Monte Carlo simulation of a statistical mechanical model of multiple protein sequence alignment
A grand canonical Monte Carlo (MC) algorithm is presented for studying the lattice gas model (LGM) of multiple protein sequence alignment, which coherently combines long-range interactions and variable-length insertions. MC simulations are used for both parameter optimization of the model and produc...
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Veröffentlicht in: | Biophysics and Physicobiology 2017, Vol.14, pp.99-110 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | A grand canonical Monte Carlo (MC) algorithm is presented for studying the lattice gas model (LGM) of multiple protein sequence alignment, which coherently combines long-range interactions and variable-length insertions. MC simulations are used for both parameter optimization of the model and production runs to explore the sequence subspace around a given protein family. In this Note, I describe the details of the MC algorithm as well as some preliminary results of MC simulations with various temperatures and chemical potentials, and compare them with the mean-field approximation. The existence of a two-state transition in the sequence space is suggested for the SH3 domain family, and inappropriateness of the mean-field approximation for the LGM is demonstrated. |
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ISSN: | 2189-4779 2189-4779 |
DOI: | 10.2142/biophysico.14.0_99 |