{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,20]],"date-time":"2026-05-20T22:04:46Z","timestamp":1779314686660,"version":"3.51.4"},"reference-count":153,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2024,10,30]],"date-time":"2024-10-30T00:00:00Z","timestamp":1730246400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"University of Medicine and Pharmacy Carol Davila"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Pharmaceuticals"],"abstract":"<jats:p>Background\/Objectives: HMG-CoA reductase is an enzyme that regulates the initial stage of cholesterol synthesis, and its inhibitors are widely used in the treatment of cardiovascular diseases. Methods: We have created a set of quantitative structure-activity relationship (QSAR) models for human HMG-CoA reductase inhibitors using nested cross-validation as the primary validation method. To develop the QSAR models, we employed various machine learning regression algorithms, feature selection methods, and fingerprints or descriptor datasets. Results: We built and evaluated a total of 300 models, selecting 21 that demonstrated good performance (coefficient of determination, R2 \u2265 0.70 or concordance correlation coefficient, CCC \u2265 0.85). Six of these top-performing models met both performance criteria and were used to construct five ensemble models. We identified the descriptors most important in explaining HMG-CoA inhibition for each of the six best-performing models. We used the top models to search through over 220,000 chemical compounds from a large database (ZINC 15) for potential new inhibitors. Only a small fraction (237 out of approximately 220,000 compounds) had reliable predictions with mean pIC50 values \u2265 8 (IC50 values \u2264 10 nM). Our svm-based ensemble model predicted IC50 values &lt; 10 nM for roughly 0.08% of the screened compounds. We have also illustrated the potential applications of these QSAR models in understanding the cholesterol-lowering activities of herbal extracts, such as those reported for an extract prepared from the Iris \u00d7 germanica rhizome. Conclusions: Our QSAR models can accurately predict human HMG-CoA reductase inhibitors, having the potential to accelerate the discovery of novel cholesterol-lowering agents and may also be applied to understand the mechanisms underlying the reported cholesterol-lowering activities of herbal extracts.<\/jats:p>","DOI":"10.3390\/ph17111448","type":"journal-article","created":{"date-parts":[[2024,10,30]],"date-time":"2024-10-30T09:10:44Z","timestamp":1730279444000},"page":"1448","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["QSAR Regression Models for Predicting HMG-CoA Reductase Inhibition"],"prefix":"10.3390","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9369-3314","authenticated-orcid":false,"given":"Robert","family":"Ancuceanu","sequence":"first","affiliation":[{"name":"Department of Pharmaceutical Botany and Cell Biology, Faculty of Pharmacy, Carol Davila University of Medicine and Pharmacy, 020021 Bucharest, Romania"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Patriciu Constantin","family":"Popovici","sequence":"additional","affiliation":[{"name":"Department of Pharmaceutical Botany and Cell Biology, Faculty of Pharmacy, Carol Davila University of Medicine and Pharmacy, 020021 Bucharest, Romania"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Doina","family":"Dr\u0103g\u0103nescu","sequence":"additional","affiliation":[{"name":"Department of Pharmaceutical Physics, Faculty of Pharmacy, Carol Davila University of Medicine and Pharmacy, 020021 Bucharest, Romania"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4678-9655","authenticated-orcid":false,"given":"\u0218tefan","family":"Busnatu","sequence":"additional","affiliation":[{"name":"Department of Cardiology, Carol Davila University of Medicine and Pharmacy, 020021 Bucharest, Romania"},{"name":"Emergency Hospital \u201cBagdasar-Arseni\u201d, 050474 Bucharest, Romania"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Beatrice Elena","family":"Lascu","sequence":"additional","affiliation":[{"name":"Department of Pharmaceutical Botany and Cell Biology, Faculty of Pharmacy, Carol Davila University of Medicine and Pharmacy, 020021 Bucharest, Romania"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mihaela","family":"Dinu","sequence":"additional","affiliation":[{"name":"Department of Pharmaceutical Botany and Cell Biology, Faculty of Pharmacy, Carol Davila University of Medicine and Pharmacy, 020021 Bucharest, Romania"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2024,10,30]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"23","DOI":"10.14797\/mdcj-15-1-23","article-title":"Statins: Then and Now","volume":"15","author":"Toth","year":"2019","journal-title":"Methodist DeBakey Cardiovasc. 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