Estimation of elimination half-lives of organic chemicals in humans using gradient boosting machine

doi:10.1016/j.bbagen.2016.05.019

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	Estimation of elimination half-lives of organic chemicals in humans using gradient boosting machine
	Lu, Jing 1; Lu, Dong 2,3,4; Zhang, Xiaochen 1; Bi, Yi 1; Cheng, Keguang 5; Zheng, Mingyue2 ; Luo, Xiaomin2,3
刊名	BIOCHIMICA ET BIOPHYSICA ACTA-GENERAL SUBJECTS
	2016-11
卷号	1860 期号:11 页码:2664-2671
关键词	Elimination half-life Gradient boosting machine Applicability domain Consensus model
ISSN号	0304-4165
DOI	10.1016/j.bbagen.2016.05.019
文献子类	Article
英文摘要	Background: Elimination half-life is an important pharmacolcinetic parameter that determines exposure duration to approach steady state of drugs and regulates drug administration. The experimental evaluation of half-life is time-consuming and costly. Thus, it is attractive to build an accurate prediction model for half-life. Methods: In this study, several machine learning methods, including gradient boosting machine (GBM), support vector regressions (RBF-SVR and Linear-SVR), local lazy regression (LLR), SA, SR, and GP, were employed to build high-quality prediction models. Two strategies of building consensus models were explored to improve the accuracy of prediction. Moreover, the applicability domains (ADs) of the models were determined by using the distance-based threshold. Results: Among seven individual models, GBM showed the best performance (R-2 = 0.820 and RMSE = 0.555 for the test set), and Linear-SVR produced the inferior prediction accuracy (R-2 = 0.738 and RMSE = 0.672). The use of distance-based ADs effectively determined the scope of QSAR models. However, the consensus models by combing the individual models could not improve the prediction performance. Some essential descriptors relevant to half-life were identified and analyzed. Conclusions: An accurate prediction model for elimination half-life was built by GBM, which was superior to the reference model (R-2 = 0.723 and RMSE = 0.698). General significance: Encouraged by the promising results, we expect that the GBM model for elimination half-life would have potential applications for the early pharmacokinetic evaluations, and provide guidance for designing drug candidates with favorable in vivo exposure profile. This article is part of a Special Issue entitled "System Genetics" Guest Editor: Dr. Yudong Cai and Dr. Tao Huang. (C) 2016 Elsevier B.V. All rights reserved.
资助项目	National Natural Science Foundation of China[81430084] ; National Natural Science Foundation of China[81573351] ; Hi-Tech Research and Development Program of China[2014AA01A302] ; State Key Laboratory of Natural and Biomimetic Drugs[00000000] ; Key Laboratory for the Chemistry and Molecular Engineering of Medicinal Resources (Guangxi Normal University), Ministry of Education of China[CMEMR2015-B09] ; Special Program for Applied Research on Super Computation of the NSFC-Guangdong Joint Fund[00000000]
WOS关键词	MOLECULAR SIMILARITY ANALYSES ; PLASMA-PROTEIN BINDING ; APPLICABILITY DOMAIN ; QSAR MODELS ; DRUG DISCOVERY ; VECTOR MACHINE ; PREDICTION ; TOXICITY ; CLASSIFICATION
WOS研究方向	Biochemistry & Molecular Biology ; Biophysics
语种	英语
出版者	ELSEVIER SCIENCE BV
WOS记录号	WOS:000383825000007
内容类型	期刊论文
源URL	[http://119.78.100.183/handle/2S10ELR8/275844]
专题	药物发现与设计中心中科院受体结构与功能重点实验室新药研究国家重点实验室
通讯作者	Zheng, Mingyue; Luo, Xiaomin
作者单位	1.Yantai Univ, Shandong Univ, Sch Pharm,Collaborat Innovat Ctr Adv Drug Deliver, Key Lab Mol Pharmacol & Drug Evaluat,Minist Educ, 32 Qingquan Rd, Yantai 264005, Peoples R China; 2.Chinese Acad Sci, Shanghai Inst Mat Med, Drug Discovery & Design Ctr, State Key Lab Drug Res, 555 Zuchongzhi Rd, Shanghai 201203, Peoples R China; 3.Peking Univ, Stake Key Lab Nat & Biomimet Drugs, 38 Xueyuan Rd, Beijing 100191, Peoples R China; 4.Univ Chinese Acad Sci, 19A Yuquan Rd, Beijing 100049, Peoples R China; 5.Guangxi Normal Univ, Key Lab Chem & Mol Engn Med Resources, Minist Educ China, Guilin 541004, Peoples R China
推荐引用方式 GB/T 7714	Lu, Jing,Lu, Dong,Zhang, Xiaochen,et al. Estimation of elimination half-lives of organic chemicals in humans using gradient boosting machine[J]. BIOCHIMICA ET BIOPHYSICA ACTA-GENERAL SUBJECTS,2016,1860(11):2664-2671.
APA	Lu, Jing.,Lu, Dong.,Zhang, Xiaochen.,Bi, Yi.,Cheng, Keguang.,...&Luo, Xiaomin.(2016).Estimation of elimination half-lives of organic chemicals in humans using gradient boosting machine.BIOCHIMICA ET BIOPHYSICA ACTA-GENERAL SUBJECTS,1860(11),2664-2671.
MLA	Lu, Jing,et al."Estimation of elimination half-lives of organic chemicals in humans using gradient boosting machine".BIOCHIMICA ET BIOPHYSICA ACTA-GENERAL SUBJECTS 1860.11(2016):2664-2671.