The proposed work develops further the statistical energy landscape approach to protein folding dynamics and structural prediction.
The specific aims are: 1) to elucidate coupling of the folding and functional energy landscapes of allosteric proteins, concentrating on the role of local frustration 2) to elucidate the mechanism of in vitro and in vivo folding of membrane proteins and to improve our ability to predict their structure. Energy landscape theory provides mathematical techniques for characterizing in probabilistic terms the energies of the ensembles of partially folded protein configurations and the dynamics of interconverting between them. We will use analytical and computer simulation approaches that will provide quantitative estimates for the role of minimally frustrated networks of interactions in guiding the protein to its native state and the role that frustration has in impeding that flow. Allosteric proteins are predicted to positively use frustration to sculpt the functional landscape. Mutation in allosteric proteins such as kinases can cause a protein to be oncogenic. Errors in the folding of membrane proteins can lead specifically to diseases such as cystic fibrosis. Advances in understanding the landscape of membrane protein can help predict their structure an important step in designing drugs. PHS 398/2590 (Rev. 11/07) Page Continuation Format Page

Public Health Relevance

Folding is a key step in translating genomic data into function. Our work on the energy landscape theory of folding helps predict protein structures of drug targets. The elucidation of folding mechanism is also important for understanding diseases caused by errors in folding, such as cystic fibrosis and Type II diabetes. PHS 398/2590 (Rev. 11/07) Page Continuation Format Page

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
5R01GM044557-20
Application #
8075017
Study Section
Macromolecular Structure and Function D Study Section (MSFD)
Program Officer
Wehrle, Janna P
Project Start
1990-07-01
Project End
2011-08-31
Budget Start
2011-06-01
Budget End
2011-08-31
Support Year
20
Fiscal Year
2011
Total Cost
$1,145
Indirect Cost
Name
University of California San Diego
Department
Chemistry
Type
Schools of Arts and Sciences
DUNS #
804355790
City
La Jolla
State
CA
Country
United States
Zip Code
92093
Ferreiro, Diego U; Komives, Elizabeth A; Wolynes, Peter G (2018) Frustration, function and folding. Curr Opin Struct Biol 48:68-73
Chen, Mingchen; Schafer, Nicholas P; Zheng, Weihua et al. (2018) The Associative Memory, Water Mediated, Structure and Energy Model (AWSEM)-Amylometer: Predicting Amyloid Propensity and Fibril Topology Using an Optimized Folding Landscape Model. ACS Chem Neurosci 9:1027-1039
Lu, Wei; Schafer, Nicholas P; Wolynes, Peter G (2018) Energy landscape underlying spontaneous insertion and folding of an alpha-helical transmembrane protein into a bilayer. Nat Commun 9:4949
Chen, Mingchen; Lin, Xingcheng; Lu, Wei et al. (2017) Protein Folding and Structure Prediction from the Ground Up II: AAWSEM for ?/? Proteins. J Phys Chem B 121:3473-3482
Zheng, Weihua; Tsai, Min-Yeh; Wolynes, Peter G (2017) Comparing the Aggregation Free Energy Landscapes of Amyloid Beta(1-42) and Amyloid Beta(1-40). J Am Chem Soc 139:16666-16676
Sirovetz, Brian J; Schafer, Nicholas P; Wolynes, Peter G (2017) Protein structure prediction: making AWSEM AWSEM-ER by adding evolutionary restraints. Proteins 85:2127-2142
Chen, Mingchen; Wolynes, Peter G (2017) Aggregation landscapes of Huntingtin exon 1 protein fragments and the critical repeat length for the onset of Huntington's disease. Proc Natl Acad Sci U S A 114:4406-4411
Chen, Mingchen; Tsai, MinYeh; Zheng, Weihua et al. (2016) The Aggregation Free Energy Landscapes of Polyglutamine Repeats. J Am Chem Soc 138:15197-15203
Zheng, Weihua; Tsai, Min-Yeh; Chen, Mingchen et al. (2016) Exploring the aggregation free energy landscape of the amyloid-? protein (1-40). Proc Natl Acad Sci U S A 113:11835-11840
Schafer, Nicholas P; Truong, Ha H; Otzen, Daniel E et al. (2016) Topological constraints and modular structure in the folding and functional motions of GlpG, an intramembrane protease. Proc Natl Acad Sci U S A 113:2098-103

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