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Antibiotic resistance is a major threat to public health and calls for chemoinformatic tools that can help the design of antibacterial discovery libraries. We present AB-DB v2.0, a freely available online database of molecular dynamics (MD) trajectories, quantum-mechanical (QM) simulations, force field parameters, and curated physico-chemical descriptors of antimicrobial compounds. AB-DB v2.0 is fully integrated into the Molecular Dynamics Data Bank (MDDB), which provides an interactive web-based environment for visualization, exploration, and on-the-fly analysis of trajectories. QM simulations are included in the ioChem-BD platform, providing a distributed and provenance-tracked repository for computational chemistry results. The database contains more than 470 molecules belonging to 51 antimicrobial classes, including the most relevant families in clinical use, such as β β -lactams and quinolones, as well as inhibitors of key bacterial targets and peptide-based agents. Force field parameters and molecular descriptors are available for the major micro-species at physiological pH, ensuring direct reusability in MD, docking, modelling, and machine-learning workflows. Scientific Contribution By integrating MD trajectories, QM simulations, force field parameters, and curated physico-chemical descriptors in a single and inter-connected resource, AB-DB v2.0 provides a unique multidimensional framework for antimicrobial data analysis and discovery. This combination enables direct reusability in MD, docking, modelling, and machine-learning workflows.
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Gervasoni et al. (2026) studied this question.
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