RETRACTED: Why proteins evolve at different rates: The functional hypothesis versus the mistranslation‐induced protein misfolding hypothesis

Park, Donghyun; Choi, Sun Shim

doi:10.1016/j.febslet.2009.02.033

Cited by 5 publications

(4 citation statements)

References 52 publications

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“…Unexpectedly for such fast-evolving proteins, amyloids also show higher expression levels compared with the reference proteins (Wilcoxon rank-sum test p-value < 0.05), as well as higher abundance (Wilcoxon rank-sum test p-value < 0.001, see Figure 1). These findings do not agree with the well-established observation that highly expressed proteins evolve slowly (Drummond et al 2005; Drummond et al 2006; Park and Choi 2009; Zhang and Yang 2015). As extracellular location (Feyertag et al 2017) and the presence of disulphide bonds (Feyertag and Alvarez-Ponce 2017) have been found to characterize fast-evolving proteins, we split the dataset according to these variables.…”

Section: Main Manuscriptcontrasting

confidence: 94%

Evolutionary rates in human amyloid proteins reveal their intrinsic metastability

Zea

Donagh

Benítez

et al. 2022

Preprint

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The emerging picture of protein nature reveals its intrinsic metastability. According to this idea, although a protein is kinetically trapped in a local free energy minimum that defines its native state, those kinetic barriers can be overcome by a complex mixture of the protein's intrinsic properties and environmental conditions, promoting access to more stable states such as the amyloid fibril. Proteins that are strongly driven towards aggregation in the form of these fibrils are called amyloidogenic. In this work we study the evolutionary rates of 81 human proteins for which an in vivo amyloid state is supported by experiment-based evidence. We found that these proteins evolve faster when compared with a large dataset of ~16,000 reference proteins from the human proteome. However, their evolutionary rates were indistinguishable from those of secreted proteins that are already known to evolve fast. After analyzing different parameters that correlate with evolutionary rates, we found that the evolutionary rates of amyloidogenic proteins could be modulated by factors associated with metastable transitions such as supersaturation and conformational diversity. Our results showcase the importance of protein metastability in evolutionary studies.

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Section: Main Manuscriptcontrasting

confidence: 94%

Evolutionary rates in human amyloid proteins reveal their intrinsic metastability

Zea

Donagh

Benítez

et al. 2022

Preprint

View full text Add to dashboard Cite

show abstract

“…One of the conditions of submission of a paper for publication is that authors declare explicitly that their work is original and has not been submitted for or appeared in a publication elsewhere [78].…”

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confidence: 99%

Retraction Notices: Who Authored Them?

2018

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Unlike other academic publications whose authorship is eagerly claimed, the provenance of retraction notices (RNs) is often obscured presumably because the retraction of published research is associated with undesirable behavior and consequently carries negative consequences for the individuals involved. The ambiguity of authorship, however, has serious ethical ramifications and creates methodological problems for research on RNs that requires clear authorship attribution. This article reports a study conducted to identify RN textual features that can be used to disambiguate obscured authorship, ascertain the extent of authorship evasion in RNs from two disciplinary clusters, and determine if the disciplines varied in the distributions of different types of RN authorship. Drawing on a corpus of 370 RNs archived in the Web of Science for the hard discipline of Cell Biology and the soft disciplines of Business, Finance, and Management, this study has identified 25 types of textual markers that can be used to disambiguate authorship, and revealed that only 25.68% of the RNs could be unambiguously attributed to authors of the retracted articles alone or jointly and that authorship could not be determined for 28.92% of the RNs. Furthermore, the study has found marked disciplinary differences in the different categories of RN authorship. These results point to the need for more explicit editorial requirements about RN authorship and their strict enforcement.

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“…This is important because an incorrect understanding of protein age can lead to premature conclusions on network evolution. For example, the observation that old proteins tend to have more interactions has been proposed as evidence supporting the Preferential Attachment model of network evolution [49,51], but a slow rate of sequence evolution as well as a low propensity for gene loss have been associated with increased connectivity [27,52-54], which would be an alternative explanation.…”

Section: Resultsmentioning

confidence: 99%

Gene duplications contribute to the overrepresentation of interactions between proteins of a similar age

2012

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BackgroundThe study of biological networks and how they have evolved is fundamental to our understanding of the cell. By investigating how proteins of different ages are connected in the protein interaction network, one can infer how that network has expanded in evolution, without the need for explicit reconstruction of ancestral networks. Studies that implement this approach show that proteins are often connected to proteins of a similar age, suggesting a simultaneous emergence of interacting proteins. There are several theories explaining this phenomenon, but despite the importance of gene duplication in genome evolution, none consider protein family dynamics as a contributing factor.ResultsIn an S. cerevisiae protein interaction network we investigate to what extent edges that arise from duplication events contribute to the observed tendency to interact with proteins of a similar age. We find that part of this tendency is explained by interactions between paralogs. Age is usually defined on the level of protein families, rather than individual proteins, hence paralogs have the same age. The major contribution however, is from interaction partners that are shared between paralogs. These interactions have most likely been conserved after a duplication event. To investigate to what extent a nearly neutral process of network growth can explain these results, we adjust a well-studied network growth model to incorporate protein families. Our model shows that the number of edges between paralogs can be amplified by subsequent duplication events, thus explaining the overrepresentation of interparalog edges in the data. The fact that interaction partners shared by paralogs are often of the same age as the paralogs does not arise naturally from our model and needs further investigation.ConclusionWe amend previous theories that explain why proteins of a similar age prefer to interact by demonstrating that this observation can be partially explained by gene duplication events. There is an ongoing debate on whether the protein interaction network is predominantly shaped by duplication and subfunctionalization or whether network rewiring is most important. Our analyses of S. cerevisiae protein interaction networks demonstrate that duplications have influenced at least one property of the protein interaction network: how proteins of different ages are connected.

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RETRACTED: Why proteins evolve at different rates: The functional hypothesis versus the mistranslation‐induced protein misfolding hypothesis

Cited by 5 publications

References 52 publications

Evolutionary rates in human amyloid proteins reveal their intrinsic metastability

Evolutionary rates in human amyloid proteins reveal their intrinsic metastability

Retraction Notices: Who Authored Them?

Gene duplications contribute to the overrepresentation of interactions between proteins of a similar age

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