Biophysical inference of epistasis and the effects of mutations on protein stability and function

TL;DR

This paper presents a statistical method to infer the biophysical effects of mutations on protein stability and function from high-throughput binding data, providing detailed energy landscapes and insights into epistasis.

Contribution

The study introduces a thermodynamic modeling approach that accurately infers folding energies and explains epistasis in protein binding, advancing understanding of mutation effects.

Findings

Accurately infers folding energies in physical units.

Explains most observed epistasis through a biophysical model.

Identifies dynamic regions through residual epistasis analysis.

Abstract

Understanding the relationship between protein sequence, function, and stability is a fundamental problem in biology. While high-throughput methods have produced large numbers of sequence-function pairs, functional assays do not distinguish whether mutations directly affect function or are destabilizing the protein. Here, we introduce a statistical method to infer the underlying biophysics from a high-throughput binding assay by combining information from many mutated variants. We fit a thermodynamic model describing the bound, unbound, and unfolded states to high quality data of protein G domain B1 binding to IgG-Fc. We infer an energy landscape with distinct folding and binding energies for each substitution providing a detailed view of how mutations affect binding and stability across the protein. We accurately infer folding energy of each variant in physical units, validated by independent data, whereas previous high-throughput methods could only measure indirect changes in stability. While we assume an additive sequence-energy relationship, the binding fraction is epistatic due its non-linear relation to energy. Despite having no epistasis in energy, our model explains much of the observed epistasis in binding fraction, with the remaining epistasis identifying conformationally dynamic regions.