Coarse-grained biomolecular simulation with REACH: realistic extension algorithm via covariance Hessian

Area of Science:

• Biophysics
• Computational Biology
• Protein Dynamics

Background:

• Simulating large biological systems requires efficient computational methods.
• Coarse-graining reduces complexity but often sacrifices accuracy.
• Elastic network models are useful but require accurate parameterization.

Purpose of the Study:

• Introduce the REACH (Residue-scale Elastic Network model with Atomistic force constants from Coarse-grained simulation) method.
• Develop a coarse-graining approach using atomistic molecular dynamics (MD) data.
• Enable accurate and efficient simulation of large-scale protein dynamics.

Main Methods:

• Calculated residue-scale elastic network model force constants from atomistic MD variance-covariance matrices.
• Utilized 1-ns MD trajectories of myoglobin (monomeric and dimeric) to derive force constants.
• Developed analytical functions for distance-dependent interresidue force constants for rapid normal mode calculation.

Main Results:

• REACH force constants from monomeric and dimeric myoglobin were similar.
• Residue-scale REACH normal modes accurately reproduced MD fluctuations and vibrational density of states without parameter rescaling.
• Temperature-dependent analysis showed nonlocal interactions primarily drive the dynamical transition in protein fluctuations.

Conclusions:

• The REACH method reliably determines protein spatiotemporal motion.
• REACH offers an efficient alternative to computationally expensive long atomistic MD simulations.
• This approach enhances the simulation of large biological systems.