Balancing bond, nonbond, and gō-like terms in coarse grain simulations of conformational dynamics.
Characterization of the protein conformational landscape remains a challenging problem, whether it concerns elucidating folding mechanisms, predicting native structures or modeling functional transitions. Coarse-grained molecular dynamics simulation methods enable exhaustive sampling of the energetic landscape at resolutions of biological interest. The general utility of structure-based models is reviewed along with their differing levels of approximation. Simple Gō models incorporate attractive native interactions and repulsive nonnative contacts, resulting in an ideal smooth landscape. Non-Gō coarse-grained models reduce the parameter set as needed but do not include bias to any desired native structure. While non-Gō models have achieved limited success in protein coarse-graining, they can be combined with native structured-based potentials to create a balanced and powerful force field. Recent applications of such Gō-like models have yielded insight into complex folding mechanisms and conformational transitions in large macromolecules. The accuracy and usefulness of reduced representations are also revealed to be a function of the mathematical treatment of the intrinsic bonded topology.
Department of Pharmaceutical Sciences, University of New England, Portland, ME, USA.
Ronald D
RD
Hills
D000465:Algorithms; D008958:Models, Molecular; D056004:Molecular Dynamics Simulation; D011487:Protein Conformation; D017510:Protein Folding; D011506:Proteins / Q000737:chemistry*
D011506:Proteins