Travel depth, a new shape descriptor for macromolecules: application to ligand binding

Area of Science:

• Structural Biology
• Computational Chemistry
• Biophysics

Background:

• Macromolecular depth is crucial for understanding molecular function but lacks rigorous definition and computational tools.
• Existing methods struggle to quantify depth in complex macromolecular structures like DNA grooves or protein active sites.

Purpose of the Study:

• To develop a robust computational method for quantifying macromolecule depth.
• To introduce the concept of 'travel depth' as a measure of physical distance from a surface point to a reference surface.
• To enable high-throughput analysis of macromolecule depth and its impact on molecular interactions.

Main Methods:

• Defined a reference surface using the convex hull of the molecular surface.
• Developed a fast approximation algorithm to compute travel depth for every surface point.
• Applied the method to analyze protein-small molecule binding pockets and magnesium ion distribution in RNA.

Main Results:

• The travel depth algorithm effectively quantifies depth in pockets of varying complexity, including DNA grooves and molecular tunnels.
• Analysis of binding pockets revealed subtle but significant effects of depth on ligand binding localization and strength.
• Investigated magnesium ion distribution in RNA, demonstrating the method's utility in high-throughput structural analysis.

Conclusions:

• Travel depth provides a versatile and accurate metric for quantifying macromolecular surface features.
• The developed algorithm facilitates deeper insights into structure-function relationships, particularly in ligand binding and molecular recognition.
• This computational approach opens new avenues for high-throughput structural analysis and drug discovery.