Structural basis of Omicron immune evasion: A comparative computational study

Is the BNT162b2 vaccine still effective against the latest variant: XBB.1.5?

Background

The XBB.1.5 sub-variant of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron now continues to spread rapidly due to the increased transmission rate as a result of increased affinity of the virus binding over the ACE-2 receptor - a gained property due to the mutation that occurred in spike protein.

Aim

The protectivity of BNT162b2 antibodies produced in the serum of patients is an important parameter for preventing transmission. However, the affinity of the antibodies of patients vaccinated with BNT162b2 over the latest SARS-CoV-2 variant, XBB.1.5, is not well established. This study aimed to evaluate the efficacy of the BNT162b2 vaccine-induced antibody on XBB.1.5 by comparing the X-ray crystallographic structures and spike protein mutations of BA.5 and XBB.1.5 using in silico methods.

Materials and Methods

Binding points and binding affinity values of the BNT162b2 antibody with BA.5 and XBB.1.5 spike protein were calculated using ClusPro 2.0 protein-protein docking and Discovery Studio 2021 Client software. Mutations in the genetic code of the spike protein for SARS-CoV-2 BA.5 and XBB.1.5 sub-variants were screened using the GISAID database.

Results

Binding affinity values showed that BNT162b2 had higher negative values in the XBB.1.5 sub-variant than BA.5 at the mutation sites at the binding region. The results suggested that BNT162b2 may retain its activity despite mutations and conformational changes in the binding site of the XBB.1.5.

Conclusion

The findings of this study shed light on the importance and usability of the current BNT162b2 vaccine for XBB.1.5 and future variants of concern.

Affinity maturation of antibody fragments: A review encompassing the development from random approaches to computational rational optimization

Routinely screened antibody fragments usually require further in vitro maturation to achieve the desired biophysical properties. Blind in vitro strategies can produce improved ligands by introducing random mutations into the original sequences and selecting the resulting clones under more and more stringent conditions. Rational approaches exploit an alternative perspective that aims first at identifying the specific residues potentially involved in the control of biophysical mechanisms, such as affinity or stability, and then to evaluate what mutations could improve those characteristics. The understanding of the antigen-antibody interactions is instrumental to develop this process the reliability of which, consequently, strongly depends on the quality and completeness of the structural information. Recently, methods based on deep learning approaches critically improved the speed and accuracy of model building and are promising tools for accelerating the docking step. Here, we review the features of the available bioinformatic instruments and analyze the reports illustrating the result obtained with their application to optimize antibody fragments, and nanobodies in particular. Finally, the emerging trends and open questions are summarized.

Comparative computational study to augment UbiA prenyltransferases inherent in purple photosynthetic bacteria cultured from mangrove microbial mats in Qatar for coenzyme Q10 biosynthesis

Coenzyme Q10 (CoQ10) is a powerful antioxidant with a myriad of applications in healthcare and cosmetic industries. The most effective route of CoQ10 production is microbial biosynthesis. In this study, four CoQ10 biosynthesizing purple photosynthetic bacteria: Rhodobacter blasticus, Rhodovulum adriaticum, Afifella pfennigii and Rhodovulum marinum, were identified using 16S rRNA sequencing of enriched microbial mat samples obtained from Purple Island mangroves (Qatar). The membrane bound enzyme 4-hydroxybenzoate octaprenyltransferase (UbiA) is pivotal for bacterial biosynthesis of CoQ10. The identified bacteria could be inducted as efficient industrial bio-synthesizers of CoQ10 by engineering their UbiA enzymes. Therefore, the mutation sites and substitution residues for potential functional enhancement were determined by comparative computational study. Two mutation sites were identified within the two conserved Asp-rich motifs, and the effect of proposed mutations in substrate binding affinity of the UbiA enzymes was assessed using multiple ligand simultaneous docking (MLSD) studies, as a groundwork for experimental studies.

Genomic and structural mechanistic insight to reveal the differential infectivity of omicron and other variants of concern

BACKGROUND

The genome of SARS-CoV-2, is mutating rapidly and continuously challenging the management and preventive measures adopted and recommended by healthcare agencies. The spike protein is the main antigenic site that binds to the host receptor hACE-2 and is recognised by antibodies. Hence, the mutations in this site were analysed to assess their role in differential infectivity of lineages having these mutations, rendering the characterisation of these lineages as variants of concern (VOC) and variants of interest (VOI).

METHODS

In this work, we examined the genome sequence of SARS-CoV-2 VOCs and their phylogenetic relationships with the other PANGOLIN lineages. The mutational landscape of WHO characterized variants was determined and mutational diversity was compared amongst the different severity groups. We then computationally studied the structural impact of the mutations in receptor binding domain of the VOCs. The binding affinity was quantitatively determined by molecular dynamics simulations and free energy calculations.

RESULTS

The mutational frequency, as well as phylogenetic distance, was maximum in the case of omicron followed by the delta variant. The maximum binding affinity was for delta variant followed by the Omicron variant. The increased binding affinity of delta strain followed by omicron as compared to other variants and wild type advocates high transmissibility and quick spread of these two variants and high severity of delta variant.

CONCLUSION

This study delivers a foundation for discovering the improved binding knacks and structural features of SARS-CoV-2 variants to plan novel therapeutics and vaccine candidates against the virus.

In Silico Analysis of the Effects of Omicron Spike Amino Acid Changes on the Interactions with Human Proteins

The SARS-CoV-2 variant Omicron is characterized, among others, by more than 30 amino acid changes occurring on the spike glycoprotein with respect to the original SARS-CoV-2 spike protein. We report a comprehensive analysis of the effects of the Omicron spike amino acid changes in the interaction with human antibodies, obtained by modeling them into selected publicly available resolved 3D structures of spike–antibody complexes and investigating the effects of these mutations at structural level. We predict that the interactions of Omicron spike with human antibodies can be either negatively or positively affected by amino acid changes, with a predicted total loss of interactions only in a few complexes. Moreover, our analysis applied also to the spike-ACE2 interaction predicts that these amino acid changes may increase Omicron transmissibility. Our approach can be used to better understand SARS-CoV-2 transmissibility, detectability, and epidemiology and represents a model to be adopted also in the case of other variants.