Most frequently harboured missense variants of hACE2 across different populations exhibit varying patterns of binding interaction with spike glycoproteins of emerging SARS-CoV-2 of different lineages.

Since the emergence of SARS-CoV-2 at Wuhan in the Hubei province of China in 2019, the virus has accumulated various mutations, giving rise to many variants. According to the combinations of mutations acquired, these variants are classified into lineages and greatly differ in infectivity and transmissibility. In 2021 alone, a variant of interest (VoI) Mu (B.1.621), as well as, variants of concern (VoC) Delta (B.1.617.2) and Omicron (BA.1, BA.2) and later in 2022, BA.4, BA.5, and BA.2.12.1 have emerged. Since then, the world has seen prominent surges in the rate of infection during short periods of time. However, not all populations have suffered equally, which suggests a possible role of host genetic factors. Here, we investigated the strength of binding of the spike glycoprotein receptor-binding domain (RBD) of the SARS-CoV-2 variants: Mu, Delta, Delta Plus (AY.1), Omicron sub-variants BA.1, BA.2, BA.4, BA.5, and BA.2.12.1 with the human angiotensin-converting enzyme 2 (hACE2) missense variants prevalent in major populations. In this purpose, molecular docking analysis, as well as, molecular dynamics simulation was performed of the above-mentioned SARS-CoV-2 RBD variants with the hACE2 containing the single amino acid substitutions prevalent in African (E37K), Latin American (F40L), non-Finnish European (D355 N), and South Asian (P84T) populations, in order to predict the effects of the lineage-defining mutations of the viral variants on receptor binding. The effects of these mutations on protein stability were also explored. The protein-protein docking and molecular dynamics simulation analyses have revealed variable strength of attachment and exhibited altered interactions in the case of different hACE2-RBD complexes. In vitro studies are warranted to confirm these findings which may enable early prediction regarding the risk of transmissibility of newly emerging variants across different populations in the future.

Prediction of putative potential siRNAs for inhibiting SARS-CoV-2 strains, including variants of concern and interest.

Aim: To predict siRNAs as a therapeutic intervention for highly infectious new variants of SARS-CoV-2. Methods: Conserved coding sequence regions of 11 SARS-CoV-2 proteins were used to construct siRNAs through sampling of metadata comprising 214,256 sequences. Results: Predicted siRNAs S1: 5'-UCAUUGAGAAAUGUUUACGCA-3' and S2: 5'-AAAGACAUCAGCAUACUCCUG-3' against RdRp of SARS-CoV-2 satisfied all the stringent filtering processes and showed good binding characteristics. The designed siRNAs are expected to inhibit viral replication and transcription of various coronavirus strains encompassing variants of concern and interest. Conclusion: The predicted siRNAs are expected to be potent against SARS-CoV-2, and following in vitro and in vivo validations may be considered as potential therapeutic measures.

An in-depth in silico and immunoinformatics approach for designing a potential multi-epitope construct for the effective development of vaccine to combat against SARS-CoV-2 encompassing variants of concern and interest.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the latest of the several viral pathogens that have acted as a threat to human health around the world. Thus, to prevent COVID-19 and control the outbreak, the development of vaccines against SARS-CoV-2 is one of the most important strategies at present. The study aimed to design a multi-epitope vaccine (MEV) against SARS-CoV-2. For the development of a more effective vaccine, 1549 nucleotide sequences were taken into consideration, including the variants of concern (B.1.1.7, B.1.351, P.1 and, B.1.617.2) and variants of interest (B.1.427, B.1.429, B.1.526, B.1.617.1 and P.2). A total of 11 SARS-CoV-2 proteins (S, N, E, M, ORF1ab polyprotein, ORF3a, ORF6, ORF7a, ORF7b, ORF8, ORF10) were targeted for T-cell epitope prediction and S protein was targeted for B-cell epitope prediction. MEV was constructed using linkers and adjuvant beta-defensin. The vaccine construct was verified, based on its antigenicity, physicochemical properties, and its binding potential, with toll-like receptors (TLR2, TLR4), ACE2 receptor and B cell receptor. The selected vaccine construct showed considerable binding with all the receptors and a significant immune response, including elevated antibody titer and B cell population along with augmented activity of TH cells, Tc cells and NK cells. Thus, immunoinformatics and in silico-based approaches were used for constructing MEV which is capable of eliciting both innate and adaptive immunity. In conclusion, the vaccine construct developed in this study has all the potential for the development of a next-generation vaccine which may in turn effectively combat the new variants of SARS-CoV-2 identified so far. However, in vitro and animal studies are warranted to justify our findings for its utility as probable preventive measure.