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ChemBCPP: A freely available web server for calculating commonly used physicochemical properties

文献类型： 外文期刊

作者： Dong, Jie 1 ; Wang, Ning-Ning 1 ; Liu, Ke-Yi 2 ; Zhu, Min-Feng 1 ; Yun, Yong-Huan 4 ; Zeng, Wen-Bin 1 ; Chen, Alex F.; 1 ;

作者机构： 1.Cent S Univ, Xiangya Sch Pharmaceut Sci, Changsha 410013, Hunan, Peoples R China

2.Sichuan Univ, West China Sch Med, Chengdu, Sichuan, Peoples R China

3.Cent S Univ, Xiangya Hosp 3, Ctr Vasc Dis & Translat Med, Changsha 410013, Hunan, Peoples R China

4.Chinese Acad Trop Agr Sci, Inst Environm & Plant Protect, Haikou 571101, Hainan, Peoples R China

关键词： QSPR;Cheminformatics;Physiochemical property prediction;Machine learning;Web server

期刊名称：CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS （ 影响因子：3.491； 五年影响因子：3.839 ）

ISSN： 0169-7439

年卷期： 2017 年 171 卷

页码：

收录情况： SCI

摘要： The behavior of a chemical in human or environment mostly depends on its several key physicochemical properties, such as aqueous solubility, octanol-water partition coefficient (logP), boiling point (BP), density, flash point (FP), viscosity, surface tension (ST), vapor pressure (VP) and melting point (MP). Commonly, these properties are important for the environmental sciences and drug discovery, such as the absorption, distribution, metabolism, excretion, and toxicity (ADMET) for medicinal compounds and the common risk assessment for problematic chemicals. At present, the quantitative structure-property relationship (QSPR) model was widely applied to save time and money investment in the early stage of chemical research. Although some satisfactory models were already obtained, most of them are not available for the public researchers and thus cannot be directly applied to practical research projects. Herein, in this study, we developed a user-friendly web server named ChemBCPP that can be used to predict aforementioned 8 important physicochemical properties and calculate several other commonly used properties just by uploading a molecular structure or file. In addition, for a new chemical entity, users can not only get its predicted value but also obtain a leverage value (h value) which can be used to evaluate the reliability of predictive result. We believe that ChemBCPP could be widely applied in environmental science, chemical synthesis and drug ADMET fields with the demand for high quality of chemical properties. ChemBCPP could be freely available via http://chembcpp.scbdd.com.

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