Scientists discover molecular characteristics of antibodies to spikes in SARS-CoV-2.

Researchers from the US have recently identified an array of anti-severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibodies to identify the molecular components of public antibodies to SARS-CoV-2 spike protein.

Study: A large-scale systematic examination of SARS-CoV-2 antibodies reveals frequent molecular signatures. Image Credits: Mongkolchon Akesin/Shutterstock

While the study is available on the preprint server Peer review will be carried out.


Since the beginning of the coronavirus disease 2019 (COVID-19) pandemic, numerous studies have been conducted to characterize the immune system’s humoral responses triggered by the natural SARS-CoV-2 virus and vaccination. In order to identify effective therapeutic strategies monoclonal antibody that target the spike protein of SARS have been identified and characterized.

The SARS-CoV-2 spike proteins have three main domains: the receptor-binding and N-terminal domains (RBD), as well as the S2 domain. Of these domains the RBD is the most immunogenic and has been identified as the principal source of development for neutralizing antibodies..

A public antibody response refers to an array of antigen-specific antibodies derived from various individuals with genetic elements and modes of antigen recognition. The most common strategy of studying public antibody response is to identify antibodies from different individuals that share the same immunoglobulin heavy variable (IGHV) gene and complementarity-determining region (CDR) H3 sequences.

The current study consists of an exhaustive review and compilation of a massive database of monoclonal anti-SARS-CoV-2 antibodies with donor information. Utilizing the data they have examined the public response to SARS-CoV-2 spike protein.

Important observations

The scientists looked over 88 articles and 13 patents and created a database comprising more than 8,000 anti-SARS CoV-2 monoclonal antibody spikes from more than 200 donors.

They examined the immunoglobulin variable gene usage and discovered that antibodies against the NTD, RBD, and S2 had distinct patterns of V gene usage. Given the significance of CDR H3 in determining antigen-antibody binding and determining the convergence of CDR H3 sequences in anti-spike antibodies. CDR H3 sequence is the primary determinant of public antibody responses to RBD and S2 and a majority of anti-NTD antibodies have paratope antigen binding sites that aren’t dominated.

They identified a group of antibodies with paratopes primarily comprised of CDR H3 and light chain. They also observed high concentrations of anti-S2 antibodies from the immunoglobulin heavy constant Delta (IGHD1-26) gene. This gene is primarily encoded by the IGHV3-30. About 70 percent of these antibodies have an CDR H3 of 14 amino acids. After further analysis they discovered that the IGHD-dependent public antibody response to S2 is mainly driven by the heavy chain, and that IGHV3-30/IGHD1-26 is a public antibody response to a highly conserved epitope in S2.

By analyzing somatic hypermutation among anti-SARS-CoV-2 antibodies, they identified multiple recurring somatic hypermutations, including VH F27V, T28I, and Y58F, in IGHV3-53/3-66-encoded public clonotypes. They also identified novel regular somatic hypermutations that are heavy or light-chain in an IGHV1–58/IGKV3-20 clonotype.

After further investigation, they found that antibodies belonging to the IGHV158/IGKV3-20 public clonotype are able to bind to increase the RBD. These antibodies could be inducible through either infection or vaccination with different SARS-CoV-2 variants according to the research available. Moreover they are extremely efficient in neutralizing different SARS-CoV-2 variants of concern (VOCs).

They identified VL S29R as an salt bridge that connects with another somatic hypermutation in order to stabilize antigen-antibody interactions by studying the structure of the complex.

Analyse of specificity of the antigen

To distinguish between anti-spike (HA) and anti-influenza (HA) scientists employed an advanced deep-learning model. The model was trained using six CDR sequences (H1 L2, L2, and L3) and produced 4,736 antispike antibodies as well as 2,204 antifluenza HA antibodies.

The model had the best performance in distinguishing antigen-specific antibodies when trained by all six CDRs. A similar performance was also achieved when trained by three heavy-chain CDRs (H1, H2, and H3). When trained with three light-chain CDRs the model performed well. This suggests that the molecular information contained in the heavy chain sequence is the most useful in determining the antigen specificity.

Study’s importance

The study highlights a variety of molecular characteristics in the public antibody responses to SARS/CoV-2 spike protein. The researchers stated that the study findings can be used as a useful resource for understanding the molecular drivers of antigen specificity.

*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.

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Gemma Wilson

Gemma is a journalism graduate with keen interest in covering business news – specifically startups. She has as a keen eye for technologies and has predicted quite a few successful startups over the last couple of years.

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