Prediction of Hemolytic Toxicity for Saponins by Machine-Learning Methods

doi:10.1021/acs.chemrestox.8b00347

科研成果详情

题名	Prediction of Hemolytic Toxicity for Saponins by Machine-Learning Methods
作者	Zheng, Suqing1,2; Wang, Yibing 3,4; Liu, Hongmei 1; Chang, Wenping 1; Xu, Yong 5; Lin, Fu1
发表日期	2019-06
发表期刊	CHEMICAL RESEARCH IN TOXICOLOGY 影响因子和分区
语种	英语
原始文献类型	Article
其他关键词	TRITERPENOID SAPONINS ; NATURAL COMPOUND ; CYTOTOXICITY ; CELL ; CLASSIFICATION ; CHOLESTEROL ; DIGITONIN ; OSW-1 ; MEMBRANES ; BEARING
摘要	Saponins are a type of compounds bearing a hydrophobic steroid/triterpenoid moiety and hydrophilic carbohydrate branches. The majority of the saponins demonstrate a broad range of prominent pharmacological activities. Nevertheless, many saponins also possess harmful hemolytic toxicity, which can cause the lysis of erythrocytes and thereby hamper their applications in medicine. As such, the organic synthesis of diverse saponins with versatile therapeutic effects and without hemolytic toxicity has gained considerable interests among medicinal/organic chemists. To date, the non-hemolytic saponins of interests have usually been designed by the traditional trial-and-error method or discovered by serendipity. It would be more efficient to develop an in silico method to rationally design promising saponins without hemolytic toxicity prior to the laborious organic synthesis, despite the fact that there is, so far, no computational model to predict the hemolytic toxicity of saponins. To this end, we manually curate 331 hemolytic and 121 non-hemolytic saponins from the literature for the first time and build the first machine-learning-based hemolytic toxicity classification model for the saponins, which provides encouraging performance with 95% confidence intervals for accuracy (0.906 +/- 0.009), precision (0.904 +/- 0.012), specificity (0.711 +/- 0.039), sensitivity (0.978 +/- 0.010), Fl-score (0.939 +/- 0.006), and Matthews correlation coefficient (0.756 +/- 0.025) on the test set by averaging over 19 different random data-partitioning schemes. Moreover, we have developed a free program called e-Hemolytic-Saponin for the automatic prediction and design of hemolytic/non-hemolytic saponins. To the best of our knowledge, we herein compile the first comprehensive saponin dataset focused on hemolytic toxicity, build the first informative model of hemolytic toxicity for the saponins, and implement the first convenient software that will enable organic/medicinal chemists to automatically predict and design the saponins of interests.
资助项目	Natural Science Foundation of Zhejiang ProvinceNatural Science Foundation of Zhejiang Province [LY17B030007]; Wenzhou Medical University
出版者	AMER CHEMICAL SOC
出版地	WASHINGTON
ISSN	0893-228X
EISSN	1520-5010
卷号	32 期号:6 页码:1014-1026
DOI	10.1021/acs.chemrestox.8b00347
页数	13
WOS类目	Chemistry, Medicinal ; Chemistry, Multidisciplinary ; Toxicology
WOS研究方向	Pharmacology & Pharmacy ; Chemistry ; Toxicology
WOS记录号	WOS:000472241800013
收录类别	SCIE ; PUBMED ; SCOPUS
URL	查看原文
PubMed ID	30915843
SCOPUSEID	2-s2.0-85064829867
通讯作者地址	[Zheng, Suqing]School of Pharmaceutical Sciences,Wenzhou Medical University,Wenzhou, Zhejiang,325035,China
Scopus学科分类	Toxicology
引用统计	被引频次：8[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	https://kms.wmu.edu.cn/handle/3ETUA0LF/10344
专题	药学院（分析测试中心）药学院（分析测试中心）_生物有机与药物化学研究中心
通讯作者	Zheng, Suqing
作者单位	1.School of Pharmaceutical Sciences,Wenzhou Medical University,Wenzhou, Zhejiang,325035,China; 2.Chemical Biology Research Center,Wenzhou Medical University,Wenzhou, Zhejiang,325035,China; 3.Genetic Screening Center,National Institute of Biological Sciences,Beijing,102206,China; 4.Tsinghua Institute of Multidisciplinary Biomedical Research,Tsinghua University,Beijing,100084,China; 5.Center of Chemical Biology,Guangzhou Institute of Biomedicine and Health,Chinese Academy of Sciences,Guangzhou, Guangdong,510530,China
第一作者单位	药学院（分析测试中心）; 生物有机与药物化学研究中心
通讯作者单位	药学院（分析测试中心）
第一作者的第一单位	药学院（分析测试中心）
推荐引用方式 GB/T 7714	Zheng, Suqing,Wang, Yibing,Liu, Hongmei,et al. Prediction of Hemolytic Toxicity for Saponins by Machine-Learning Methods[J]. CHEMICAL RESEARCH IN TOXICOLOGY,2019,32(6):1014-1026.
APA	Zheng, Suqing, Wang, Yibing, Liu, Hongmei, Chang, Wenping, Xu, Yong, & Lin, Fu. (2019). Prediction of Hemolytic Toxicity for Saponins by Machine-Learning Methods. CHEMICAL RESEARCH IN TOXICOLOGY, 32(6), 1014-1026.
MLA	Zheng, Suqing,et al."Prediction of Hemolytic Toxicity for Saponins by Machine-Learning Methods".CHEMICAL RESEARCH IN TOXICOLOGY 32.6(2019):1014-1026.