title: Coarse-Grained Protein Model Coupled with a Coarse-Grained Water Model:  Molecular Dynamics Study of Polyalanine-Based Peptides.
abstract: The coupling of a coarse-grained (CG) protein model with the CG water model developed by Marrink et al. (J. Phys. Chem. B 2004, 108, 750) is presented. The model was used in the molecular dynamics studies of Ac-(Ala)6-Xaa-(Ala)7-NHMe, Xaa = Ala, Leu, Val, and Gly. A Gly mutation in the middle of polyalanine is found to destabilize the helix and stabilize the hairpin by favoring a type-II' turn and probably to speed up hairpin folding. The simulations allow us to derive thermodynamic parameters of, in particular, the helical propensities (s) of amino acids in these polyalanine-based peptides. The calculated s values are 1.18 (Ala), 0.84 (Leu), 0.30 (Val), and <0.02 (Gly) at 291 K, in excellent agreement with experimental values (R(2)=0.970). Analyses using a structural approach method show that the helical propensity difference of these amino acids mainly comes from solvation effect. Leu and Val have lower helical propensities than Ala mainly because the larger side chains shield the solvation of helical structures, while Gly has a much poorer helical propensity mainly due to the much better solvation for the coil structures than for the helical structures. Overall, the model is at least about 10(2) times faster than current all-atom MD methods with explicit solvent.
authors.affiliation: Department of Chemistry, The Hong Kong University of Science & Technology, Kowloon, Hong Kong, China, and State Key Lab of Molecular Dynamics and Stable Structures, College of Chemistry, Peking University, Beijing, China.
authors.forename: Wei
authors.initials: W
authors.lastname: Han
authors.affiliation: Department of Chemistry, The Hong Kong University of Science & Technology, Kowloon, Hong Kong, China, and State Key Lab of Molecular Dynamics and Stable Structures, College of Chemistry, Peking University, Beijing, China.
authors.forename: Yun-Dong
authors.initials: YD
authors.lastname: Wu