Data and code for: Molecular Dynamics and AI-Assisted Ligand Generation Identify a Cryptic Binding Site Candidate in CTX-M-15 beta-lactamase

Résumé fourni par la source

This dataset supports the manuscript “Molecular Dynamics and AI-Assisted Ligand Generation Identify a Cryptic Binding Site Candidate in CTX-M-15 beta-lactamase.” The archive contains data and code from a computational workflow used to identify and evaluate a ligand-stabilized adjacent pocket (LSAP) candidate in CTX-M-15 beta-lactamase. The workflow included replicate molecular dynamics simulations of apo and avibactam-bound CTX-M-15, fpocket-based ensemble pocket detection, Pocket2Mol ligand generation, short protein-ligand molecular dynamics triage, and final triplicate 200 ns simulations of four LSAP-centered candidate molecules. The archive includes raw production output files for the six initial apo and avibactam-bound holoenzyme 200 ns simulations, fpocket screening outputs, selected pocket files, Pocket2Mol input and output files from the first-round and LSAP-centered generation stages, source files and summary outputs for 20 ns triage simulations, processed/fitted 200 ns trajectories for the four final LSAP-centered candidates, representative protein-ligand structures, analysis scripts, tabulated source data, file manifests, and SHA256 checksums. The data are intended to support reproduction of the reported manuscript figures, tables, screening-funnel summaries, protein-stability analyses, ligand-to-LSAP distance analyses, and final LSAP-associated fraction calculations. These files document computational discovery and prioritization only; they do not constitute experimental evidence of ligand binding affinity, enzymatic inhibition, or an allosteric mechanism.

Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.