Omicron and Delta variant spike protein mutations comparison and their interaction with ACE2 receptor

The current outbreak of coronavirus-associated disease characterized as coronavirus disease 19 (COVID-19) marked its existence in late 2019. Since then, it has been a concern for human health and safety. Coronaviruses (CoVs) are known to cause a wide range of diseases;out of which common cold and pneumonia occur in human beings. In this review, we elaborate on the basic characteristics, structure, variants mutations and the pathological attributes of SARS-CoV 2. We also discuss the interaction of the viral proteins with the host cell receptor known as the ACE2 receptor and various therapeutics for the treatment of disease.

Screening of phytochemical compounds of Tinospora cordifolia for their inhibitory activity on SARS-CoV-2: an in silico study.

In the present study, we explored phytochemical constituents of Tinospora cordifolia in terms of its binding affinity targeting the active site pocket of the main protease (3CL pro) of SARS-CoV-2 using molecular docking study and assessed the stability of top docking complex of tinosponone and 3CL pro using molecular dynamics simulations with GROMACS 2020.2 version. Out of 11 curated screened compounds, we found the significant docking score for tinosponone, xanosporic acid, cardiofolioside B, tembetarine and berberine in Tinospora cordifolia. Based on the findings of the docking study, it was confirmed that tinosponone is the potent inhibitor of main protease of SARS-CoV-2 with the best binding affinity of -7.7 kcal/mol. Further, ADME along with toxicity analysis was studied to predict the pharmacokinetics and drug-likeness properties of five top hits compounds. The molecular dynamics simulation analysis confirmed the stability of tinosponone and 3CL pro complex with a random mean square deviation (RMSD) value of 0.1 nm. The computer-aided drug design approach proved that the compound tinosponone from T. cordifolia is a potent inhibitor of 3CL main protease of SARS-CoV-2. Further, the in vitro and in vivo-based testing will be required to confirm its inhibitory effect on SARS-CoV-2.Communicated by Ramaswamy H. Sarma.

Design of multi-epitope vaccine candidate against SARS-CoV-2: a in-silico study

The best therapeutic strategy to find an effective vaccine against SARS-CoV-2 is to explore the target structural protein. In the present study, a novel multi-epitope vaccine is designed using in silico tools that potentially trigger both CD4 and CD8 T-cell immune responses against the novel Coronavirus. The vaccine candidate was designed using B and T-cell epitopes that can act as an immunogen and elicits immune response in the host system. NCBI was used for the retrieval of surface spike glycoprotein, of novel corona virus (SARS-CoV-2) strains. VaxiJen server screens the most important immunogen of all the proteins and IEDB server gives the prediction and analysis of B and T cell epitopes. Final vaccine construct was designed in silico composed of 425 amino acids including the 50S ribosomal protein adjuvant and the construct was computationally validated in terms of antigenicity, allergenicity and stability on considering all critical parameters into consideration. The results subjected to the modeling and docking studies of vaccine were validated. Molecular docking study revealed the protein-protein binding interactions between the vaccine construct and TLR-3 immune receptor. The MD simulations confirmed stability of the binding pose. The immune simulation results showed significant response for immune cells. The findings of the study confirmed that the final vaccine construct of chimeric peptide could able to enhance the immune response against nCoV-19.

Molecular docking and dynamic simulations for antiviral compounds against SARS-CoV-2: A computational study.

The aim of this study was to develop an appropriate anti-viral drug against the SARS-CoV-2 virus. An immediately qualifying strategy would be to use existing powerful drugs from various virus treatments. The strategy in virtual screening of antiviral databases for possible therapeutic effect would be to identify promising drug molecules, as there is currently no vaccine or treatment approved against COVID-19. Targeting the main protease (pdb id: 6LU7) is gaining importance in anti-CoV drug design. In this conceptual context, an attempt has been made to suggest an in silico computational relationship between US-FDA approved drugs, plant-derived natural drugs, and Coronavirus main protease (6LU7) protein. The evaluation of results was made based on Glide (Schrödinger) dock score. Out of 62 screened compounds, the best docking scores with the targets were found for compounds: lopinavir, amodiaquine, and theaflavin digallate (TFDG). Molecular dynamic (MD) simulation study was also performed for 20 ns to confirm the stability behaviour of the main protease and inhibitor complexes. The MD simulation study validated the stability of three compounds in the protein binding pocket as potent binders.