Evolution and disorder

Brown, Celeste J.; Johnson, Audra; Dunker, A. Keith; Daughdrill, Gary W.

doi:10.1016/j.sbi.2011.02.005

Cited by 264 publications

(245 citation statements)

References 50 publications

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“…We found that genes with a low GDI had a significantly higher than normal D (i.e., low complexity, biased amino acid composition with respect to the median composition of human proteins; P = 2.80 × 10 −54 ), whereas genes with a high GDI had low D values (i.e., a relatively unbiased amino acid composition; P = 0.04). These results are consistent with previous studies reporting a correlation between positive selection and protein disorder/complexity bias (33,34). As expected, we found that genes with a low GDI had significantly shorter CDS than the median value for all genes (P = 4.19 × 10 −152 ), whereas genes with a high GDI had significantly longer CDS (P = 5.25 × 10 −35 ).…”

Section: Correlation Of Gdi With Protein Complexity and Coding Sequencesupporting

confidence: 92%

The human gene damage index as a gene-level approach to prioritizing exome variants

Itan

Shang

Boisson

et al. 2015

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

224

239

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The protein-coding exome of a patient with a monogenic disease contains about 20,000 variants, only one or two of which are disease causing. We found that 58% of rare variants in the protein-coding exome of the general population are located in only 2% of the genes. Prompted by this observation, we aimed to develop a gene-level approach for predicting whether a given human protein-coding gene is likely to harbor disease-causing mutations. To this end, we derived the gene damage index (GDI): a genome-wide, gene-level metric of the mutational damage that has accumulated in the general population. We found that the GDI was correlated with selective evolutionary pressure, protein complexity, coding sequence length, and the number of paralogs. We compared GDI with the leading gene-level approaches, genic intolerance, and de novo excess, and demonstrated that GDI performed best for the detection of false positives (i.e., removing exome variants in genes irrelevant to disease), whereas genic intolerance and de novo excess performed better for the detection of true positives (i.e., assessing de novo mutations in genes likely to be disease causing). The GDI server, data, and software are freely available to noncommercial users from lab.rockefeller.edu/casanova/GDI.

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Section: Correlation Of Gdi With Protein Complexity and Coding Sequencesupporting

confidence: 92%

The human gene damage index as a gene-level approach to prioritizing exome variants

Itan

Shang

Boisson

et al. 2015

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

224

239

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“…This observation is in line with the finding that whether an IDP is elastomeric or amyloidic depends largely on the relative compositions of proline and glycine [228], and is consistent with the central role of aromatic composition in a set of IDP interactions that are presumably underpinned by cation-p attraction [236]. Relative to the substitution matrices for globular proteins, substitution matrices for IDPs/IDRs entail a generally higher probability of evolutionary changes, but some residues such as tryptophan and tyrosine tend to be highly conserved in IDPs/IDRs, perhaps because of their critical role in protein-protein interfaces [244,246].…”

Section: Biophysical Constraints On Evolution Of Intrinsically Disordmentioning

confidence: 55%

Biophysics of protein evolution and evolutionary protein biophysics

Sikosek

Chan

2014

J. R. Soc. Interface.

224

207

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The study of molecular evolution at the level of protein-coding genes often entails comparing large datasets of sequences to infer their evolutionary relationships. Despite the importance of a protein's structure and conformational dynamics to its function and thus its fitness, common phylogenetic methods embody minimal biophysical knowledge of proteins. To underscore the biophysical constraints on natural selection, we survey effects of protein mutations, highlighting the physical basis for marginal stability of natural globular proteins and how requirement for kinetic stability and avoidance of misfolding and misinteractions might have affected protein evolution. The biophysical underpinnings of these effects have been addressed by models with an explicit coarse-grained spatial representation of the polypeptide chain. Sequence-structure mappings based on such models are powerful conceptual tools that rationalize mutational robustness, evolvability, epistasis, promiscuous function performed by 'hidden' conformational states, resolution of adaptive conflicts and conformational switches in the evolution from one protein fold to another. Recently, protein biophysics has been applied to derive more accurate evolutionary accounts of sequence data. Methods have also been developed to exploit sequence-based evolutionary information to predict biophysical behaviours of proteins. The success of these approaches demonstrates a deep synergy between the fields of protein biophysics and protein evolution.

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“…From an evolutionary perspective, disordered regions have been classified as fast evolving (8), because they show a different pattern of accepted point mutations and present higher rates of insertions and deletions (9,10). However, IDPs will not accept and incorporate any random mutation, and it has been recently shown that long unstructured stretches in proteins are significantly more conserved than their flanking ordered regions or loops in well structured proteins (11,12).…”

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confidence: 99%

The Role of Structural Disorder in the Rewiring of Protein Interactions through Evolution

Mosca

Pache

Aloy

2012

Molecular & Cellular Proteomics

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Structurally disordered regions play a key role in proteinprotein interaction networks and the evolution of highly connected proteins, enabling the molecular mechanisms for multiple binding. However, the role of protein disorder in the evolution of interaction networks has only been investigated through the analysis of individual proteins, making it impossible to distinguish its specific impact in the (re)shaping of their interaction environments. Now, the availability of large interactomes for several model organisms permits exploration of the role of disorder in protein interaction networks not only at the level of the interacting proteins but of the interactions themselves. By comparing the interactomes of human, fly, and yeast, we discovered that, despite being much more abundant, disordered interactions are significantly less conserved than their ordered counterparts. Furthermore, our analyses provide evidence that this happens not only because disordered proteins are less conserved but also because they display a higher capacity to rewire their interaction neighborhood through evolution. Overall, our results support the hypothesis that conservation of disorder gives a clear evolutionary advantage, facilitating the change of interaction partners during evolution. Moreover, this mechanism is not exclusive of a few anecdotal cases but a global feature present in the interactome networks of entire organisms.

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Evolution and disorder

Cited by 264 publications

References 50 publications

The human gene damage index as a gene-level approach to prioritizing exome variants

The human gene damage index as a gene-level approach to prioritizing exome variants

Biophysics of protein evolution and evolutionary protein biophysics

The Role of Structural Disorder in the Rewiring of Protein Interactions through Evolution

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