Refinement of Protein NMR Structure under Membrane-like Environments with an Implicit Solvent Model

Abstract

Refinement of NMR structures by molecular dynamics (MD) simulations with a solvent model has improved the structural quality. In this study, we applied MD refinement with the generalized Born (GB) implicit solvent model to protein structure determined under membrane-like environments. Despite popularity of the GB model, its applications to the refinement of NMR structures of hydrophobic proteins, in which detergents or organic solvents enclose proteins, are limited, and there is little information on the use of another GB parameter for these cases. We carried out MD refinement of crambin NMR structure in dodecylphosphocholine (DPC) micelles (Ahn et al., J. Am. Chem. Soc. 2006, 128, 4398-4404) with GB/Surface area model and two different surface tension coefficients, one for aquatic and the other for hydrophobic conditions. Our data show that, of two structures by MD refinement with G B model, the one refined with the parameter to consider hydrophobic condition had the better qualities in terms of precision and solvent accessibility.