title: PASS Targets: Ligand-based multi-target computational system based on a public data and naïve Bayes approach.
abstract: Estimation of interactions between drug-like compounds and drug targets is very important for drug discovery and toxicity assessment. Using data extracted from the 19th version of the ChEMBL database ( https://www.ebi.ac.uk/chembl ) as a training set and a Bayesian-like method realized in PASS software ( http://www.way2drug.com/PASSOnline ), we developed a computational tool for the prediction of interactions between protein targets and drug-like compounds. After training, PASS Targets became able to predict interactions of drug-like compounds with 2507 protein targets from different organisms based on analysis of structure-activity relationships for 589,107 different chemical compounds. The prediction accuracy, estimated as AUC ROC calculated by the leave-one-out cross-validation and 20-fold cross-validation procedures, was about 96%. Average AUC ROC value was about 90% for the external test set from approximately 700 known drugs interacting with 206 protein targets.
authors: a Department for Bioinformatics; Institute of Biomedical Chemistry , Pirogov Russian National Research Medical University , Moscow , Russia.|b Medico-Biological Faculty , Pirogov Russian National Research Medical University , Moscow , Russia.
authors: P V
authors: PV
authors: Pogodin
authors: a Department for Bioinformatics; Institute of Biomedical Chemistry , Pirogov Russian National Research Medical University , Moscow , Russia.|b Medico-Biological Faculty , Pirogov Russian National Research Medical University , Moscow , Russia.
authors: A A
authors: AA
authors: Lagunin
authors: a Department for Bioinformatics; Institute of Biomedical Chemistry , Pirogov Russian National Research Medical University , Moscow , Russia.
authors: D A
authors: DA
authors: Filimonov
authors: a Department for Bioinformatics; Institute of Biomedical Chemistry , Pirogov Russian National Research Medical University , Moscow , Russia.|b Medico-Biological Faculty , Pirogov Russian National Research Medical University , Moscow , Russia.
authors: V V
authors: VV
authors: Poroikov
mesh_terms: D001499:Bayes Theorem; D003198:Computer Simulation; D062126:Databases, Chemical; D055808:Drug Discovery; D008024:Ligands; D004364:Pharmaceutical Preparations / Q000737:chemistry*; D011506:Proteins / Q000737:chemistry; D021281:Quantitative Structure-Activity Relationship; D012984:Software
chemical_list: D008024:Ligands; D004364:Pharmaceutical Preparations; D011506:Proteins
keywords: (Q)SAR; ChEMBL; PASS; in silico drug discovery; protein targets