DisVis: quantifying and visualizing accessible interaction space of distance-restrained biomolecular complexes

Area of Science:

• Structural Biology
• Computational Biology
• Biophysics

Background:

• Analyzing protein-protein interactions is crucial for understanding biological processes.
• Accurate structural models of protein complexes are essential for drug discovery and functional studies.
• Existing methods may lack efficient ways to assess the quality and information content of experimental restraints.

Purpose of the Study:

• To introduce DisVis, a computational tool for analyzing distance-restrained protein complexes.
• To enable visualization and quantification of the information content within distance restraints.
• To provide a generalizable approach applicable to various structural biology and computational tasks.

Main Methods:

• Developed DisVis as a Python package and command-line tool.
• Implemented methods to calculate the reduced accessible interaction space for binary protein complexes.
• Integrated the approach for use as a knowledge-based distance energy term in Fast Fourier Transform (FFT)-based docking.

Main Results:

• DisVis allows for direct visualization of the conformational space of protein complexes.
• The tool quantifies the information content derived from distance restraints.
• The approach is effective when integrated into FFT-based docking for enhanced sampling.

Conclusions:

• DisVis offers a novel method for evaluating distance restraints in protein complex analysis.
• The tool facilitates a deeper understanding of the structural information encoded in experimental data.
• DisVis has potential applications in structural biology, computational drug design, and structural genomics.