Deriving Coarse-Grained Charges from All-Atom Systems: An Analytic Solution.

Area of Science:

• Computational chemistry
• Biophysics
• Molecular modeling

Background:

• Accurate molecular simulations require precise charge assignment.
• Existing coarse-graining methods can be computationally expensive and less accurate.
• Reproducing electrostatic potentials is vital for understanding protein interactions.

Purpose of the Study:

• To develop a computationally efficient analytic method for optimal coarse-grained charge assignment.
• To improve the accuracy of coarse-grained models in reproducing all-atom electrostatic potentials.
• To validate the method on aggregating protein systems.

Main Methods:

• Developed an analytic method for optimal coarse-grained charge assignment based on electrostatic potential matching.
• Implemented a minimization procedure for coarse-grained positions.
• Applied the joint optimal-charge and optimal-position method to aggregating proteins at single-site per amino acid resolution.

Main Results:

• The method achieves computational efficiency orders of magnitude greater than grid-integration charge-fitting.
• Coarse-grained models accurately reproduce vacuum and Debye-Hückel screened all-atom electrostatic potentials.
• The models approximate all-atom dimerization electrostatic potential energy for 10 aggregating proteins with high accuracy.

Conclusions:

• The presented analytic method provides an efficient and accurate approach for coarse-grained molecular modeling.
• Optimal charge and position assignment is critical for reproducing electrostatic properties of proteins.
• This method enhances the reliability of coarse-grained simulations for studying protein aggregation and interactions.