title: Proteometric study of ghrelin receptor function variations upon mutations using amino acid sequence autocorrelation vectors and genetic algorithm-based least square support vector machines.
abstract: Functional variations on the human ghrelin receptor upon mutations have been associated with a syndrome of short stature and obesity, of which the obesity appears to develop around puberty. In this work, we reported a proteometrics analysis of the constitutive and ghrelin-induced activities of wild-type and mutant ghrelin receptors using amino acid sequence autocorrelation (AASA) approach for protein structural information encoding. AASA vectors were calculated by measuring the autocorrelations at sequence lags ranging from 1 to 15 on the protein primary structure of 48 amino acid/residue properties selected from the AAindex database. Genetic algorithm-based multilinear regression analysis (GA-MRA) and genetic algorithm-based least square support vector machines (GA-LSSVM) were used for building linear and non-linear models of the receptor activity. A genetic optimized radial basis function (RBF) kernel yielded the optimum GA-LSSVM models describing 88% and 95% of the cross-validation variance for the constitutive and ghrelin-induced activities, respectively. AASA vectors in the optimum models mainly appeared weighted by hydrophobicity-related properties. However, differently to the constitutive activity, the ghrelin-induced activity was also highly dependent of the steric features of the receptor.
authors.affiliation: Molecular Modeling Group, Center for Biotechnological Studies, Faculty of Agronomy, University of Matanzas, 44740 Matanzas, Cuba.
authors.forename: Julio
authors.initials: J
authors.lastname: Caballero
authors.forename: Leyden
authors.initials: L
authors.lastname: Fernández
authors.forename: Miguel
authors.initials: M
authors.lastname: Garriga
authors.forename: José Ignacio
authors.initials: JI
authors.lastname: Abreu
authors.forename: Simona
authors.initials: S
authors.lastname: Collina
authors.forename: Michael
authors.initials: M
authors.lastname: Fernández
mesh_terms: D000465:Algorithms; D000595:Amino Acid Sequence; D001185:Artificial Intelligence; D030562:Databases, Protein; D006801:Humans; D066298:In Vitro Techniques; D016018:Least-Squares Analysis; D016014:Linear Models; D008958:Models, Molecular; D009154:Mutation; D017711:Nonlinear Dynamics; D040901:Proteomics / Q000379:methods* / Q000706:statistics & numerical data; D021281:Quantitative Structure-Activity Relationship; D043562:Receptors, G-Protein-Coupled / Q000737:chemistry* / Q000235:genetics* / Q000378:metabolism; D054440:Receptors, Ghrelin
chemical_list: D043562:Receptors, G-Protein-Coupled; D054440:Receptors, Ghrelin