title: DDI-CPI, a server that predicts drug-drug interactions through implementing the chemical-protein interactome.
abstract: Drug-drug interactions (DDIs) may cause serious side-effects that draw great attention from both academia and industry. Since some DDIs are mediated by unexpected drug-human protein interactions, it is reasonable to analyze the chemical-protein interactome (CPI) profiles of the drugs to predict their DDIs. Here we introduce the DDI-CPI server, which can make real-time DDI predictions based only on molecular structure. When the user submits a molecule, the server will dock user's molecule across 611 human proteins, generating a CPI profile that can be used as a feature vector for the pre-constructed prediction model. It can suggest potential DDIs between the user's molecule and our library of 2515 drug molecules. In cross-validation and independent validation, the server achieved an AUC greater than 0.85. Additionally, by investigating the CPI profiles of predicted DDI, users can explore the PK/PD proteins that might be involved in a particular DDI. A 3D visualization of the drug-protein interaction will be provided as well. The DDI-CPI is freely accessible at http://cpi.bio-x.cn/ddi/.
authors.affiliation: Bio-X Institutes, Shanghai Jiao Tong University, Shanghai 200030, China University of Arkansas at Little Rock/University of Arkansas for Medical Sciences, Little Rock, AR 72204, USA.
authors.forename: Heng
authors.initials: H
authors.lastname: Luo
authors.affiliation: Healthcare Analytics Research Group, IBM T.J. Watson Research Center, Yorktown Heights, NY 10598, USA.
authors.forename: Ping
authors.initials: P
authors.lastname: Zhang
authors.affiliation: Bio-X Institutes, Shanghai Jiao Tong University, Shanghai 200030, China.
authors.forename: Hui
authors.initials: H
authors.lastname: Huang
authors.affiliation: Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute and Harvard School of Public Heath, Boston, MA 02215, USA.
authors.forename: Jialiang
authors.initials: J
authors.lastname: Huang
authors.affiliation: Department of Bioengineering, University of California at Berkeley, Berkeley, CA 94720, USA.
authors.forename: Emily
authors.initials: E
authors.lastname: Kao
authors.affiliation: School of Pharmacy, Fudan University, Shanghai 201203, China.
authors.forename: Leming
authors.initials: L
authors.lastname: Shi
authors.affiliation: Bio-X Institutes, Shanghai Jiao Tong University, Shanghai 200030, China.
authors.forename: Lin
authors.initials: L
authors.lastname: He
authors.affiliation: Bio-X Institutes, Shanghai Jiao Tong University, Shanghai 200030, China lun.yang@gmail.com.
authors.forename: Lun
authors.initials: L
authors.lastname: Yang
mesh_terms: D015195:Drug Design; D006801:Humans; D020407:Internet; D062105:Molecular Docking Simulation; D004364:Pharmaceutical Preparations / Q000737:chemistry; D011506:Proteins / Q000737:chemistry* / Q000187:drug effects; D020280:Sertraline / Q000737:chemistry; D012984:Software
chemical_list: D004364:Pharmaceutical Preparations; D011506:Proteins; D020280:Sertraline