Interplay between translational diffusion and large-amplitude angular jumps of water molecules

Turning an energy-based defect detector into a multi-molecule structural indicator for water

Recent studies have provided conclusive evidence for the existence of a liquid-liquid critical point in numerical models of water. Such a scenario implies the competition between two local molecular arrangements of different densities: a high-density liquid (HDL) and a low-density liquid (LDL). Within this context, the development of accurate structural indicators to properly characterize the two interconverting local structures is demanded. In a previous study, we introduced a reliable energy-based structural descriptor that properly discriminates water molecules into tetrahedrally arranged molecules (T molecules) and distorted molecules (D molecules). The latter constitute defects in terms of hydrogen bond (HB) coordination and have been shown to represent a minority component, even at high temperatures above the melting point. In addition, the D molecules tend to form high-quality HBs with three T molecules and to be surrounded by T and D molecules at further distances. Thus, it became evident that, while the LDL state might consist of a virtually pure T state, the HDL state would comprise mixed molecular arrangements including the D molecules. Such a need to abandon the single-molecule description requires the investigation of the degree of structural information to be incorporated in order to build an appropriate multi-molecule indicator. Hence, in this work, we shall study the effect of the local structural constraints on the water molecules in order to discriminate the different molecular arrangements into two disjoint classes. This will enable us to build a multi-molecule structural indicator for water whose performance will then be investigated within the water's supercooled regime.

The collective burst mechanism of angular jumps in liquid water

Understanding the microscopic origins of collective reorientational motions in aqueous systems requires techniques that allow us to reach beyond our chemical imagination. Herein, we elucidate a mechanism using a protocol that automatically detects abrupt motions in reorientational dynamics, showing that large angular jumps in liquid water involve highly cooperative orchestrated motions. Our automatized detection of angular fluctuations, unravels a heterogeneity in the type of angular jumps occurring concertedly in the system. We show that large orientational motions require a highly collective dynamical process involving correlated motion of many water molecules in the hydrogen-bond network that form spatially connected clusters going beyond the local angular jump mechanism. This phenomenon is rooted in the collective fluctuations of the network topology which results in the creation of defects in waves on the THz timescale. The mechanism we propose involves a cascade of hydrogen-bond fluctuations underlying angular jumps and provides new insights into the current localized picture of angular jumps, and its wide use in the interpretations of numerous spectroscopies as well in reorientational dynamics of water near biological and inorganic systems. The role of finite size effects, as well as of the chosen water model, on the collective reorientation is also elucidated.

Water Diffusion Proceeds via a Hydrogen-Bond Jump Exchange Mechanism

The self-diffusion of water molecules plays a key part in a broad range of essential processes in biochemistry, medical imaging, material science, and engineering. However, its molecular mechanism and the role played by the water hydrogen-bond network rearrangements are not known. Here we combine molecular dynamics simulations and analytic modeling to determine the molecular mechanism of water diffusion. We establish a quantitative connection between the water diffusion coefficient and hydrogen-bond jump exchanges, and identify the features that determine the underlying energetic barrier. We thus provide a unified framework to understand the coupling between translational, rotational, and hydrogen-bond dynamics in liquid water. It explains why these different dynamics do not necessarily exhibit identical temperature dependences although they all result from the same hydrogen-bond exchange events. The consequences for the understanding of water diffusion in supercooled conditions and for water transport in complex aqueous systems, including ionic, biological, and confined solutions, are discussed.

Protein Solvent Shell Structure Provides Rapid Analysis of Hydration Dynamics

The solvation layer surrounding a protein is clearly an intrinsic part of protein structure-dynamics-function, and our understanding of how the hydration dynamics influences protein function is emerging. We have recently reported simulations indicating a correlation between regional hydration dynamics and the structure of the solvation layer around different regions of the enzyme Candida antarctica lipase B, wherein the radial distribution function (RDF) was used to calculate the pairwise entropy, providing a link between dynamics (diffusion) and thermodynamics (excess entropy) known as Rosenfeld scaling. Regions with higher RDF values/peaks in the hydration layer (the first peak, within 6 Å of the protein surface) have faster diffusion in the hydration layer. The finding thus hinted at a handle for rapid evaluation of hydration dynamics at different regions on the protein surface in molecular dynamics simulations. Such an approach may move the analysis of hydration dynamics from a specialized venture to routine analysis, enabling an informatics approach to evaluate the role of hydration dynamics in biomolecular function. This paper first confirms that the correlation between regional diffusive dynamics and hydration layer structure (via water center of mass around protein side-chain atom RDF) is observed as a general relationship across a set of proteins. Second, it seeks to devise an approach for rapid analysis of hydration dynamics, determining the minimum amount of information and computational effort required to get a reliable value of hydration dynamics from structural data in MD simulations based on the protein-water RDF. A linear regression model using the integral of the hydration layer in the water-protein RDF was found to provide statistically equivalent apparent diffusion coefficients at the 95% confidence level for a set of 92 regions within five different proteins. In summary, RDF analysis of 10 ns of data after simulation convergence is sufficient to accurately map regions of fast and slow hydration dynamics around a protein surface. Additionally, it is anticipated that a quick look at protein-water RDFs, comparing peak heights, will be useful to provide a qualitative ranking of regions of faster and slower hydration dynamics at the protein surface for rapid analysis when investigating the role of solvent dynamics in protein function.