title: QSAR study on melanocortin-4 receptors by support vector machine.
abstract: Quantitative structure activity relationship (QSAR) of the melanocortin-4 receptor (MC4R) binding affinities (K(i)) of trans-4-(4-chlorophenyl) pyrrolidine-3-carboxamides of piperazinecyclohexanes was studied. A suitable set of molecular descriptors was calculated and the genetic algorithm (GA) was employed to select those descriptors that resulted in the best-fit models. The multiple linear regression (MLR), and the support vector machine (SVM) were utilized to construct the linear and nonlinear QSAR models. The models were validated using Leave-One-Out (LOO) and Leave-Group-Out (LGO) cross-validation, external test set, and chance correlation. The SVM model generalizes better than the MLR model. The SVM model, with high statistical significance (R(2)(train)=0.908, Q(2)(LOO)=0.781, Q(2)(LGO)=0.872), could be used to predict melanocortin-4 receptor binding affinities of piperazinecyclohexanes.
authors.affiliation: Faculty of Chemistry, University of Tehran, Center of Excellence in Electrochemistry, Tehran, Iran.
authors.forename: Eslam
authors.initials: E
authors.lastname: Pourbasheer
authors.forename: Siavash
authors.initials: S
authors.lastname: Riahi
authors.forename: Mohammad Reza
authors.initials: MR
authors.lastname: Ganjali
authors.forename: Parviz
authors.initials: P
authors.lastname: Norouzi
mesh_terms: D000465:Algorithms; D017606:Chlorine Compounds / Q000737:chemistry* / Q000378:metabolism; D003510:Cyclohexanes / Q000737:chemistry* / Q000378:metabolism; D016014:Linear Models; D008954:Models, Biological; D015394:Molecular Structure; D011759:Pyrrolidines / Q000737:chemistry* / Q000378:metabolism; D021281:Quantitative Structure-Activity Relationship; D044105:Receptor, Melanocortin, Type 4 / Q000737:chemistry* / Q000378:metabolism
chemical_list: D017606:Chlorine Compounds; D003510:Cyclohexanes; D011759:Pyrrolidines; D044105:Receptor, Melanocortin, Type 4