The novel coronavirus disease 2019 (COVID-19) was firstly reported from Wuhan city of China and found as a highly contagious, transmittable and pathogenic viral infection. The World Health Organization declared COVID-19 as a pandemic since its emergence from China. The RNA-dependent RNA polymerase (nsp-12) is a complex with nsp-7 and nsp-8 cofactors and is a major constituent of viral replication and RNA synthesis machinery. In the current study, the RdRp of the virus was selected as a receptor protein for computational drug discovery. Computational homology modelling was done in order to find the hidden secondary structures and structural assessment of the viral protein to target them via antiviral drugs. The study was based on molecular docking of different phytochemicals to check their potentials against viral replicative proteins. Out of 200 ligands used in this study from different plants, the best ten were selected based on drug discovery parameters such as S-score, ligand interactions, hydrophobic interactions and druglikeness. The ten best selected ligands were found to be verbenalin, epigallocatechin, swertisin, nobiletin, pinoresinol, caftaric acid, hesperetin, islandicin, neochlorogenic acid and sesamin that exploit the potency as antagonists of viral protein. Among binding interactions of all ligands, Arg339 centred as the main interacting residue among almost all the ligands. Till now, many antiviral agents have shown potency in only mild cases of SARS-CoV-2, but no effective drug has been found for critical pulmonary cases. In clinical trials, many broad-spectrum antiviral agents have been still in trial periods of testing against SARS-CoV-2. Till date, no effective drug or vaccine has been validated with significant efficacy and potency against the SARS-CoV-2; therefore, there is an urgent need to design effective vaccine against nCoV-19 infection.

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.

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.

Autoimmune disorder is a chronic immune imbalance which is developed through a series of pathways. The defect in B cells, T cells, and lack of self-tolerance has been greatly associated with the onset of many types of autoimmune complications including rheumatoid arthritis, systemic lupus erythematosus (SLE), multiple sclerosis, and chronic inflammatory demyelinating polyneuropathy. The SLE is an autoimmune disease with a common type of lupus that causes tissue and organ damage due to the wide spread of inflammation. In the current study, twenty anti-inflammatory peptides derived from plant and animal sources were docked as ligands or peptides counter to proinflammatory cytokines. Interferon gamma (IFN-γ), interleukin 3 (IL-3), and tumor necrosis factor alpha (TNF-α) were targeted in this study as these are involved in the pathogenesis of SLE in many clinical studies. Two docking approaches (i.e., protein-ligand docking and peptide-protein docking) were employed in this study using Molecular Operating Environment (MOE) software and HADDOCK web server, respectively. Amongst docked twenty peptides, the peptide DEDTQAMMPFR with S -score of -11.3018 and HADDOCK score of − 10.3 ± 2.5  kcal/mol showed the best binding interactions and energy validation with active amino acids of IFN-γ protein in both docking approaches. Depending upon these results, this peptide could be used as a potential drug candidate to target IFN-γ, IL-3, and TNF-α proteins to control inflammatory events. Other peptides (i.e., QEPQESQQ and FRDEHKK) also revealed good binding affinity with IFN-γ with S -scores of -10.98 and -10.55, respectively. Similarly, the peptides KHDRGDEF, FRDEHKK, and QEPQESQQ showed best binding interactions with IL-3 with S -scores of -8.81, -8.64, and -8.17, respectively.

The Middle East respiratory syndrome coronavirus (MERS-CoV) is the major leading cause of respiratory infections listed as blueprint of diseases by the World Health Organization. It needs immediate research in the developing countries including Saudi Arabia, South Korea, and China. Still no vaccine has been developed against MERS-CoV; therefore, an effective strategy is required to overcome the devastating outcomes of MERS. Computer-aided drug design is the effective method to find out potency of natural phytochemicals as inhibitors of MERS-CoV. In the current study, the molecular docking approach was employed to target receptor binding of CoV. A total of 150 phytochemicals were docked as ligands in this study and found that some of the phytochemicals successfully inhibited the catalytic triad of MERS-CoV. The docking results brought novel scaffolds which showed strong ligand interactions with Arg178, Arg339, His311, His230, Lys146, and Arg139 residues of the viral domains. From the top ten ligands found in this study (i.e., rosavin, betaxanthin, quercetin, citromitin, pluviatilol, digitogenin, ichangin, methyl deacetylnomilinate, kobusinol A, and cyclocalamin) based on best S -score values, two phytochemicals (i.e., pluviatilol and kobusinol A) exhibited all drug-likeness properties following the pharmacokinetic parameters which are important for bioavailability of drug-like compounds, and hence, they can serve as potential drug candidates to stop the viral load. The study revealed that these phytochemicals would serve as strong potential inhibitors and a starting point for the development of vaccines and proteases against MERS-CoV. Further, in vivo studies are needed to confirm the efficacy of these potential drug candidates.