期刊
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
卷 109, 期 39, 页码 15763-15768出版社
NATL ACAD SCIENCES
DOI: 10.1073/pnas.1212842109
关键词
energy landscape theory; biomolecular dynamics
资金
- National Natural Science Foundation (NSF) of China [21190040, 11174105]
- 973 project [2009CB930100, 2010CB933600]
- National Science Foundation [PHY-0822283]
- Brazilian Agency Fundacao de Amparo a Pesquisa do Estado de Sao Paulo
- Brazilian Agency Coordenacao de Aperfeicoamento de Pessoal de Nivel Superior
- Brazilian Agency Conselho Nacional de Desenvolvimento Cientifico e Tecnologico
- Center for Theoretical Biological Physics
- NSF-MCB-1214457
- Cancer Prevention and Research Institute of Texas
- Direct For Biological Sciences
- Div Of Molecular and Cellular Bioscience [1214457] Funding Source: National Science Foundation
- Division Of Physics
- Direct For Mathematical & Physical Scien [1308264] Funding Source: National Science Foundation
The energy landscape approach has played a fundamental role in advancing our understanding of protein folding. Here, we quantify protein folding energy landscapes by exploring the underlying density of states. We identify three quantities essential for characterizing landscape topography: the stabilizing energy gap between the native and nonnative ensembles delta E, the energetic roughness Delta E, and the scale of landscape measured by the entropy S. We show that the dimensionless ratio between the gap, roughness, and entropy of the system Lambda = delta E/(Delta E root 2S) accurately predicts the thermodynamics, as well as the kinetics of folding. Large Lambda implies that the energy gap (or landscape slope towards the native state) is dominant, leading to more funneled landscapes. We investigate the role of topological and energetic roughness for proteins of different sizes and for proteins of the same size, but with different structural topologies. The landscape topography ratio Lambda is shown to be monotonically correlated with the thermodynamic stability against trapping, as characterized by the ratio of folding temperature versus trapping temperature. Furthermore, Lambda also monotonically correlates with the folding kinetic rates. These results provide the quantitative bridge between the landscape topography and experimental folding measurements.
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