ArticleBiophysics and physicobiology2017
Monte Carlo simulation of a statistical mechanical model of multiple protein sequence alignment.
Article in Biophysics and physicobiology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed.
- Preventing Pathogenic Dimerization in a Misfolded Antibody Light Chain through the Design of an Inhibitory Peptide.The journal of physical chemistry. B · 2026Article
- Biophysical and Mechanistic Models for Disease-Causing Protein Variants.Trends in biochemical sciences · 2019Review
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Abstract
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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