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A Data-Driven Hydrophobicity Scale for Predicting Liquid–Liquid Phase Separation of Proteins by Thomas Dannenhoffer-Lafage; Robert B. Best is a Chemistry article available to read on EtoBox.

What is A Data-Driven Hydrophobicity Scale for Predicting Liquid–Liquid Phase Separation of Proteins about?

An accurate model for macroscale disordered assemblies of biological macromolecules such as those formed in so-called membraneless organelles would greatly assist in studying their structure, function, and dynamics. Recent evidence has suggested that liquid-liquid phase separation (LLPS) underlies the formation of membraneless organelles. While the general mechanism of exchange of macromolecule/water for macromolecule/macromolecule interactions is known to be the driving force for LLPS, the specific interactions involved are not well understood. One way that protein-water and protein-protein interactions have been understood historically is via hydrophobicity scales. However, these scales are typically optimized for describing these relative interactions in certain cases, such as protein folding or insertion of proteins into membranes. To better describe the relative interactions of proteins that undergo LLPS, we have developed a new, data-driven hydrophobicity scale. To determine the new scale, we used coarse-grained molecular dynamics simulations using the hydrophobicity scale coarse-grained model, which relates the interactions between amino acids to their hydrophobicity. Hydrop

Who reads A Data-Driven Hydrophobicity Scale for Predicting Liquid–Liquid Phase Separation of Proteins?

It is typically read by researchers, students, and practitioners in Chemistry.

Author
Thomas Dannenhoffer-Lafage; Robert B. Best
Publisher
American Chemical Society (ACS)
Published
2021
Language
EN
Field
Chemistry (Physical Sciences)

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