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Modeling Proteins at the Interface of Structure, Evolution, and Population Genetics

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Computational Modeling of Biological Systems

Part of the book series: Biological and Medical Physics, Biomedical Engineering ((BIOMEDICAL))

Abstract

Biological systems span multiple layers of organization and modeling across layers of organization enables inference that is not possible by analyzing just one layer. An example of this is seen in an organism’s fitness, which can be directly impacted by selection for output from a metabolic or signal transduction pathway. Even this complex process is already several layers removed from the environment and ecosystem. Within the pathway are individual enzymatic reactions and protein–protein, protein–small molecule, and protein–DNA interactions. Enzymatic and physical constants characterize these reactions and interactions, where selection dictates ranges and thresholds of values that are dependent upon values for other links in the pathway. The physical constants (for protein–protein binding, for example) are dictated by the amino acid sequences at the interface. These constants are also constrained by the amino acid sequences that are necessary to maintain a properly folded structure as a scaffold to maintain the interaction interface. As sequences evolve, population genetic and molecular evolutionary models describe the availability of combinations of amino acid changes for selection, depending in turn on parameters like the mutation rate and effective population size. As the systems biology level of constraints has not been thoroughly characterized, it is this multiscale modeling problem that describes the interplay between protein biophysical chemistry and population genetics/molecular evolution that we will describe.

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Acknowledgements

D.A.L. is funded by NSF DBI-0743374 and NIH-INBRE award P20 RR016474. A.I.T. is supported by the aforementioned NSF award, while J.A.G. is supported by the aforementioned NIH-INBRE award.

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Authors and Affiliations

  1. Department of Molecular Biology, University of Wyoming, Laramie, WY, 82071, USA

    Ashley I. Teufel, Johan A. Grahnen & David A. Liberles

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  1. Ashley I. Teufel
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  2. Johan A. Grahnen
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  3. David A. Liberles
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Correspondence to David A. Liberles .

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  1. , Biochemistry and Biophysics, University of North Carolina at Chapel H, Mason Farm Rd 120, Chapel Hill, 27599-7260, North Carolina, USA

    Nikolay V Dokholyan

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Teufel, A.I., Grahnen, J.A., Liberles, D.A. (2012). Modeling Proteins at the Interface of Structure, Evolution, and Population Genetics. In: Dokholyan, N. (eds) Computational Modeling of Biological Systems. Biological and Medical Physics, Biomedical Engineering. Springer, Boston, MA. https://doi.org/10.1007/978-1-4614-2146-7_15

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  • DOI: https://doi.org/10.1007/978-1-4614-2146-7_15

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