as the library grows, with the score improving log-linearly with library size. Finally, as library size increases, so too do rare molecules that rank artifactually well. Although the nature of these artifacts changes from target to target, the expectation of their occurrence does not, and simple strategies can minimize their impact.

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Authors: Lyu, J., Irwin, J. J., & Shoichet, B. K.
Affiliations: University of California, San Francisco (US)
Corresponding author: Irwin, John J.
Shoichet, Brian K.
ORCID: Lyu, Jiankun
Irwin, John J.
Shoichet, Brian K.
Venue: Nature Chemical Biology
Publisher: Springer Science and Business Media LLC
Published: 2023-01-16
Volume: 19
Issue: 6
Pages: 712-718
ISSN: 1552-4450 (ISSN-L)
1552-4469
DOI: 10.1038/s41589-022-01234-w
PMC: PMC10243288
OpenAlex: W4316507591
Cited by: 193
References: 53
Citations by year: 2026: 49 · 2025: 57 · 2024: 55 · 2023: 31
FWCI: 27.17
Type: journal article
Language: en
Open access: bronze
doi.org
Licence: www.springernature.com/gp/researchers/text-and-data-mining (tdm)
www.springernature.com/gp/researchers/text-and-data-mining (vor)
Locations: Nature Chemical Biology (publishedVersion)
ChemRxiv (acceptedVersion, cc-by-nc-nd)
PubMed (publishedVersion)
PubMed Central (acceptedVersion)
eScholarship (California Digital Library) (submittedVersion)
Funders: U.S. Department of Health & Human Services | NIH | National Institute of General Medical Sciences (GM133836, R35GM122481)
Topics: Life Sciences › Pharmacology, Toxicology and Pharmaceutics › Drug Discovery › Computational Drug Discovery Methods
Physical Sciences › Chemistry › Organic Chemistry › Chemical Synthesis and Analysis
Physical Sciences › Chemistry › Organic Chemistry › Synthesis and Characterization of Heterocyclic Compounds
Keywords: library size, molecular diversity, molecular similarity, protein-ligand docking
MeSH terms: Libraries, Digital, Molecular Docking Simulation

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