Proteometric study of ghrelin receptor function variations upon mutations using amino acid sequence autocorrelation...

Area of Science:

• Biochemistry
• Genetics
• Computational Biology

Background:

• Mutations in the human ghrelin receptor are linked to short stature and obesity syndromes.
• Obesity associated with these mutations often manifests around puberty.

Purpose of the Study:

• To perform a proteometrics analysis of wild-type and mutant ghrelin receptor activity.
• To encode protein structural information using amino acid sequence autocorrelation (AASA).
• To build predictive models for receptor activity.

Main Methods:

• Calculated AASA vectors based on 48 amino acid properties from the AAindex database.
• Employed genetic algorithm-based multilinear regression analysis (GA-MRA) and least square support vector machines (GA-LSSVM).
• Utilized a genetically optimized radial basis function (RBF) kernel for GA-LSSVM models.

Main Results:

• Achieved 88% and 95% cross-validation variance for constitutive and ghrelin-induced activities, respectively.
• AASA vectors were primarily influenced by hydrophobicity-related properties.
• Ghrelin-induced activity additionally depended on the receptor's steric features, unlike constitutive activity.

Conclusions:

• Proteometrics analysis combined with AASA effectively models ghrelin receptor activity.
• Hydrophobicity and steric properties are critical determinants of ghrelin receptor function.
• This approach offers insights into the structural basis of obesity syndromes linked to ghrelin receptor mutations.