Diabetes mellitus termed as metabolic disorder is a collection of interlinked diseases and mainly body’s inability to manage glucose level which leads to cardiovascular diseases, renal failure, neurological disorders, and many others. The drugs contemporarily used for diabetes have many inevitable side effects, and many of them have become less responsive to this multifactorial disorder. Momordica charantia commonly known as bitter gourd has many bioactive compounds with antidiabetic properties. The current study was designed to use computational methods to discover the best antidiabetic peptides devised from hypoglycemic polypeptide‐P of M. charantia. The binding affinity and interaction patterns of peptides were evaluated against four receptor proteins (i.e., as agonists of insulin receptor and inhibitors of sodium‐glucose cotransporter 1, dipeptidyl peptidase‐IV, and glucose transporter 2) using molecular docking approach. A total of thirty‐seven peptides were docked against these receptors. Out of which, top five peptides against each receptor were shortlisted based on their S‐scores and binding affinities. Finally, the eight best ligands (i.e., LIVA, TSEP, EKAI, LKHA, EALF, VAEK, DFGAS, and EPGGGG) were selected as these ligands strictly followed Lipinski’s rule of five and exhibited good ADMET profiling. One peptide EPGGGG showed activity towards insulin and SGLT1 receptor proteins. The top complex for both these targets was subjected to 50 ns of molecular dynamics simulations and MM‐GBSA binding energy test that concluded both complexes as highly stable, and the intermolecular interactions were dominated by van der Waals and electrostatic energies. Overall, the selected ligands strongly fulfilled the drug‐like evaluation criterion and proved to have good antidiabetic properties.

Among primary liver cancers, hepatocellular carcinoma (HCC) is one of the most common forms and it has been categorized as the joint-fourth largest reason of cancer-related deaths globally. Different factors such as alcohol abuse, hepatitis B and C, viral infections, and fatty liver diseases are mainly related to the pathogenesis of HCC. In the current study, 1000 total various plant phytochemicals were docked to proteins involved in HCC. The compounds were docked to the active site amino acids of epidermal growth factor receptor and caspase-9 as receptor proteins in order to explore their inhibiting potential. The top five compounds against each receptor protein were explored as potential drug candidates on the basis of their binding affinity and root-mean square deviation values. The top two compounds against each protein were found to be liquoric acid (S-score −9.8 kcal/mol) and madecassic acid (S-score −9.3 kcal/mol) against EGFR, and limonin (S-score −10.5 kcal/mol) and obamegine (S-score −9.3 kcal/mol) against the caspase-9 protein. The selected phytochemicals were further assessed through drug scanning using Lipinski’s rule of five to explore their molecular properties and druggability. According to the ADMET analysis, the selected phytochemicals were found to be non-toxic and non-carcinogenic. Finally, the molecular dynamics simulation study revealed that liquoric acid and limonin were stabilized within the binding pockets of EGFR and capase-9, respectively, and stayed firmly bound throughout the simulation. In light of the current findings, the phytochemicals reported in this study, especially liquoric acid and limonin, could be used as potential drugs for the treatment of HCC in the future.

Objective: Medicinal herbs are being investigated for medicationhg development against SARS-CoV-2 as a rich source of bioactive chemicals. One of the finest approaches for finding therapeutically effective drug molecules in real time is virtual screening scheme such as molecular docking in conjunction with molecular dynamics (MD) simulation. These virtual techniques provide an ample opportunity for the screening of plausible inhibitors of SARS-CoV-2 different target proteins from a comprehensive and extensive phytochemical library. The study was designed to identify potential phytochemicals by virtual screening against different receptor proteins. Methods: In the current study, a library of plant secondary metabolites was created by manually curating 120 phytochemicals known to have antimicrobial as well as antiviral properties. In the current study, different potential phytochemicals were identified by virtual screening against various selected receptor proteins (i.e., viral main proteases, RNA-dependent RNA polymerase (RdRp), ADP ribose phosphatase, nonstructural proteins NSP7, NSP8, and NSP9) which are key proteins responsible for transcription, replication and maturation of SARS-CoV-2 in the host. Top three phytochemicals were selected against each viral receptor protein based on their best S-scores, RMSD values, molecular interactions, binding patterns and drug-likeness properties. Results: The results of molecular docking study revealed that phytochemicals (i.e., baicalin, betaxanthin, epigallocatechin, fomecin A, gallic acid, hortensin, ichangin, kaempferol, limonoic acid, myricetin hexaacetat, pedalitin, quercetin, quercitrin, and silvestrol) have strong antiviral potential against SARS-CoV-2. Additionally, the reported preeminent reliable phytochemicals also revealed toxicity by no means during the evaluation through ADMET profiling. Moreover, the MD simulation study also exhibited thermal stability and stable binding affinity of the pedalitin with SARS-CoV-2 RdRp and SARS-CoV-2 main protease which suggests appreciable efficacy of the lead optimization. Conclusion: The biological activity and pharmacologically distinguishing characteristics of these lead compounds also satisfied as repurposing antiviral drug contenders and are worth substantial evaluation in the biological laboratory for the recommendation of being plausible antiviral drug candidates against SARS-CoV-2.

Antimicrobial resistance is the key threat to global health due to high morbidity and mortality. The alteration of bacterial proteins, enzymatic degradation, and change of membrane permeability towards antimicrobial agents are the key mechanisms of antimicrobial resistance. Based on the current condition, there is an urgent clinical need to develop new drugs to treat these bacterial infections. In the current study, the binding patterns of selected antimicrobial peptides (AMPs) with different multidrug‐resistant bacterial strains have been analyzed. Among ten selected AMPs in this study, napin and snakin‐1 exhibited the best scores and binding patterns. Napin exhibited strong interactions with penicillin‐binding protein 1a of Acinetobacter baumannii (with a binding score of ‐158.7 kcal/mol and ten hydrogen bonds), with glucose‐1‐phosphate thymidylyltransferase of Mycobacterium tuberculosis H37Rv (with a binding score of ‐107.8 kcal/mol and twelve hydrogen bonds), and with streptomycin 3 ^″‐adenylyltransferase protein of Salmonella enterica (with a binding score of ‐84.2 kcal/mol and four hydrogen bonds). Similarly, snakin‐1 showed strong interactions with oxygen‐insensitive NADPH nitroreductase of Helicobacter pylori (with a binding score of ‐105.0 kcal/mol and thirteen hydrogen bonds) and with penicillin‐binding protein 2a of methicillin‐resistant Staphylococcus aureus (with a binding score of ‐103.8 kcal/mol and twenty‐three hydrogen bonds). The docking results were further validated by molecular dynamics simulations. The results of this computational approach support the evidence of efficiency of these AMPs as potent inhibitors of these specific proteins of bacterial strains. However, further validations are required to fully evaluate the potential of selected AMPs as drug candidates against these resistant bacterial strains.

Tumor necrosis factor alpha (TNF‐α) plays a critical role in the progression of inflammation and affects the cells of the synovial membrane. Another key factor in the progression of rheumatoid inflammation is interleukin‐6 (IL‐6). Both TNF‐α and IL‐6 promote the proliferation of synovial membrane cells thus stimulating the production of matrix metalloproteinases and other cytotoxins and leading towards bone erosion and destruction of the cartilage. Growth differentiation factor‐11 (GDF11) and growth differentiation factor‐8 (GDF8) which is also known as myostatin are members of the transforming growth factor‐β family and could be used as antagonists to inflammatory responses which are associated with rheumatoid arthritis. In the current study, to elucidate the evolutionary relationships of GDF11 with its homologs from other closely related organisms, a comprehensive phylogenetic analysis was performed. From the phylogram, it was revealed that the clade of Primates that belong to superorder Euarchontoglires showed close evolutionary relationships with order Cetartiodactyla of the Laurasiatheria superorder. Fifty tetrapeptides were devised from conserved regions of GDF11 which served as ligands in protein‐ligand docking against TNF‐α and IL‐6 followed by drug scanning and ADMET profiling of best selected ligands. The peptides SAGP showed strong interactions with IL‐6, and peptides AFDP and AGPC showed strong interactions with TNF‐α, and all three peptides fulfilled all the pharmacokinetic parameters which are important for bioavailability. The potential of GDF8 as an antagonist to TNF‐α and IL‐6 was also explored using a protein‐protein docking approach. The binding patterns of GDF8 with TNF‐α and IL‐6 showed that GDF8 could be used as a potential inhibitor of TNF‐α and IL‐6 to treat rheumatoid arthritis.