Literature DB >> 10752620

Optimal region of average side-chain entropy for fast protein folding.

O V Galzitskaya1, A K Surin, H Nakamura.   

Abstract

Search and study the general principles that govern kinetics and thermodynamics of protein folding generates new insight into the factors that control this process. Here, we demonstrate based on the known experimental data and using theoretical modeling of protein folding that side-chain entropy is one of the general determinants of protein folding. We show for proteins belonging to the same structural family that there exists an optimal relationship between the average side-chain entropy and the average number of contacts per residue for fast folding kinetics. Analysis of side-chain entropy for proteins that fold without additional agents demonstrates that there exists an optimal region of average side-chain entropy for fast folding. Deviation of the average side-chain entropy from the optimal region results in an anomalous protein folding process (prions, alpha-lytic protease, subtilisin, some DNA-binding proteins). Proteins with high or low side-chain entropy would have extended unfolded regions and would require some additional agents for complete folding. Such proteins are common in nature, and their structure properties have biological importance.

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Year:  2000        PMID: 10752620      PMCID: PMC2144575          DOI: 10.1110/ps.9.3.580

Source DB:  PubMed          Journal:  Protein Sci        ISSN: 0961-8368            Impact factor:   6.725


  40 in total

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  3 in total

1.  To be folded or to be unfolded?

Authors:  Sergiy O Garbuzynskiy; Michail Yu Lobanov; Oxana V Galzitskaya
Journal:  Protein Sci       Date:  2004-11       Impact factor: 6.725

2.  Prediction of protein domain boundaries from sequence alone.

Authors:  Oxana V Galzitskaya; Bogdan S Melnik
Journal:  Protein Sci       Date:  2003-04       Impact factor: 6.725

3.  Prediction of amyloidogenic and disordered regions in protein chains.

Authors:  Oxana V Galzitskaya; Sergiy O Garbuzynskiy; Michail Yurievich Lobanov
Journal:  PLoS Comput Biol       Date:  2006-11-06       Impact factor: 4.475

  3 in total

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