Path to facilitate the prediction of functional amino acid substitutions in red blood cell disorders--a computational approach

Abstract

Background: A major area of effort in current genomics is to distinguish mutations that are functionally neutral from those that contribute to disease. Single Nucleotide Polymorphisms (SNPs) are amino acid substitutions that currently account for approximately half of the known gene lesions responsible for human inherited diseases. As a result, the prediction of non-synonymous SNPs (nsSNPs) that affect protein functions and relate to disease is an important task.

Principal findings: In this study, we performed a comprehensive analysis of deleterious SNPs at both functional and structural level in the respective genes associated with red blood cell metabolism disorders using bioinformatics tools. We analyzed the variants in Glucose-6-phosphate dehydrogenase (G6PD) and isoforms of Pyruvate Kinase (PKLR & PKM2) genes responsible for major red blood cell disorders. Deleterious nsSNPs were categorized based on empirical rule and support vector machine based methods to predict the impact on protein functions. Furthermore, we modeled mutant proteins and compared them with the native protein for evaluation of protein structure stability.

Significance: We argue here that bioinformatics tools can play an important role in addressing the complexity of the underlying genetic basis of Red Blood Cell disorders. Based on our investigation, we report here the potential candidate SNPs, for future studies in human Red Blood Cell disorders. Current study also demonstrates the presence of other deleterious mutations and also endorses with in vivo experimental studies. Our approach will present the application of computational tools in understanding functional variation from the perspective of structure, expression, evolution and phenotype.

Figure 1. Distribution of predicted nsSNPs in Glucose-6-phosphate dehydrogenase and Pyruvate kinase genes.

Bar diagram displays the percentage (%) of deleterious and benign nsSNPS by SIFT, PolyPhen, I-Mutant-2.0 and PANTHER. Blue rectangle bar indicates percentage of nsSNPs found to be deleterious by SIFT and PANTHER, damaging (Possibly/Probably) by PolyPhen, and decrease stability by I-Mutant-2.0. Red rectangle indicates percentage of nsSNPs tolerated by SIFT and PANTHER, benign by PolyPhen, and increase stability by I-Mutant-2.0.

Figure 2. Superimposition of native and mutant modeled structures (cartoon shape) of G6PD, PKLR and PKM2 genes.

(A). Superimposed structure of native amino acid Alanine in sphere shape (red color) with mutant amino acid Glycine (blue color) at position 44 in PDB ID 2BHL of G6PD gene with RMSD 1.88 Å. (B). Superimposed structure of native amino acid Argenine in sphere shape (red color) with mutant amino acid Cysteine (blue color) at position 163 in PDB ID 2VGB of PKLR gene with RMSD 2.82 Å. (C). Superimposed structure of native amino acid Glutamine sphere shape (red color) with mutant amino acid Proline (blue color) at position 310 in PDB ID 1T5A of PKM2 gene with RMSD 2.8 Å.