{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,5]],"date-time":"2026-06-05T11:16:00Z","timestamp":1780658160725,"version":"3.54.1"},"reference-count":43,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2012,11,27]],"date-time":"2012-11-27T00:00:00Z","timestamp":1353974400000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/2.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Cheminform"],"published-print":{"date-parts":[[2012,12]]},"abstract":"<jats:title>Abstract<\/jats:title>\n          <jats:sec>\n            <jats:title>Background<\/jats:title>\n            <jats:p>In this work, we analyzed and compared the distribution profiles of a wide variety of molecular properties for three compound classes: drug-like compounds in MDL Drug Data Report (MDDR), non-drug-like compounds in Available Chemical Directory (ACD), and natural compounds in Traditional Chinese Medicine Compound Database (TCMCD).<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Results<\/jats:title>\n            <jats:p>The comparison of the property distributions suggests that, when all compounds in MDDR, ACD and TCMCD with molecular weight lower than 600 were used, MDDR and ACD are substantially different while TCMCD is much more similar to MDDR than ACD. However, when the three subsets of ACD, MDDR and TCMCD with similar molecular weight distributions were examined, the distribution profiles of the representative physicochemical properties for MDDR and ACD do not differ significantly anymore, suggesting that after the dependence of molecular weight is removed drug-like and non-drug-like molecules cannot be effectively distinguished by simple property-based filters; however, the distribution profiles of several physicochemical properties for TCMCD are obviously different from those for MDDR and ACD. Then, the performance of each molecular property on predicting drug-likeness was evaluated. No single molecular property shows good performance to discriminate between drug-like and non-drug-like molecules. Compared with the other descriptors, fractional negative accessible surface area (FASA-) performs the best. Finally, a PCA-based scheme was used to visually characterize the spatial distributions of the three classes of compounds with similar molecular weight distributions.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Conclusion<\/jats:title>\n            <jats:p>If FASA- was used as a drug-likeness filter, more than 80% molecules in TCMCD were predicted to be drug-like. Moreover, the principal component plots show that natural compounds in TCMCD have different and even more diverse distributions than either drug-like compounds in MDDR or non-drug-like compounds in ACD.<\/jats:p>\n          <\/jats:sec>","DOI":"10.1186\/1758-2946-4-31","type":"journal-article","created":{"date-parts":[[2012,11,27]],"date-time":"2012-11-27T05:27:06Z","timestamp":1353994026000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":73,"title":["Drug-likeness analysis of traditional Chinese medicines: 1. property distributions of drug-like compounds, non-drug-like compounds and natural compounds from traditional Chinese medicines"],"prefix":"10.1186","volume":"4","author":[{"given":"Mingyun","family":"Shen","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sheng","family":"Tian","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Youyong","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qian","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaojie","family":"Xu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Junmei","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tingjun","family":"Hou","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2012,11,27]]},"reference":[{"key":"351_CR1","doi-asserted-by":"publisher","first-page":"1011","DOI":"10.2174\/1381612043452721","volume":"10","author":"TJ Hou","year":"2004","unstructured":"Hou TJ, Xu XJ: Recent development and application of virtual screening in drug discovery: An overview. Curr Pharm Des. 2004, 10: 1011-1033. 10.2174\/1381612043452721.","journal-title":"Curr Pharm Des"},{"key":"351_CR2","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1016\/S0169-409X(96)00423-1","volume":"23","author":"CA Lipinski","year":"1997","unstructured":"Lipinski CA, Lombardo F, Dominy BW, Feeney PJ: Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Adv Drug Deliver Rev. 1997, 23: 3-25. 10.1016\/S0169-409X(96)00423-1.","journal-title":"Adv Drug Deliver Rev"},{"key":"351_CR3","doi-asserted-by":"publisher","first-page":"251","DOI":"10.1023\/A:1008130001697","volume":"14","author":"TI Oprea","year":"2000","unstructured":"Oprea TI: Property distribution of drug-related chemical databases. J Comput Aid Mol Des. 2000, 14: 251-264. 10.1023\/A:1008130001697.","journal-title":"J Comput Aid Mol Des"},{"key":"351_CR4","doi-asserted-by":"publisher","first-page":"259","DOI":"10.1038\/nrd1063","volume":"2","author":"WP Walters","year":"2003","unstructured":"Walters WP, Namchuk M: Designing screens: how to make your hits a hit. Nat Rev Drug Discov. 2003, 2: 259-266. 10.1038\/nrd1063.","journal-title":"Nat Rev Drug Discov"},{"key":"351_CR5","doi-asserted-by":"publisher","first-page":"1841","DOI":"10.1021\/jm015507e","volume":"44","author":"I Muegge","year":"2001","unstructured":"Muegge I, Heald SL, Brittelli D: Simple selection criteria for drug-like chemical matter. J Med Chem. 2001, 44: 1841-1846. 10.1021\/jm015507e.","journal-title":"J Med Chem"},{"key":"351_CR6","doi-asserted-by":"publisher","first-page":"856","DOI":"10.1021\/ci050031j","volume":"45","author":"SX Zheng","year":"2005","unstructured":"Zheng SX, Luo XM, Chen G, Zhu WL, Shen JH, Chen KX, Jiang HL: A new rapid and effective chemistry space filter in recognizing a druglike database. J Chem Inf Model. 2005, 45: 856-862. 10.1021\/ci050031j.","journal-title":"J Chem Inf Model"},{"key":"351_CR7","doi-asserted-by":"publisher","first-page":"55","DOI":"10.1021\/cc9800071","volume":"1","author":"AK Ghose","year":"1999","unstructured":"Ghose AK, Viswanadhan VN, Wendoloski JJ: A knowledge-based approach in designing combinatorial or medicinal chemistry libraries for drug discovery. 1. A qualitative and quantitative characterization of known drug databases. J Comb Chem. 1999, 1: 55-68. 10.1021\/cc9800071.","journal-title":"J Comb Chem"},{"key":"351_CR8","doi-asserted-by":"publisher","first-page":"218","DOI":"10.1021\/ci0200467","volume":"43","author":"M Feher","year":"2003","unstructured":"Feher M, Schmidt JM: Property distributions: Differences between drugs, natural products, and molecules from combinatorial chemistry. J Chem Inf Comput Sci. 2003, 43: 218-227. 10.1021\/ci0200467.","journal-title":"J Chem Inf Comput Sci"},{"key":"351_CR9","doi-asserted-by":"publisher","first-page":"1394","DOI":"10.1021\/ci050459i","volume":"46","author":"D Biswas","year":"2006","unstructured":"Biswas D, Roy S, Sen S: A simple approach for indexing the oral druglikeness of a compound: discriminating druglike compounds from nondruglike ones. J Chem Inf Model. 2006, 46: 1394-1401. 10.1021\/ci050459i.","journal-title":"J Chem Inf Model"},{"key":"351_CR10","doi-asserted-by":"publisher","first-page":"1177","DOI":"10.1021\/ci000026+","volume":"40","author":"J Xu","year":"2000","unstructured":"Xu J, Stevenson J: Drug-like index: a new approach to measure drug-like compounds and their diversity. J Chem Inf Comput Sci. 2000, 40: 1177-1187. 10.1021\/ci000026+.","journal-title":"J Chem Inf Comput Sci"},{"key":"351_CR11","doi-asserted-by":"publisher","first-page":"2887","DOI":"10.1021\/jm9602928","volume":"39","author":"GW Bemis","year":"1996","unstructured":"Bemis GW, Murcko MA: Properties of known drugs. 1. Molecular frameworks. J Med Chem. 1996, 39: 2887-2893. 10.1021\/jm9602928.","journal-title":"J Med Chem"},{"key":"351_CR12","doi-asserted-by":"publisher","first-page":"5095","DOI":"10.1021\/jm9903996","volume":"42","author":"GW Bemis","year":"1999","unstructured":"Bemis GW, Murcko MA: Properties of known drugs. 2. Side chains. J Med Chem. 1999, 42: 5095-5099. 10.1021\/jm9903996.","journal-title":"J Med Chem"},{"key":"351_CR13","doi-asserted-by":"publisher","first-page":"55","DOI":"10.1021\/ci900398f","volume":"50","author":"JM Wang","year":"2010","unstructured":"Wang JM, Hou TJ: Drug and drug candidate building block analysis. J Chem Inf Model. 2010, 50: 55-67. 10.1021\/ci900398f.","journal-title":"J Chem Inf Model"},{"key":"351_CR14","doi-asserted-by":"publisher","first-page":"3314","DOI":"10.1021\/jm970666c","volume":"41","author":"Ajay","year":"1998","unstructured":"Ajay , Walters WP, Murcko MA: Can we learn to distinguish between \"drug-like\" and \"nondrug-like\" molecules?. J Med Chem. 1998, 41: 3314-3324. 10.1021\/jm970666c.","journal-title":"J Med Chem"},{"key":"351_CR15","doi-asserted-by":"publisher","first-page":"1882","DOI":"10.1021\/ci0341161","volume":"43","author":"E Byvatov","year":"2003","unstructured":"Byvatov E, Fechner U, Sadowski J, Schneider G: Comparison of support vector machine and artificial neural network systems for drug\/nondrug classification. J Chem Inf Comput Sci. 2003, 43: 1882-1889. 10.1021\/ci0341161.","journal-title":"J Chem Inf Comput Sci"},{"key":"351_CR16","doi-asserted-by":"publisher","first-page":"186","DOI":"10.1021\/ci600329u","volume":"47","author":"MC Hutter","year":"2007","unstructured":"Hutter MC: Separating drugs from nondrugs: a statistical approach using atom pair distributions. J Chem Inf Model. 2007, 47: 186-194. 10.1021\/ci600329u.","journal-title":"J Chem Inf Model"},{"key":"351_CR17","doi-asserted-by":"publisher","first-page":"1776","DOI":"10.1021\/ci700107y","volume":"47","author":"QL Li","year":"2007","unstructured":"Li QL, Bender A, Pei JF, Lai LH: A large descriptor set and a probabilistic kernel-based classifier significantly improve druglikeness classification. J Chem Inf Model. 2007, 47: 1776-1786. 10.1021\/ci700107y.","journal-title":"J Chem Inf Model"},{"key":"351_CR18","doi-asserted-by":"publisher","first-page":"2048","DOI":"10.1021\/ci0340916","volume":"43","author":"VV Zernov","year":"2003","unstructured":"Zernov VV, Balakin KV, Ivaschenko AA, Savchuk NP, Pletnev IV: Drug discovery using support vector machines. The case studies of drug-likeness, agrochemical-likeness, and enzyme inhibition predictions. J Chem Inf Comput Sci. 2003, 43: 2048-2056. 10.1021\/ci0340916.","journal-title":"J Chem Inf Comput Sci"},{"key":"351_CR19","doi-asserted-by":"publisher","first-page":"769","DOI":"10.1016\/j.cell.2007.08.021","volume":"130","author":"TW Corson","year":"2007","unstructured":"Corson TW, Crews CM: Molecular understanding and modern application of traditional medicines: triumphs and trials. Cell. 2007, 130: 769-774. 10.1016\/j.cell.2007.08.021.","journal-title":"Cell"},{"key":"351_CR20","doi-asserted-by":"publisher","first-page":"188","DOI":"10.1126\/science.299.5604.188","volume":"299","author":"D Normile","year":"2003","unstructured":"Normile D: Asian medicine: the new face of traditional Chinese medicine. Science. 2003, 299: 188-190. 10.1126\/science.299.5604.188.","journal-title":"Science"},{"key":"351_CR21","first-page":"177","volume-title":"Traditional chinese medicine","author":"S Wang","year":"2005","unstructured":"Wang S, Li Y, Devinsky O, Schachter SC, Pacia S: Traditional chinese medicine. 2005, New York, NY, USA: Demos Medical Pub, 177-182."},{"key":"351_CR22","doi-asserted-by":"publisher","first-page":"461","DOI":"10.1021\/np068054v","volume":"70","author":"DJ Newman","year":"2007","unstructured":"Newman DJ, Cragg GM: Natural products as sources of new drugs over the last 25\u2009years. J Nat Prod. 2007, 70: 461-477. 10.1021\/np068054v.","journal-title":"J Nat Prod"},{"key":"351_CR23","doi-asserted-by":"publisher","first-page":"481","DOI":"10.1021\/ci010113h","volume":"42","author":"XB Qiao","year":"2002","unstructured":"Qiao XB, Hou TJ, Zhang W, Guo SL, Xu SJ: A 3D structure database of components from Chinese traditional medicinal herbs. J Chem Inf Comput Sci. 2002, 42: 481-489. 10.1021\/ci010113h.","journal-title":"J Chem Inf Comput Sci"},{"key":"351_CR24","doi-asserted-by":"publisher","first-page":"2327","DOI":"10.2174\/0929867033456729","volume":"10","author":"JH Shen","year":"2003","unstructured":"Shen JH, Xu XY, Cheng F, Liu H, Luo XM, Shen JK, Chen KX, Zhao WM, Shen X, Jiang HL: Virtual screening on natural products for discovering active compounds and target information. Curr Med Chem. 2003, 10: 2327-2342. 10.2174\/0929867033456729.","journal-title":"Curr Med Chem"},{"key":"351_CR25","doi-asserted-by":"publisher","first-page":"92","DOI":"10.1016\/j.clpt.2005.03.010","volume":"78","author":"JF Wang","year":"2005","unstructured":"Wang JF, Zhou H, Han LY, Chen X, Chen YZ, Cao ZW: Traditional Chinese medicine information database. Clin Pharmacol Ther. 2005, 78: 92-93. 10.1016\/j.clpt.2005.03.010.","journal-title":"Clin Pharmacol Ther"},{"key":"351_CR26","volume-title":"PLoS One","author":"CY-C Chen","year":"2011","unstructured":"Chen CY-C: TCM Database@Taiwan: The world's largest traditional Chinese medicine database for drug screening In Silico. PLoS One. 2011, 6:"},{"key":"351_CR27","doi-asserted-by":"publisher","first-page":"2875","DOI":"10.1021\/mp300198d","volume":"9","author":"S Tian","year":"2012","unstructured":"Tian S, Wang JM, Li YY, Xu XJ, Hou TJ: Drug-likeness analysis of traditional Chinese medicines: prediction of drug-likeness using machine learning approaches. Mol Pharm. 2012, 9: 2875-2886. 10.1021\/mp300198d.","journal-title":"Mol Pharm"},{"key":"351_CR28","first-page":"1788","volume":"59","author":"TJ Hou","year":"2001","unstructured":"Hou TJ, Qiao XB, Xu XJ: Research and development of 3D molecular structure database of traditional Chinese drugs. Acta Chimica Sinica. 2001, 59: 1788-1792.","journal-title":"Acta Chimica Sinica"},{"key":"351_CR29","first-page":"10","volume-title":"Chemical Computing Group","author":"MOE","year":"2009","unstructured":"MOE: Chemical Computing Group. 2009, Montreal, 10-http:\/\/www.chemcomp.com,"},{"key":"351_CR30","doi-asserted-by":"publisher","first-page":"490","DOI":"10.1002\/(SICI)1096-987X(199604)17:5\/6<490::AID-JCC1>3.0.CO;2-P","volume":"17","author":"TA Halgren","year":"1996","unstructured":"Halgren TA: Merck molecular force field .1. Basis, form, scope, parameterization, and performance of MMFF94. J Comput Chem. 1996, 17: 490-519. 10.1002\/(SICI)1096-987X(199604)17:5\/6<490::AID-JCC1>3.0.CO;2-P.","journal-title":"J Comput Chem"},{"key":"351_CR31","doi-asserted-by":"publisher","first-page":"3325","DOI":"10.1021\/jm9706776","volume":"41","author":"J Sadowski","year":"1998","unstructured":"Sadowski J, Kubinyi H: A scoring scheme for discriminating between drugs and nondrugs. J Med Chem. 1998, 41: 3325-3329. 10.1021\/jm9706776.","journal-title":"J Med Chem"},{"key":"351_CR32","doi-asserted-by":"publisher","first-page":"280","DOI":"10.1021\/ci990266t","volume":"40","author":"M Wagener","year":"2000","unstructured":"Wagener M, van Geerestein VJ: Potential drugs and nondrugs: prediction and identification of important structural features. J Chem Inf Comput Sci. 2000, 40: 280-292. 10.1021\/ci990266t.","journal-title":"J Chem Inf Comput Sci"},{"key":"351_CR33","first-page":"497","volume":"12","author":"TJ Hou","year":"2009","unstructured":"Hou TJ, Li YY, Zhang W, Wang JM: Recent developments of In silico predictions of intestinal absorption and oral bioavailability. Comb Chem High T Scr. 2009, 12: 497-506.","journal-title":"Comb Chem High T Scr"},{"key":"351_CR34","doi-asserted-by":"publisher","first-page":"2653","DOI":"10.2174\/092986706778201558","volume":"13","author":"TJ Hou","year":"2006","unstructured":"Hou TJ, Wang JM, Zhang W, Wang W, Xu X: Recent advances in computational prediction of drug absorption and permeability in drug discovery. Curr Med Chem. 2006, 13: 2653-2667. 10.2174\/092986706778201558.","journal-title":"Curr Med Chem"},{"key":"351_CR35","doi-asserted-by":"publisher","first-page":"865","DOI":"10.1021\/js960177k","volume":"86","author":"F Csizmadia","year":"1997","unstructured":"Csizmadia F, TsantiliKakoulidou A, Panderi I, Darvas F: Prediction of distribution coefficient from structure.1. Estimation method. J Pharm Sci. 1997, 86: 865-871. 10.1021\/js960177k.","journal-title":"J Pharm Sci"},{"key":"351_CR36","doi-asserted-by":"publisher","first-page":"1488","DOI":"10.1021\/ci000392t","volume":"41","author":"IV Tetko","year":"2001","unstructured":"Tetko IV, Tanchuk VY, Kasheva TN, Villa AEP: Estimation of aqueous solubility of chemical compounds using E-state indices. J Chem Inf Comput Sci. 2001, 41: 1488-1493. 10.1021\/ci000392t.","journal-title":"J Chem Inf Comput Sci"},{"key":"351_CR37","volume-title":"Molecular Connectivity Indices in Chemistry and Drug Research","author":"BB Kier","year":"1976","unstructured":"Kier BB, Hall LH: Molecular Connectivity Indices in Chemistry and Drug Research. 1976, Academic Press, New York, NY, USA: New York, Vol. 14"},{"key":"351_CR38","unstructured":"Discovery Studio 2.5 Guide. 2009, Accelrys Inc, San Diego, http:\/\/www.accelrys.com,"},{"key":"351_CR39","doi-asserted-by":"publisher","first-page":"759","DOI":"10.1517\/17425255.4.6.759","volume":"4","author":"T Hou","year":"2008","unstructured":"Hou T, Wang J: Structure - ADME relationship: still a long way to go?. Expet Opin Drug Metabol Toxicol. 2008, 4: 759-770. 10.1517\/17425255.4.6.759.","journal-title":"Expet Opin Drug Metabol Toxicol"},{"key":"351_CR40","doi-asserted-by":"publisher","first-page":"208","DOI":"10.1021\/ci600343x","volume":"47","author":"TJ Hou","year":"2007","unstructured":"Hou TJ, Wang JM, Zhang W, Xu XJ: ADME evaluation in drug discovery. 7. Prediction of oral absorption by correlation and classification. J Chem Inf Model. 2007, 47: 208-218. 10.1021\/ci600343x.","journal-title":"J Chem Inf Model"},{"key":"351_CR41","doi-asserted-by":"publisher","first-page":"2137","DOI":"10.1021\/ci034134i","volume":"43","author":"TJ Hou","year":"2003","unstructured":"Hou TJ, Xu XJ: ADME evaluation in drug discovery. 3. Modeling blood\u2013brain barrier partitioning using simple molecular descriptors. J Chem Inf Comput Sci. 2003, 43: 2137-2152. 10.1021\/ci034134i.","journal-title":"J Chem Inf Comput Sci"},{"key":"351_CR42","doi-asserted-by":"publisher","first-page":"1585","DOI":"10.1021\/ci049884m","volume":"44","author":"TJ Hou","year":"2004","unstructured":"Hou TJ, Zhang W, Xia K, Qiao XB, Xu XJ: ADME evaluation in drug discovery. 5. Correlation of Caco-2 permeation with simple molecular properties. J Chem Inf Comput Sci. 2004, 44: 1585-1600. 10.1021\/ci049884m.","journal-title":"J Chem Inf Comput Sci"},{"key":"351_CR43","doi-asserted-by":"publisher","first-page":"266","DOI":"10.1021\/ci034184n","volume":"44","author":"TJ Hou","year":"2004","unstructured":"Hou TJ, Xia K, Zhang W, Xu XJ: ADME evaluation in drug discovery. 4. Prediction of aqueous solubility based on atom contribution approach. J Chem Inf Comput Sci. 2004, 44: 266-275. 10.1021\/ci034184n.","journal-title":"J Chem Inf Comput Sci"}],"container-title":["Journal of Cheminformatics"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1186\/1758-2946-4-31.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1186\/1758-2946-4-31\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1186\/1758-2946-4-31.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,9,1]],"date-time":"2021-09-01T21:42:48Z","timestamp":1630532568000},"score":1,"resource":{"primary":{"URL":"https:\/\/jcheminf.biomedcentral.com\/articles\/10.1186\/1758-2946-4-31"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2012,11,27]]},"references-count":43,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2012,12]]}},"alternative-id":["351"],"URL":"https:\/\/doi.org\/10.1186\/1758-2946-4-31","relation":{},"ISSN":["1758-2946"],"issn-type":[{"value":"1758-2946","type":"electronic"}],"subject":[],"published":{"date-parts":[[2012,11,27]]},"assertion":[{"value":"1 September 2012","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"21 November 2012","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"27 November 2012","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}],"article-number":"31"}}