title: TargetNet: a web service for predicting potential drug-target interaction profiling via multi-target SAR models.
abstract: Drug-target interactions (DTIs) are central to current drug discovery processes and public health fields. Analyzing the DTI profiling of the drugs helps to infer drug indications, adverse drug reactions, drug-drug interactions, and drug mode of actions. Therefore, it is of high importance to reliably and fast predict DTI profiling of the drugs on a genome-scale level. Here, we develop the TargetNet server, which can make real-time DTI predictions based only on molecular structures, following the spirit of multi-target SAR methodology. Naïve Bayes models together with various molecular fingerprints were employed to construct prediction models. Ensemble learning from these fingerprints was also provided to improve the prediction ability. When the user submits a molecule, the server will predict the activity of the user's molecule across 623 human proteins by the established high quality SAR model, thus generating a DTI profiling that can be used as a feature vector of chemicals for wide applications. The 623 SAR models related to 623 human proteins were strictly evaluated and validated by several model validation strategies, resulting in the AUC scores of 75-100 %. We applied the generated DTI profiling to successfully predict potential targets, toxicity classification, drug-drug interactions, and drug mode of action, which sufficiently demonstrated the wide application value of the potential DTI profiling. The TargetNet webserver is designed based on the Django framework in Python, and is freely accessible at http://targetnet.scbdd.com .
authors.affiliation: School of Pharmaceutical Sciences, Central South University, Changsha, 410013, People's Republic of China.|College of Chemistry and Chemical Engineering, Central South University, Changsha, 410083, People's Republic of China.
authors.forename: Zhi-Jiang
authors.initials: ZJ
authors.lastname: Yao
authors.affiliation: School of Pharmaceutical Sciences, Central South University, Changsha, 410013, People's Republic of China.
authors.forename: Jie
authors.initials: J
authors.lastname: Dong
authors.affiliation: School of Mathematics and Statistics, Central South University, Changsha, 410083, People's Republic of China.
authors.forename: Yu-Jing
authors.initials: YJ
authors.lastname: Che
authors.affiliation: School of Mathematics and Statistics, Central South University, Changsha, 410083, People's Republic of China.
authors.forename: Min-Feng
authors.initials: MF
authors.lastname: Zhu
authors.affiliation: College of Chemistry and Chemical Engineering, Central South University, Changsha, 410083, People's Republic of China.
authors.forename: Ming
authors.initials: M
authors.lastname: Wen
authors.affiliation: School of Pharmaceutical Sciences, Central South University, Changsha, 410013, People's Republic of China.
authors.forename: Ning-Ning
authors.initials: NN
authors.lastname: Wang
authors.affiliation: College of Chemistry and Chemical Engineering, Central South University, Changsha, 410083, People's Republic of China.
authors.forename: Shan
authors.initials: S
authors.lastname: Wang
authors.affiliation: Institute of Advancing Translational Medicine in Bone and Joint Diseases, School of Chinese Medicine, Hong Kong Baptist University, Hong Kong, SAR, People's Republic of China.
authors.forename: Ai-Ping
authors.initials: AP
authors.lastname: Lu
authors.affiliation: School of Pharmaceutical Sciences, Central South University, Changsha, 410013, People's Republic of China. oriental-cds@163.com.|Institute of Advancing Translational Medicine in Bone and Joint Diseases, School of Chinese Medicine, Hong Kong Baptist University, Hong Kong, SAR, People's Republic of China. oriental-cds@163.com.
authors.forename: Dong-Sheng
authors.initials: DS
authors.lastname: Cao
mesh_terms: D000465:Algorithms; D001499:Bayes Theorem; D055808:Drug Discovery; D004347:Drug Interactions; D064420:Drug-Related Side Effects and Adverse Reactions; D006801:Humans; D020407:Internet; D008962:Models, Theoretical; D004364:Pharmaceutical Preparations / Q000737:chemistry* / Q000378:metabolism; D011485:Protein Binding; D011506:Proteins / Q000737:chemistry* / Q000378:metabolism; D012984:Software
chemical_list: D004364:Pharmaceutical Preparations; D011506:Proteins
keywords: Drug–target interaction; Multi-target SAR; Naïve Bayes; SAR models; Web server