The overall aim of this project is to improve our understanding of first principles structure prediction of proteins. Based upon our earlier research work on the Astro-Fold (Klepeis and Floudas, 2003c) (see Figure 1 in section C.2), the proposed research is directed towards the development of an enhanced framework for protein structure prediction. This framework consists of (a) free energy calculations for helical segment prediction, (b) a combinatorial optimization approach for the prediction of beta strands and beta sheet topology, (c) a new proposed approach for predicting inter-helical tertiary contacts, (d) a new proposed approach for general residue-residue contact prediction, (e) the derivation of improved distance restraints from predictions in (a-d), and a new proposed optimization-based iterative approach, (e) the generation of an ensemble of low energy tertiary protein structures via the aBB deterministic global optimization approach and torsional angle dynamics, and (f) a new proposed approach for the selection of the predicted tertiary protein structure, from the ensemble of low energy protein structures, using a distance dependent force field developed based on high and/or medium resolution decoys. We put forward the following four specific aims:
Specific Aim 1 : Investigate and develop a novel approach for the prediction of inter-helical tertiary contacts for a-helical proteins, and a/b proteins.
Specific Aim 2 : Investigate and develop a novel optimization method for the prediction of residue-residue contacts in alpha helical, alpha/beta and beta proteins.
Specific Aim 3 : Investigate a new iterative optimization-based approach for the generation of additional and improved distance restraints for the tertiary structure prediction.
Specific Aim 4 : Study and develop a powerful force field which will be able to discriminate the folded structure among high resolution and/or medium resolution decoys generated from the search of tertiary protein structures. Study a robust optimization approach for the force held development. Investigate, test, and validate the overall proposed enhanced framework for protein structure prediction.

Public Health Relevance

The protein structure prediction using first principles is not only of fundamental importance to computational biology and chemistry, but also of major importance for advancing the understanding of protein-protein and protein-peptide interactions which have a direct impact on drug discovery. Improvements of predictive methods for the elucidation of protein structures for globular and membrane proteins will lead into development of novel drugs which will benefit the public health.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
5R01GM052032-10
Application #
7683007
Study Section
Macromolecular Structure and Function D Study Section (MSFD)
Program Officer
Wehrle, Janna P
Project Start
1996-05-01
Project End
2012-08-31
Budget Start
2009-09-01
Budget End
2010-08-31
Support Year
10
Fiscal Year
2009
Total Cost
$245,449
Indirect Cost
Name
Princeton University
Department
Engineering (All Types)
Type
Schools of Engineering
DUNS #
002484665
City
Princeton
State
NJ
Country
United States
Zip Code
08544
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Tamamis, Phanourios; Floudas, Christodoulos A (2014) Elucidating a key component of cancer metastasis: CXCL12 (SDF-1?) binding to CXCR4. J Chem Inf Model 54:1174-88
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Tamamis, Phanourios; Floudas, Christodoulos A (2014) Elucidating a key anti-HIV-1 and cancer-associated axis: the structure of CCL5 (Rantes) in complex with CCR5. Sci Rep 4:5447

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