RESUMEN
Dengue virus has emerged as infectious mosquito borne disease involved in lowering platelets and white blood cells (WBC) count particularly. The genome structure is based on several structural and non-structural proteins essential for viral replication and progeny. One of the major proteins of replication is non-structural protein 3 (NS3) that transforms polyproteins into functional proteins with a cofactor non-structural protein (NS2B). Heat Shock Protein 70 (HSP70), is a human protein that assists in replication, viral entry and virion synthesis. Therefore, to inhibit the spread of dengue infection, there is a need of antivirals targeting replication proteins and other human proteins that help in dengue virus multiplication. By systemic approach based on molecular docking, ADMET (absorption, distribution, metabolism, excretion and toxicity) properties and molecular dynamic simulation (MD), potent inhibitors can be predicted. Inhibition of NS2B/NS3 dengue and HSP70 proteins involved in multiple steps in dengue virus progression can be prevented by using different phytochemicals. Molecular docking was performed using AutoDock Vina, PatchDock, and SwissDock. Interactions of obtained complex were observed in PyMOL and PLIP. Validation was checked by PROCHEK, simulation was performed using iMODS followed by preclinical testing by admetSAR. Ladanein, a flavonoid of Orthosiphon aristatus, was obtained as the lead compound to inhibit major replication protein of dengue virus with inhibitory potential against HSP70 protein. In summary, various in silico approaches were used to obtain the best phytochemical having anti-dengue potential.Communicated by Ramaswamy H. Sarma.
RESUMEN
The World Health Organization categorized SARS-CoV-2 as a variant of concern, having numerous mutations in spike protein, which have been found to evade the effect of antibodies stimulated by the COVID-19 vaccine. The susceptibility to omicron variant by immunization-induced antibodies are direly required for risk evaluation. To avoid the risk of arising viral illness, the construction of a specific vaccine that triggers the production of targeted antibodies to combat infection remains highly imperative. The aim of the present study is to develop a particular vaccine exploiting bioinformatics approaches which can target B- and T-cells epitopes. Through this approach, novel epitopes of the S protein-SARS-CoV-2 were predicted for the development of a multiple epitope vaccine. Multiple epitopes were selected on the basis of toxicity, immunogenicity and antigenicity, and vaccine subunit was constructed having potential immunogenic properties. The epitopes were linked with 3 types of linker EAAAK, AAY and GPGPG for vaccine construction. Subsequently, vaccine structure was docked with the receptor and cloned in a pET-28a (+) vector. The constructed vaccine was ligated in pET-28a (+) vector in E. coli using the SnapGene tool for the expression study and a good immune response was observed. Several computational tools were used to predict and analyze the vaccine constructed by using spike protein sequence of omicrons. The current study identified a Multi-Epitope Vaccine (MEV) as a significant vaccine candidate that could potentially help the global world to combat SARS-CoV-2 infections.
