Scaling laws for protein folding

Wenzel, Wolfgang; Hamacher, Kay

doi:10.1007/BFb0105008

Wolfgang Wenzel¹ &
Kay Hamacher¹

Part of the book series: Lecture Notes in Physics ((LNP,volume 527))

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Abstract

We investigated the scaling behaviour of stochastic optimization methods for a simple model potential energy surface (PES) with a perfect funnel structure that reflects key characteristics of the protein interactions. Generalized Monte-Carlo (MCM) and simulated-annealing methods (STUN) avoid an enumerative search of the exponentially complex PES in favor of power-law scaling of the computational effort, thus providing a natural resolution of the Levinthal paradox. We find that the computational effort grows with approximately the eighth power of the system size for MCM and STUN, while a genetic algorithm was found to scale exponentially. The scaling behaviour of a derived lattice model is also rationalized.

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Institut für Physik, Universität Dortmund, D-44221, Dortmund, Germany
Wolfgang Wenzel & Kay Hamacher

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Wolfgang Wenzel
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Kay Hamacher
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D. Reguera J.M.G. Vilar J.M. Rubí

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Wenzel, W., Hamacher, K. (1999). Scaling laws for protein folding. In: Reguera, D., Vilar, J., Rubí, J. (eds) Statistical Mechanics of Biocomplexity. Lecture Notes in Physics, vol 527. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0105008

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DOI: https://doi.org/10.1007/BFb0105008
Published: 29 April 2007
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-66245-7
Online ISBN: 978-3-540-48486-8
eBook Packages: Springer Book Archive

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