Structure-Activity Relationships and Design of Focused Libraries Tailored for Staphylococcus aureus Inhibition

24 February 2025, Version 1
This content is a preprint and has not undergone peer review at the time of posting.

Abstract

Staphylococcus aureus is a bacterium classified among the ESKAPE pathogens, which are anticipated to pose a significant global health emergency in the coming decades. The FabI enzyme, present in both Gram-positive and Gram-negative bacteria, is a key enzyme involved in fatty acid synthesis II (FAS-II). In this study, we utilized transformation rules to expand the chemical space from the most potent S. aureus FabI inhibitors. Three newly generated focused libraries, named INDDS, DIADS, and PYRDS, encompassed 172,026 compounds. These compounds were ranked based on structural similarity and predicted pIC50 values obtained from machine learning models. This approach allowed to prioritize compounds in each focused library targeting S. aureus FabI. We analyzed the pharmacological properties and chemical space diversity of the S. aureus FabI inhibitors to gather relevant insights and support the prioritization of compounds for further study. The three newly generated libraries are freely available at https://github.com/DIFACQUIM/S.aureus_inhibitors

Keywords

activity cliffs
chemical space
drug discovery
machine learning
ESKAPE pathogens
enoyl -acyl carrier protein reductase (FabI)
cheminformatics
multidrug-resistant bacteria
FAS-II
transformation rules

Supplementary materials

Title
Description
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Title
Supporting figures and tables
Description
Eleven supporting figures and eight tables.
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Supplementary weblinks

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