Space Layout of Low-entropy Hydration Shells Guides Protein Binding

TL;DR

This study reveals that low-entropy hydration shells around proteins, especially their shape-matched regions, guide protein binding through hydrophobic interactions, enabling accurate prediction of binding sites.

Contribution

The paper introduces a novel method to identify low-entropy hydration shell regions and demonstrates their role in guiding protein-protein binding, improving prediction accuracy.

Findings

Largest low-entropy hydration regions cover binding sites

Shape matching of hydration shells correlates with binding sites

Hydrophobic collapse guides protein binding

Abstract

Protein-protein binding enables orderly and lawful biological self-organization, and is therefore considered a miracle of nature. Protein-protein binding is steered by electrostatic forces, hydrogen bonding, van der Waals force, and hydrophobic interactions. Among these physical forces, only the hydrophobic interactions can be considered as long-range intermolecular attractions between proteins in intracellular and extracellular fluid. Low-entropy regions of hydration shells around proteins drive hydrophobic attraction among them that essentially coordinate protein-protein docking in rotational-conformational space of mutual orientations at the guidance stage of the binding. Here, an innovative method was developed for identifying the low-entropy regions of hydration shells of given proteins, and we discovered that the largest low-entropy regions of hydration shells on proteins typically cover the binding sites. According to an analysis of determined protein complex structures, shape matching between the largest low-entropy hydration shell region of a protein and that of its partner at the binding sites is revealed as a regular pattern. Protein-protein binding is thus found to be mainly guided by hydrophobic collapse between the shape-matched low-entropy hydration shells that is verified by bioinformatics analyses of hundreds of structures of protein complexes. A simple algorithm is developed to precisely predict protein binding sites.