title: MPGraph: multi-view penalised graph clustering for predicting drug-target interactions.
abstract: Identifying drug-target interactions has been a key step for drug repositioning, drug discovery and drug design. Since it is expensive to determine the interactions experimentally, computational methods are needed for predicting interactions. In this work, the authors first propose a single-view penalised graph (SPGraph) clustering approach to integrate drug structure and protein sequence data in a structural view. The SPGraph model does clustering on drugs and targets simultaneously such that the known drug-target interactions are best preserved in the clustering results. They then apply the SPGraph to a chemical view with drug response data and gene expression data in NCI-60 cell lines. They further generalise the SPGraph to a multi-view penalised graph (MPGraph) version, which can integrate the structural view and chemical view of the data. In the authors' experiments, they compare their approach with some comparison partners, and the results show that the SPGraph could improve the prediction accuracy in a small scale, and the MPGraph can achieve around 10% improvements for the prediction accuracy. They finally give some new targets for 22 Food and Drug Administration approved drugs for drug repositioning, and some can be supported by other references.
authors.affiliation: Department of Information Sciences, School of Mathematics and Statistics, Xi'an Jiaotong University, Xi'an 710049, People's Republic of China. liminli@mail.xjtu.edu.cn.
authors.forename: Limin
authors.initials: L
authors.lastname: Li
mesh_terms: D000465:Algorithms; D000893:Anti-Inflammatory Agents / Q000737:chemistry; D000970:Antineoplastic Agents / Q000737:chemistry; D000998:Antiviral Agents / Q000737:chemistry; D019540:Area Under Curve; D045744:Cell Line, Tumor; D002626:Chemistry, Pharmaceutical / Q000379:methods / Q000639:trends*; D016000:Cluster Analysis; D003198:Computer Simulation; D015195:Drug Design; D055808:Drug Discovery; D020869:Gene Expression Profiling; D015972:Gene Expression Regulation, Neoplastic; D006801:Humans; D008962:Models, Theoretical; D004364:Pharmaceutical Preparations / Q000737:chemistry*; D015203:Reproducibility of Results; D012984:Software
chemical_list: D000893:Anti-Inflammatory Agents; D000970:Antineoplastic Agents; D000998:Antiviral Agents; D004364:Pharmaceutical Preparations