Objective: Cardiovascular disease (CVD) is a leading cause of death worldwide. Malfunctioning of genes that are responsible for several inflammatory processes is the major cause for its initiation. Cytokine genes are one such group of genes that are involved in the development of CVD. Hence, the prediction of potential point mutations in these genes is important for diagnostic purposes. Such mutations result in altered protein structure and function when compared to neutral ones.Methods: In this study, interleukin factor 6 (IL6), tumor necrosis factor α (TNF-α), interleukin factor 4 (IL4), and interferon gamma have been analyzed using sorting intolerant from tolerant and PolyPhen 2.0 tools.Results: Several single nucleotide polymorphisms (SNPs), in IL6, TNF-α, and IL4, are found to be potentially deleterious. In addition, bond analysis has also been performed on these SNPs. It has been predicted that L119P and R196H of IL6 as well as K87T and T181N of TNF-α are potential ns-SNP’s that may cause structural and functional variations in the corresponding proteins. The hydrogen and Cation-Pi bond analysis performed in this study provides molecular-based evidence that support the predicted deleterious potential of such SNPs for these CVD candidate genes along with other conventional in silico tools.Conclusion: The study testifies the importance of adopting a computational approach to narrow down potential point mutants for disease predictions.

Padma Thiagarajan

Department of Bio-Medical Sciences

School of Bio Sciences and Technology

Vellore Campus

Ramesh A.S

Sethumadhavan R

Fulltext

Vellore Institute of Technology (VIT) is a private university located in&nbsp;Tamil Nadu, India. Founded in 1984, as Vellore Engineering College, the institution offers 20 undergraduate, 34 postgraduate, four integrated and four research programs. It has campuses in Vellore, Amravati, Bhopal and Chennai.

VIT is one of the top ranked private universities in India according to NIRF, THE and QS Rankings.&nbsp;Govt. of India has recognized&nbsp;VIT, Vellore as an&nbsp;Institution of Eminence. This has allowed VIT to take independent quality initiatives and move up in world ranking.

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VIT University

Asian Journal of Pharmaceutical and Clinical Research

CYP1A1 gene belongs to the cytochrome P450 family and is known better as smokers' gene due to its hyperactivation as a consequence of long term smoking. The expression of CYP1A1 induces polycyclic aromatic hydrocarbon production in the lungs, which when over expressed, is known to cause smoking related diseases, such as cardiovascular pathologies, cancer, and diabetes. Single nucleotide polymorphisms (SNPs) are the simplest form of genetic variations that occur at a higher frequency, and are denoted as synonymous and non-synonymous SNPs on the basis of their effects on the amino acids. This study adopts a systematic in silico approach to predict the deleterious SNPs that are associated with disease conditions. It is inferred that four SNPs are highly deleterious, among which the SNP with rs17861094 is commonly predicted to be harmful by all tools. Hydrophobic (isoleucine) to hydrophilic (serine) amino acid variation was observed in the candidate gene. Hence, this investigation aims to characterize a candidate gene from 159 SNPs of CYP1A1. © 2013 Springer Science+Business Media New York.

Cell Biochemistry and Biophysics

Profiling Deleterious Non-synonymous SNPs of Smoker's Gene CYP1A1

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 &amp; 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. © 2011 C, B.

PLoS ONE

Path to Facilitate the Prediction of Functional Amino Acid Substitutions in Red Blood Cell Disorders – A Computational Approach

International Tables for Crystallography

PROCHECK: validation of protein-structure coordinates

Computational and Mathematical Methods in Medicine

Analyzing Effects of Naturally Occurring Missense Mutations

Human Mutation

Prediction of missense mutation functionality depends on both the algorithm and sequence alignment employed

IMPACT OF DELETERIOUS NON-SYNONYMOUS SINGLE NUCLEOTIDE POLYMORPHISMS OF CYTOKINE GENES ON NON-CLASSICAL HYDROGEN BONDS PREDISPOSING TO CARDIOVASCULAR DISEASE: AN IN SILICO APPROACH

Journal	Asian Journal of Pharmaceutical and Clinical Research
Publisher	Innovare Academic Sciences Pvt Ltd
ISSN	0974-2441
Open Access	Yes