Pseudopotentials for coarse-grained cross-link-assisted modeling of protein structures

Area of Science:

• Computational biology
• Biophysics
• Molecular dynamics

Background:

• Protein structure prediction is crucial for understanding function.
• Coarse-grained simulations offer computational efficiency for large biomolecules.
• Accurate representation of chemical cross-links is essential for certain simulation types.

Purpose of the Study:

• To develop and validate new pseudopotentials for chemical cross-links in coarse-grained simulations.
• To improve the accuracy of protein models generated through cross-link-assisted simulations.

Main Methods:

• Canonical molecular dynamics simulations using the Amber14sb force field.
• Development of distance- and orientation-dependent potentials for cross-links.
• Implementation of new potentials within the UNRES coarse-grained force field.
• Assessment of model quality using 11 monomeric and 1 dimeric proteins with experimental or synthetic cross-link data.

Main Results:

• New pseudopotentials were determined for glutamic/aspartic acid and lysine side chains cross-linked with various agents.
• The potentials prevent unrealistic cross-link contacts within protein globules.
• Simulations using the new potentials showed improved model quality compared to unrestrained simulations and simulations with previous statistical potentials.

Conclusions:

• The developed pseudopotentials enhance the accuracy of coarse-grained protein modeling.
• This approach improves the reliability of cross-link-assisted simulation methods.
• The findings contribute to more precise protein structure prediction and analysis.