paper

On the origin of diverse time scales in the protein hydration layer solvation dynamics: A molecular dynamics simulation study

arXiv:1708.01210 · doi:10.1063/1.4995420

Abstract

In order to inquire the microscopic origin of observed multiple time scales in solvation dynamics we carry out several computer experiments. We perform atomistic molecular dynamics simulations on three protein-water systems namely, Lysozyme, Myoglobin and sweet protein Monellin. In these experiments we mutate the charges of the neighbouring amino acid side chains of certain natural probes (Tryptophan) and also freeze the side chain motions. In order to distinguish between different contributions, we decompose the total solvation energy response in terms of various components present in the system. This allows us to capture the interplay among different self and cross-energy correlation terms. Freezing the protein motions removes the slowest component that results from side chain fluctuations, but a part of slowness remains. This leads to the conclusion that the slow component in the ~20-80 ps range arises from slow water molecules present in the hydration layer. While the more than 100 ps component may arise from various sources namely, adjacent charges in amino acid side chains, the water molecules that are hydrogen bonded to them and a dynamically coupled motion between side chain and water. The charges, in addition, enforce a structural ordering of nearby water molecules and helps to form local long-lived hydrogen bonded network. Further separation of the spatial and temporal responses in solvation dynamics reveals different roles of hydration and bulk water. We find that the hydration layer water molecules are largely responsible for the slow component whereas the initial ultrafast decay arise predominantly (~80%) due to the bulk. This agrees with earlier theoretical observations. We also attempt to rationalise our results with the help of a molecular hydrodynamic theory that was developed using classical time dependent density functional theory in a semi quantitative manner.

arXiv comment27 pages, 9 figures

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