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High-Resolution Neutron Spectroscopy to Study Picosecond-Nanosecond Dynamics of Proteins and Hydration Water

High-Resolution Neutron Spectroscopy to Study Picosecond-Nanosecond Dynamics of Proteins and Hydration Water

Published on: April 28, 2022

Modeling the hydration layer around proteins: HyPred.

Jouko J Virtanen¹, Lee Makowski, Tobin R Sosnick

¹Department of Chemistry, The University of Chicago, Chicago, Illinois, USA.

Biophysical Journal

|September 7, 2010

Summary

This summary is machine-generated.

We developed a precise method to predict protein hydration layers using radial distribution functions from molecular dynamics simulations. Immobilizing proteins during simulations significantly improved prediction accuracy for protein function and stability.

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Neutron Crystallography Data Collection and Processing for Modelling Hydrogen Atoms in Protein Structures

Neutron Crystallography Data Collection and Processing for Modelling Hydrogen Atoms in Protein Structures

Published on: December 1, 2020

Area of Science:

Biophysics
Computational Biology
Structural Biology

Background:

Protein hydration is crucial for protein function and stability.
Accurate prediction of solvent density around proteins is essential for understanding these roles.
Existing methods may lack atomic-level precision or require extensive computational resources.

Purpose of the Study:

To develop a simple, atomic-level precise method for predicting the solvent density near protein surfaces.
To create a predictive model for protein hydration layers without requiring additional simulations.
To quantitatively understand protein solvation and its impact on protein structure and function.

Main Methods:

Utilized all-atom, explicit solvent molecular dynamics simulations for three globular proteins.
Defined and calculated proximal radial distribution functions for various protein atom types.
Developed a predictive model based on these distribution functions, testing with both mobile and immobile protein simulations.

Main Results:

A significant improvement in hydration layer prediction was achieved when proteins were held immobile during simulations.
The developed model accurately predicted hydration layers with sub-1-Angstrom resolution.
Predictions for water density in hydration shells showed good agreement with experimental crystal structure data.

Conclusions:

The developed solvation model provides a basis for quantitatively understanding protein solvation.
This method allows for accurate prediction of protein hydration layers without the need for further simulations.
The findings enhance our ability to predict protein function and stability based on hydration properties.