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Confirmatory Results

Coevolutionary analyses require phylogenetically deep alignments and better null models to accurately detect inter-protein contacts within and between species

Aram Avila-Herrera, Katherine S. Pollard
doi: https://doi.org/10.1101/014902
Aram Avila-Herrera
1Bioinformatics Graduate Program, University of California, San Francisco, CA 94158, US
2Gladstone Institute of Cardiovascular Disease, University of California, San Francisco, CA 94158, US
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Katherine S. Pollard
1Bioinformatics Graduate Program, University of California, San Francisco, CA 94158, US
2Gladstone Institute of Cardiovascular Disease, University of California, San Francisco, CA 94158, US
3Department of Epidemiology and Biostatistics, University of California, San Francisco, CA 94158, US
4Institute for Human Genetics, University of California, San Francisco, CA 94158, US
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Abstract

When biomolecules physically interact, natural selection operates on them jointly. Contacting positions in protein and RNA structures exhibit correlated patterns of sequence evolution due to constraints imposed by the interaction, and molecular arms races can develop between interacting proteins in pathogens and their hosts. To evaluate how well methods developed to detect coevolving residues within proteins can be adapted for cross-species, inter-protein analysis, we used statistical criteria to quantify the performance of these methods in detecting interprotein residues within 8 angstroms of each other in the co-crystal structures of 33 bacterial protein interactions. We also evaluated their performance for detecting known residues at the interface of a host-virus protein complex with a partially solved structure. Our quantitative benchmarking showed that all coevolutionary methods clearly benefit from alignments with many sequences. Methods that aim to detect direct correlations generally outperform other approaches. However, faster mutual information based methods are occasionally competitive in small alignments and with relaxed false positive rates. All commonly used null distributions are anti-conservative and have high false positive rates in some scenarios, although the empirical distribution of scores performs reasonably well with deep alignments. We conclude that coevolutionary analysis of cross-species protein interactions holds great promise but requires sequencing many more species pairs.

Key points

  1. Coevolutionary analyses of cross-species protein-protein interactions is largely hindered by a lack of phylogenetically deep protein alignments for many proteins.

  2. Commonly used null distributions generally fail to control false positives in coevolutionary analyses, though errors are best controlled by the empirical null in large alignments.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted February 06, 2015.
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Coevolutionary analyses require phylogenetically deep alignments and better null models to accurately detect inter-protein contacts within and between species
Aram Avila-Herrera, Katherine S. Pollard
bioRxiv 014902; doi: https://doi.org/10.1101/014902
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Coevolutionary analyses require phylogenetically deep alignments and better null models to accurately detect inter-protein contacts within and between species
Aram Avila-Herrera, Katherine S. Pollard
bioRxiv 014902; doi: https://doi.org/10.1101/014902

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