BactProNET: A Structural-Mechanistic Platform for Deciphering Target-Mediated Antimicrobial Resistance

Antibiotics are the frontline therapy for bacterial infections, yet their efficacy is critically threatened by antimicrobial resistance (AMR), a crisis largely driven by mutations in protein targets. While this mechanism is prevalent, data on its structural impact remains highly dispersed, and existing resources like CARD and ResFinder prioritize gene identification over mechanistic insight. To address this gap, we developed BactProNET, a bioinformatics platform for the structural and evolutionary analysis of target-mediated resistance. Its core innovation is a multi-level data integration that establishes a "wild-type reference system" for mechanistic inference. The platform integrates curated resistance mutations with AlphaFold 2-predicted 3D structures, molecular docking models defining an "optimal binding" baseline, and integrated phylogenetic and sequence alignment views. Currently housing data on 110 protein targets, 205 mutation sites, and 644 docking models, BactProNET is accessible via an interface with embedded BLAST and MSA tools. As a one-stop platform, it accelerates the understanding of AMR's molecular mechanisms and provides a robust, data-driven foundation for the rational design of next-generation antimicrobial drugs.