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Computational analysis of a sequence variant p.N103K in leptin gene involved in obesity

. Saqib Ishaq, Muhammad Kashif , Muhammad Inam Ul Haq, Raheel Tahir , Obaid Habib, Muhammad Afzal, Musarrat Jabeen, Zaib Un Nisa, Muhammad Kamran & Abdul Aziz


Obesity and its associated  health complications is a huge health burden worldwide. Genetic factors play a crucial role in determining an individual’s predisposition to the weight gain and being obese.Leptin, a key appetite-regulating hormone derived from the white adipose tissue, primarily acts on hypothalamic neurons to activate catabolic pathway and inhibit anabolic pathway, which can result in anorexia and weight reduction.Congenital leptin deficiency is a autosomal recessive disease characterised by hyperphagia and early-onset obesity.Genome wide association studies (GWAS) approach and their findings signified a number of genetic variants predisposing to obesity, which further needs the insilico analysis to confirm the damaging effect on protein structure and function. A missense variant (c.309C>A; p.N103K) in LEPTIN gene in Egyptian child, identified through Whole exome sequencing was selected form the literature for In Silico analysis. The pathogenicity of the variant was evaluated through computational tools including Mupro, Predict, Fathmm, provean, SNAP2. additionally, the secondary structure of the normal protein and solvent accessibility were checked through RaptorX tools. The 3-Dimensional Structure was constructed via biovia discovery studio. The energy minimization of mutant structure was carried out by SWISS PDB Viewer. In the present study, Molecular Docking were performed which predicted that there is drastic decrease in the stability of the mutant protein. The energy calculation also revealed that there is a difference of kj/mol which also indicates that the variant has significantly decreased the stability of protein consequently resulting in obesity.


Key words: Insilico Analysis, Obesity, Missense variants, Molecular Docking, leptin

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