In Silico Analysis of Honey Bee Peptides as Potential Inhibitors of Capripoxvirus DNA-Directed RNA Polymerase.

The genus Capripoxvirus belongs to the Poxviridae family. The sheeppox, goatpox, and lumpy skin disease viruses are three species of this genus with 96% identity in their genomes. These are financially devastating viral infections among cattle, which cause a reduction in animal products and lead to a loss in livestock industries. In the current study, the phylogenetic analysis was carried out to reveal the evolutionary relationships of Capripoxvirus species (i.e., sheeppox virus (SPPV), goatpox virus (GTPV), and lumpy skin disease virus (LSDV)) with other viruses from the Poxviridae family with >96% query coverage to find the similarity index among all members. The three viruses (i.e., SPPV, GTPV, and LSDV) joined the clade of Capripoxvirus of the Poxviridae family in the phylogenetic tree and exhibited close evolutionary relationships. The multiple sequence alignment using ClustalOmega revealed significant variations in the protein sequences of the DNA-dependent RNA polymerase of SPPV, GTPV, and LSDV. The three-dimensional structures of five selected bee peptides and DNA-directed RNA polymerase of SPPV, GTPV, and LSDV were predicted using trRosetta and I-TASSER and used for molecular docking and simulation studies. The protein-protein docking was carried out using HADDOCK server to explore the antiviral activity of peptides as honey bee proteins against SPPV, GTPV, and LSDV. In total, five peptides were docked to DNA-directed RNA polymerase of these viruses. The peptides mellitin and secapin-1 displayed the lowest binding scores (-106.9 +/- 7.2 kcal/mol and -101.4 +/- 11.3 kcal/mol, respectively) and the best patterns with stable complexes. The molecular dynamics simulation indicated that the complex of protein DNA-dependent RNA polymerase and the peptide melittin stayed firmly connected and the peptide binding to the receptor protein was stable. The findings of this study provide the evidence of bee peptides as potent antimicrobial agents against sheeppox, goatpox, and lumpy skin disease viruses with no complexity.

Molecular Docking and Simulation-Binding Analysis of Plant Phytochemicals with the Hepatocellular Carcinoma Targets Epidermal Growth Factor Receptor and Caspase-9.

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.

Identification of Plant Peptides as Novel Inhibitors of Orthohepevirus A (HEV) Capsid Protein by Virtual Screening.

Hepatitis E virus (HEV) is the notable causative agent of acute and chronic hepatic, renal, pancreatic, neurological, and hematopoietic blood cell infections with high risk in immunocompromised patients. Hepatic failure is mostly documented among adults, pregnant women, and patients with preexisting liver disease. HEV is a positive sense RNA virus of 7.2 kb genome size with typically three open reading frames (ORFs) which play essential roles in viral replication, genome assembly, and transcription. The mutational substitution in the viral RNA genome makes more it difficult to understand the actual relationship in the host-virus association. ORFs of HEV encode different structural and non-structural proteins and one of them is the capsid protein which is coded by ORF2. The capsid protein mediates the encapsulation of the viral genome as well as being involved in virion assembly. In the current study, the ligand-based docking approach was employed to inhibit the active amino acids of the viral capsid protein. Depending upon S-score, ADMET profiling, and drug scanning, the top ten tetrapeptides were selected as potential drug candidates with no toxicity counter to HEV receptor protein. The S-score or docking score is a mathematical function which predicts the binding affinities of docked complexes. The binding affinity of the predicted drug-target complexes helps in the selectivity of the desired compound as a potential drug. The best two selected peptides (i.e., TDGH with S-score of -8.5 and EGDE with S-score of -8.0) interacted with the active site amino acids of the capsid protein (i.e., Arg399, Gln420, and Asp444). The molecular dynamics simulations of RMSD trajectories of TDGH-capsid protein and EDGE-capsid protein have revealed that both docked complexes were structurally stable. The study revealed that these tetrapeptides would serve as strong potential inhibitors and a starting point for the development of new drug molecules against the HEV capsid protein. In future, in vivo studies are needed to explore selected peptides as potential drug candidates.

Investigation of Plant Antimicrobial Peptides against Selected Pathogenic Bacterial Species Using a Peptide-Protein Docking Approach.

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.

Identification of Peptides as Novel Inhibitors to Target IFN-γ, IL-3, and TNF-α in Systemic Lupus Erythematosus.

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.

Molecular Docking and Simulation Studies of Antidiabetic Agents Devised from Hypoglycemic Polypeptide-P of Momordica charantia.

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.

Sequence and Structural Characterization of Toll-Like Receptor 6 from Human and Related Species.

Toll-like receptors (TLRs) play an important role in the innate immune response against various pathogens. They serve as expected targets of natural selection in those species which are adapted to habitats with contrasting pathogen burdens. Till date, sufficient literature about TLRs especially TLR6 is not available. The current study was therefore planned to show evolutionary patterns of human TLRs generally and TLR6 specifically along with their conservation and diversity. The study also deals with characteristic polymorphic patterns of TLR6 in humans which are involved in serious clinical consequences. The sequence analysis of TLR6 from different mammals revealed conserved regions in the protein sequence. With respect to TLR6 evolution, human showed a close evolutionary relationship with chimpanzee and orangutans, while monkeys were appeared in a separate clade showing a distant evolutionary relationship. Old World monkeys and New World monkeys made their separate clades but both have evolved from a common ancestor. The C-terminal of human TLRs (TLR1 to TLR10) exhibited more conservation as compared to other regions. The phylogram of human TLRs showed that TLR6 is closely related to TLR1 and both TLRs shared a common ancestor with TLR10. The domain analysis has revealed that TLR1 and TLR10 have least (i.e., 4) number of leucine-rich repeat (LRR) while TLR6 contains five LRRs. Three single nucleotide polymorphisms were found in TLR6 which were found to be associated with benign. Conclusively, the current comparative sequence analyses and phylogenetic analyses provided informative insights into the process of TLR evolution in mammals. Furthermore, the polymorphism analysis would serve as a useful marker in the early detection of susceptibility and resistance against cancers and other diseases in humans.

In Silico Characterization of Growth Differentiation Factors as Inhibitors of TNF-Alpha and IL-6 in Immune-Mediated Inflammatory Disease Rheumatoid Arthritis.

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-ß 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.

An in silico approach to target RNA-dependent RNA polymerase of COVID-19 with naturally occurring phytochemicals.

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.

Investigation of Hypoglycemic Peptides Derived from Conserved Regions of adMc1 to Reveal Their Antidiabetic Activities.

Diabetes mellitus is the most common chronic disorder and leading cause of renal, neurological, and gastrointestinal manifestations in developed and developing countries. Despite of many drugs and combinational therapies, the complications of diabetes are still listed due to severe consequences of those drugs. In past few years, plant-derived drugs draw special attention due to their higher efficacy and fewer side-effects. Momordica charantia also known as bitter melon is referred as an antidiabetic and hypoglycemic plant in native populations of Asia and East Africa. In current study, an in silico approach was used to evaluate the interactions and binding patterns of plant-derived peptides devised from a hypoglycemic protein adMc1 of M. charantia as potential inhibitor of DPP-IV, SGLT1, and GLUT2 receptor proteins. The study has described a novel approach to investigate hypoglycemic peptides to cure diabetes. A total of eighty tetra-, penta-, and hexapeptides were devised from conserved regions of adMc1 homologs. The molecular docking approach using MOE software was employed to reveal inhibiting potentials of devised peptides against three selected proteins. Out of 30 shortlisted ligands six peptides (i.e. SMCG, DECC, TTIT, RTTI, ARNL and TVEV) accomplished the criteria of being good drug candidates against selected receptor proteins following the drugability assessment test. The overall results are acceptable on the basis of ADMET profiling for being good drug candidates against selected proteins.

The COVID-19 puzzle: a global nightmare.

In December 2019, WHO was informed with several unknown pneumonia cases and later it was found as highly contagious, transmittable and pathogenic viral infection. The novel coronavirus (nCoV-19) was firstly reported from Wuhan city in China. COVID-19 has raised the concern of the world since its emergence from China. The WHO has declared an ongoing COVID-19 outbreak as a pandemic. Till now 6,057,853 confirmed cases with 371,166 deaths have been reported from approximately 213 countries of the world. The aim of this study is to discuss all the aspects related to recently discovered novel coronavirus. The article, therefore, provides a comprehensive study on the genomic, epidemiological, social, clinical and environmental aspects of SARS-CoV-2. SARS-CoV-2 uses human ACE2 receptor as a ligand to bind and transmit its genome just like the SARS-CoV. The clinical symptoms of SARS-CoV-2 are very non-specific and include fever, sore throat, wheezing, rales, headache and rhinorrhoea with round-glass pulmonary opacifications shadowing in X-ray. Many antiviral drugs show efficacy but only in mild to moderate infection levels. Though efforts on development of SARS-CoV-2 vaccine have been started earlier as soon as the pandemic was emerged, till date no effective drug or vaccine has been validated with significant efficacy against the disease; therefore, there is a dire need to design effective vaccine against SARS-CoV-2. Multiple vaccine candidates are still in evaluation and exploratory stages on different clinical models with potential results on different animals and human models. mRNA-1273, ChAdOx1, Ad5-nCoV, INO-4800, LV-SMENP-DC and pathogen-specific aAPC are the most advanced and potential drug candidates against COVID-19. Recent studies have revealed any attractive vaccine candidates as promising therapeutic agents based on different strategies of vaccines. Here, the rationale of this review was also to provide an overview of the pathogenesis of the virus and summarize the updated potential vaccine candidates against SARS-CoV-2.

Screening and molecular docking of selected phytochemicals against NS5B polymerase of hepatitis c virus.

Hepatitis C virus (HCV) has major role in spreading of liver diseases worldwide. The HCV nonstructural NS5B is a polymerase (RdRp) that is present at the carboxylic-end of the polyprotein chain. It is essential and most important for the replication cycle. In current study, the potential of 100 phytochemicals against HCV NS5B polymerase was determined. Phytochemical structures were retrieved from PubChem database. The phytochemicals were docked with the NS5B active site amino acids, in order to discover their attractions as inhibitors. After docking, molecules with top five conformations were selected from 100 molecules by docking scores and RMSD values. The results demonstrated strong interactions of phytochemicals with the NS5B. The selected compounds with best docking scores and RMSD were found to be glycitein, ferulic acid, eugenol, 1-octanol and sebacic acid. These were further evaluated through Lipinski's rule of five to explore their molecular properties and drug-likeliness characteristics and all five selected phytochemicals were found to have drug-likeliness characteristics. Further, according to ADME analysis, the ferulic acid, 1-octanol and eugenol were found to be nontoxic, non-carcinogenic and have the ability to cross the blood brain barriers. Therefore, these phytochemicals could be strong drug candidates for HCV NS5B.