Farnesoid X receptor (FXR) modulates the expression of genes involved in lipid and carbohydrate homeostasis and inflammatory processes. This nuclear receptor is likely a tumor suppressor in several cancers but its molecular mechanism of suppression is still under study. Several studies reported that FXR agonism increase the survival of colorectal, biliary tract and liver cancer patients. In addition, FXR expression was shown to be downregulated in many diseases such as obesity, irritable bowel syndrome, glomerular inflammation, diabetes, proteinuria and ulcerative colitis. Therefore, development of novel FXR agonists may have significant potential in the prevention and treatment of these diseases. In this scenario, computer-aided drug design procedures can be resourcefully applied for the rapid identification of promising drug candidates. In the present research study, we applied the molecular docking method in conjunction with molecular dynamics (MD) simulations to find out potential agonists for FXR based on structural similarity with the drug that is currently used as FXR agonist, obeticholic acid. Our results showed that alvimopan and montelukast could be used as potent FXR activators and outperform the binding affinity of obeticholic acid by forming stable conformation with the protein in silico. However, further investigational studies and validations of the selected drugs are essential to figure out their suitability for in vivo experiments and clinical trials.

14-Membered cyclopeplide alkaloids, franganine, frangufoline, amphiblne-0 and mauritine-A has been isolated from the whole plant of Zizyphus xylopyra and their structures established by spectral evidences. This is the first report of these alkaloids from Z. xylupyra.

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The whole world is drastically affected by the current pandemic due to severe virus, SARS-CoV-2 and scientists are rigorously looking for the efficient vaccine against it that become an emergent issue. Reverse vaccinology approach may provide us with significant therapeutic leads in this direction and further determination of T-cell / B-cell response to antigen. In the present study, we conducted population coverage analysis referring to the diverse Indian population. By using tools from Immune epitope database (IEDB), HLA- distribution analysis was performed to find the most promiscuous T-cell epitope out of In silico determined epitope of Spike protein from SARS-CoV-2. Selection of these epitopes have been conducted based on their binding affinity with the maximum number of HLA alleles belong to the highest population coverage rate values for the chosen geographical area in India. 404 cleavage sites within the 1288 amino acids sequence of spike glycoprotein were determined by NetChop proteasomal cleavage prediction suggesting that this protein has adequate sites in the protein sequence for cleaving into appropriate epitopes. For population coverage analysis, 221 selected epitopes are considered that shows the projected population coverage as 83.08% with 19.29 average hit (average number of epitope hits/HLA combinations recognized by the population) and 5.91 pc90 (minimum number of epitope hits/HLA combinations recognized by 90% of the population). 54 epitopes are found with the highest coverage among the Indian population and highly conserved within the given spike RBD domain sequence. Docking analysis of each epitope with their respective allele suggests that the epitope NSFTRGVYY represents highest binding affinity with docking score -7.6 kcal/mol with its allele HLA-C*07:01 among all the epitopes. Since the Covid-19 cases are still in progress and seem to remain like this until we find an effective vaccine, moreover in countries like India, vast diversity in the population may present a hindrance to particular vaccine efficiency. Outcomes from this study could be critical to design vaccine against SARS-CoV-2 for a different set of the population within the country.