{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,24]],"date-time":"2026-02-24T12:15:41Z","timestamp":1771935341000,"version":"3.50.1"},"reference-count":39,"publisher":"Oxford University Press (OUP)","issue":"8","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2013,4,15]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Motivation: Molecular representation for small molecules has been routinely used in QSAR\/SAR, virtual screening, database search, ranking, drug ADME\/T prediction and other drug discovery processes. To facilitate extensive studies of drug molecules, we developed a freely available, open-source python package called chemoinformatics in python (ChemoPy) for calculating the commonly used structural and physicochemical features. It computes 16 drug feature groups composed of 19 descriptors that include 1135 descriptor values. In addition, it provides seven types of molecular fingerprint systems for drug molecules, including topological fingerprints, electro-topological state (E-state) fingerprints, MACCS keys, FP4 keys, atom pairs fingerprints, topological torsion fingerprints and Morgan\/circular fingerprints. By applying a semi-empirical quantum chemistry program MOPAC, ChemoPy can also compute a large number of 3D molecular descriptors conveniently.<\/jats:p><jats:p>Availability: The python package, ChemoPy, is freely available via http:\/\/code.google.com\/p\/pychem\/downloads\/list, and it runs on Linux and MS-Windows.<\/jats:p><jats:p>Contact: \u00a0yizeng_liang@263.net<\/jats:p><jats:p>Supplementary information: \u00a0Supplementary data are available at Bioinformatics online.<\/jats:p>","DOI":"10.1093\/bioinformatics\/btt105","type":"journal-article","created":{"date-parts":[[2013,3,15]],"date-time":"2013-03-15T11:03:31Z","timestamp":1363345411000},"page":"1092-1094","source":"Crossref","is-referenced-by-count":211,"title":["ChemoPy: freely available python package for computational biology and chemoinformatics"],"prefix":"10.1093","volume":"29","author":[{"given":"Dong-Sheng","family":"Cao","sequence":"first","affiliation":[{"name":"1 Research Center of Modernization of Traditional Chinese Medicines, Central South University, Changsha 410083, P. R. China, 2School of Mathematics and Statistics, Central South University, Changsha 410083, P. R. China and 3Key Laboratory of Combinatorial Biosynthesis and Drug Discovery (Wuhan University), Ministry of Education, Wuhan 430071, P. R. China"}]},{"given":"Qing-Song","family":"Xu","sequence":"additional","affiliation":[{"name":"1 Research Center of Modernization of Traditional Chinese Medicines, Central South University, Changsha 410083, P. R. China, 2School of Mathematics and Statistics, Central South University, Changsha 410083, P. R. China and 3Key Laboratory of Combinatorial Biosynthesis and Drug Discovery (Wuhan University), Ministry of Education, Wuhan 430071, P. R. China"}]},{"given":"Qian-Nan","family":"Hu","sequence":"additional","affiliation":[{"name":"1 Research Center of Modernization of Traditional Chinese Medicines, Central South University, Changsha 410083, P. R. China, 2School of Mathematics and Statistics, Central South University, Changsha 410083, P. R. China and 3Key Laboratory of Combinatorial Biosynthesis and Drug Discovery (Wuhan University), Ministry of Education, Wuhan 430071, P. R. China"}]},{"given":"Yi-Zeng","family":"Liang","sequence":"additional","affiliation":[{"name":"1 Research Center of Modernization of Traditional Chinese Medicines, Central South University, Changsha 410083, P. R. China, 2School of Mathematics and Statistics, Central South University, Changsha 410083, P. R. China and 3Key Laboratory of Combinatorial Biosynthesis and Drug Discovery (Wuhan University), Ministry of Education, Wuhan 430071, P. R. China"}]}],"member":"286","published-online":{"date-parts":[[2013,3,15]]},"reference":[{"key":"2023012810302873400_btt105-B1","doi-asserted-by":"crossref","first-page":"263","DOI":"10.1126\/science.1158140","article-title":"Drug target identification using side-effect similarity","volume":"321","author":"Campillos","year":"2008","journal-title":"Science"},{"key":"2023012810302873400_btt105-B2","doi-asserted-by":"crossref","first-page":"584","DOI":"10.1002\/cem.1321","article-title":"Prediction of aqueous solubility of druglike organic compounds using partial least squares, back-propagation network and support vector machine","volume":"24","author":"Cao","year":"2010","journal-title":"J. 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