SARS-CoV-2 (severe acute respiratory syndrome causing coronavirus 2) caused an epidemic that swept the globe and resulted in large number of casualties. It is still sporadically causing cases and has a long-term impact on the health of once infected individuals. Molnupiravir binds RNA dependent RNA polymerase (RdRp) of SARS-CoV-2 as well as spike protein. In this study, we assessed the mutated spike protein of BA.5 variant and BQ.1.1 subvariant of COVID-19 and tested their binding with it. Multiple sequence and structural alignment of homologous structures revealed highly conserved amino acid residues at the active site of the domain. The molecular docking of Molnupiravir with the active site of the domain, comprised conserved motifs (motif A-G), and exhibited considerable binding affinity against variant and subvariant protein targets. Molnupiravir exhibited stability in its interactions with the Omicron and BQ.1.1 spike proteins, preserving constant engagement within the active site. The protein and Ligand reached An equilibrium with An RMSD of 10.46 Å after 100 nanoseconds, whereas the Ligand measured 8.0 Å. Fluctuations were noted between 40 And 75 nanoseconds, stabilizing from 80 to 100 ns. In simulations including the BQ.1.1 subvariant, the RMSD values demonstrated considerable stability, exhibiting Little variations. The ligand demonstrated flexibility, altering its binding orientation over time, resulting in An average RMSD of 18.72 Å. Herein, investigation of molecular dynamics trajectories elucidated the conformational stability of Molnupiravir, emphasizing its interactions with active residues and the hydrogen bond acceptor and donor environments. The results highlighted the crucial function of protein loops in offering flexibility and enabling ligand binding within the active site. It is concluded that Molnupiravir has the potential to function as an inhibitor of both omicron and its subvariant BQ.1.1.

Insulin-producing β-cells are destroyed in type 1 diabetes mellitus (T1DM), a chronic autoimmune disease that results in complete insulin insufficiency and metabolic dysfunction. According to a survival study that used p values, some hub genes are important for predicting and diagnosing illness. Scientists have inferred medicines to identify possible therapies that interact with the identified hub genes. The GSE10586 gene expression dataset from the Gene Expression Omnibus (GEO) was used for this investigation, which included 27 samples from 15 healthy controls and 12 diabetic patients. Normalization methods such as variance stabilization normalization (VSN) were used as part of the data pretreatment. A protein‒protein interaction (PPI) network was constructed, principal component analysis (PCA) was performed, heatmaps were created, and the Limma algorithm was used to analyze differential gene expression. Using DAVID v6.8 and KEGG pathway annotations, the functional enrichment of differentially expressed genes (DEGs) was evaluated. Furthermore, a computational study revealed CERS6 to be one of the potential hub genes. Four drugs, methotrexate, eliglustat, myriocin and statin, were the focus of further studies on the basis of predictions made via ChemSpider and PubChem database analysis. To determine the optimal binding positions of these drugs with CERS6, we used molecular docking techniques. The binding affinity of methotrexate was 8.48 kcal/mol, that of myriocin was 7.85 kcal/mol, that of eliglustat was − 6.62 kcal/mol, and that of serine was − 4.90 kcal/mol against the binding pocket’s active residues. To determine how consistently each drug interacted with the CERS6 protein over time, molecular dynamics (MD) simulations were run. Throughout the simulation intervals, both medications were confirmed to be stable, with minor alterations in the CERS6 protein loop region. Therefore, the investigation of structure-based drug design has potential for identifying specific therapeutic targets. Ten hub genes were identified via network analysis of differentially expressed genes. These hub genes could serve as novel targets for T1DM detection, prognosis, and targeting. CERS6 exhibited the highest degree of interaction. Methotrexate, eliglustat, myriocin and statins were identified as potential drugs for CERS6. Overall, these findings provide valuable insights that could pave the way for new experimental strategies in T1DM therapy.

Monkeypox virus is a zoonotic virus of the genus Orthopox viruses. It can be transmitted through direct or indirect contact with animals or infected ones. Owing similarity of pathogenesis with smallpox, the same drugs can be used for both viruses, but they are not specific and only help to relieve the symptoms only. Therefore, the absence of antiviral treatment or licensed vaccine highlights an urgent need, especially due to its rapid prevalence. The study screened the library of compounds to retrieve drug-like molecules that can act against monkeypox virus. The highly virulent target gene B8R having uniport ID Q3I8J0 was chosen. Targeting B8R is substantial for global health and can align with SDG 3 and awareness of disease management. The B8R was modelled via Artificial intelligence (AI) AlphaFold method and then exposed to a library of compounds. Complementary interactions in the active site were shown by molecular docking. The Complex-1 had the greatest binding affinity (–8.4 kcal/mol), followed by Complex-2 (–8.1 kcal/mol) and Complex-3 (–7.7 kcal/mol). After 125 ns, Complex-1 reached equilibrium at 7.5 Å RMSD, according to MD simulations, exhibiting stable ligand retention and reliable interactions with crucial residues Gly135 and Lys136. Complex-3 shown intermediate protein stability (6 Å RMSD) but notable ligand fluctuation (48 Å RMSF), while Complex-2 displayed increased protein RMSD (8 Å RMSD) and delayed ligand stabilisation (16 Å RMSF). These results were corroborated by PCA analysis, which showed that Complex-1 exhibits coherent structural development whereas Complex-2 and Complex-3 show scattered and compact trajectories, respectively. Complex-1 promise for Mpox viral inhibition was highlighted by the fact that it was the most stable and dynamically favourable contender overall. The N-terminal follows the folding trend. The insilico analysis not only proposed a potent compound but also provides deep insight into the behavior of protein. The proposed potent compound against this zoonotic virus can be helpful to combat the monkeypox virus by subjecting it further towards experimental investigation.