Epistasis in a Fitness Landscape Defined by Antibody-Antigen Binding Free Energy

Adams, R. M., Kinney, J. B., Walczak, A. M., Mora, T. (December 2018) Epistasis in a Fitness Landscape Defined by Antibody-Antigen Binding Free Energy. Cell Syst, 8 (1). pp. 86-93. ISSN 2405-4712 (Print)2405-4712

URL: https://www.ncbi.nlm.nih.gov/pubmed/30611676
DOI: 10.1016/j.cels.2018.12.004

Abstract

Epistasis is the phenomenon by which the effect of a mutation depends on its genetic background. While it is usually defined in terms of organismal fitness, for single proteins, it must reflect physical interactions among residues. Here, we systematically extract the specific contribution pairwise epistasis makes to the physical affinity of antibody-antigen binding relevant to affinity maturation, a process of accelerated Darwinian evolution. We find that, among competing definitions of affinity, the binding free energy is the most appropriate to describe epistasis. We show that epistasis is pervasive, accounting for 25%-35% of variability, of which a large fraction is beneficial. This work suggests that epistasis both constrains, through negative epistasis, and enlarges, through positive epistasis, the set of possible evolutionary paths that can produce high-affinity sequences during repeated rounds of mutation and selection.

Item Type: Paper
Subjects: bioinformatics
bioinformatics > genomics and proteomics > genetics & nucleic acid processing
bioinformatics > genomics and proteomics
bioinformatics > genomics and proteomics > genetics & nucleic acid processing > protein structure, function, modification
bioinformatics > quantitative biology
bioinformatics > genomics and proteomics > genetics & nucleic acid processing > protein structure, function, modification > protein types > antibodies
evolution
bioinformatics > genomics and proteomics > genetics & nucleic acid processing > protein structure, function, modification > protein types
bioinformatics > quantitative biology > quantitative genetics > quantitative epistasis
bioinformatics > quantitative biology > quantitative genetics
CSHL Authors:
Communities: CSHL labs > Kinney lab
CSHL Cancer Center Program > Gene Regulation and Inheritance Program
Depositing User: Matthew Dunn
Date: 27 December 2018
Date Deposited: 10 Jan 2019 21:43
Last Modified: 06 Feb 2024 20:32
PMCID: PMC6487650
Related URLs:
URI: https://repository.cshl.edu/id/eprint/37661

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