Optimality theory in evolutionary biology

Parker, G. A.; Smith, John Maynard

doi:10.1038/348027a0

Cited by 829 publications

(637 citation statements)

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“…1)? Using thermodynamic and kinetic constraints, we address the question of whether evolution tends to arrive at optimal molecular processes (31), building on established concepts of optimality-derived evolutionary convergence (32,33). Presumably, performance advantages in the central task of ATP synthesis would be under significant evolutionary pressure.…”

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confidence: 99%

Biophysical comparison of ATP synthesis mechanisms shows a kinetic advantage for the rotary process

Anandakrishnan

Zhang

Donovan-Maiye

et al. 2016

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

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The ATP synthase (F-ATPase) is a highly complex rotary machine that synthesizes ATP, powered by a proton electrochemical gradient. Why did evolution select such an elaborate mechanism over arguably simpler alternating-access processes that can be reversed to perform ATP synthesis? We studied a systematic enumeration of alternative mechanisms, using numerical and theoretical means. When the alternative models are optimized subject to fundamental thermodynamic constraints, they fail to match the kinetic ability of the rotary mechanism over a wide range of conditions, particularly under low-energy conditions. We used a physically interpretable, closed-form solution for the steady-state rate for an arbitrary chemical cycle, which clarifies kinetic effects of complex free-energy landscapes. Our analysis also yields insights into the debated "kinetic equivalence" of ATP synthesis driven by transmembrane pH and potential difference. Overall, our study suggests that the complexity of the F-ATPase may have resulted from positive selection for its kinetic advantage.ATP synthase | kinetic mechanism | free-energy landscape | nonequilibrium steady state | evolution T he F-ATPase performs molecular-level free-energy (FE) transduction to phosphorylate ADP and yield ATP, the primary energy carrier that drives a vast range of cellular processes. It spurred Mitchell's chemiosmotic hypothesis (1) and Boyer's now-validated proposal for the binding-change mechanism (2) in which a proton electrochemical gradient is transduced to rotationbased mechanical energy and then back to chemical FE as ADP is phosphorylated. The F-ATPase's two-domain uniaxial rotary structure is conserved across all three domains of life (3-6), and details of its function have been the subject of a multitude of studies (e.g., refs. 7-30).Here, we address a relatively narrow question with potentially significant evolutionary implications: Why is ATP synthesized by a rotary mechanism instead of a potentially much simpler alternating-access mechanism (Fig. 1)? Using thermodynamic and kinetic constraints, we address the question of whether evolution tends to arrive at optimal molecular processes (31), building on established concepts of optimality-derived evolutionary convergence (32, 33). Presumably, performance advantages in the central task of ATP synthesis would be under significant evolutionary pressure. Previous modeling studies of the F-ATPase have addressed structural and mechanistic questions about the rotary mechanism (e.g., refs. 11-20), but not the metaissue of the mechanism itself compared with alternatives.To assess whether the rotary mechanism possesses any intrinsic performance advantage, we constructed a series of kinetic models abstracted from known mechanisms (Fig. 1). Beyond the rotarybased model, we considered a series of alternating-access analogs (Fig. 2), building on the demonstrated capacity for ATP-hydrolyzing transporters to be driven in reverse to synthesize ATP (34, 35). The discrete-state models do not include structural details, bu...

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confidence: 99%

Biophysical comparison of ATP synthesis mechanisms shows a kinetic advantage for the rotary process

Anandakrishnan

Zhang

Donovan-Maiye

et al. 2016

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

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“…Optimization theory has played an important role in evolutionary biology over the past three decades (see, for example, Maynard Smith & Price 1973;Alexander 1982;Maynard Smith 1982;Parker & Maynard Smith 1990). The aim of optimization theory has been to calculate physically, physiologically or behaviourally optimal solutions to adaptive problems that may serve as a benchmark in evaluating actual biological adaptations.…”

Section: Discussionmentioning

confidence: 99%

Bayesian natural selection and the evolution of perceptual systems

Geisler

Diehl

2002

Phil. Trans. R. Soc. Lond. B

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In recent years, there has been much interest in characterizing statistical properties of natural stimuli in order to better understand the design of perceptual systems. A fruitful approach has been to compare the processing of natural stimuli in real perceptual systems with that of ideal observers derived within the framework of Bayesian statistical decision theory. While this form of optimization theory has provided a deeper understanding of the information contained in natural stimuli as well as of the computational principles employed in perceptual systems, it does not directly consider the process of natural selection, which is ultimately responsible for design. Here we propose a formal framework for analysing how the statistics of natural stimuli and the process of natural selection interact to determine the design of perceptual systems. The framework consists of two complementary components. The rst is a maximum tness ideal observer, a standard Bayesian ideal observer with a utility function appropriate for natural selection. The second component is a formal version of natural selection based upon Bayesian statistical decision theory. Maximum tness ideal observers and Bayesian natural selection are demonstrated in several examples. We suggest that the Bayesian approach is appropriate not only for the study of perceptual systems but also for the study of many other systems in biology. BACKGROUNDThe evolution of a species occurs as the result of interactions between its environment and its genome. Thus, achieving a rigorous account of evolution depends as much on understanding the properties of environments as it does on understanding the properties of nucleic acid and protein chemistry. Although many laws of nature are usefully described in deterministic terms, the complexity of evolution often requires a description of both environments and genetics in statistical/probabilistic terms. Research in the areas of population genetics and theoretical ecology has emphasized genetics and its relationship to natural selection. However, recent advances in measuring the statistical regularities of natural environments, especially in the area of perceptual systems, raise the possibility of developing more complete theories of evolution by combining precise statistical descriptions of the environment with precise statistical descriptions of genetics.Here we show that a constrained form of Bayesian statistical decision theory provides an appropriate framework for exploring the formal link between the statistics of the environment and the evolving genome. The framework consists of two components. One is a Bayesian ideal observer with a utility function appropriate for natural selection. The other is a Bayesian formulation of natural selection that neatly divides natural selection into several factors that are measured individually and then combined to characterize the process as a whole. In the Bayesian * Author for correspondence (geisler@psy.utexas.edu). formulation, each allele vector (i.e. each instance of a polymor...

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“…Sometimes a gene-centric perspective is needed, to account for phenomena such as segregation distortion and junk DNA.⁹ There are also many other ways in which evolution routinely falls short of ''optimality'', some of which will be covered in later sections. ⁷ Williams and Nesse 1991;Trevathan, Smith and McKenna 1999. ⁸ Parker and Smith 1990.…”

Section: The Evolution Heuristicmentioning

confidence: 99%

The Wisdom of Nature: An Evolutionary Heuristic for Human Enhancement

Bostrom

Sandberg

2017

Philosophy and Medicine

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Human beings are a marvel of evolved complexity. Such systems can be difficult to enhance. When we manipulate complex evolved systems, which are poorly understood, our interventions often fail or backfire. It can appear as if there is a ''wisdom of nature'' which we ignore at our peril. Sometimes the belief in nature's wisdom-and corresponding doubts about the prudence of tampering with nature, especially human nature-manifest as diffusely moral objections against enhancement. Such objections may be expressed as intuitions about the superiority of the natural or the troublesomeness of hubris, or as an evaluative bias in favor of the status quo. This chapter explores the extent to which such prudence-derived anti-enhancement sentiments are justified. We develop a heuristic, inspired by the field of evolutionary medicine, for identifying promising human enhancement interventions. The heuristic incorporates the grains of truth contained in ''nature knows best'' attitudes while providing criteria for the special cases where we have reason to believe that it is feasible for us to improve on nature.

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Optimality theory in evolutionary biology

Cited by 829 publications

References 40 publications

Biophysical comparison of ATP synthesis mechanisms shows a kinetic advantage for the rotary process

Biophysical comparison of ATP synthesis mechanisms shows a kinetic advantage for the rotary process

Bayesian natural selection and the evolution of perceptual systems

The Wisdom of Nature: An Evolutionary Heuristic for Human Enhancement

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