Abstract

The proposed work develops further the statistical energy landscape approach to protein folding dynamics and structural prediction.
The specific aims are: 1) To elucidate the mechanism of in vitro and in vivo folding of membrane proteins and to improve our ability to predict their structure 2) To quantify the role of folding in the evolution by comparing the physical energy landscape to co-evolutionary sequence analysis in folding and to use this knowledge to develop algorithms to predict the location of binding sites and allosteric initiation regions in proteins. 3) To understand the role of frustration and self-recognition in the initiation of protein aggregation. To use the tools of energy landscape analysis to predict and classify the structures of oligomers of A peptide and study their binding to ApoE, a genetic marker for Alzheimer's disease.

Public Health Relevance

Folding is a key part of translating genomic data into function. Our work using the energy landscape theory of membrane protein folding will help predict protein structures for drug targets. We will also elucidate the misfolding events important for diseases such as Alzheimer's.

  Funding Agency

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
5R01GM044557-27
Application #
9455687
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Wehrle, Janna P
Project Start
1990-07-01
Project End
2019-03-31
Budget Start
2018-04-01
Budget End
2019-03-31
Support Year
27
Fiscal Year
2018
Total Cost
Indirect Cost

  Institution

Name
Rice University
Department
Chemistry
Type
Schools of Arts and Sciences
DUNS #
050299031
City
Houston
State
TX
Country
United States
Zip Code
77005

  Publications

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; Lin, Xingcheng; Zheng, Weihua et al. (2016) Protein Folding and Structure Prediction from the Ground Up: The Atomistic Associative Memory, Water Mediated, Structure and Energy Model. J Phys Chem B 120:8557-65
Tsai, Min-Yeh; Zheng, Weihua; Balamurugan, D et al. (2016) Electrostatics, structure prediction, and the energy landscapes for protein folding and binding. Protein Sci 25:255-69
Tsai, Min-Yeh; Zhang, Bin; Zheng, Weihua et al. (2016) Molecular Mechanism of Facilitated Dissociation of Fis Protein from DNA. J Am Chem Soc :

Showing the most recent 10 out of 88 publications