Technological advancements in recent years, such as next-generation sequencing, have made it possible for large antibody repertoire databases to exist. Databases provide an invaluable resource for researchers worldwide, providing scientists with insights into antibody structure, function, and design. This article will provide an overview and examples for sequence, antibody structure, therapeutic, and experimental databases, and its great potential to accelerate the development of therapeutic antibodies through antibody engineering and discovery.
Sequence Database
Antibody sequences are required in the antibody development and engineering process. This includes antigen binding affinity, target specificity, biological efficacy from epitope analysis, and developability properties. Therefore, database information on antibody sequences and properties are highly informative and can provide training data for artificial intelligence (AI) deep learning models.1
The Observed Antibody Space (OAS) is a sequence database collecting immune repertoires for use in large-scale analysis. It contains approximately 1.5 billion paired variable fragments and unpaired sequences, from over 80 different studies, annotated with predicted sequence errors. They cover diverse immune states, organisms, and individuals.2 Various AI models have used this database to develop humanized antibody sequences.3
The International Immunogenetics Information System (IMGT) provides databases for germline antibody sequences and is well-known for integrating sequence, genome, and structural data, particularly gene assignments for recombined antibodies.4,5
Structure Database
Antibody structures are important in antibody design, as it determines how the antibody will interact with antigens and its binding properties. Databases give researchers the resources to improve binding affinity and predict epitope and paratopes.
The Protein Data Bank (PDB) is a database for 3D structures of large biological molecules, including proteins and nucleic acids. It has been used to build up other datasets and integration systems, such as the Antibody Structure Database (AbDb), Structural Antibody Database (SAbDab), and abYsis.1,6
Therapeutic Database
Databases curating therapeutic antibody information are useful for researchers who are developing therapeutics. TABS is a database offering antibody, antigen, and company data linked to a variety of associated information on clinical trials, patents, papers, news, and regulatory agencies.7
Similarly, the Therapeutic Structural Antibody Database (Thera-SAbDab) describes antibody- and nanobody-derived therapeutics with known sequences recognized by the World Health Organization, including monoclonal antibodies and bispecifics. It also covers structural data from the PDB, and metadata for clinical trials, target antigen specificity, and companies involved in development.8
Experimental Database
These sequences and structure databases can be further enriched with antibody-specific experimental data. The Immune Epitope Database (IEDB) contains manually curated antibody and T cell epitopes researched in humans and other species, and links to epitope-specific antibody sequences.9 Furthermore, determining antibody-epitope interactions involves binding affinity information, which can be found in SAbDab and PDBBind databases.4,10
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Kim, J., McFee, M., Fang, Q., Abdin, O., & Kim, P. M. (2023). Computational and artificial intelligence-based methods for antibody development. Trends in Pharmacological Sciences, 44(3), 175–189. https://doi.org/10.1016/J.TIPS.2022.12.005
Olsen, T. H., Boyles, F., & Deane, C. M. (2022). Observed Antibody Space: A diverse database of cleaned, annotated, and translated unpaired and paired antibody sequences. Protein Science, 31(1), 141–146. https://doi.org/10.1002/PRO.4205
Marks, C., Hummer, A. M., Chin, M., & Deane, C. M. (2021). Humanization of antibodies using a machine learning approach on large-scale repertoire data. Bioinformatics, 37(22), 4041-4047. https://doi.org/10.1093/bioinformatics/btab434
Norman, R. A., Ambrosetti, F., Bonvin, A. M., Colwell, L. J., Kelm, S., Kumar, S., & Krawczyk, K. (2020). Computational approaches to therapeutic antibody design: Established methods and emerging trends. Briefings in Bioinformatics, 21(5), 1549-1567. https://doi.org/10.1093/bib/bbz095
IMGT®, the international ImMunoGeneTics information system®. (2023). IMGT. https://www.imgt.org/
RCSB PDB: Homepage. (2023). RCSB. https://www.rcsb.org/
TABS Therapeutic Antibody Database. (2023). Tabs. https://tabs.craic.com/users/sign_in
SAbDab: The Structural Antibody Database. (2023). Oxford Protein Informatics Group. https://opig.stats.ox.ac.uk/webapps/sabdab-sabpred/sabdab
IEDB.org: Free epitope database and prediction resource. (2023). IEDB. https://iedb.org/
Welcome to PDBbind-CN database. (2020). PDBbind. http://www.pdbbind.org.cn/
The therapeutic efficacy of antibodies is closely related to their ability to recognize and bind specific epitopes on target antigens. Epitopes, or antigenic determinants, are a group of amino acids or other chemical groups that are part of a molecule to which an antibody attaches itself. Epitope characterization can help reveal the mechanism of antibody binding and apply intellectual property (patent) protection for novel antibodies, in addition to designing antibodies with high specificity and minimal cross-reactivity.
Understanding the differences between antibody specificity and selectivity is essential for designing and interpreting antibody-based assays in research for experimental accuracy and data interpretation. Antibody specificity refers to an antibody's ability to recognize and bind to a particular epitope—a unique part of an antigen that elicits an immune response.
Antibody-based assays are essential tools in biomedical research, providing the means to detect, quantify, and visualize specific proteins or antigens within complex biological samples. These assays' efficacy hinges on the antibodies' precise properties. While affinity, avidity, specificity, and selectivity are fundamental to antibody performance, the ultimate impact of these properties is heavily influenced by the experimental context in which the antibody is employed.
Biologics, particularly antibodies, have become indispensable in biomedical research and therapeutic development. Research-use-only (RUO) biologics play a pivotal role in preclinical studies, providing researchers with the necessary tools to explore antibody functions and therapeutic potential in vivo.
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