ArticlePLoS computational biology2011
Predictability of evolutionary trajectories in fitness landscapes.
Article in PLoS computational biology, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers, 1 of them a synthesis that pooled it.
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Who cites it
37 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Phenotypic landscape inference reveals multiple evolutionary paths to C4 photosynthesis.eLife · 2013Pooled it
- Phase diagrams for biophysical fitness landscape design.bioRxiv : the preprint server for biology · 2026Article
- Evolutionary repeatability of emergent properties of ecological communities.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2023Review
- Novelty Search Promotes Antigenic Diversity in Microbial Pathogens.Pathogens (Basel, Switzerland) · 2023Article
- Getting higher on rugged landscapes: Inversion mutations open access to fitter adaptive peaks in NK fitness landscapes.PLoS computational biology · 2022Article
- A Family of Fitness Landscapes Modeled through Gene Regulatory Networks.Entropy (Basel, Switzerland) · 2022Article
- Evolutionary Pathways and Trajectories in Antibiotic Resistance.Clinical microbiology reviews · 2021Article
- Both Binding Strength and Evolutionary Accessibility Affect the Population Frequency of Transcription Factor Binding Sequences in Arabidopsis thaliana.Genome biology and evolution · 2021Article
- Unbiased inference of the fitness landscape ruggedness from imprecise fitness estimates.Evolution; international journal of organic evolution · 2021Article
- Experimental Resurrection of Ancestral Mammalian CPEB3 Ribozymes Reveals Deep Functional Conservation.Molecular biology and evolution · 2021Article
- Potential for Applying Continuous Directed Evolution to Plant Enzymes: An Exploratory Study.Life (Basel, Switzerland) · 2020Article
- Analysis of statistical correlations between properties of adaptive walks in fitness landscapes.Royal Society open science · 2020Article
- Phenotypic determinism and contingency in the evolution of hypothetical tree-like organisms.PloS one · 2019Article
- Modeling genome-wide enzyme evolution predicts strong epistasis underlying catalytic turnover rates.Nature communications · 2018Article
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- Evolutionary constraints in fitness landscapes.Heredity · 2018Article
- Selecting among three basic fitness landscape models: Additive, multiplicative and stickbreaking.Theoretical population biology · 2018Article
- Predicting metabolic adaptation from networks of mutational paths.Nature communications · 2017Article
- Adaptive multiscapes: an up-to-date metaphor to visualize molecular adaptation.Biology direct · 2017Article
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3 authors.
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Abstract
Experimental studies on enzyme evolution show that only a small fraction of all possible mutation trajectories are accessible to evolution. However, these experiments deal with individual enzymes and explore a tiny part of the fitness landscape. We report an exhaustive analysis of fitness landscapes constructed with an off-lattice model of protein folding where fitness is equated with robustness to misfolding. This model mimics the essential features of the interactions between amino acids, is consistent with the key paradigms of protein folding and reproduces the universal distribution of evolutionary rates among orthologous proteins. We introduce mean path divergence as a quantitative measure of the degree to which the starting and ending points determine the path of evolution in fitness landscapes. Global measures of landscape roughness are good predictors of path divergence in all studied landscapes: the mean path divergence is greater in smooth landscapes than in rough ones. The model-derived and experimental landscapes are significantly smoother than random landscapes and resemble additive landscapes perturbed with moderate amounts of noise; thus, these landscapes are substantially robust to mutation. The model landscapes show a deficit of suboptimal peaks even compared with noisy additive landscapes with similar overall roughness. We suggest that smoothness and the substantial deficit of peaks in the fitness landscapes of protein evolution are fundamental consequences of the physics of protein folding.
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