Denatured-state energy landscapes of a protein structural database reveal the energetic determinants of a framework model for folding.
Position-specific denatured-state thermodynamics were determined for a database of human proteins by use of an ensemble-based model of protein structure. The results of modeling denatured protein in this manner reveal important sequence-dependent thermodynamic properties in the denatured ensembles as well as fundamental differences between the denatured and native ensembles in overall thermodynamic character. The generality and robustness of these results were validated by performing fold-recognition experiments, whereby sequences were matched with their respective folds based on amino acid propensities for the different energetic environments in the protein, as determined through cluster analysis. Correlation analysis between structure and energetic information revealed that sequence segments destined for beta-sheet in the final native fold are energetically more predisposed to a broader repertoire of states than are sequence segments destined for alpha-helix. These results suggest that within the subensemble of mostly unstructured states, the energy landscapes are dominated by states in which parts of helices adopt structure, whereas structure formation for sequences destined for beta-strand is far less probable. These results support a framework model of folding, which suggests that, in general, the denatured state has evolutionarily evolved to avoid low-energy conformations in sequences that ultimately adopt beta-strand. Instead, the denatured state evolved so that sequence segments that ultimately adopt alpha-helix and coil will have a high intrinsic structure formation capability, thus serving as potential nucleation sites.
Wang
Suwei
S
Department of Biochemistry and Molecular Biology and Sealy Center for Structural Biology and Molecular Biophysics, University of Texas Medical Branch, Galveston, TX 77555, USA.
Gu
Jenny
J
Larson
Scott A
SA
Whitten
Steven T
ST
Hilser
Vincent J
VJ
D000465:Algorithms; D000595:Amino Acid Sequence; D000596:Amino Acids / Q000737:chemistry; D030562:Databases, Protein; D006801:Humans; D008958:Models, Molecular; D008969:Molecular Sequence Data; D011489:Protein Denaturation; D017510:Protein Folding; D017433:Protein Structure, Secondary; D011506:Proteins / Q000737:chemistry* / Q000378:metabolism*; D016415:Sequence Alignment; D013816:Thermodynamics
D000596:Amino Acids; D011506:Proteins