Protein Solvent Shell Structure Provides Rapid Analysis of Hydration Dynamics

Abstract

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.

Enhancing the Catalytic Performance of Candida antarctica Lipase B by Chemical Modification With Alkylated Betaine Ionic Liquids

“…When the temperature was increased to higher than the optimum temperature, the modified enzymes exhibited improved tolerance and maintained a high enzyme activity at temperatures up to 70°C. This may be due to the hydrophobic structure of long chain alkyl betaine ionic liquids, resulting in a relatively hydrophobic microenvironment for the modified enzymes and avoiding direct exposure to high temperatures and solvents, while proteins and long chain alkanes can effectively enhance the rigid structure of the enzyme ( Wan et al, 2017 ; Dahanayake et al, 2019 ).As shown in Figure 3B , the optimal pH for both the native and modified enzyme was 7.5, resulting in the activity of all modified enzymes being improved. Consistent with the observed effect of temperature on enzyme activity, the [BetaineC 16 ][H 2 PO 4 ]-CALB modified enzyme exhibited the highest enzyme activity, with a relatively stable performance at pH < 6.5, while activity was significantly improved compared with the original enzyme at pH > 6.5.…”

Probing Adaptation of Hydration and Protein Dynamics to Temperature

“…MD simulations provide further information regarding the water distribution around proteins, including the structure and dynamics of water in hydration layers. The number of hydration water molecules in the loosely and tightly bound layers, respectively, is determined by calculating the number of water molecules involved in hydrogen bond to the protein surface, and within the bound hydration layers of the protein (approximately within the peak of the second layer of the water–protein radial distribution function). , MD simulations were performed over the same temperature range as the experiments.…”

SPEADI: Accelerated Analysis of IDP-Ion Interactions from MD-Trajectories

“…When the conformation of a protein is stable over the simulation time, this approach can provide a fairly accurate description of key solvent properties such as coordination numbers, mean distances, potentials of mean force and hydration [ 36 , 37 , 38 , 39 ]. The shape of a solvent’s RDF peaks even correlate with hydration dynamics [ 40 ].…”