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publisher‐imprint‐name Springer volume‐issue‐count 1 issue‐article‐count 0 issue‐toc‐levels 0 issue‐pricelist‐year 2020 issue‐copyright‐holder The Author(s) issue‐copyright‐year 2020 article‐contains‐esm No article‐numbering‐style Unnumbered article‐registration‐date‐year 2020 article‐registration‐date‐month 1 article‐registration‐date‐day 7 article‐toc‐levels 0 toc‐levels 0 volume‐type Regular journal‐product ArchiveJournal numbering‐style Unnumbered article‐grants‐type OpenChoice metadata‐grant OpenAccess abstract‐grant OpenAccess bodypdf‐grant OpenAccess bodyhtml‐grant OpenAccess bibliography‐grant OpenAccess esm‐grant OpenAccess online‐first false pdf‐file‐reference BodyRef/PDF/40169_2020_Article_258.pdf pdf‐type Typeset target‐type OnlinePDF issue‐type Regular article‐type OriginalPaper journal‐subject‐primary Medicine & Public Health journal‐subject‐secondary Medicine/Public Health, general journal‐subject‐collection Medicine open‐access true --> Background: The Peroxisome proliferator‐activated receptor gamma gene (PPARG), encodes a member of the peroxisome‐activated receptor subfamily of nuclear receptors. PPARs form heterodimers with retinoid X receptors (RXRs) which regulate transcription of various genes. Three subtypes of PPARs are known: PPAR‐alpha, PPAR‐delta and PPAR‐gamma. The protein encoded by this gene is PPAR‐gamma which is a regulator of adipocyte differentiation. PPARG‐gamma has been implicated in the pathology of numerous diseases including obesity, diabetes, atherosclerosis and cancer. Aim: This study aimed to perform insilico analysis to predict the effects that can be imposed by SNPs reported in PPARG gene. Methodology: This gene was investigated in NCBI database (http://www.ncbi.nlm.nih.gov/) during the year 2016 and the SNPs in coding region (exonal SNPs) that are non‐synonymous (ns SNPs) were analyzed by computational softwares. SIFT, Polyphen, I‐Mutant and PHD‐SNP softwares). SIFT was used to filter the deleterious SNPs, Polyphen was used to determine the degree of pathogenicity, I‐Mutant was used to determine the effect of mutation on protein stability while PHD‐SNP software was used to investigate the effect of mutation on protein function. Furthermore, Structural and functional analysis of ns SNPs was also studied using Project HOPE software and modeling was conducted by Chimera. Results: A total of 34,035 SNPs from NCBI, were found, 21,235 of them were found in Homo sapiens, 134 in coding non synonymous (missense) and 89 were synonymous. Only SNPs present in coding regions were selected for analysis. Out of 12 deleterious SNPs sorted by SIFT, 10 were predicted by Polyphen to be probably damaging with PISC score = 1 and only two were benign. All these 10 double positive SNPs were disease related as predicted by PHD‐SNPs and revealed decreased stability indicated by I‐Mutant. Conclusion: Based on the findings of this study, it can be concluded that the deleterious ns SNPs (rs72551364 and rs121909244SNPs) of PPARG are important candidates for the cause of different types of human diseases including diabetes mellitus. [ABSTRACT FROM AUTHOR]