The emergence of Omicron (B.1.1.529), a new Variant of Concern in the COVID-19 pandemic, while accompanied by the ongoing Delta variant infection, has once again fueled fears of a new infection wave and global health concern. In the Omicron variant, the receptor-binding domain (RBD) of its spike glycoprotein is heavily mutated, a feature critical for the transmission rate of the virus by interacting with hACE2. In this study, we used a combination of conventional and advanced neural network-based in silico approaches to predict how these mutations would affect the spike protein. The results demonstrated a decrease in the electrostatic potentials of residues corresponding to receptor recognition sites, an increase in the alkalinity of the protein, a change in hydrophobicity, variations in functional residues, and an increase in the percentage of alpha-helix structure. Moreover, several mutations were found to modulate the immunologic properties of the potential epitopes predicted from the spike protein. Our next step was to predict the structural changes of the spike and their effect on its interaction with the hACE2. The results revealed that the RBD of the Omicron variant had a higher affinity than the reference. Moreover, all-atom molecular dynamics simulations concluded that the RBD of the Omicron variant exhibits a more dispersed interaction network since mutations resulted in an increased number of hydrophobic interactions and hydrogen bonds with hACE2.

The emergence of Omicron (B.1.1.529), a new Variant of Concern in the COVID-19 outbreak, while accompanied by the ongoing Delta variant infection, has once again fueled fears of a new infection wave and global health concern. In the Omicron variant, the receptor-binding domain (RBD) of its spike glycoprotein is heavily mutated, a feature critical for the transmission rate of the virus by interacting with hACE2. In this study, we used a combination of conventional and advanced neural network-based in silico approaches to predict how these mutations would affect the spike protein. The results demonstrated a decrease in the electrostatic potentials of residues corresponding to receptor recognition sites, an increase in the alkalinity of the protein, a change in hydrophobicity, variations in functional residues, and an increase in the percentage of alpha-helix structure. Our next step was to predict the structural changes of the spike protein using the AI-based tool Alphafold2 and dock it with hACE2. The results revealed that the RBD of the Omicron variant had a higher affinity than the reference. Moreover, all-atom molecular dynamics simulations concluded that the RBD of the Omicron variant exhibits a more dispersed interaction network since mutations resulted in an increased number of hydrophobic interactions and hydrogen bonds with hACE2 compared to the reference RBD. In summary, our current study highlighted the potential structural basis for the enhanced transmissibility and pathogenicity of the Omicron variant, although further research is needed to investigate its epidemiological and biological implications.

The highly pathogenic virus SARS-CoV-2 has shattered the healthcare system of the world causing the COVID-19 pandemic since first detected in Wuhan, China. Therefore, scrutinizing the genome structure and tracing the transmission of the virus has gained enormous interest in designing appropriate intervention strategies to control the pandemic. In this report, we examined 4,622 sequences from Bangladesh and found that they belonged to thirty-five major PANGO lineages, while Delta alone accounted for 39%, and 78% were from just four primary lineages. Our research has also shown Dhaka to be the hub of viral transmission and observed the virus spreading back and forth across the country at different times by building a transmission network. The analysis resulted in 7,659 unique mutations, with an average of 24.61 missense mutations per sequence. Moreover, our analysis of genetic diversity and mutation patterns revealed that eight genes were under negative selection pressure to purify deleterious mutations, while three genes were under positive selection pressure. Together with an ongoing genomic surveillance program, these data will contribute to a better understanding of SARS-CoV-2, as well as its evolution pattern and pandemic characteristics in Bangladesh.

The highly pathogenic virus SARS-CoV-2 has shattered the healthcare system of the world causing the COVID-19 pandemic since first detected in Wuhan, China. Therefore, scrutinizing the genome structure and tracing the transmission of the virus has gained enormous interest in designing appropriate intervention strategies to control the pandemic. In this report, we examined 4622 sequences from Bangladesh and found that they belonged to thirty-five major PANGO lineages, while Delta alone accounted for 39%, and 78% were from just four primary lineages. Our research has also shown Dhaka to be the hub of viral transmission and observed the virus spreading back and forth across the country at different times by building a transmission network. The analysis resulted in 7659 unique mutations, with an average of 24.61 missense mutations per sequence. Moreover, our analysis of genetic diversity and mutation patterns revealed that eight genes were under negative selection pressure to purify deleterious mutations, while three genes were under positive selection pressure.