biostudies-literatureGervasoni SU.S. Department of Health & Human Services | NIH | National Institute of Allergy and Infectious Diseases (NIAID)NIAID NIH HHSU.S. Department of Health & Human Services | NIH | National Institute of Allergy and Infectious DiseasesFondazione Banco di Sardegna148https://www.ebi.ac.uk/biostudies/studies/S-EPMC8976083biostudies-literatureUnknown9(1)Antibiotic resistance is a major threat to public health. The development of chemo-informatic tools to guide medicinal chemistry campaigns in the efficint design of antibacterial libraries is urgently needed. We present AB-DB, an open database of all-atom force-field parameters, molecular dynamics trajectories, quantum-mechanical properties, and curated physico-chemical descriptors of antimicrobial compounds. We considered more than 300 molecules belonging to 25 families that include the most relevant antibiotic classes in clinical use, such as β-lactams and (fluoro)quinolones, as well as inhibitors of key bacterial proteins. We provide traditional descriptors together with properties obtained with Density Functional Theory calculations. Noteworthy, AB-DB contains less conventional descriptors extracted from μs-long molecular dynamics simulations in explicit solvent. In addition, for each compound we make available force-field parameters for the major micro-species at physiological pH. With the rise of multi-drug-resistant pathogens and the consequent need for novel antibiotics, inhibitors, and drug re-purposing strategies, curated databases containing reliable and not straightforward properties facilitate the integration of data mining and statistics into the discovery of new antimicrobials.Scientific dataAB-DB: Force-Field parameters, MD trajectories, QM-based data, and Descriptors of Antimicrobials.PMC8976083R01 AI136799R01AI136799Zgurskaya HIMalloci GBosin ARuggerone PGervasoni SVargiu AVfalseAB-DB: Force-Field parameters, MD trajectories, QM-based data, and Descriptors of Antimicrobials.Antibiotic resistance is a major threat to public health. The development of chemo-informatic tools to guide medicinal chemistry campaigns in the efficint design of antibacterial libraries is urgently needed. We present AB-DB, an open database of all-atom force-field parameters, molecular dynamics trajectories, quantum-mechanical properties, and curated physico-chemical descriptors of antimicrobial compounds. We considered more than 300 molecules belonging to 25 families that include the most relevant antibiotic classes in clinical use, such as β-lactams and (fluoro)quinolones, as well as inhibitors of key bacterial proteins. We provide traditional descriptors together with properties obtained with Density Functional Theory calculations. Noteworthy, AB-DB contains less conventional descriptors extracted from μs-long molecular dynamics simulations in explicit solvent. In addition, for each compound we make available force-field parameters for the major micro-species at physiological pH. With the rise of multi-drug-resistant pathogens and the consequent need for novel antibiotics, inhibitors, and drug re-purposing strategies, curated databases containing reliable and not straightforward properties facilitate the integration of data mining and statistics into the discovery of new antimicrobials.2022-01-01T00:00:00Z2022 Apr2025-04-25T18:03:01.449Z2025-04-25T18:03:01.449ZS-EPMC89760833536566210.1038/s41597-022-01261-1