The relationship of maternal age, BMI, serum Tenascin-C, and HOMA-IR values with gestational diabetes mellitus.

Objectives: To explore the relationship, if any, of gestational diabetes mellitus with maternal age, body mass index, serum tenascin-C and homeostatic model assessment for insulin resistance, and to see if these could act as predictive markers for gestational diabetes mellitus. METHODS: The case-control study was conducted from February to August 2022 at the outpatient department of gynaecology and obstetrics at the Civil Hospital, Karachi, and comprised pregnant females aged 18-40 years having gestational age 20-34 weeks. After noting down baseline characteristics and anthropometric measurements, the participants were subjected to oral glucose tolerance test on the basis of which they were divided into three groups; pregnant healthy controls in group 1, those with gestational diabetes mellitus on diet control in group 2, and those with gestational diabetes mellitus taking medicines for the condition in group 3. Fasting serum samples were used for further analysis using enzyme-linked immunosorbent assay kits. Data was analysed using SPSS 21. RESULTS: Of the 90 subjects, 30(33.3%) were in group 1 with mean age 26.0±4.9 years, 30(33.3%) were in group 2 with mean age 30.7±5.6 years, and 30(33.3%) were in group 3 with mean age 29.1±5.5 years. Age, gestational age, body mass index and homeostatic model assessment for insulin resistance values were significantly higher in groups 2 and 3 compared to group 1 (p<0.05), while serum Tenascin-C values were not significantly different (p>0.05). CONCLUSIONS: HOMA-IR values and BMI were more reliable in diagnosing GDM before its onset, and should be included in the screening test for GDM in early pregnancy.

Understanding the impact of structural modifications at the NNAT gene's post-translational acetylation site: in silico approach for predicting its drug-interaction role in anorexia nervosa.

PURPOSE: Anorexia nervosa (AN) is a neuropsychological public health concern with a socially disabling routine and affects a person's healthy relationship with food. The role of the NNAT (Neuronatin) gene in AN is well established. The impact of mutation at the protein's post-translational modification (PTM) site has been exclusively associated with the worsening of the protein's biochemical dynamics. METHODS: To understand the relationship between genotype and phenotype, it is essential to investigate the appropriate molecular stability of protein required for proper biological functioning. In this regard, we investigated the PTM-acetylation site of the NNAT gene in terms of 19 other specific amino acid probabilities in place of wild type (WT) through various in silico algorithms. Based on the highest pathogenic impact computed through the consensus classifier tool, we generated 3 residue-specific (K59D, P, W) structurally modified 3D models of NNAT. These models were further tested through the AutoDock Vina tool to compute the molecular drug binding affinities and inhibition constant (Ki) of structural variants and WT 3D models. RESULTS: With trained in silico machine learning algorithms and consensus classifier; the three structural modifications (K59D, P, W), which were also the most deleterious substitution at the acetylation site of the NNAT gene, showed the highest structural destabilization and decreased molecular flexibility. The validation and quality assessment of the 3D model of these structural modifications and WT were performed. They were further docked with drugs used to manage AN, it was found that the ΔGbind (kcal/mol) values and the inhibition constants (Ki) were relatively lower in structurally modified models as compared to WT. CONCLUSION: We concluded that any future structural variation(s) at the PTM-acetylation site of the NNAT gene due to possible mutational consequences, will serve as a basis to explore its relationship with the propensity of developing AN. LEVEL OF EVIDENCE: No level of evidence-open access bioinformatics research.

In Silico Characterization of Withania coagulans Bioactive Compounds as Potential Inhibitors of Hydroxymethylglutaryl (HMG-CoA) Reductase of Mus musculus.

Hypercholesterolemia is a mediator for the etiology of cardiovascular diseases, which are characterized as the global leading cause of mortality. We aimed to investigate the inhibitory activity of Withania coagulans compounds against 3-hydroxy-3-methylglutaryl-coenzyme A reductase (Hmgcr) of Mus musculus using an extensive in silico approach. The 3D structure of the Hmgcr protein is not yet known, so we performed the homology modeling using MODELLER and SWISS-MODEL tools, followed with structural validation and assessment. The PROCHECK web server showed that the top-ranked homology model from SWISS-MODEL has 93.4% of residues in the most-favorable region, the quality factor was 98%, and the Verify3D score was 91.43%, compared to the other generated models. The druggable protein-binding cavities in a 3D model of Hmgcr were investigated with the aid of commonly prescribed statin compounds using the CB-dock approach. We compiled a 3D compound library of W. coagulans, followed by drug-likeness evaluation, and found 20 eligible compounds. The pattern of consensus residues obtained from the CB-dock procedure was then used for grid-box docking of W. coagulans compounds and statin drugs using AutoDock 4.2, respectively. The results showed that withanolide R (-10.77 kcal/mol), withanolide Q (-10.56 kcal/mol), withanolide J (-10.52 kcal/mol), atorvastatin (-8.99 kcal/mol), simvastatin (-8.66 kcal/mol), and rosuvastatin (-8.58 kcal/mol) were promising candidates that bind Hmgcr protein. The key residues involved in protein-ligand (withanolide R) interactions were Y516, C526, V529, I530, M533, I535, and V537, and the formation of a H-bond was at C526, M533, and I535 residues. M533 was the consensus residue having a tendency to form a H-bond with withanolide Q, too. Molecular dynamics simulations were used to validate the top-ranked docked complexes for the stability of the modeled protein. We also predicted the pharmacokinetic properties of binding affinity-based top-ranked compounds and concluded that they could be used as potential inhibitors of Hmgcr. However, further in vitro and in vivo studies are essential to completing the drug development process.