Genome-Scale Screening of Drug-Target Associations Relevant to Ki Using a Chemogenomics Approach

Dong-Sheng Cao, Yi-Zeng Liang, Zhe Deng, Qian-Nan Hu, Min He, Qing-Song Xu, Guang-Hua Zhou, Liu-Xia Zhang, Zi-xin Deng and Shao Liu

PLOS ONE, 2013, vol. 8, issue 4, 1-12

Abstract: The identification of interactions between drugs and target proteins plays a key role in genomic drug discovery. In the present study, the quantitative binding affinities of drug-target pairs are differentiated as a measurement to define whether a drug interacts with a protein or not, and then a chemogenomics framework using an unbiased set of general integrated features and random forest (RF) is employed to construct a predictive model which can accurately classify drug-target pairs. The predictability of the model is further investigated and validated by several independent validation sets. The built model is used to predict drug-target associations, some of which were confirmed by comparing experimental data from public biological resources. A drug-target interaction network with high confidence drug-target pairs was also reconstructed. This network provides further insight for the action of drugs and targets. Finally, a web-based server called PreDPI-Ki was developed to predict drug-target interactions for drug discovery. In addition to providing a high-confidence list of drug-target associations for subsequent experimental investigation guidance, these results also contribute to the understanding of drug-target interactions. We can also see that quantitative information of drug-target associations could greatly promote the development of more accurate models. The PreDPI-Ki server is freely available via: http://sdd.whu.edu.cn/dpiki.

Date: 2013
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0057680

DOI: 10.1371/journal.pone.0057680

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