A description of conformational transitions in molecules is fundamental to science and technology. Knowing the pathways not only provides knowledge of the intermediates but is useful in designing protein ligands for technological or pharmaceutical purposes and in designing molecular machines. This knowledge is also often needed for calculating binding affinities in cases where conformational changes occur. Obtaining this information experimentally is difficult and/or costly, which motivates the wide use of computer simulations. However, the current methods for finding transitional paths or binding free energies for large molecular systems are limited. Promising results for smaller molecules suggest that such methods can be developed, which is the objective of this project. Robust and efficient methods will be constructed for the calculation of transitional paths and their application to biologically interesting systems such as SRC protein tyrosine kinase. Innovative techniques will be developed for obtaining reasonable first approximations and for refining them. These paths will be defined as the minimum of some functional for a well chosen set of reduced variables. In addition, pathways are often needed for the calculation of free energies of binding. The techniques developed here will be combined with a recently published free energy method that uses a restraining potential. By employing advanced sampling methods, the method will be applied to larger systems such as KID:KIX and cMyb:KIX complexes involved in DNA transcription. The methodology will be disseminated through established contacts with software developers as well as new stand-alone software. Understanding the activity of proteins and their interactions with drugs is needed for developing treatments for disease. The increasing power of computers makes it cost effective to do studies on the computer prior to experiments in the laboratory. However, this also requires the availability of sophisticated software employing advanced mathematics, whose development is the aim of this project. ? ? ?

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
5R01GM083605-02
Application #
7477790
Study Section
Special Emphasis Panel (ZGM1-CBCB-5 (BM))
Program Officer
Wehrle, Janna P
Project Start
2007-08-01
Project End
2011-07-31
Budget Start
2008-08-01
Budget End
2009-07-31
Support Year
2
Fiscal Year
2008
Total Cost
$374,138
Indirect Cost
Name
Purdue University
Department
Biostatistics & Other Math Sci
Type
Schools of Arts and Sciences
DUNS #
072051394
City
West Lafayette
State
IN
Country
United States
Zip Code
47907
Skeel, Robert D; Zhao, Ruijun; Post, Carol Beth (2017) A minimization principle for transition paths of maximum flux for collective variables. Theor Chem Acc 136:
Dickson, Bradley M; Huang, He; Post, Carol Beth (2012) Unrestrained computation of free energy along a path. J Phys Chem B 116:11046-55
Huang, He; Zhao, Ruijun; Dickson, Bradley M et al. (2012) *C helix as a switch in the conformational transition of Src/CDK-like kinase domains. J Phys Chem B 116:4465-75
Dickson, Bradley M (2011) Approaching a parameter-free metadynamics. Phys Rev E Stat Nonlin Soft Matter Phys 84:037701
Dadarlat, Voichita M; Skeel, Robert D (2011) Dual role of protein phosphorylation in DNA activator/coactivator binding. Biophys J 100:469-77
Zhao, Ruijun; Shen, Juanfang; Skeel, Robert D (2010) Maximum Flux Transition Paths of Conformational Change. J Chem Theory Comput 6:2411-2423
Skeel, Robert D (2009) WHAT MAKES MOLECULAR DYNAMICS WORK? SIAM J Sci Comput 31:1363-1378
Huang, He; Ozkirimli, Elif; Post, Carol Beth (2009) A Comparison of Three Perturbation Molecular Dynamics Methods for Modeling Conformational Transitions. J Chem Theory Comput 5:1301-1314
Hairer, Ernst; McLachlan, Robert I; Skeel, Robert D (2009) ON ENERGY CONSERVATION OF THE SIMPLIFIED TAKAHASHI-IMADA METHOD. Esaim Math Model Numer Anal 43:631-644
Sweet, Christopher R; Hampton, Scott S; Skeel, Robert D et al. (2009) A separable shadow Hamiltonian hybrid Monte Carlo method. J Chem Phys 131:174106

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