Context Dependence and Coevolution Among Amino Acid Residues in Proteins

Wang, Zhengyuan O.; Pollock, David D.

doi:10.1016/s0076-6879(05)95040-4

Cited by 29 publications

(28 citation statements)

References 32 publications

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“…We have shown that compensatory mutations do tend to occur closer to their associated deleterious mutations than is expected by chance. Such clustering of compensatory mutations is expected because of the importance of local interactions affecting the overall shape of the protein (Chikenji et al 2006), and these results reinforce the conclusions of phylogenetic analysis that show frequent coevolution of nearby amino acid residues (Pollock 2002;Wang & Pollock 2005;Castoe et al 2008). We have confirmed this prediction in these data, finding that the nearestneighbour distance between compensatory mutations is approximately 40 per cent lower than would be expected by chance.…”

Section: K6supporting

confidence: 86%

Compensatory mutations are repeatable and clustered within proteins

2009

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Compensatory mutations improve fitness in genotypes that contain deleterious mutations but have no beneficial effects otherwise. As such, compensatory mutations represent a very specific form of epistasis. We show that intragenic compensatory mutations occur non-randomly over gene sequence. Compensatory mutations are more likely to appear at some sites than others. Moreover, the sites of compensatory mutations are more likely than expected by chance to be near the site of the original deleterious mutation. Furthermore, compensatory mutations tend to occur more commonly in certain regions of the protein even when controlling for clustering around the site of the deleterious mutation. These results suggest that compensatory evolution at the protein level is partially predictable and may be convergent.

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Section: K6supporting

confidence: 86%

Compensatory mutations are repeatable and clustered within proteins

2009

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“…The spatially distant coevolving positions may reflect certain structural or functional constraints of the entire proteins/protein complexes (e.g., [8,14,25]). To verify the functional importance of coevolving positions, we examined the coevolving positions from 25 proteins or protein complexes that were derived from the top 100 family pairs and had known structures.…”

Section: Coevolving Positions Are At Functionally Important Sitesmentioning

confidence: 99%

Detecting the Coevolution in and among Protein Domains

Yeang

Haussler

2005

PLoS Comput Biol

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Correlated changes of nucleic or amino acids have provided strong information about the structures and interactions of molecules. Despite the rich literature in coevolutionary sequence analysis, previous methods often have to trade off between generality, simplicity, phylogenetic information, and specific knowledge about interactions. Furthermore, despite the evidence of coevolution in selected protein families, a comprehensive screening of coevolution among all protein domains is still lacking. We propose an augmented continuous-time Markov process model for sequence coevolution. The model can handle different types of interactions, incorporate phylogenetic information and sequence substitution, has only one extra free parameter, and requires no knowledge about interaction rules. We employ this model to large-scale screenings on the entire protein domain database (Pfam). Strikingly, with 0.1 trillion tests executed, the majority of the inferred coevolving protein domains are functionally related, and the coevolving amino acid residues are spatially coupled. Moreover, many of the coevolving positions are located at functionally important sites of proteins/protein complexes, such as the subunit linkers of superoxide dismutase, the tRNA binding sites of ribosomes, the DNA binding region of RNA polymerase, and the active and ligand binding sites of various enzymes. The results suggest sequence coevolution manifests structural and functional constraints of proteins. The intricate relations between sequence coevolution and various selective constraints are worth pursuing at a deeper level.

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“…As different locations undergo substitutions, the context of other sites will change. These changing interactions between locations with substitutions in the protein have motivated work on correlated substitutions or coevolution (3,4,8,10,11), and most such work has found strong evidence that coevolution is extremely common. The model also implies that a nonpreferred amino acid will always be nonpreferred, and therefore, although occasionally observed, it will be unstable over evolutionary time.…”

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confidence: 99%

Amino acid coevolution induces an evolutionary Stokes shift

Pollock

Thiltgen²,

Goldstein³

2012

Proc. Natl. Acad. Sci. U.S.A.

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307

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The process of amino acid replacement in proteins is contextdependent, with substitution rates influenced by local structure, functional role, and amino acids at other locations. Predicting how these differences affect replacement processes is difficult. To make such inference easier, it is often assumed that the acceptabilities of different amino acids at a position are constant. However, evolutionary interactions among residue positions will tend to invalidate this assumption. Here, we use simulations of purple acid phosphatase evolution to show that amino acid propensities at a position undergo predictable change after an amino acid replacement at that position. After a replacement, the new amino acid and similar amino acids tend to become gradually more acceptable over time at that position. In other words, proteins tend to equilibrate to the presence of an amino acid at a position through replacements at other positions. Such a shift is reminiscent of the spectroscopy effect known as the Stokes shift, where molecules receiving a quantum of energy and moving to a higher electronic state will adjust to the new state and emit a smaller quantum of energy whenever they shift back down to the original ground state. Predictions of changes in stability in real proteins show that mutation reversals become less favorable over time, and thus, broadly support our results. The observation of an evolutionary Stokes shift has profound implications for the study of protein evolution and the modeling of evolutionary processes.A major focus of modern evolutionary studies is to understand how structural and functional contexts determine the patterns of evolutionary change at different positions in a biological macromolecule. Such an understanding is important to phylogenetics, partially because the position-specific processes of evolution are known to determine our ability to reconstruct deep nodes in the tree of life (1) but also because features of the evolutionary process such as convergence can deterministically mislead phylogenetic reconstruction (2). Understanding patterns of evolution and how they respond to details of structure and function can also potentially help us to better decode the evolutionary record, allowing us to distinguish between structural and functional constraints and identify the signatures of positive selection. This finding can lead to improved understanding of a biomolecule's structure, dynamics, thermodynamics, functionality, and physiological context. Key questions concern how evolutionary processes vary among sites and over time and particularly, how the evolution at different locations influences each other. For example, coevolution between different locations in a protein can slow the amino acid replacement process, allowing phylogenetic inference at deep nodes that would otherwise have been swamped by recurrent neutral changes. Furthermore, coevolution tends to depend on proximity in the 3D structure of proteins, leading to the hope that, if properly understood, it could improve our ability...

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Context Dependence and Coevolution Among Amino Acid Residues in Proteins

Cited by 29 publications

References 32 publications

Compensatory mutations are repeatable and clustered within proteins

Compensatory mutations are repeatable and clustered within proteins

Detecting the Coevolution in and among Protein Domains

Amino acid coevolution induces an evolutionary Stokes shift

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