Study uses computational modeling of coronavirus spike proteins to examine dynamics responsible for immunogenicity and immune escape

The ongoing coronavirus disease 2019 (COVID-19) pandemic is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). This is a highly infectious RNA virus belonging to the family Coronaviridae of the genus Betacoronavirus.

One of the most significant properties of this virus has been its ability to adapt to new hosts via mutations. Owing to the continual emergence of SARS-CoV-2 variants, rapid characterization of SARS-CoV-2 related proteins is needed to develop relevant treatment and prevention strategies.

Role of SARS-CoV-2’s spike protein in host cell infection

Coronaviruses have crown-like Spike (S) glycoproteins on their surface, which is a member of the class I membrane fusion protein. S proteins of the virus interact with the host and, subsequently, promote the entry of the viral capsid into the host cell cytoplasm. Scientists have revealed that S protein is a trimeric structure containing two functional subunits, i.e., the N-terminal S1 subunit and the C-terminal S2 subunit. The S1 domain assists in binding to the host cell receptor, and the S2 domain enables fusion with the host cellular membrane.

In SARS-CoV-2, the Receptor Binding Domain (RBD) on the S1 subunit binds to the human ACE2 receptor and, subsequently, proteolytic cleavage of S protein occurs. This triggers the viral fusion and replication cascade and promotes the transmission of COVID-19. The dynamic behavior and structural orientation of the RBD are vital for the binding to ACE2 of humans.

How can the binding of RBD to human ACE2 be blocked?

The S protein is an important target in the development of immunogen design. The neutralizing antibodies inhibit the attachment of the virus to the host cell by blocking the receptor binding site. Two other mechanisms by which the interaction between RBD and ACE2 is inhibited are prevention of ACE2 binding through steric clashes and inducement of conformational shifts that prevent binding.

The study of these mechanisms has been instrumental in the development of COVID-19 vaccines. Researchers have faced multiple challenges while considering the informed design of immunogenic S protein variants. Scientists have designed several different mutations of the S protein of SARS-CoV-2, such as N-terminal domain (NTD) mutations, trimerization motif editing, proline mutations, cleavage site mutations, etc., to understand viral mechanisms and determine the best neutralizing variants. They believe there is a lack of research in regards to the identification of stabilized and effective immunogens even though researchers have successfully developed the first-generation vaccine candidates targeting the S protein.

A new study

A new study published on the bioRxiv* preprint server focused on the development of dynamic computational models for a large subset of S proteins of SARS-CoV, MERS-CoV, and SARS-CoV-2. In this study, the researchers applied coarse-grained elastic network models and normal mode analysis (NMA) to characterize S proteins.

NMA is used as a standard method for generating protein dynamics. It helps understand biologically relevant fluctuations of proteins, the mechanism behind protein deformations, large molecular complexes, energy transport properties, and ligand-gated ion channels. Scientists applied these models to systematically study local protein domain dynamics of S protein systems and their thermal stability to characterize structural and dynamical variability among different variants.

A protein exhibits structural stability if it resists deformation and reorganization. Previous studies have used software based on Gaussian Network Model methods and machine learning trained on limited NMR structures to characterize the protein structure. This study developed a new algorithm for coronavirus S proteins especially; however, it applies to all biological structures in general.

To analyze the properties of various mutations and their associated viral cellular fusion mechanisms, scientists compared domains dynamics between SARS-CoV-2 mutants with SARS-CoV and MERS-CoV’s S proteins. The results obtained were compared with available antibody-binding and epitope data to generate a SARS-CoV-2 antigenic map. This model predicted u1S2q, BiPro, HexaPro, BiPro-1, and SC2.C2.1P.TM3 can elicit the most varied antibody response.

The comparative study between the dynamics of the S protein of SARS-CoV-2 and those of SARS-CoV and MERS-CoV helps understand the differential antibody binding and cellular fusion mechanisms. Subsequently, it indicates the factors owing to which the rate of transmission of SARS-CoV-2 is much higher than SARS-CoV and MERS.

The current research revealed that alterations in trimerization motifs affect trimer thermal stability and influence the overall level of global dynamics experienced by the structure. Alterations to the first 32 residues, owing to the addition or deletion of signal peptides, modify the stability of the NTD region due to the disruption of critical bonds.

S proteins of SARS-CoV-2 are structurally and dynamically sensitive to S1/S2 furin cleavage mutations, which enhance the infectiousness of the virus. This model could predict the thermal stability of the virus and reveal proline mutations and specific furin cleavage mutations that increase thermal stability. The study proposed a new approach for the characterization and screening of potential mutant candidates for the molecular design of immunogens.

Future recommendations

The scientists recommend that to design a SARS-CoV-2 S protein immunogen, it is advisable to create a multi RBD up structure with dynamics on either end of a spectrum of flexibility. Key mutations for creating such a structure would be GSAS furin cleavage site, 6P in S2, A570L, T572I, F855Y, N856I, and stabilizing the trimerization motif.

*Important notice

bioRxiv publishes preliminary scientific reports that are not peer-reviewed and, therefore, should not be regarded as conclusive, guide clinical practice/health-related behavior, or treated as established information.

Written by

Dr. Priyom Bose

Priyom holds a Ph.D. in Plant Biology and Biotechnology from the University of Madras, India. She is an active researcher and an experienced science writer. Priyom has also co-authored several original research articles that have been published in reputed peer-reviewed journals. She is also an avid reader and an amateur photographer.