Ebola viruses (EBOVs) have been identified as an emerging threat in recent year as it causes severe haemorrhagic fever in human. Epitope-based vaccine design for EBOVs remains a top priority because a mere progress has been made in this regard. Another reason is the lack of antiviral drug and licensed vaccine although there is a severe outbreak in Central Africa. In this study, we aimed to design an epitope-based vaccine that can trigger a significant immune response as well as to prognosticate inhibitor that can bind with potential drug target sites using various immunoinformatics and docking simulation tools. The capacity to induce both humoral and cell-mediated immunity by T cell and B cell was checked for the selected protein. The peptide region spanning 9 amino acids from 42 to 50 and the sequence TLASIGTAF were found as the most potential B and T cell epitopes, respectively. This peptide could interact with 12 HLAs and showed high population coverage up to 80.99%. Using molecular docking, the epitope was further appraised for binding against HLA molecules to verify the binding cleft interaction. In addition with this, the allergenicity of the epitopes was also evaluated. In the post-therapeutic strategy, docking study of predicted 3D structure identified suitable therapeutic inhibitor against targeted protein. However, this computational epitope-based peptide vaccine designing and target site prediction against EBOVs open up a new horizon which may be the prospective way in Ebola viruses research; the results require validation by in vitro and in vivo experiments.

Recent concerning facts of Chikungunya virus (CHIKV); a Togaviridae family alphavirus has proved this as a worldwide emerging threat which causes Chikungunya fever and devitalizing arthritis. Despite severe outbreaks and lack of antiviral drug, a mere progress has been made regarding to an epitope-based vaccine designed for CHIKV. In this study, we aimed to design an epitope-based vaccine that can trigger a significant immune response as well as to prognosticate inhibitor that can bind with potential drug target sites by using various immunoinformatics and docking simulation tools. Initially, whole proteome of CHIKV was retrieved from database and perused to identify the most immunogenic protein. Structural properties of the selected protein were analyzed. The capacity to induce both humoral and cell-mediated immunity by T cell and B cell were checked for the selected protein. The peptide region spanning 9 amino acids from 397 to 405 and the sequence YYYELYPTM were found as the most potential B cell and T cell epitopes respectively. This peptide could interact with as many as 19 HLAs and showed high population coverage ranging from 69.50% to 84.94%. By using in silico docking techniques the epitope was further assessed for binding against HLA molecules to verify the binding cleft interaction. In addition with this, the allergenicity of the epitopes was also evaluated. In the post therapeutic strategy, three dimensional structure was predicted along with validation and verification that resulted in molecular docking study to identify the potential drug binding sites and suitable therapeutic inhibitor against targeted protein. Finally, pharmacophore study was also performed in quest of seeing potent drug activity. However, this computational epitope-based peptide vaccine designing and target site prediction against CHIKV opens up a new horizon which may be the prospective way in Chikungunya virus research; the results require validation by in vitro and in vivo experiments.

Background Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), the etiologic agent of coronavirus disease 2019 (COVID-19), is rapidly acquiring new mutations. Analysis of these mutations is necessary for gaining knowledge regarding different aspects of therapeutic development. Previously, we have reported a Sanger method-based genome sequence of a viral isolate named SARS-CoV-2 NIB-1, circulating in Bangladesh. The genome has four novel non-synonymous mutations in V121D, V843F, A889V, and G1691C positions. Results Using different computational tools, we have found V121D substitution has the potential to destabilize the non-structural protein-1 (NSP-1). NSP-1 inactivates the type-1 interferon-induced antiviral system. Hence, this mutant could be a basis of attenuated vaccines against SARS-CoV-2. V843F, A889V, and G1691C are all located in nonstructural protein-3 (NSP-3). G1691C can decrease the flexibility of the protein. V843F and A889V might change the binding pattern and efficacy of SARS-CoV-2 papain-like protease (PLPro) inhibitor GRL0617. V843F substitution in PLPro was the most prevalent mutation in the clinical samples. This mutation showed a reduced affinity for interferon-stimulated gene-15 protein (ISG-15) and might have an impact on innate immunity and viral spread. However, V843F+A889V double mutant exhibited the same binding affinity as wild type PLPro. A possible reason behind this phenomenon can be that V843F is a conserved residue of PLPro which damaged the protease structure, but A889V, a less conserved residue, presumably neutralized that damage. Conclusions Mutants of NSP-1 could provide attenuated vaccines against coronavirus. Also, these mutations of PLPro might be targeted to develop better anti-SARS therapeutics. We hope our study will help to get better insides during the development of attenuated vaccine and PLPro inhibitors.

ABSTRACT A coding-complete genome sequence of a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) isolate was revealed. The sample for the virus was isolated from a female patient from Dhaka, Bangladesh, suffering from coronavirus disease-2019 (COVID-19).

Diabetes mellitus (DM) is one of the most prevalent metabolic disorders which can affect the quality of life severely. Injectable insulin is currently being used to treat DM which is mainly associated with patient inconvenience. Small molecules that can act as insulin receptor (IR) agonist would be better alternatives to insulin injection. Herein, ten bioactive small compounds derived from Gymnema sylvestre (G. sylvestre) were chosen to determine their IR binding affinity and ADMET properties using a combined approach of molecular docking study and computational pharmacokinetic elucidation. Designing structural analogues were also performed for the compounds associated with toxicity and less IR affinity. Among the ten parent compounds, six were found to have significant pharmacokinetic properties with considerable binding affinity towards IR while four compounds were associated with toxicity and less IR affinity. Among the forty structural analogues, four compounds demonstrated considerably increased binding affinity towards IR and less toxicity compared with parent compounds. Finally, molecular interaction analysis revealed that six parent compounds and four analogues interact with the active site amino acids of IR. So this study would be a way to identify new therapeutics and alternatives to insulin for diabetic patients.