Artificial intelligence (AI) and computational methods are a powerful tool for antibody discovery and engineering. Despite historical prevalence in small molecule-related applications, AI is progressively being utilized in the discovery and advancement of therapeutic antibodies, backed by the surge in computational power and innovative algorithms, with an increasing amount of data obtained through next-generation sequencing and related drug modalities such as VHH antibodies.1
The main uses of these approaches in antibody research involve2:
Building antibody databases
Target discovery and validation
Structural and functional modeling
Development assessment and activity improvements
De novo antibody design
In combination with other tools (e.g. bioinformatics and X-ray crystallography protein structure analysis)
These computational methods can provide much more cost-efficient and rapid turnaround time compared to the laborious experimental methods that are common in antibody discovery. Escalating costs are often a significant impediment to the advancement of drug discovery.
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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
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
Antibody specificity refers to an antibody's ability to selectively bind to a unique epitope on a target antigen while avoiding interactions with unrelated antigens. This property arises from the highly specialized antigen-binding site located in the variable region of the antibody, which determines its unique binding characteristics.
Antibody affinity refers to the strength of the binding interaction between a single antigen epitope and the paratope (binding site) of an antibody. This interaction is a fundamental measure of how well an antibody recognizes its specific antigen target.
Recombinant antibodies are produced using genetic engineering techniques, unlike traditional antibody production, where the immune system generates antibodies without direct control over their sequence. By introducing genes encoding antibody fragments into host cells, such as bacteria or mammalian cells, recombinant antibodies can be expressed, purified, and deployed for applications including research, diagnostics, and therapeutics.
Recombinant antibody expression is a biotechnological process that involves engineering and producing antibodies outside their natural context using recombinant DNA technology.
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