Computational Methods in Immunology and Vaccinology: Design and Development of Antibodies and Immunogens

Abstract

The design of new biomolecules able to harness immune mechanisms for the treatment of diseases is a prime challenge for computational and simulative approaches. For instance, in recent years, antibodies have emerged as an important class of therapeutics against a spectrum of pathologies. In cancer, immune-inspired approaches are witnessing a surge thanks to a better understanding of tumor-associated antigens and the mechanisms of their engagement or evasion from the human immune system. Here, we provide a summary of the main state-of-the-art computational approaches that are used to design antibodies and antigens, and in parallel, we review key methodologies for epitope identification for both B- and T-cell mediated responses. A special focus is devoted to the description of structure- and physics-based models, privileged over purely sequence-based approaches. We discuss the implications of novel methods in engineering biomolecules with tailored immunological properties for possible therapeutic uses. Finally, we highlight the extraordinary challenges and opportunities presented by the possible integration of structure- and physics-based methods with emerging Artificial Intelligence technologies for the prediction and design of novel antigens, epitopes, and antibodies.

PAbFold: Linear Antibody Epitope Prediction using AlphaFold2

“…In this work we did not focus on using AlphaFold2 to predict conformational epitopes primarily because of the complex structures that conformational epitopes possess. Literature reports suggest that prediction of the complexes between antibodies and both whole antigens and conformational epitope proteins has proven to be very difficult for AlphaFold2, and indeed the authors themselves make this observation (12, 42, 43). Notably, the structures that proved most difficult to predict for AF2 and other tools in the CASP15-CAPRI154 challenges were antibody-antigen complexes (44).…”

Utilizing Extraepitopic Amino Acid Substitutions to Define Changes in the Accessibility of Conformational Epitopes of the Bacillus cereus HlyII C-Terminal Domain

“…The identification of epitopes is important in the development of highly specific and harmless vaccines, and therapeutic and diagnostic antibodies [17,18], since epitopes, namely, allow the immune system to recognize and respond to specific pathogens [19]. Therefore, it is especially important to determine the epitope of an antibody capable of neutralizing one of the significant pathogenic factors of B. cereus in order to design a mimetic, based on which a protection against the action of HlyII of various B. cereus strains can be created.…”

In Silico Therapeutic Study: The Next Frontier in the Fight against SARS-CoV-2 and Its Variants

“…QSAR models contribute to predicting the biological activities of chemical compounds based on their structural features, enhancing the screening process for potential drug candidates [100]. Computational approaches extend to antibody interactions with the virus at a molecular level, aiding in the design and optimization of antibodies for maximum efficacy in neutralizing the virus [101]. ML has also been in practice for accelerating the drug discovery process by identifying novel compounds with anti-SARS-CoV-2 activity.…”