{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,30]],"date-time":"2025-07-30T15:48:29Z","timestamp":1753890509837,"version":"3.41.2"},"reference-count":56,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2022,11,22]],"date-time":"2022-11-22T00:00:00Z","timestamp":1669075200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["81874288 92053105 82003590"],"award-info":[{"award-number":["81874288 92053105 82003590"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100017445","name":"Natural Science Fund for Distinguished Young Scholars of Shandong Province","doi-asserted-by":"publisher","award":["ZR2019LZL004 ZR2020QH342"],"award-info":[{"award-number":["ZR2019LZL004 ZR2020QH342"]}],"id":[{"id":"10.13039\/100017445","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Chem."],"abstract":"<jats:p>As a potent zinc chelator, hydroxamic acid has been applied in the design of inhibitors of zinc metalloenzyme, such as histone deacetylases (HDACs). A series of hydroxamic acids with HDAC inhibitory activities were subjected to the QSRR (Quantitative Structure\u2013Retention Relationships) study. Experimental data in combination with calculated molecular descriptors were used for the development of the QSRR model. Specially, we employed PCA (principal component analysis) to accomplish dimension reduction of descriptors and utilized the principal components of compounds (16 training compounds, 4 validation compounds and 7 test compounds) to execute GA (genetic algorithm)-BP (error backpropagation) algorithm. We performed double cross-validation approach for obtaining a more convincing model. Moreover, we introduced molecular interaction-based features (molecular docking scores) as a new type of molecular descriptor to represent the interactions between analytes and the mobile phase. Our results indicated that the incorporation of molecular interaction-based features significantly improved the accuracy of the QSRR model, (R<jats:sup>2<\/jats:sup> value is 0.842, RMSEP value is 0.440, and MAE value is 0.573). Our study not only developed QSRR model for the prediction of the retention time of hydroxamic acid in HPLC but also proved the feasibility of using molecular interaction-based features as molecular descriptors.<\/jats:p>","DOI":"10.3389\/fchem.2022.1056701","type":"journal-article","created":{"date-parts":[[2022,11,22]],"date-time":"2022-11-22T05:41:00Z","timestamp":1669095660000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":3,"title":["Development of QSRR model for hydroxamic acids using PCA-GA-BP algorithm incorporated with molecular interaction-based features"],"prefix":"10.3389","volume":"10","author":[{"given":"Yiming","family":"Nie","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jia","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xinying","family":"Yang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xuben","family":"Hou","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hao","family":"Fang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1965","published-online":{"date-parts":[[2022,11,22]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"1972","DOI":"10.3390\/pharmaceutics14091972","article-title":"Application of DFT calculations in designing polymer-based drug delivery systems: An overview","volume":"14","author":"Adekoya","year":"2022","journal-title":"Pharmaceutics"},{"key":"B2","doi-asserted-by":"publisher","first-page":"1316","DOI":"10.1021\/acs.jcim.5b00206","article-title":"Beware of R(2): Simple, unambiguous assessment of the prediction accuracy of QSAR and QSPR models","volume":"55","author":"Alexander","year":"2015","journal-title":"J. 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