NAPS update: network analysis of molecular dynamics data and protein-nucleic acid complexes

Area of Science:

• Biophysics
• Computational Biology
• Structural Biology

Background:

• Network theory is a key method for understanding protein structure, folding, and function.
• Molecular dynamics (MD) simulations combined with network theory provide insights into conformational changes, flexibility, and allosteric communications.
• Existing tools may have limitations in analyzing diverse biomolecular systems and MD trajectories comprehensively.

Purpose of the Study:

• To present an updated version of the Network Analysis of Proteins (NAPS) tool.
• To expand NAPS capabilities for comprehensive network analysis of proteins, protein-protein/nucleic acid complexes, MD trajectories, and RNA.
• To enhance visualization and analysis options for biomolecular network studies.

Main Methods:

• Utilizing network theory principles applied to biomolecular structures.
• Integrating molecular dynamics (MD) simulation data for network construction.
• Employing inter-residue interaction energies derived from standard force fields for network edge-weights.
• Developing advanced visualization and interactive plotting features.

Main Results:

• The updated NAPS tool facilitates network analysis across a wide range of biomolecules, including proteins, complexes, and RNA.
• NAPS offers diverse analysis options for MD trajectories, such as individual and average network construction, comparative analysis, and dynamic cross-correlations.
• The tool enables network construction and analysis for entire protein-nucleic acid complexes or their interfaces.
• Atomistic details are captured through network construction based on inter-residue interaction energies with realistic edge-weights.

Conclusions:

• The enhanced NAPS tool provides a robust platform for comprehensive biomolecular network analysis.
• NAPS supports detailed investigation of protein dynamics, allosteric mechanisms, and drug binding pockets.
• Improved visualization and bulk execution features streamline the analysis workflow for researchers.