Biased Monte Carlo optimization of protein sequences

Adrian P. Cootes; P. M G Curmi; Andrew E. Torda

doi:10.1063/1.482067

Biased Monte Carlo optimization of protein sequences

Adrian P. Cootes, P. M G Curmi, Andrew E. Torda

Research output: Contribution to journal › Article › peer-review

17 Citations (Scopus)

Abstract

The biased Monte Carlo method is used to optimize the amino acid sequences. The sequences optimized from the approach are then compared with conventional Monte Carlo and a self-consistent mean-field (SCMF) method. For more complex systems, the biased Monte Carlo method is found to be more efficient. However, biased Monte Carlo does not converge as quickly as SCMF, but often found better sequences.

Original language	English
Pages (from-to)	2489-2496
Number of pages	8
Journal	Journal of Chemical Physics
Volume	113
Issue number	6
DOIs	https://doi.org/10.1063/1.482067
Publication status	Published - Aug 2000

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title = "Biased Monte Carlo optimization of protein sequences",

abstract = "The biased Monte Carlo method is used to optimize the amino acid sequences. The sequences optimized from the approach are then compared with conventional Monte Carlo and a self-consistent mean-field (SCMF) method. For more complex systems, the biased Monte Carlo method is found to be more efficient. However, biased Monte Carlo does not converge as quickly as SCMF, but often found better sequences.",

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AB - The biased Monte Carlo method is used to optimize the amino acid sequences. The sequences optimized from the approach are then compared with conventional Monte Carlo and a self-consistent mean-field (SCMF) method. For more complex systems, the biased Monte Carlo method is found to be more efficient. However, biased Monte Carlo does not converge as quickly as SCMF, but often found better sequences.

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Biased Monte Carlo optimization of protein sequences

Abstract

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