Understanding the complementarity and plasticity of antibody–antigen interfaces

Author:

Myung Yoochan1234,Pires Douglas E V235ORCID,Ascher David B1234ORCID

Affiliation:

1. Structural Biology and Bioinformatics, Department of Biochemistry and Pharmacology, University of Melbourne , Melbourne, VIC 3010, Australia

2. Computational Biology and Clinical Informatics, Baker Heart and Diabetes Institute , Melbourne, VIC 3044, Australia

3. Systems and Computational Biology, Bio21 Institute, University of Melbourne , Melbourne, VIC 3052, Australia

4. School of Chemistry and Molecular Biosciences, University of Queensland , St Lucia, QLD 4072, Australia

5. School of Computing and Information Systems, University of Melbourne , Melbourne, VIC 3010, Australia

Abstract

Abstract Motivation While antibodies have been ground-breaking therapeutic agents, the structural determinants for antibody binding specificity remain to be fully elucidated, which is compounded by the virtually unlimited repertoire of antigens they can recognize. Here, we have explored the structural landscapes of antibody–antigen interfaces to identify the structural determinants driving target recognition by assessing concavity and interatomic interactions. Results We found that complementarity-determining regions utilized deeper concavity with their longer H3 loops, especially H3 loops of nanobody showing the deepest use of concavity. Of all amino acid residues found in complementarity-determining regions, tryptophan used deeper concavity, especially in nanobodies, making it suitable for leveraging concave antigen surfaces. Similarly, antigens utilized arginine to bind to deeper pockets of the antibody surface. Our findings fill a gap in knowledge about the antibody specificity, binding affinity, and the nature of antibody–antigen interface features, which will lead to a better understanding of how antibodies can be more effective to target druggable sites on antigen surfaces. Availability and implementation The data and scripts are available at: https://github.com/YoochanMyung/scripts.

Funder

National Health and Medical Research Council

Publisher

Oxford University Press (OUP)

Subject

Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability

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