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Published on: November 17, 2019
Identification of drug-target interaction from interactome network with 'guilt-by-association' principle and topology
Zhan-Chao Li1, Meng-Hua Huang1, Wen-Qian Zhong1
1School of Chemistry and Chemical Engineering, Guangdong Pharmaceutical University, Guangzhou 510006, People's Republic of China.
Motivation:
Identifying drug-target protein interaction is a crucial step in the process of drug research and development. Wet-lab experiment are laborious, time-consuming and expensive. Hence, there is a strong demand for the development of a novel theoretical method to identify potential interaction between drug and target protein.
Results:
We use all known proteins and drugs to construct a nodes- and edges-weighted biological relevant interactome network. On the basis of the 'guilt-by-association' principle, novel network topology features are proposed to characterize interaction pairs and random forest algorithm is employed to identify potential drug-protein interaction. Accuracy of 92.53% derived from the 10-fold cross-validation is about 10% higher than that of the existing method. We identify 2272 potential drug-target interactions, some of which are associated with diseases, such as Torg-Winchester syndrome and rhabdomyosarcoma. The proposed method can not only accurately predict the interaction between drug molecule and target protein, but also help disease treatment and drug discovery.
Contacts:
zhanchao8052@gmail.com or ceszxy@mail.sysu.edu.cn
Supplementary Information:
Supplementary data are available at Bioinformatics online.
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