QSAR study on melanocortin-4 receptors by support vector machine.

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.

[1]  C. Harmon,et al.  Recent developments in our understanding of melanocortin system in the regulation of food intake , 2003, Obesity reviews : an official journal of the International Association for the Study of Obesity.

[2]  M. Ganjali,et al.  QSPR Study of the Distribution Coefficient Property for Hydantoin and 5‐Arylidene Derivatives. A Genetic Algorithm Application for the Variable Selection in the MLR and PLS Methods , 2008 .

[3]  Bernard F. Buxton,et al.  Drug Design by Machine Learning: Support Vector Machines for Pharmaceutical Data Analysis , 2001, Comput. Chem..

[4]  Eslam Pourbasheer,et al.  Support Vector Machine‐Based Quantitative Structure–Activity Relationship Study of Cholesteryl Ester Transfer Protein Inhibitors , 2009, Chemical biology & drug design.

[5]  R. Maki,et al.  Molecular Determinants of Melanocortin 4 Receptor Ligand Binding and MC4/MC3 Receptor Selectivity , 2003, Journal of Pharmacology and Experimental Therapeutics.

[6]  D. Marks,et al.  The use of melanocortin antagonists in cachexia of chronic disease , 2005, Expert opinion on investigational drugs.

[7]  Beth A. Fleck,et al.  Synthesis and characterization of trans-4-(4-chlorophenyl)pyrrolidine-3-carboxamides of piperazinecyclohexanes as ligands for the melanocortin-4 receptor. , 2007, Bioorganic & medicinal chemistry letters.

[8]  M. Ganjali,et al.  Quantitative Structure–Activity Relationship Study on the Anti‐HIV‐1 Activity of Novel 6‐Naphthylthio HEPT Analogs , 2009, Chemical biology & drug design.

[9]  A. Habibi-Yangjeh,et al.  Prediction of Melting Point for Drug-like Compounds Using Principal Component-Genetic Algorithm-Artificial Neural Network , 2008 .

[10]  Chen Chen.  Recent progress toward nonpeptide ligands for the melanocortin-4 receptor. , 2007, Progress in medicinal chemistry.

[11]  F. Burden.  Molecular identification number for substructure searches , 1989, J. Chem. Inf. Comput. Sci..

[12]  Ruisheng Zhang,et al.  Prediction of the Isoelectric Point of an Amino Acid Based on GA-PLS and SVMs , 2004, J. Chem. Inf. Model..

[13]  Ruisheng Zhang,et al.  QSAR Study of Ethyl 2-[(3-Methyl-2, 5-dioxo(3-pyrrolinyl))amino]-4-(trifluoromethyl) pyrimidine-5-carboxylate: An Inhibitor of AP-1 and NF-B Mediated Gene Expression Based on Support Vector Machines , 2003, J. Chem. Inf. Comput. Sci..

[14]  R. Nargund,et al.  Melanocortin-4 receptor (MC4R) agonists for the treatment of obesity. , 2006, Journal of medicinal chemistry.

[15]  Eslam Pourbasheer,et al.  QSRR Study of GC Retention Indices of Essential-Oil Compounds by Multiple Linear Regression with a Genetic Algorithm , 2008 .

[16]  Zhide Hu,et al.  QSAR method for prediction of protein-peptide binding affinity: application to MHC class I molecule HLA-A*0201. , 2007, Journal of molecular graphics & modelling.

[17]  Jie Yang,et al.  Support Vector Machine In Chemistry , 2004 .

[18]  Eamonn F. Healy,et al.  Development and use of quantum mechanical molecular models. 76. AM1: a new general purpose quantum mechanical molecular model , 1985 .

[19]  Michael J. S. Dewar,et al.  Evaluation of AM1 calculated proton affinities and deprotonation enthalpies , 1986 .

[20]  Eslam Pourbasheer,et al.  Development of a New Combined Chemometrics Method, Applied in the Simultaneous Voltammetric Determination of Cinnamic Acid and 3, 4-Dihydroxy Benzoic Acid , 2009 .

[21]  M. Ganjali,et al.  Exploring QSARs for Antiviral Activity of 4‐Alkylamino‐6‐(2‐hydroxyethyl)‐2‐methylthiopyrimidines by Support Vector Machine , 2008, Chemical biology & drug design.

[22]  Wenjian Wang,et al.  Determination of the spread parameter in the Gaussian kernel for classification and regression , 2003, Neurocomputing.

[23]  Alexander J. Smola,et al.  Learning with kernels , 1998 .

[24]  Aalt Bast,et al.  Comprehensive medicinal chemistry , 1991 .

[25]  Jens Sadowski,et al.  Comparison of Support Vector Machine and Artificial Neural Network Systems for Drug/Nondrug Classification , 2003, J. Chem. Inf. Comput. Sci..

[26]  Palanisamy Thanikaivelan,et al.  Application of quantum chemical descriptor in quantitative structure activity and structure property relationship , 2000 .

[27]  X. Lu,et al.  Quantitative Structure–Activity Relationships Study on the Ah Receptor Binding Affinities of Polybrominated Diphenyl Ethers Using a Support Vector Machine , 2007 .

[28]  Roberto Todeschini,et al.  Handbook of Molecular Descriptors , 2002 .

[29]  Mohammad Hossein Fatemi,et al.  Prediction of ozone tropospheric degradation rate constant of organic compounds by using artificial neural networks , 2006 .

[30]  Thorsten Joachims,et al.  Learning to classify text using support vector machines - methods, theory and algorithms , 2002, The Kluwer international series in engineering and computer science.

[31]  Knut Baumann,et al.  Chance Correlation in Variable Subset Regression: Influence of the Objective Function, the Selection Mechanism, and Ensemble Averaging , 2005 .

[32]  M. Ganjali,et al.  Investigation of different linear and nonlinear chemometric methods for modeling of retention index of essential oil components: concerns to support vector machine. , 2009, Journal of hazardous materials.

[33]  Nello Cristianini,et al.  An introduction to Support Vector Machines , 2000 .

[34]  Corwin Hansch,et al.  Comprehensive medicinal chemistry : the rational design, mechanistic study & therapeutic application of chemical compounds , 1990 .

[35]  R. Cone.  Anatomy and regulation of the central melanocortin system , 2005, Nature Neuroscience.

[36]  M. Ganjali,et al.  QSAR Study of 2‐(1‐Propylpiperidin‐4‐yl)‐1H‐Benzimidazole‐4‐Carboxamide as PARP Inhibitors for Treatment of Cancer , 2008, Chemical biology & drug design.

[37]  M. Ganjali,et al.  Development and Validation of a Rapid Chemometrics-Assisted Spectrophotometry and Liquid Chromatography Methods for the Simultaneous Determination of the Phenylalanine, Tryptophan and Tyrosine in the Pharmaceutical Products , 2008 .

[38]  R. Brereton,et al.  Support vector machines for classification and regression. , 2010, The Analyst.