DPDR-CPI, a server that predicts Drug Positioning and Drug Repositioning via Chemical-Protein Interactome

• DOI: 10.1038/srep35996
• Publication Date: 2016-11-02T12:20:18Z
• Authors: Heng Luo; Ping Zhang; Xi Hang Cao; Dizheng Du; Hao Ye; Hui Huang; Can Li; Shengying Qin; Chunling Wan; Leming Shi; Lin He; Lun Yang
• Keywords: Internet; 0303 health sciences; Drug Repositioning; Proteins; Article; 3. Good health; Molecular Docking Simulation; Pyridazines; Rosiglitazone; User-Computer Interface; 03 medical and health sciences; Pharmaceutical Preparations; ROC Curve; Area Under Curve; Humans; Thiazolidinediones; Protein Binding

AbstractThe cost of developing a new drug has increased sharply over the past years. To ensure a reasonable return-on-investment, it is useful for drug discovery researchers in both industry and academia to identify all the possible indications for early pipeline molecules. For the first time, we propose the term computational “drug candidate positioning” or “drug positioning”, to describe the above process. It is distinct from drug repositioning, which identifies new uses for existing drugs and maximizes their value. Since many therapeutic effects are mediated by unexpected drug-protein interactions, it is reasonable to analyze the chemical-protein interactome (CPI) profiles to predict indications. Here we introduce the server DPDR-CPI, which can make real-time predictions based only on the structure of the small molecule. When a user submits a molecule, the server will dock it across 611 human proteins, generating a CPI profile of features that can be used for predictions. It can suggest the likelihood of relevance of the input molecule towards ~1,000 human diseases with top predictions listed. DPDR-CPI achieved an overall AUROC of 0.78 during 10-fold cross-validations and AUROC of 0.76 for the independent validation. The server is freely accessible via http://cpi.bio-x.cn/dpdr/.