Physical foundations of biological complexity

Wolf, Yuri I.; Katsnelson, M. I.; Koonin, Eugene V.

doi:10.1073/pnas.1807890115

Cited by 98 publications

(90 citation statements)

References 151 publications

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“…Competition between affinity and specificity also constrains evolution at the cellular level of protein-protein interaction networks; similar to our findings, evolutionary adaptation can still occur by adjusting the fitness consequences of this inescapable conflict Heo et al (2011). More broadly, frustration effects occur across scales of biological organisation, as evidenced by the ubiquity of tradeoffs (Wolf et al, 2018). The prevalence of constraint-breaking mutations is less apparent, but environmental change, which is also ubiquitous, can act as a transient constraint-breaker (De Vos et al, 2015).…”

Section: Discussionsupporting

confidence: 80%

“…It seems plausible that fitness landscapes with similar “improvable trade-off” properties could occur more widely than the protein folding landscape studied here. The stability-aggregation tradeoff in our model is an example of “frustration” caused by competing interactions (Wolf et al, 2018). Frustration seems to be a universal feature of biological macromolecules (Ferreiro et al, 2014, 2018), where competition occurs between the tendency to engage in beneficial interactions and the tendency to engage in deleterious interactions, i.e.…”

Section: Discussionmentioning

confidence: 99%

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Evolution rapidly optimizes stability and aggregation in lattice proteins despite pervasive landscape valleys and mazes

Bertram

Masel

2019

Preprint

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AbstractFitness landscapes are widely used to visualize the dynamics and long-term outcomes of evolution. The fitness landscapes of genetic sequences are characterized by high dimensionality and “ruggedness” due to sign epistasis. Ascending from low to high fitness on such landscapes can be difficult because adaptive trajectories get stuck at low-fitness local peaks. Compounding matters, recent computational complexity arguments have proposed that extremely long, winding adaptive paths may be required to even reach local peaks, a “maze-like” landscape topography. The extent to which peaks and mazes shape the mode and tempo of evolution is poorly understood due to empirical limitations and the abstractness of many landscape models. We develop a biophysically-grounded computational model of protein evolution based on two novel extensions of the classic hydrophobic-polar lattice model of protein folding. First, rather than just considering fold stability we account for the tradeoff between stability and aggregation propensity. Second, we use a “hydrophobic zipping” algorithm to kinetically generate ensembles of post-translationally folded structures. Our stability-aggregation fitness landscape exhibits extensive sign epistasis and local peaks galore. We confirm the postulated existence of maze-like topography in our biologically-grounded landscape. Although these landscape features frequently obstruct adaptive ascent to high fitness and virtually eliminate reproducibility of evolutionary outcomes, many adaptive paths do successfully complete the long ascent from low to high fitness. This delicate balance of “hard but possible” adaptation could occur more broadly provided that the optimal outcomes possible under a tradeoff are improved by rare constraint-breaking substitutions.

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Section: Discussionsupporting

confidence: 80%

Section: Discussionmentioning

confidence: 99%

Evolution rapidly optimizes stability and aggregation in lattice proteins despite pervasive landscape valleys and mazes

Bertram

Masel

2019

Preprint

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“…In conclusion, we have shown that finite size spin lattices with long-range competing RKKY interactions can serve as a platform to create a rich variety of magnetic regimes, ranging from robust double well potentials, toward glassy landscapes and multi-well landscapes. The necessity of such states are recently discussed in the context of biological complexity [31,32]. In addition to the peculiarity that we see spin glass like behavior in relatively small systems, the multi-well landscapes are at the edge of chaos, between the ferromagnetic DW regime that is too simple and the spin glass regime that is too complex.…”

Section: Resultsmentioning

confidence: 93%

Atom-by-atom construction of attractors in a tunable finite size spin array

et al. 2020

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We demonstrate that a two-dimensional finite and periodic array of Ising spins coupled via RKKY-like exchange can exhibit tunable magnetic states ranging across three distinct magnetic regimes: (1) a conventional ferromagnetic regime, (2) a glass-like regime, and (3) a new multi-well regime. These magnetic regimes can be tuned by one gate-like parameter, namely the ratio between the lattice constant and the oscillating interaction wavelength. We characterize the various magnetic regimes, quantifying the distribution of low energy states, aging relaxation dynamics, and scaling behavior. The glassy and multi-well behavior results from the competing character of the oscillating long-range exchange interactions with respect to the lattice. The multi-well structure features multiple attractors, each with a sizable basin of attraction. This may open the possible application of such atomic arrays as associative memories.

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“…Thus, the individual organism phenotype and the physiological system are likely to be more important in understanding biological complexity of the function. As a result, explanations for biological complexity and diversity include the cell as the primary unit of function and natural selection, the revived interest in organism biology and natural history (organisms interacting with the environment) . The knowledge from natural history studies and the physical collections of a variety of organisms reflecting characteristics of their natural history can provide some ultimate explanations for biological complexity.…”

Section: Analysis Of the Physical Aspects Of Nhc Phenotypic Diversitymentioning

confidence: 99%

Natural History Collections as Inspiration for Technology

et al. 2019

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Living organisms are the ultimate survivalists, having evolved phenotypes with unprecedented adaptability, ingenuity, resourcefulness, and versatility compared to human technology. To harness these properties, functional descriptions and design principles from all sources of biodiversity information must be collated − including the hundreds of thousands of possible survival features manifest in natural history museum collections, which represent 12% of total global biodiversity. This requires a consortium of expert biologists from a range of disciplines to convert the observations, data, and hypotheses into the language of engineering. We hope to unite multidisciplinary biologists and natural history museum scientists to maximize the coverage of observations, descriptions, and hypotheses relating to adaptation and function across biodiversity, to make it technologically useful. This is to be achieved by developments in meta‐ taxonomic classification, phylogenetics, systematics, biological materials research, structure and morphological characterizations, and ecological data gathering from the collections − the aim being to identify and catalogue features essential for good biomimetic design.

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Physical foundations of biological complexity

Cited by 98 publications

References 151 publications

Evolution rapidly optimizes stability and aggregation in lattice proteins despite pervasive landscape valleys and mazes

Evolution rapidly optimizes stability and aggregation in lattice proteins despite pervasive landscape valleys and mazes

Atom-by-atom construction of attractors in a tunable finite size spin array

Natural History Collections as Inspiration for Technology

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