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In silico analysis of nonsynonymous single nucleotide polymorphisms of the human adiponectin receptor 2 (ADIPOR2) gene

Solayman M, Saleh MA, Paul S, Khalil MI, Gan SH

Comput Biol Chem, 2017 Jun;68:175-185.
PMID: 28359874 DOI: 10.1016/j.compbiolchem.2017.03.005

Polymorphisms of the ADIPOR2 gene are frequently linked to a higher risk of developing diseases including obesity, type 2 diabetes and cardiovascular diseases. Though mutations of the ADIPOR2 gene are detrimental, there is a lack of comprehensive in silico analyses of the functional and structural impacts at the protein level. Considering the involvement of ADIPOR2 in glucose uptake and fatty acid oxidation, an in silico functional analysis was conducted to explore the possible association between genetic mutations and phenotypic variations. A genomic analysis of 82 nonsynonymous SNPs in ADIPOR2 was initiated using SIFT followed by the SNAP2, nsSNPAnalyzer, PolyPhen-2, SNPs&GO, FATHMM and PROVEAN servers. A total of 10 mutations (R126W, L160Q, L195P, F201S, L235R, L235P, L256R, Y328H, E334K and Q349H) were predicted to have deleterious effects on the ADIPOR2 protein and were therefore selected for further analysis. Theoretical models of the variants were generated by comparative modeling via MODELLER 9.16. A protein structural analysis of these amino acid variants was performed using SNPeffect, I-Mutant, ConSurf, Swiss-PDB Viewer and NetSurfP to explore their solvent accessibility, molecular dynamics and energy minimization calculations. In addition, FTSite was used to predict the ligand binding sites, while NetGlycate, NetPhos2.0, UbPerd and SUMOplot were used to predict post-translational modification sites. All of the variants showed increased free energy, though F201S exhibited the highest energy increase. The root mean square deviation values of the modeled mutants strongly indicated likely pathogenicity. Remarkably, three binding sites were detected on ADIPOR2, and two mutations at positions 328 and 201 were found in the first and second binding pockets, respectively. Interestingly, no mutations were found at the post-translational modification sites. These genetic variants can provide a better understanding of the wide range of disease susceptibility associated with ADIPOR2 and aid the development of new molecular diagnostic markers for these diseases. The findings may also facilitate the development of novel therapeutic elements for associated diseases.

Matched MeSH terms: Receptors, Adiponectin/genetics*
Fulltext Impacts of Nonsynonymous Single Nucleotide Polymorphisms of Adiponectin Receptor 1 Gene on Corresponding Protein Stability: A Computational Approach

Saleh MA, Solayman M, Paul S, Saha M, Khalil MI, Gan SH

Biomed Res Int, 2016;2016:9142190.
PMID: 27294143 DOI: 10.1155/2016/9142190

Despite the reported association of adiponectin receptor 1 (ADIPOR1) gene mutations with vulnerability to several human metabolic diseases, there is lack of computational analysis on the functional and structural impacts of single nucleotide polymorphisms (SNPs) of the human ADIPOR1 at protein level. Therefore, sequence- and structure-based computational tools were employed in this study to functionally and structurally characterize the coding nsSNPs of ADIPOR1 gene listed in the dbSNP database. Our in silico analysis by SIFT, nsSNPAnalyzer, PolyPhen-2, Fathmm, I-Mutant 2.0, SNPs&GO, PhD-SNP, PANTHER, and SNPeffect tools identified the nsSNPs with distorting functional impacts, namely, rs765425383 (A348G), rs752071352 (H341Y), rs759555652 (R324L), rs200326086 (L224F), and rs766267373 (L143P) from 74 nsSNPs of ADIPOR1 gene. Finally the aforementioned five deleterious nsSNPs were introduced using Swiss-PDB Viewer package within the X-ray crystal structure of ADIPOR1 protein, and changes in free energy for these mutations were computed. Although increased free energy was observed for all the mutants, the nsSNP H341Y caused the highest energy increase amongst all. RMSD and TM scores predicted that mutants were structurally similar to wild type protein. Our analyses suggested that the aforementioned variants especially H341Y could directly or indirectly destabilize the amino acid interactions and hydrogen bonding networks of ADIPOR1.

Matched MeSH terms: Receptors, Adiponectin/genetics*
High-intensity interval training induced PGC-1∝ and AdipoR1 gene expressions and improved insulin sensitivity in obese individuals

Asilah Za'don NH, Amirul Farhana MK, Farhanim I, Sharifah Izwan TO, Appukutty M, Salim N, et al.

Med J Malaysia, 2019 12;74(6):461-467.
PMID: 31929469

INTRODUCTION: High-intensity interval training (HIIT) has been found to improve cardiometabolic health outcome as compared to moderate-intensity continuous exercise. However, there is still limited data on the benefits of HIIT on the expression of regulatory proteins that are linked to skeletal muscle metabolism and insulin sensitivity in obese adults. This study investigated the effects of HIIT intervention on expressions of peroxisome proliferatoractivated receptor-γ coactivator 1-∝ (PGC-1∝) and adiponectin receptor-1 (AdipoR1), insulin sensitivity (HOMAIR index), and body composition in overweight/obese individuals.
METHODS: Fifty overweight/obese individuals aged 22-29 years were assigned to either no-exercise control (n=25) or HIIT (n=25) group. The HIIT group underwent a 12-week intervention, three days/week, with intensity of 65-80% of age-based maximum heart rate. Anthropometric measurements, homeostatic model of insulin resistance (HOMA-IR) and gene expression analysis were conducted at baseline and post intervention.
RESULTS: Significant time-by-group interactions (p<0.001) were found for body weight, BMI, waist circumference and body fat percentage. The HIIT group had lower body weight (2.3%, p<0.001), BMI (2.7%, p<0.001), waist circumference (2.4%, p<0.001) and body fat percentage (4.3%, p<0.001) post intervention. Compared to baseline, expressions of PGC-1∝ and AdipoR1 were increased by approximately three-fold (p=0.019) and two-fold (p=0.003) respectively, along with improved insulin sensitivity (33%, p=0.019) in the HIIT group.
CONCLUSION: Findings suggest that HIIT possibly improved insulin sensitivity through modulation of PGC-1∝ and AdipoR1. This study also showed that improved metabolic responses can occur despite modest reduction in body weight in overweight/obese individuals undergoing HIIT intervention.

Matched MeSH terms: Receptors, Adiponectin/genetics*

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