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arxiv: cond-mat/0305288 · v1 · submitted 2003-05-13 · ❄️ cond-mat.soft · cond-mat.stat-mech· q-bio.BM

Mean Field Approach for a Statistical Mechanical Model of Proteins

classification ❄️ cond-mat.soft cond-mat.stat-mechq-bio.BM
keywords modelmean-fieldresultsapproachesdatadescriptionexperimentalfolding
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We study the thermodynamical properties of a topology-based model proposed by Galzitskaya and Finkelstein for the description of protein folding. We devise and test three different mean-field approaches for the model, that simplify the treatment without spoiling the description. The validity of the model and its mean-field approximations is checked by applying them to the $\beta$-hairpin fragment of the immunoglobulin-binding protein (GB1) and making a comparison with available experimental data and simulation results. Our results indicate that this model is a rather simple and reasonably good tool for interpreting folding experimental data, provided the parameters of the model are carefully chosen. The mean-field approaches substantially recover all the relevant exact results and represent reliable alternatives to the Monte Carlo simulations.

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