{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,4]],"date-time":"2026-10-04T19:11:34Z","timestamp":1791141094191,"version":"4.1.0"},"reference-count":79,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2025,6,13]],"date-time":"2025-06-13T00:00:00Z","timestamp":1749772800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Pharmaceuticals"],"abstract":"<jats:p>Background: Prostate cancer is the most common cancer in men, especially after the age of 50. It is a malignant disease that is increasing due to the increased life expectancy of the world population. Its development and progression are dependent on androgenic stimulation. Objectives: This study aimed to identify potential inhibitors with anti-prostate cancer activity through the application of chemoinformatics tools, exploring the Princeton (~1.2 million compounds) and Zinc Drug (~175 million compounds) databases. Methods: The methodology used several computational techniques, such as ROCS (Rapid Chemical Structure Superposition) and EON (Electrostatic Potential Screening), predictions of pharmacokinetic and toxicological properties, molecular docking, synthetic accessibility, biological activity, and molecular dynamics. Results: At the end of all these virtual screening steps, the study resulted in four promising potential candidates for the treatment of prostate cancer: the molecules ZINC34176694, ZINC03876158, ZINC04097308, and ZINC03977981, which exhibited all the desirable pharmacokinetic parameters (ADME\/Tox) for a potential drug. Conclusions: Docking and molecular dynamics studies demonstrate stability and interaction with the androgen receptor of the selected compounds, showing them to be promising candidates for the development of new drugs.<\/jats:p>","DOI":"10.3390\/ph18060888","type":"journal-article","created":{"date-parts":[[2025,6,13]],"date-time":"2025-06-13T06:19:28Z","timestamp":1749795568000},"page":"888","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Identification of Inhibitors with Potential Anti-Prostate Cancer Activity: A Chemoinformatics Approach"],"prefix":"10.3390","volume":"18","author":[{"given":"Norberto S.","family":"Costa","sequence":"first","affiliation":[{"name":"Graduate Program in Pharmaceutical Sciences, Federal University of Amap\u00e1, Macapa 68902-280, AP, Brazil"},{"name":"Laboratory of Modeling and Computational Chemistry, Department of Biological and Health Sciences, Federal University of Amap\u00e1, Macapa 68902-280, AP, Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"L\u00facio R.","family":"Lima","sequence":"additional","affiliation":[{"name":"Laboratory of Modeling and Computational Chemistry, Department of Biological and Health Sciences, Federal University of Amap\u00e1, Macapa 68902-280, AP, Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0529-3714","authenticated-orcid":false,"given":"Jorddy N.","family":"Cruz","sequence":"additional","affiliation":[{"name":"Laboratory of Modeling and Computational Chemistry, Department of Biological and Health Sciences, Federal University of Amap\u00e1, Macapa 68902-280, AP, Brazil"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Igor V. 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