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Geometric Potentials for Computational Protein Sequence Design

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Computational Protein Design

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1529))

Abstract

Computational protein sequence design is the rational design based on computer simulation of new protein molecules to fold to target three-dimensional structures, with the ultimate goal of designing novel functions. It requires a good understanding of the thermodynamic equilibrium properties of the protein of interest. Here, we consider the contribution of the solvent to the stability of the protein. We describe implicit solvent models, focusing on approximations of their nonpolar components using geometric potentials. We consider the surface area (SA) model in which the nonpolar solvation free energy is expressed as a sum of the contributions of all atoms, assumed to be proportional to their accessible surface areas (ASAs). We briefly review existing numerical and analytical approaches that compute the ASA. We describe in more detail the alpha shape theory as it provides a unifying mathematical framework that enables the analytical calculations of the surface area of a macromolecule represented as a union of balls.

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Acknowledgment

Patrice Koehl acknowledges support from the Ministry of Education of Singapore through Grant Number: MOE2012-T3-1-008.

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Authors and Affiliations

  1. Computational and Systems Biology Group, Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore, Singapore

    Jie Li

  2. Department of Computer Science and Genome Center, University of California, Davis, CA, 95616, USA

    Patrice Koehl

Authors
  1. Jie Li
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  2. Patrice Koehl
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Corresponding author

Correspondence to Patrice Koehl .

Editor information

Editors and Affiliations

  1. Department of Plants and Environmental Sciences, Weizmann Institute of Science, Rehovot, Israel

    Ilan Samish

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Li, J., Koehl, P. (2017). Geometric Potentials for Computational Protein Sequence Design. In: Samish, I. (eds) Computational Protein Design. Methods in Molecular Biology, vol 1529. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-6637-0_5

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  • DOI: https://doi.org/10.1007/978-1-4939-6637-0_5

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  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-6635-6

  • Online ISBN: 978-1-4939-6637-0

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