The goal of the proposed project is to develop several new coarse-grained computational models to describe protein structures and protein dynamics. These innovations will let us approach much larger structures, as well as to comprehend important functional behaviors more readily. The realization of the proposed project might be extremely important for the development of computational cell biology and for practical applications in drug design. The project focuses on three specific aims:
Specific Aim I : Study protein dynamics using the Gaussian Network Model and Anisotropic Network Model. We will develop a mixed coarse-grained method where the 'interesting' or functional parts of proteins are modeled at a higher resolution than the remainder of the structure. By using this approach, normal mode analysis can be performed to discern the important functional motions with high computational efficiency for large biologically important molecules.
Specific Aim II : Develop an extremely efficient transfer matrix method for attrition-free generation of lattice proteins on the square lattice in 2-dimensions and for the cubic lattice in 3-dimensions. The proposed method is an extension of the transfer matrix method for generating and the enumerating compact self-avoiding walks on lattices previously developed by the project's investigators.
Specific Aim I ll: Conduct an off-lattice study of the dependencies between protein shapes and their conformations. The goal is to generate libraries of possible three-dimensional protein structures using a minimal set of assumptions. We constrict the shape of the protein within a three-dimensional ellipsoid of revolution and generate all possible compact protein conformations within the shape. We will also study in a systematic way the interdependence between the structures and the shapes of the proteins, as well as their dynamics with the Gaussian Network Models developed in the Specific Aim 1. These findings open the way for more abstract and mathematical representations of biological structure that can lead directly to a better and more complete comprehension of structure and function.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
1R01GM072014-01
Application #
6829176
Study Section
Special Emphasis Panel (ZGM1-CMB-0 (MB))
Program Officer
Whitmarsh, John
Project Start
2004-07-01
Project End
2008-06-30
Budget Start
2004-07-01
Budget End
2005-06-30
Support Year
1
Fiscal Year
2004
Total Cost
$263,238
Indirect Cost
Name
Iowa State University
Department
Biochemistry
Type
Schools of Arts and Sciences
DUNS #
005309844
City
Ames
State
IA
Country
United States
Zip Code
50011
Wang, Min; Zhou, Wen; Wu, Zhijun (2018) Equilibrium Distributions of Populations of Biological Species on Networks of Social Sites. J Biol Dyn :1-25
Faraggi, Eshel; Dunker, A Keith; Sussman, Joel L et al. (2018) Comparing NMR and X-ray protein structure: Lindemann-like parameters and NMR disorder. J Biomol Struct Dyn 36:2331-2341
Faraggi, Eshel; Kloczkowski, Andrzej (2017) Accurate Prediction of One-Dimensional Protein Structure Features Using SPINE-X. Methods Mol Biol 1484:45-53
Kouza, M; Banerji, A; Kolinski, A et al. (2017) Oligomerization of FVFLM peptides and their ability to inhibit beta amyloid peptides aggregation: consideration as a possible model. Phys Chem Chem Phys 19:2990-2999
Liu, Jie; Sankar, Kannan; Wang, Yuan et al. (2017) Directional Force Originating from ATP Hydrolysis Drives the GroEL Conformational Change. Biophys J 112:1561-1570
Faraggi, Eshel; Kouza, Maksim; Zhou, Yaoqi et al. (2017) Fast and Accurate Accessible Surface Area Prediction Without a Sequence Profile. Methods Mol Biol 1484:127-136
Sankar, Kannan; Jia, Kejue; Jernigan, Robert L (2017) Knowledge-based entropies improve the identification of native protein structures. Proc Natl Acad Sci U S A 114:2928-2933
Zimmermann, Michael T; Jia, Kejue; Jernigan, Robert L (2016) Ribosome Mechanics Informs about Mechanism. J Mol Biol 428:802-810
Rashin, Alexander A; Jernigan, Robert L (2016) Clusters of Structurally Similar MHC I HLA-A2 Molecules, Found with a New Method, Suggest Mechanisms of T-Cell Receptor Avidity. Biochemistry 55:167-85
Chopra, Nikita; Wales, Thomas E; Joseph, Raji E et al. (2016) Dynamic Allostery Mediated by a Conserved Tryptophan in the Tec Family Kinases. PLoS Comput Biol 12:e1004826

Showing the most recent 10 out of 82 publications