Unknown

Dataset Information

0

Quantitative theory of hydrophobic effect as a driving force of protein structure.


ABSTRACT: Various studies suggest that the hydrophobic effect plays a major role in driving the folding of proteins. In the past, however, it has been challenging to translate this understanding into a predictive, quantitative theory of how the full pattern of sequence hydrophobicity in a protein shapes functionally important features of its tertiary structure. Here, we extend and apply such a phenomenological theory of the sequence-structure relationship in globular protein domains, which had previously been applied to the study of allosteric motion. In an effort to optimize parameters for the model, we first analyze the patterns of backbone burial found in single-domain crystal structures, and discover that classic hydrophobicity scales derived from bulk physicochemical properties of amino acids are already nearly optimal for prediction of burial using the model. Subsequently, we apply the model to studying structural fluctuations in proteins and establish a means of identifying ligand-binding and protein-protein interaction sites using this approach.

SUBMITTER: Perunov N 

PROVIDER: S-EPMC3970890 | biostudies-literature | 2014 Apr

REPOSITORIES: biostudies-literature

altmetric image

Publications

Quantitative theory of hydrophobic effect as a driving force of protein structure.

Perunov Nikolay N   England Jeremy L JL  

Protein science : a publication of the Protein Society 20140219 4


Various studies suggest that the hydrophobic effect plays a major role in driving the folding of proteins. In the past, however, it has been challenging to translate this understanding into a predictive, quantitative theory of how the full pattern of sequence hydrophobicity in a protein shapes functionally important features of its tertiary structure. Here, we extend and apply such a phenomenological theory of the sequence-structure relationship in globular protein domains, which had previously  ...[more]

Similar Datasets

| S-EPMC6480146 | biostudies-literature
| S-EPMC2678466 | biostudies-literature
| S-EPMC5713874 | biostudies-literature
| S-EPMC5300504 | biostudies-literature
| S-EPMC1978086 | biostudies-other
| S-EPMC2927784 | biostudies-literature
2006-03-21 | GSE3810 | GEO
| S-EPMC3241986 | biostudies-literature
| S-EPMC4124868 | biostudies-other
| S-EPMC5662758 | biostudies-literature