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A Protocol for Computer-Based Protein Structure and Function Prediction
Published on: November 3, 2011
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The simplicity of protein sequence-function relationships
Yeonwoo Park1,2, Brian P H Metzger3,4, Joseph W Thornton5,6
1Committee on Genetics, Genomics, and Systems Biology, University of Chicago, Chicago, IL, USA.
Nature Communications
|September 11, 2024
Summary
Protein sequence-function relationships are simpler than previously thought. A new reference-free method reveals that basic amino acid effects and pairwise interactions explain most protein function, challenging complex epistasis models.
Area of Science:
- Molecular Biology
- Genetics
- Biophysics
Background:
- High-order epistatic interactions are believed to govern protein sequence-function relationships, implying complexity and unpredictability.
- Previous studies may overestimate epistasis due to reference-dependent analyses and failure to account for global nonlinearities.
Purpose of the Study:
- To develop and validate a reference-free method for inferring protein sequence-function relationships.
- To determine the true extent of epistasis and identify key determinants of protein function.
Main Methods:
- A novel reference-free computational method was developed to jointly infer epistatic interactions and global nonlinearity.
- The method was applied to 20 diverse experimental datasets covering protein sequence-function relationships.
Main Results:
- Amino acid effects and pairwise interactions, with a simple nonlinearity, explain a median of 96% of phenotypic variance across datasets.
- Higher-order epistasis affects only a small fraction of genotypes, and sequence-function relationships are sparse.
- The new method is robust to noise, missing data, and model misspecification.
Conclusions:
- Protein sequence-function causality is largely simple and predictable, dominated by context-independent effects and pairwise interactions.
- This simplification opens avenues for tractable methods to characterize protein genetic architecture.
- The findings challenge the pervasive view of complex, high-order epistasis in protein evolution.
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