A structural model of latent evolutionary potentials underlying neutral networks in proteins

Wroe, Richard; Chan, Hue Sun; Bornberg‐Bauer, Erich

doi:10.2976/1.2739116

Cited by 31 publications

(44 citation statements)

References 49 publications

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“…conformational diversity) is generally conducive to higher evolution rates that can be beneficial to organisms in rapidly changing environments [261,262] through selection of 'moonlighting' [263] promiscuous functions [264]. We will elaborate below on how the relatively new view of protein dynamics and conformational distribution [202,203,265] has enriched our understanding of evolution.…”

Section: Protein Dynamics and Phenotypic Plasticity: What Is A Molecumentioning

confidence: 99%

“…Opportunistic binding of excited-state conformations can also facilitate evolution of new functions that are not necessarily allosteric [122,202,203]. During such an evolutionary process, a sequence with a multi-basin energy landscape can serve as an evolutionary bridge.…”

Section: Conformational Diversity Is Often Needed For Functionmentioning

confidence: 99%

“…Figure 8. Mutational paths can be guided by selection for hidden conformational states: a more detailed view of the sequence-space fitness/mortality landscapes (top) of two of the HP model neutral nets in figure 6, with the conformational energy landscapes (bottom) of four adjacent sequences highlighted to illustrate the concept of excited-state selection [178,203,239]. Idealized folding funnels at the bottom provide a schematic depiction of the relative populations of the blue and red structures.…”

Section: Evolvability Hidden States and Promiscuous Functionsmentioning

confidence: 99%

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Biophysics of protein evolution and evolutionary protein biophysics

Sikosek

Chan

2014

J. R. Soc. Interface.

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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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Section: Protein Dynamics and Phenotypic Plasticity: What Is A Molecumentioning

confidence: 99%

Section: Conformational Diversity Is Often Needed For Functionmentioning

confidence: 99%

Section: Evolvability Hidden States and Promiscuous Functionsmentioning

confidence: 99%

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Biophysics of protein evolution and evolutionary protein biophysics

Sikosek

Chan

2014

J. R. Soc. Interface.

Self Cite

224

207

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“…Again, we find that the genotype space is characterized by large areas of neutrality that facilitate evolvability, and again we find that continuous evolution at the genotype level yields occasional discontinuity at the phenotypic one. In particular, Wroe et al (2007) have shown that new protein functions may arise through what they term the 'promiscuity' of existing proteins. This is a phenomenon by which the same protein can perform two functions because of its ability to alternate between different thermodynamically stable forms.…”

Section: G!p Mapping Of Simple Biological Systems: Rna Folding and Prmentioning

confidence: 99%

“…Fontana 2002;Cowperthwaite & Meyers 2007;Fernández & Solé 2007;Sumedha et al 2007;Wroe et al 2007;Stich et al 2008;Takeuchi & Hogeweg 2008). RNA folding is relatively well understood at a chemicalphysical level, with increasingly sophisticated computer models capable of predicting the three-dimensional folding of a linear sequence of nucleotides based on thermodynamic considerations.…”

Section: G!p Mapping Of Simple Biological Systems: Rna Folding and Prmentioning

confidence: 99%

Genotype–phenotype mapping and the end of the ‘genes as blueprint’ metaphor

Pigliucci

2010

Phil. Trans. R. Soc. B

234

150

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In a now classic paper published in 1991, Alberch introduced the concept of genotype -phenotype (G!P) mapping to provide a framework for a more sophisticated discussion of the integration between genetics and developmental biology that was then available. The advent of evo-devo first and of the genomic era later would seem to have superseded talk of transitions in phenotypic space and the like, central to Alberch's approach. On the contrary, this paper shows that recent empirical and theoretical advances have only sharpened the need for a different conceptual treatment of how phenotypes are produced. Old-fashioned metaphors like genetic blueprint and genetic programme are not only woefully inadequate but positively misleading about the nature of G!P, and are being replaced by an algorithmic approach emerging from the study of a variety of actual G!P maps. These include RNA folding, protein function and the study of evolvable software. Some generalities are emerging from these disparate fields of analysis, and I suggest that the concept of 'developmental encoding' (as opposed to the classical one of genetic encoding) provides a promising computational -theoretical underpinning to coherently integrate ideas on evolvability, modularity and robustness and foster a fruitful framing of the G!P mapping problem.

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