Bioinformatics Study of m.9053G>A Mutation at the ATP6 Gene in Relation to Type 2 Diabetes Mellitus and Cataract Diseases

Proposed molecular mechanism of non-competitive inhibition using molecular dynamics simulations between α-glucosidase enzyme and mangostin compound as antidiabetic

CONTEXT

Further understanding of the molecular mechanisms is necessary since it is important for designing new drugs. This study aimed to understand the molecular mechanisms involved in the design of drugs that are inhibitors of the α-glucosidase enzyme. This research aims to gain further understanding of the molecular mechanisms underlying antidiabetic drug design. The molecular docking process yielded 4 compounds with the best affinity energy, including γ-Mangostin, 1,6-dimethyl-ester-3-isomangostin, 1,3,6-trimethyl-ester-α-mangostin, and 3,6,7-trimethyl-ester-γ-mangostin. Free energy calculation with molecular mechanics with generalized born and surface area solvation indicated that the 3,6,7-trimethyl-γ-mangostin had a better free energy value compared to acarbose and simulated maltose together with 3,6,7-trimethyl-γ-mangostin compound. Based on the analysis of electrostatic, van der Waals, and intermolecular hydrogen interactions, 3,6,7-trimethyl-γ-mangostin adopts a noncompetitive inhibition mechanism, whereas acarbose adopts a competitive inhibition mechanism. Consequently, 3,6,7-trimethyl-ester-γ-mangostin, which is a derivative of γ-mangostin, can provide better activity in silico with molecular docking approaches and molecular dynamics simulations.

METHOD

This research commenced with retrieving protein structures from the RCSB database, generating the formation of ligands using the ChemDraw Professional software, conducting molecular docking with the Autodock Vina software, and performing molecular dynamics simulations using the Amber software, along with the evaluation of RMSD values and intermolecular hydrogen bonds. Free energy, electrostatic interactions, and Van der Waals interaction were calculated using MM/GBSA. Acarbose, used as a positive control, and maltose are simulated together with test compound that has the best free energy. The forcefields used for molecular dynamics simulations are ff19SB, gaff2, and tip3p.

In Silico Study of Mangostin Compounds and Its Derivatives as Inhibitors of α-Glucosidase Enzymes for Anti-Diabetic Studies

Diabetes is a chronic disease with a high mortality rate worldwide and can cause other diseases such as kidney damage, narrowing of blood vessels, and heart disease. The concomitant use of drugs such as metformin, sulfonylurea, miglitol, and acarbose may cause side effects with long-term administration. Therefore, natural ingredients are the best choice, considering that their long-term side effects are not significant. One of the compounds that can be used as a candidate antidiabetic is mangostin; however, information on the molecular mechanism needs to be further analyzed through molecular docking, simulating molecular dynamics, and testing the in silico antidiabetic potential. This study focused on modeling the protein structure, molecular docking, and molecular dynamics simulations and analyses. This process produces RMSD values, free energies, and intermolecular hydrogen bonding. Based on the analysis results, all molecular dynamics simulations can occur under physiological conditions, and γ-mangostin is the best among the test compounds.

Inflammatory Mechanisms of Diabetes and Its Vascular Complications

The main cause of death in patients with type 2 DM is cardiovascular complications resulting from the progression of atherosclerosis. The pathophysiology of the association between diabetes and its vascular complications is complex and multifactorial and closely related to the toxic effects of hyperglycemia that causes increased generation of reactive oxygen species and promotes the secretion of pro-inflammatory cytokines. Subsequent oxidative stress and inflammation are major factors of the progression of type 2 DM and its vascular complications. Data on the pathogenesis of the development of type 2 DM and associated cardiovascular diseases, in particular atherosclerosis, open up broad prospects for the further development of new diagnostic and therapeutic approaches.

Molecular Dynamics Simulation of T10609C and C10676G Mutations of Mitochondrial ND4L Gene Associated With Proton Translocation in Type 2 Diabetes Mellitus and Cataract Patients

The mutation rate of mitochondrial DNA (mtDNA) is 17 times higher than nuclear DNA, and these mutations can cause mitochondrial disease in 1 of 10.000 people. The T10609C mutation was identified in type 2 diabetes mellitus (T2DM) patients and the C10676G mutation in cataract patients, with both mutations occurring in the ND4L gene of mtDNA that encodes ND4L protein. ND4L protein, a subunit of complex I in the respiratory complex, has been shown to play a role in the proton translocation process. The purpose of this study was to investigate the effect of both mutations on the proton translocation mechanism. Mutation mapping showed changes in amino acids M47T (T10609C) and C69W (C10676G). The 100 ns molecular dynamics (MD) simulations performed on native and mutants of ND4L-ND6 subunits. It is revealed that the native model had a similar proton translocation pathway to that of complex I from other organisms. Interestingly, the mutant M47T and C69W showed the interruption of the translocation pathway by a hydrogen bond formation between Glu34 and Tyr157. It is observed that the mutations were restricting the passage of water molecules through the transmembrane region. These results could help to develop the computational assay for the validation of a specific genetic biomarker for T2DM and cataracts.

Mitochondrial ND1 T4216C and ND2 C5178A mutations are associated with maternally transmitted diabetes mellitus

Mutations in mitochondrial DNA (mtDNA) are important causes for type 2 diabetes mellitus (T2DM). To investigate the association between mtDNA mutations/variants and diabetes, we reported here clinical, genetic and biochemical characterization of a Chinese pedigree with maternally transmitted T2DM. Using PCR and direct sequencing analysis of mitochondrial genomes from the matrilineal relatives, we identified two potential pathogenic mutations, m.T4216C (p.Y304H) and m.C5178A (p.L237M) in the ND1 and ND2 genes, respectively, together with a set of genetic polymorphisms belonging to the human mitochondrial haplogroup D4b. Moreover, by isolating and analyzing polymononuclear leukocytes generated from the T2DM patients and controls, we identified lower levels of mitochondrial membrane potential and ATP production in T2DM patients than in the controls, in contrast, a significantly higher level of reactive oxygen species was observed in the T2DM patients carrying both of the m.T4216C and m.C5178A mutations (p < 0.05 for all). In addition, the plasma levels of malondialdehyde and 8-hydroxydeoxyguanosine in the T2DM patients markedly increased, while the level of superoxide dismutase decreased (p < 0.05 for all). Taken together, our data indicated that the ND1 T4216C and ND2 C5178A mutations may lead to oxidative stress and impair the mitochondrial function, and this, in turn, might have been involved in the pathogenesis and progression of T2DM in this pedigree. Thus, our study provides novel insight into the pathophysiology of T2DM that is manifested by mitochondrial dysfunction.

Mitogenomic Perspectives on the Adaptation to Extreme Alkaline Environment of Amur ide (Leuciscus waleckii)

Amur ide (Leuciscus waleckii, Family Cyprinidae) is widely distributed in Northeast Asia. L. waleckii usually inhabits freshwater environments but can also survive in the Lake Dali Nur, one of the most extreme aquatic environments on the earth, with an alkalinity up to 50 mmol/L (pH 9.6). To investigate mechanisms of mitogenomic evolution underlying adaptation to extreme environments, we determined 30 complete mitogenomes that included Lake Dali Nur (alkaline environment, AL) population and Amur basin (freshwater environment, FW) population. Through phylogenetic and divergence time analysis, we found that AL and FW populations forming distinct two groups which were consistent with geographic divergence (the formation of Lake Dali Nur). In addition, we found that almost of the windows exhibited higher nucleotide diversity in FW population (avg 0.0046) than AL population (avg 0.0012). This result indicated that severe environment selection had remarkably reduced the genetic diversity of mitogenome in AL population and suggested that severe environment selection had remarkably reduced the genetic diversity of mitogenome in the AL population. Compared with the FW population (ω = 0.064), the AL population (ω = 0.092) had a larger mean ω (dN/dS ratios) value for the 13 concatenated mitochondrial protein-coding genes, indicating that the high alkaline tolerated group had accumulated more nonsynonymous mutations. These nonsynonymous mutations had resulted in slightly beneficial amino acid changes that allowed adaption to the severe conditions. This study provides an additional view to decipher the adaptive mitogenome evolution of L. waleckii of the high alkaline environment.