The In Vitro α-glucosidase and α-amylase inhibitory activity and In Vivo postprandial antihyperglycemic activity of Ficus nota Blanco Merr. and Ficus septica Burm. F. leaf methanolic extracts

Background@#One of the therapeutic strategies for type 2 diabetes mellitus involves suppressing postprandial hyperglycemia by inhibiting key enzymes in carbohydrate digestion, α-glucosidase and α-amylase. While such inhibitors are commercially available, some researchers have turned to plants for potentially cheaper and safer alternatives.@*Objectives@#The study aimed to investigate the in vitro α-glucosidase and α-amylase inhibitory activities of the leaf methanolic extracts of two native Philippine plants Ficus nota Blanco Merr. and Ficus septica Burm F, as well as their effects on postprandial blood glucose levels in a mouse model.@*Methodology@#The in vitro activities of the leaf methanolic extracts were evaluated against porcine pancreatic α-amylase and yeast αglucosidase. The most active extract was partially purified into fractions by sequential solvent partitioning and subjected to in vitro testing. Postprandial antihyperglycemic activity was then assessed in normoglycemic ICR mice. Phytochemical analysis was also performed@*Results@#The most active extract and fraction in vitro were FS-crude and FS-HexF, respectively, having significantly more potent αglucosidase inhibitory activity than the commercial drug acarbose. FS-crude and FS-HexF exhibited strong inhibition of αglucosidase and weak inhibition of α-amylase, which is considered favorable for novel inhibitors as it is hypothesized to reduce gastrointestinal adverse effects. However, FS-crude and FS-HexF did not significantly attenuate postprandial blood glucose levels in the oral starch tolerance test. Phytochemical analysis of FS-HexF putatively identified 6-gingerol as one of the possible bioactive components.@*Conclusion@#F. septica could be a potential source of glycoside inhibitors as it showed promising in vitro inhibition of α-amylase and α-glucosidase. While it did not exhibit significant postprandial antihyperglycemic activity in this study, more robust testing is recommended to make a definitive conclusion.

In silico prediction of SARS-COV-2 epitopes for vaccine development

@#The ongoing coronavirus disease (COVID-19) pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is causing major damages in health and economies worldwide. The development of safe and effective vaccines for COVID-19 is of utmost importance yet none have been licensed to date. One of the strategies for vaccine development utilizes dendritic cells which express class I and class II human leukocyte antigen (HLA) molecules. These HLA molecules present the antigenic peptides to T cells which mediate the immune response. Thus, the study aimed to identify SARS-CoV-2 peptides with potential binding to HLA class I and class II molecules using different bioinformatics tools. SYFPEITHI and IEDB were used to predict epitopes for the most common HLA class I and II alleles among Filipinos. The top predicted epitopes were subjected to de novo and template-based molecular docking. Then, binding energies of the generated peptide-HLA complexes to putative T cell receptors were predicted using a homology modeling approach. Several predicted epitopes showed promising MHC and TCR binding, although results varied considerably between the prediction methods used. In particular, the results of de novo and template-based docking methods did not coincide, the latter of which generated complexes that more closely resemble typical peptide-HLA complexes. The results of this study will be validated by the next stage of the vaccine development project which is the in vitro assessment of the T cell responses elicited by dendritic cells pulsed with the candidate peptides.

In silico prediction of SARS-CoV-2 epitopes for vaccine development

@#The ongoing coronavirus disease (COVID-19) pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is causing major damages in health and economies worldwide. The development of safe and effective vaccines for COVID-19 is of utmost importance yet none have been licensed to date. One of the strategies for vaccine development utilizes dendritic cells which express class I and class II human leukocyte antigen (HLA) molecules. These HLA molecules present the antigenic peptides to T cells which mediate the immune response. Thus, the study aimed to identify SARS-CoV-2 peptides with potential binding to HLA class I and class II molecules using different bioinformatics tools. SYFPEITHI and IEDB were used to predict epitopes for the most common HLA class I and II alleles among Filipinos. The top predicted epitopes were subjected to de novo and template-based molecular docking. Then, binding energies of the generated peptide-HLA complexes to putative T cell receptors were predicted using a homology modeling approach. Several predicted epitopes showed promising MHC and TCR binding, although results varied considerably between the prediction methods used. In particular, the results of de novo and template-based docking methods did not coincide, the latter of which generated complexes that more closely resemble typical peptide-HLA complexes. The results of this study will be validated by the next stage of the vaccine development project which is the in vitro assessment of the T cell responses elicited by dendritic cells pulsed with the candidate peptides.