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To evaluate the enthalpic and entropic contributions of polar residues in alanine-based peptides to α-helical propensities of peptides, we applied a Brownian dynamics simulation, together with the umbrella sampling, to two alanine-based 21-residue peptides: one composed of alanine only (AAA), the other composed of 18 alanines and 3 arginines (ARA). Higher α-helical propensity of ARA than that of AAA was obtained. However, they showed similar conformational stability in enthalpy, considering the contribution of the solvation energy and the potential energy. As an evaluation of entropic effects, the fluctuation of a dihedral angle, ψ, was investigated. Arginine residue showed smaller fluctuation than alanine in elongated states. Higher α-helical propensity might originate from entropic effects. Furthermore, arginine seems to affect the α-helical propensity of alanines interacting with arginine.

We applied an atomistic Brownian dynamics (BD) simulation with multiple time step method for the folding simulation of a 13-mer α-helical peptide and a 12-mer β-hairpin peptide, giving successful folding simulations. In this model, the driving energy contribution towards folding came from both electrostatic and van der Waals interactions for the α-helical peptide and from van der Waals interactions for the β-hairpin peptide. Although, many non-native structures having the same or lower energy than that of native structure were observed, the folded states formed the most populated cluster when the structures obtained by the BD simulations were subjected to the cluster analysis based on distance-based root mean square deviation of side-chains between different structures. This result indicates that we can predict the native structures from conformations sampled by BD simulation.

We report a multiple time step algorithm applied to an atomistic Brownian dynamics simulation for simulating the long time scale dynamics of biomolecules. The algorithm was based on the original multiple time step method; a short time step was used to keep faster motions in local equilibrium. When applied to a 28-mer # # ! folded peptide, the simulation gave stable trajectories and the computation time was reduced by a factor of 160 compared to a conventional molecular dynamics simulation using explicit water molecules. We applied it for the folding simulation of a 13-mer ! -helical peptide, giving a successful folding simulation. These results indicate that the Brownian dynamics with the multiple time step algorithm is useful for studies of biomolecular motions by long time simulation.