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In silico prediction of drug-target interaction networks based on drug chemical structure and protein sequences
Li, ZW (Li, Zhengwei); Han, PY (Han, Pengyong); You, ZH (You, Zhu-Hong); Li, X (Li, Xiao); Zhang, YS (Zhang, Yusen); Yu, HQ (Yu, Haiquan); Nie, R (Nie, Ru); Chen, X (Chen, Xing)
2017
Source PublicationSCIENTIFIC REPORTS
ISSN2045-2322
Volume7Issue:9Pages:1-13
Abstract

Analysis of drug-target interactions (DTIs) is of great importance in developing new drug candidates for known protein targets or discovering new targets for old drugs. However, the experimental approaches for identifying DTIs are expensive, laborious and challenging. In this study, we report a novel computational method for predicting DTIs using the highly discriminative information of drug-target interactions and our newly developed discriminative vector machine (DVM) classifier. More specifically, each target protein sequence is transformed as the position-specific scoring matrix (PSSM), in which the evolutionary information is retained; then the local binary pattern (LBP) operator is used to calculate the LBP histogram descriptor. For a drug molecule, a novel fingerprint representation is utilized to describe its chemical structure information representing existence of certain functional groups or fragments. When applying the proposed method to the four datasets (Enzyme, GPCR, Ion Channel and Nuclear Receptor) for predicting DTIs, we obtained good average accuracies of 93.16%, 89.37%, 91.73% and 92.22%, respectively. Furthermore, we compared the performance of the proposed model with that of the state-of-the-art SVM model and other previous methods. The achieved results demonstrate that our method is effective and robust and can be taken as a useful tool for predicting DTIs.

DOI10.1038/s41598-017-10724-0
Indexed BySCI
WOS IDWOS:000410064000010
Citation statistics
Cited Times:4[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.xjipc.cas.cn/handle/365002/5036
Collection多语种信息技术研究室
Corresponding AuthorYou, ZH (You, Zhu-Hong)
Affiliation1.China Univ Min & Technol, Sch Comp Sci & Technol, Xuzhou 221116, Peoples R China
2.Univ Calgary, Cumming Sch Med, Calgary, AB T2N 4N1, Canada
3.Inner Mongolia Univ, Key Lab Mammal Reprod Biol & Biotechnol, Minist Educ, Hohhot 010021, Peoples R China
4.Chinese Acad Sci, Xinjiang Tech Inst Phys & Chem, Urumqi 830011, Peoples R China
5.Shandong Univ Weihai, Sch Math & Stat, Weihai 264209, Peoples R China
6.China Univ Min & Technol, Sch Informat & Control Engn, Xuzhou 21116, Peoples R China
Recommended Citation
GB/T 7714
Li, ZW ,Han, PY ,You, ZH ,et al. In silico prediction of drug-target interaction networks based on drug chemical structure and protein sequences[J]. SCIENTIFIC REPORTS,2017,7(9):1-13.
APA Li, ZW .,Han, PY .,You, ZH .,Li, X .,Zhang, YS .,...&Chen, X .(2017).In silico prediction of drug-target interaction networks based on drug chemical structure and protein sequences.SCIENTIFIC REPORTS,7(9),1-13.
MLA Li, ZW ,et al."In silico prediction of drug-target interaction networks based on drug chemical structure and protein sequences".SCIENTIFIC REPORTS 7.9(2017):1-13.
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