In silico approach to identify non-synonymous SNPs in human obesity related gene, MC3R (melanocortin-3-receptor)

被引:13
作者
Singh, Rajan Kumar [1 ]
Mahalingam, Kulandaivelu [1 ]
机构
[1] VIT Univ, Sch Biosci & Technol, Dept Biomed Sci, Vellore 632014, Tamil Nadu, India
关键词
MC3R Obesity; Energy homeostasis; SNPs; Homology modeling; SINGLE NUCLEOTIDE POLYMORPHISMS; PROTEIN STRUCTURES; EVOLUTIONARY INFORMATION; RECEPTOR MUTATIONS; CHILDHOOD OBESITY; STABILITY CHANGES; SUSCEPTIBILITY; CONSEQUENCES; MECHANISMS; DYNAMICS;
D O I
10.1016/j.compbiolchem.2016.12.009
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
The melanocortitt-3-receptor (MC3R) is a novel gene candidate for human obesity, which involved in controlling the energy homeostasis and food intake behavior. The main aim behind this work is to investigate the potentially deleterious non-synonymous single nucleotide polymorphisms (nsSNPs) in obesity related gene MC3R by using six computational tools viz., PolyPhen, I-Mutant, PROVEAN, SIFT, PANTHER and PhD-SNP. In our study, we predicted eight nsSNPs i.e., rs74315393 (Ile146Asn), rs368205448 (Asp121Tyr), rs143321797 (Phe45Ser), rs17847261 (Cys274Ser), rs144166442 (Pro257His), rs370533946 (Leu224Pro), rs371354428 (Pro72Leu) and rs373708098 (Gly249Ser) found to be potentially deleterious. The functional impact of three nsSNPs i.e., rs74315393, rs368205448 and rs143321797 have already been validated experimentally in the context of human obesity. Moreover, Homology modeling and structural analysis were carried out for already experimentally validated nsSNPs i.e., rs74315393, rs368205448 and rs143321797 to check the stability of predicted models. The mutant models showed higher energy and RMSD (Root mean square deviation) values. In addition, Mite server predicted one nsSNP i.e., rs368205448 (Asp121Tyr) out of eight identified nsSNPs found in the MC3R protein binding site. Thus, the present computational study may suggest that predicted nsSNPs possibly be a better drug target and contribute to the treatment and better understanding of human obesity.(C) 2016 Published by Elsevier Ltd.
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收藏
页码:122 / 130
页数:9
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