Benchmarking AlphaFold‐enabled molecular docking predictions for antibiotic discovery
Broad Institute · Massachusetts Institute of Technology · +2 more institutions
Abstract
Efficient identification of drug mechanisms of action remains a challenge. Computational docking approaches have been widely used to predict drug binding targets; yet, such approaches depend on existing protein structures, and accurate structural predictions have only recently become available from AlphaFold2. Here, we combine AlphaFold2 with molecular docking simulations to predict protein-ligand interactions between 296 proteins spanning Escherichia coli's essential proteome, and 218 active antibacterial compounds and 100 inactive compounds, respectively, pointing to widespread compound and protein promiscuity. We benchmark model performance by measuring enzymatic activity for 12 essential proteins treated…
Citation impact
- FWCI
- 35.01
- Percentile
- 100%
- References
- 53
Authors
8- FWFelix WongCorresponding
Broad Institute, Massachusetts Institute of Technology
- AKAarti Krishnan
Broad Institute, Massachusetts Institute of Technology
- EJErica J. Zheng
Broad Institute, Harvard University, Harvard University Press
- HSH. Stärk
Massachusetts Institute of Technology
- ALAbigail L. Manson
Broad Institute
Topics & keywords
- Biology
- Benchmarking
- Computational biology
- Docking (animal)
- Antibiotics
- Microbiology
- Medicine
- Good health and well-being
Funding
- NSNational Science FoundationAward: P41-GM103311
- UDU.S. Department of Health and Human ServicesAward: U19AI110818
- JSJames S. McDonnell Foundation
- WFWyss Foundation
- BIBroad InstituteAward: U19AI110818
- SNSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungAward: SNSF_ 203071
- NINational Institutes of HealthAwards: NIH P41-GM103311, U19AI110818, P41-GM103311, R01-AI146194
- UOUniversity of California, San FranciscoAwards: NIH P41-GM103311, P41-GM103311
- NINational Institute of General Medical SciencesAward: P41‐GM103311
- NINational Institute of Allergy and Infectious DiseasesAwards: NIH P41, R01‐AI146194, U19AI110818, R01-AI146194
- APAudacious Project