title: A method to explore protein side chain conformational variability using experimental data.
abstract: Experimentally measured values of molecular properties or observables of biomolecules such as proteins are generally averages over time and space, which do not contain sufficient information to determine the underlying conformational distribution of the molecules in solution. The relationship between experimentally measured NMR (3)J-coupling values and the corresponding dihedral angle values is a particularly complicated case due to its nonlinear, multiple-valued nature. Molecular dynamics (MD) simulations at constant temperature can generate Boltzmann ensembles of molecular structures that are free from a priori assumptions about the nature of the underlying conformational distribution. They suffer, however, from limited sampling with respect to time and conformational space. Moreover, the quality of the obtained structures is dependent on the choice of force field and solvation model. A recently proposed method that uses time-averaging with local-elevation (LE) biasing of the conformational search provides an elegant means of overcoming these three problems. Using a set of side chain (3)J-coupling values for the FK506 binding protein (FKBP), we first investigate the uncertainty in the angle values predicted theoretically. We then propose a simple MD-based technique to detect inconsistencies within an experimental data set and identify degrees of freedom for which conformational averaging takes place or for which force field parameters may be deficient. Finally, we show that LE MD is the best method for producing ensembles of structures that, on average, fit the experimental data.
authors.affiliation: Laboratory of Physical Chemistry, Swiss Federal Institute of Technology ETH, 8093 Zurich, Switzerland.
authors.forename: Jane R
authors.initials: JR
authors.lastname: Allison
authors.forename: Wilfred F
authors.initials: WF
authors.lastname: van Gunsteren
mesh_terms: D000465:Algorithms; D000900:Anti-Bacterial Agents / Q000737:chemistry; D056004:Molecular Dynamics Simulation; D016559:Tacrolimus / Q000031:analogs & derivatives / Q000737:chemistry; D022021:Tacrolimus Binding Proteins / Q000737:chemistry*
chemical_list: D000900:Anti-Bacterial Agents; C058028:immunomycin; D022021:Tacrolimus Binding Proteins; D016559:Tacrolimus