Promising inhibitors against main protease of SARS CoV-2 from medicinal plants: In silico identification

Some compounds reported as active against SARS CoV were selected, and docking studies were performed using the main protease of SARS CoV-2 as the receptor. The docked complex analysis shows that the ligands selectively bind with the target residues and binding affinity of amentoflavone (–10.1 kcal mol–1), isotheaflavin-3’-gallate (–9.8 kcal mol–1), tomentin A and D (–8.0 and –8.8 kcal mol–1), theaflavin-3,3’-digallate (–8.6 kcal mol–1), papyriflavonol A (–8.4 kcal mol–1), iguesterin (–8.0 kcal mol–1) and savinin (–8.3 kcal mol–1) were ranked above the binding affinity of the reference, co-crystal ligand, ML188, a furan-2-carboxamide-based compound. To pinpoint the drug-like compound among the top-ranked compounds, the Lipinski’s rule of five and pharmacokinetic properties of all the selected compounds were evaluated. The results detailed that savinin exhibits high gastrointestinal absorption and can penetrate through the blood-brain barrier. Also, modifying these natural scaffolds with excellent binding affinity may lead to discovering of anti-SARS CoV agents with promising safety profiles.

In Silico Identification of Chikungunya Virus B- and T-Cell Epitopes with High Antigenic Potential for Vaccine Development

Reverse vaccinology is an outstanding strategy to identify antigens with high potential for vaccine development. Different parameters of five prediction programs were used to assess their sensitivity and specificity to identify B-cell epitopes of Chikungunya virus (CHIKV) strains reported in the IEDB database. The results, based on the use of 15 to 20 mer epitopes and the polyproteins to which they belong, were compared to establish the best parameters to optimize the prediction of antigenic peptides of the Mexican strain CHIKV AJV21562.1. LBtope showed the highest specificity when we used the reported epitopes and polyproteins but the worst sensitivity with polyproteins; ABCpred had similar specificity to LBtope only with the epitopes reported and showed moderate specificity when we used polyproteins for the predictions. Because LBtope was more reliable in predicting true epitopes, it was used as a reference program to predict and select six novel epitopes of the Mexican strain of CHIKV according to prediction frequency, viral genome localization, and non-homology with the human proteome. On the other hand, six bioinformatics programs were used with default parameters to predict T-cell epitopes in the CHIKV strains AJV21562.1 and AJV21561.1. The sequences of the polyproteins were analyzed to predict epitopes present in the more frequent HLA alleles of the Mexican population: DQA1*03011, DQA1*0401, DQA1*0501, DQB1*0201, DQB1*0301, DQB1*0302, and DQB1*0402. Fifteen predicted epitopes in the non-structural and 15 predicted epitopes in the structural polyprotein (9- to 16-mers) with the highest scores of each allele were compared to select epitopes with at least 80% identity. Next, the epitopes predicted with at least two programs were aligned to the human proteome, and 12 sequences without identity with the human proteome were identified as potential antigenic candidates. This strategy would be useful to evaluate vaccine candidates against other viral diseases affecting the countries of the Americas and to increase knowledge about these diseases.