Benchmarking AlphaFold-enabled molecular docking predictions for antibiotic discovery.

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 with each antibacterial compound. We confirm extensive promiscuity, but find that

SUBMITTER: Wong F 

PROVIDER: S-EPMC9446081 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature