Computational Analysis of Gly482Ser Single-Nucleotide Polymorphism in PPARGC1A Gene Associated with CAD, NAFLD, T2DM, Obesity, Hypertension, and Metabolic Diseases

Abstract

Peroxisome proliferator-activated receptor-gamma coactivator 1-alpha (PPARGC1A) regulates the expression of energy metabolism’s genes and mitochondrial biogenesis. The essential roles of PPARGC1A encouraged the researchers to assess the relation between metabolism-related diseases and its variants. To study Gly482Ser (+1564G/A) single-nucleotide polymorphism (SNP) after PPARGC1A modeling, we substitute Gly482 for Ser482. Stability prediction tools showed that this substitution decreases the stability of PPARGC1A or has a destabilizing effect on this protein. We then utilized molecular dynamics simulation of both the Gly482Ser variant and wild type of the PPARGC1A protein to analyze the structural changes and to reveal the conformational flexibility of the PPARGC1A protein. We observed loss flexibility in the RMSD plot of the Gly482Ser variant, which was further supported by a decrease in the SASA value in the Gly482Ser variant structure of PPARGC1A and an increase of H-bond with the increase of β-sheet and coil and decrease of turn in the DSSP plot of the Gly482Ser variant. Such alterations may significantly impact the structural conformation of the PPARGC1A protein, and it might also affect its function. It showed that the Gly482Ser variant affects the PPARGC1A structure and makes the backbone less flexible to move. In general, molecular dynamics simulation (MDS) showed more flexibility in the native PPARGC1A structure. Essential dynamics (ED) also revealed that the range of eigenvectors in the conformational space has lower extension of motion in the Gly482Ser variant compared with WT. The Gly482Ser variant also disrupts PPARGC1A interaction. Due to this single-nucleotide polymorphism in PPARGC1A, it became more rigid and might disarray the structural conformation and catalytic function of the protein and might also induce type 2 diabetes mellitus (T2DM), coronary artery disease (CAD), and nonalcoholic fatty liver disease (NAFLD). The results obtained from this study will assist wet lab research in expanding potent treatment on T2DM.

Molecular Dynamics Simulation and Essential Dynamics of Deleterious Proline 12 Alanine Single-Nucleotide Polymorphism in PPARγ2 Associated with Type 2 Diabetes, Cardiovascular Disease, and Nonalcoholic Fatty Liver Disease

“…A higher number of H-bonds were observed in the PPAR γ 2 mutant than in the wild-type protein which might lead to a rigid structure of PPAR γ 2. Previously, we indicated which G482S leads to rigidity and instability of PPARGC1A protein [ 6 ]. Kamaraj and Purohit also showed R326H and R356Q resulting in rigidity of tyrosinase-related protein-1 (TYRP1) protein which might disturb the structural conformation and catalytic function of the structure and also play a significant role in inducing Oculocutaneous albinism type III (OCA3) [ 46 ].…”

“…Molecular dynamics simulation was indicated the difference in the dynamics of the PPAR γ 2 mutant and wild-type proteins. The dynamics of the protein are dependent on the structural flexibility of PPAR γ 2, and H-bonds are essential to stabilize the protein structure [ 6 ]. MD results displayed the decreased flexibility of the Pro12Ala polymorphism structure.…”

“…Principal component analysis was computed using g_covar and g_anaeig built-in functions of the GROMACS package. PCA is a standard protocol for the characterization of eigenvectors and the projection across the first PC1 and PC2 [ 6 ].…”

“…The nonsynonymous SNPs are further divided into missense mutations and nonsense mutations. The coding synonymous SNPs have a low effect on the protein structure, while the nonsynonymous SNPs have a great impact on the protein structure and higher risk of diseases [ 6 ]. The most common single-nucleotide polymorphism PPAR γ 2 rs1801282 (C>G Pro12Ala) was identified by Yen et al in 1997 that reduces transcription of PPAR γ 2 [ 7 , 8 ].…”

Identification of differentially expressed genes and signaling pathways in gestational diabetes mellitus by integrated bioinformatics analysis

“…ROS1 [250], WNT2 [251], PHLDA2 [252], WNT5A [253], HSD11B2 [254], CLDN1 [255], CYP24A1 [256], HRG (histidine rich glycoprotein) [257], TLR3 [258], THBS1 [259], TRPC6 [260], SELP (selectin P) [261], CLU (clusterin) [262], CDKN1A [263], ITGB1 [264], HLA-E [265], IL6R [266], TIMP1 [267], SERPINA1 [268], CD74 [269], PANX1 [270], STIM1 [271] and CXCR4 [272] were revealed to be correlated with disease outcome in patients with preeclampsia. Previously reported studies have shown that the expression of LBP (lipopolysaccharide binding protein) [273], MC1R [274], CXCL14 [275], RGN (regucalcin) [276], NPY2R [277], MFAP5 [278], WNT5A [279], EDA (ectodysplasin A) [280], THSD7A [281], NEUROD1 [282], SLIT2 [283], PPARGC1A [219], IGF1 [144], OSR1 [284], TLR3 [285], BMP7 [286], POSTN (periostin) [287], LRP1B [288], THBS1 [289], NOTCH2 [290]. LRP1 [291], CLU (clusterin) [292], SMAD3 [91], TGFB1 [293], APP (amyloid beta precursor protein) [294], ITGB2 [295], IL6R [296], TIMP1 [297], CD47 [298], CD74 [299], RARA (retinoic acid receptor alpha) [300], DOCK2 [301], F13A1 [302], IRF7 [303], STIM1 [304], CXCR4 [305], MGLL (monoglyceride lipase) [306], M6PR [307], USP22 [308] and CASP2 [309] were mainly involved in progression of obesity, but these genes might be novel targets for GDM.…”