{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,24]],"date-time":"2026-09-24T19:29:02Z","timestamp":1790278142713,"version":"4.1.0"},"reference-count":93,"publisher":"Public Library of Science (PLoS)","issue":"2","license":[{"start":{"date-parts":[[2026,2,6]],"date-time":"2026-02-06T00:00:00Z","timestamp":1770336000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["www.plosone.org"],"crossmark-restriction":false},"short-container-title":["PLoS One"],"abstract":"<jats:p>\n                    Antimicrobial resistance (AMR) poses a major challenge in treating infections such as pneumonia and typhoid fever, necessitating novel therapeutics. Plant-derived natural products provide a promising alternative. This study evaluated dichloromethane (DCM) and methanol (MeOH) extracts of\n                    <jats:italic>Dipsacus inermis<\/jats:italic>\n                    against six bacterial strains:\n                    <jats:italic>Staphylococcus aureus<\/jats:italic>\n                    ,\n                    <jats:italic>Bacillus subtilis<\/jats:italic>\n                    ,\n                    <jats:italic>Escherichia coli<\/jats:italic>\n                    ,\n                    <jats:italic>Pseudomonas aeruginosa<\/jats:italic>\n                    ,\n                    <jats:italic>Salmonella typhi<\/jats:italic>\n                    , and\n                    <jats:italic>Enterobacter aerogenes<\/jats:italic>\n                    . Antibacterial activity was assessed following standardized CLSI guidelines for both zone of inhibition (ZOI) and minimum inhibitory concentration (MIC) assays. The DCM extract demonstrated superior activity, with ZOI values of 17.87\u2009\u00b1\u20090.23\u2009mm (\n                    <jats:italic>S. aureus<\/jats:italic>\n                    and\n                    <jats:italic>E. aerogenes<\/jats:italic>\n                    ) and 16.83\u2009\u00b1\u20090.29\u2009mm (\n                    <jats:italic>S. typhi<\/jats:italic>\n                    ), and MICs of 1.562\u2009mg\/mL (\n                    <jats:italic>B. subtilis<\/jats:italic>\n                    and\n                    <jats:italic>E. aerogenes<\/jats:italic>\n                    ) and 12.5\u2009mg\/mL (\n                    <jats:italic>S. aureus<\/jats:italic>\n                    ,\n                    <jats:italic>S. typhi<\/jats:italic>\n                    ,\n                    <jats:italic>E. coli<\/jats:italic>\n                    , and\n                    <jats:italic>P. aeruginosa<\/jats:italic>\n                    ). One-way ANOVA followed by pairwise post-hoc comparisons confirmed significant differences among extract concentrations and relative to the reference control, highlighting dose-dependent potency. GC-MS and HPLC analyses identified multiple bioactive compounds, primarily terpenoids and steroids. All identified compounds were subjected to in silico studies against DNA gyrase B, tyrosyl-tRNA synthetase, PBP2X, PBP4, and DHFR. Compounds DI10 and DI31 emerged as potent multi-target leads, while DI22 exhibited selective activity against PBP4. ADMET profiling indicated favorable pharmacokinetics, high intestinal absorption, and minimal toxicity risks. DFT and MESP analyses revealed electronic features and reactive sites critical for ligand-protein interactions. Molecular dynamics simulations confirmed stable protein-ligand complexes, with RMSD stabilizing at 1.5-2.5 \u00c5, compact conformations (Rg: 16.3-21.6 \u00c5), persistent hydrogen bonds, and favorable binding free energies (\u221245 to \u221252 kcal\/mol) via MM-PBSA. These integrated\n                    <jats:italic>in vitro<\/jats:italic>\n                    and\n                    <jats:italic>in silico<\/jats:italic>\n                    findings indicate that DCM-derived compounds, particularly DI10 and DI31, are primarily responsible for the observed antibacterial activity and represent promising candidates for antimicrobial drug development.\n                  <\/jats:p>","DOI":"10.1371\/journal.pone.0341424","type":"journal-article","created":{"date-parts":[[2026,2,6]],"date-time":"2026-02-06T18:33:01Z","timestamp":1770402781000},"page":"e0341424","update-policy":"https:\/\/doi.org\/10.1371\/journal.pone.corrections_policy","source":"Crossref","is-referenced-by-count":2,"title":["Identification of antimicrobial compounds in Dipsacus inermis via phytochemical profiling, in vitro assessment, and advanced computational 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Alzahrani","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Abida","family":"Khan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Muhammad Umer","family":"Khan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"340","published-online":{"date-parts":[[2026,2,6]]},"reference":[{"key":"pone.0341424.ref001","doi-asserted-by":"crossref","DOI":"10.1201\/9781420004472","volume-title":"Natural products from plants","author":"LJ Cseke","year":"2016"},{"key":"pone.0341424.ref002","unstructured":"Nowozin S, Cseke B, Tomioka RJAINIS. f-gan: Training generative neural samplers using variational divergence minimization. 2016. 29."},{"issue":"7","key":"pone.0341424.ref003","doi-asserted-by":"crossref","first-page":"2038","DOI":"10.1021\/acs.jnatprod.9b00110","article-title":"Bioactive secondary metabolites from bacillus subtilis: a 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