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Self-guided Langevin dynamics study of regulatory interactions in NtrC.

ABSTRACT: Multiple self-guided Langevin dynamics (SGLD) simulations were performed to examine structural and dynamical properties of the receiver domain of nitrogen regulatory protein C (NtrC(r)). SGLD and MD simulations of the phosphorylated active form structure suggest a mostly stable but broad structural ensemble of this protein. The finite difference Poisson-Boltzmann calculations of the pK(a) values of the active site residues suggest an increase in the pK(a) of His-84 on phosphorylation of Asp-54. In SGLD simulations of the phosphorylated active form with charged His-84, the average position of the regulatory helix alpha4 is found closer to the starting structure than in simulations with the neutral His-84. To model the transition pathway, the phosphate group was removed from the simulations. After 7 ns of simulations, the regulatory helix alpha4 was found approximately halfway between positions in the NMR structures of the active and inactive forms. Removal of the phosphate group stimulated loss of helix alpha4, suggesting that the pathway of conformational transition may involve partial unfolding mechanism. The study illustrates the potential utility of the SGLD method in studies of the coupling between ligand binding and conformational transitions.

SUBMITTER: Damjanovic A

PROVIDER: S-EPMC3373014 | biostudies-literature | 2009 Sep

REPOSITORIES: biostudies-literature

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Self-guided Langevin dynamics study of regulatory interactions in NtrC.

Damjanović Ana A García-Moreno E Bertrand B Brooks Bernard R BR

Proteins 20090901 4

Multiple self-guided Langevin dynamics (SGLD) simulations were performed to examine structural and dynamical properties of the receiver domain of nitrogen regulatory protein C (NtrC(r)). SGLD and MD simulations of the phosphorylated active form structure suggest a mostly stable but broad structural ensemble of this protein. The finite difference Poisson-Boltzmann calculations of the pK(a) values of the active site residues suggest an increase in the pK(a) of His-84 on phosphorylation of Asp-54. ...[more]

PMID: 19384996

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Project description:This review provides a comprehensive description of the self-guided Langevin dynamics (SGLD) and the self-guided molecular dynamics (SGMD) methods and their applications. Example systems are included to provide guidance on optimal application of these methods in simulation studies. SGMD/SGLD has enhanced ability to overcome energy barriers and accelerate rare events to affordable time scales. It has been demonstrated that with moderate parameters, SGLD can routinely cross energy barriers of 20 kT at a rate that molecular dynamics (MD) or Langevin dynamics (LD) crosses 10 kT barriers. The core of these methods is the use of local averages of forces and momenta in a direct manner that can preserve the canonical ensemble. The use of such local averages results in methods where low frequency motion "borrows" energy from high frequency degrees of freedom when a barrier is approached and then returns that excess energy after a barrier is crossed. This self-guiding effect also results in an accelerated diffusion to enhance conformational sampling efficiency. The resulting ensemble with SGLD deviates in a small way from the canonical ensemble, and that deviation can be corrected with either an on-the-fly or a post processing reweighting procedure that provides an excellent canonical ensemble for systems with a limited number of accelerated degrees of freedom. Since reweighting procedures are generally not size extensive, a newer method, SGLDfp, uses local averages of both momenta and forces to preserve the ensemble without reweighting. The SGLDfp approach is size extensive and can be used to accelerate low frequency motion in large systems, or in systems with explicit solvent where solvent diffusion is also to be enhanced. Since these methods are direct and straightforward, they can be used in conjunction with many other sampling methods or free energy methods by simply replacing the integration of degrees of freedom that are normally sampled by MD or LD.

Dataset Information

Self-guided Langevin dynamics study of regulatory interactions in NtrC.

Publications

Self-guided Langevin dynamics study of regulatory interactions in NtrC.

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