The lack of reliable descriptions of conformational transitions in proteins represents a critical gap in the body of structural biology knowledge. Not only are conformational transitions at the heart of many proteins' functions --- from enzymes to motor proteins --- but structural intermediates also serve as a well-established class of targets for transition-state inhibitor drugs. We therefore propose a novel computational approach to study the dramatic conformational transitions in (a) calmodulin (CAM), which mediates essential processes from gene expression to muscle contraction to mitosis, and (b) myosin, the protein motor that causes muscle contraction. The new protocol will build on extremely promising preliminary results, which demonstrate unprecedented access to physiological timescales. Combining residue-level modeling and fine-grid discretization, the approach has already proven capable of unbiased dynamic simulation of dozens of conformational transitions in each of the two 72-residue domains of calmodulin. In fact, the protocol generates several transition events per day on an inexpensive, single-processor desktop computer. This high efficiency will enable the study of myosin with modest computer resources. A multi-level approach to modeling is central to this proposal. Results generated from initial """"""""coarse grained"""""""" models (e.g., residue-level) will be refined using a series of progressively more accurate force fields. Combined with the high-quality sampling enabled by discretization, multi-level modeling will permit a high degree of confidence in the computational data. Indeed, the simulation results --- including models of structural intermediates and the identities of kinetically critical residues --- will be used to design experiments (to be performed by collaborators) aimed toward improving our detailed understanding of structural events. Because of its speed and simplicity, the new protocol forms an ideal basis for a software tool of value to expert and non-expert alike. A detailed plan for distributing user-friendly software packages is presented, and the source code will be available for modification by expert users. ? ?

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
5R01GM070987-04
Application #
7265311
Study Section
Special Emphasis Panel (ZRG1-SSS-H (90))
Program Officer
Preusch, Peter C
Project Start
2004-04-01
Project End
2009-07-31
Budget Start
2007-08-01
Budget End
2008-07-31
Support Year
4
Fiscal Year
2007
Total Cost
$206,290
Indirect Cost
Name
University of Pittsburgh
Department
Biology
Type
Schools of Medicine
DUNS #
004514360
City
Pittsburgh
State
PA
Country
United States
Zip Code
15213
Bhatt, Divesh; Zuckerman, Daniel M (2011) Beyond microscopic reversibility: Are observable non-equilibrium processes precisely reversible? J Chem Theory Comput 7:2520-2527
Mamonov, Artem B; Zhang, Xin; Zuckerman, Daniel M (2011) Rapid sampling of all-atom peptides using a library-based polymer-growth approach. J Comput Chem 32:396-405
Cashman, D J; Mamonov, A B; Bhatt, D et al. (2011) Thermal motions of the E. coli glucose-galactose binding protein studied using well-sampled, semi-atomistic simulations. Curr Top Med Chem 11:211-20
Adelman, Joshua L; Dale, Amy L; Zwier, Matthew C et al. (2011) Simulations of the alternating access mechanism of the sodium symporter Mhp1. Biophys J 101:2399-407
Lettieri, Steven; Mamonov, Artem B; Zuckerman, Daniel M (2011) Extending fragment-based free energy calculations with library Monte Carlo simulation: annealing in interaction space. J Comput Chem 32:1135-43
Bhatt, Divesh; Zhang, Bin W; Zuckerman, Daniel M (2010) Steady-state simulations using weighted ensemble path sampling. J Chem Phys 133:014110
Ding, Ying; Mamonov, Artem B; Zuckerman, Daniel M (2010) Efficient equilibrium sampling of all-atom peptides using library-based Monte Carlo. J Phys Chem B 114:5870-7
Zhang, Bin W; Jasnow, David; Zuckerman, Daniel M (2010) The ""weighted ensemble"" path sampling method is statistically exact for a broad class of stochastic processes and binning procedures. J Chem Phys 132:054107
Bhatt, Divesh; Zuckerman, Daniel M (2010) Heterogeneous path ensembles for conformational transitions in semi-atomistic models of adenylate kinase. J Chem Theory Comput 6:3527-3539
Zhang, Xin; Mamonov, Artem B; Zuckerman, Daniel M (2009) Absolute free energies estimated by combining precalculated molecular fragment libraries. J Comput Chem 30:1680-91

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