Evolutionary couplings detect side-chain interactions

Patterns of amino acid covariation in large protein sequence alignments can inform the prediction of de novo protein structures, binding interfaces, and mutational effects. While algorithms that detect these so-called evolutionary couplings between residues have proven useful for practical applicati...

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Veröffentlicht in:PeerJ (San Francisco, CA) Jg. 7; S. e7280
Hauptverfasser: Hockenberry, Adam J., Wilke, Claus O.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: United States PeerJ. Ltd 08.07.2019
PeerJ, Inc
PeerJ Inc
Schlagworte:
Accuracy
Algorithms
Amino acid sequence
Amino acids
Bioinformatics
Biology
Biophysics
Computational Biology
Contact prediction
Datasets
Deep learning
Epistasis
Evolution
Evolutionary couplings
Evolutionary Studies
Interfaces
Mutation
Neural networks
Protein binding
Protein evolution
Proteins
Structural constraints
United States > US
Protein evolution
Epistasis
Evolutionary couplings
Structural constraints
Contact prediction
ISSN:2167-8359, 2167-8359
Online-Zugang:Volltext
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Zusammenfassung:Patterns of amino acid covariation in large protein sequence alignments can inform the prediction of de novo protein structures, binding interfaces, and mutational effects. While algorithms that detect these so-called evolutionary couplings between residues have proven useful for practical applications, less is known about how and why these methods perform so well, and what insights into biological processes can be gained from their application. Evolutionary coupling algorithms are commonly benchmarked by comparison to true structural contacts derived from solved protein structures. However, the methods used to determine true structural contacts are not standardized and different definitions of structural contacts may have important consequences for interpreting the results from evolutionary coupling analyses and understanding their overall utility. Here, we show that evolutionary coupling analyses are significantly more likely to identify structural contacts between side-chain atoms than between backbone atoms. We use both simulations and empirical analyses to highlight that purely backbone-based definitions of true residue–residue contacts (i.e., based on the distance between Cα atoms) may underestimate the accuracy of evolutionary coupling algorithms by as much as 40% and that a commonly used reference point (Cβ atoms) underestimates the accuracy by 10–15%. These findings show that co-evolutionary outcomes differ according to which atoms participate in residue–residue interactions and suggest that accounting for different interaction types may lead to further improvements to contact-prediction methods.
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ISSN:2167-8359
2167-8359
DOI:10.7717/peerj.7280