Network Pharmacology and Experimental Validation to Explore the Potential Mechanism of Nigella sativa for the Treatment of Breast Cancer.

Breast cancer is a prevalent and potentially life-threatening disease that affects women worldwide. Natural products have gained attention as potential anticancer agents due to their fewer side effects, low toxicity, and cost effectiveness compared to traditional chemotherapy drugs. In the current study, the network pharmacology approach was used following a molecular docking study to evaluate the therapeutic potential of N. sativa-derived phytochemicals against breast cancer. Specifically, the study aimed to identify potential anticancer agents targeting key proteins implicated in breast cancer progression. Five proteins (i.e., EGFR, MAPK3, ESR1, MAPK1, and PTGS2) associated with breast cancer were selected as receptor proteins. Fourteen phytochemicals from N. sativa were prioritized based on drug-likeness (DL) and oral bioavailability (OB) parameters (with criteria set at DL > 0.18 and OB > 30%, respectively). Subsequent analysis of gene targets identified 283 overlapping genes primarily related to breast cancer pathogenesis. Ten hub genes were identified through topological analysis based on their significance in the KEGG pathway and GO annotations. Molecular docking revealed strong binding affinities between folic acid, betulinic acid, stigmasterol, and selected receptor proteins. These phytochemicals also demonstrated druggability potential. In vitro experiments in the MDA-MB-231 breast cancer cell line revealed that betulinic acid and stigmasterol significantly reduced cell viability after 24 h of treatment, confirming their anticancer activity. Furthermore, in vivo evaluation using a DMBA-induced rat model showed that betulinic acid and stigmasterol contributed to the significant recovery of cancer markers. This study aimed to explore the mechanisms underlying the anticancer potential of N. sativa phytochemicals against breast cancer, with the ultimate goal of identifying novel therapeutic candidates for future drug development. Overall, these results highlight betulinic acid and stigmasterol as promising candidates to develop novel anticancer agents against breast cancer. The comprehensive approach of this study, which integrates network pharmacology and molecular docking study and its experimental validation, strengthens the evidence supporting the therapeutic benefits of N. sativa-derived phytochemicals in breast cancer treatment, making them promising candidates for the development of novel anticancer agents against breast cancer.

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.

Exploring the antihyperglycemic potential of tetrapeptides devised from AdMc1 via different receptor proteins inhibition using in silico approaches.

INTRODUCTION: Diabetes mellitus is a heterogenous group of chronic metabolic disorders that results due to deficiency in insulin secretion and signalling. Multiple factors held responsible for onset of diabetes due to defects in glucose metabolism and cellular signalling mechanism. Over the past few years, many plant derived bioactive compounds have been recorded with increased efficacy and fewer side-effects against variety of diseases. METHODS: In the current study, molecular docking and molecular dynamics simulation approaches were employed to evaluate the tetrapeptides devised from AdMc1 protein of Momordica charantia. Due to unavailability of appropriate template for modelling of 3D structure of AdMc1 protein, I-TASSER server was employed for prediction of good quality tertiary structure. Predicted model was refined by GalaxyRefine Web and evaluated by Verify 3D, ERRAT and Ramachandran plot analysis. Next, a ready-to-dock library of fifty tetrapeptides as potent inhibitors was prepared and docked against aldose reductase (AR), protein tyrosine phosphatase 1B (PTP1B), α-glucosidase, α-amylase and glycogen synthase kinase 3-beta as receptor proteins. Molecular dynamics (MD) simulation was performed on Schrodinger's Desmond Module to check stability of the best docking complex. RESULTS: Top five ligands were selected against each receptor protein based on their binding pattern and docking scores. Among selected ligands (i.e. VEID, TVEV, AYAY, EEIA, ITTV, TTIT, LPSM, RGIE, TTVE and EIAR) followed all parameters in drug scanning and ADMET screening tests. The MD simulations confirmed that the best selected peptide (i.e. VEID) docked with AR and PTP1B was structurally stable. CONCLUSION: In the light of overall results of all analyses employed in this study, the selected ligands could be further processed as potential hypoglycaemic drug candidates.

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.

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.