Modeling pH-Dependent Protein Dynamics by Integrating Coarse-Grained Molecular Simulation and the Deep Neural Network Model

Key Points

• This research aims to improve modeling of pH-dependent protein dynamics by integrating coarse-grained simulations with neural network predictions.
• Integrated coarse-grained molecular simulations with deep neural networks
• Focused on the treatment of electrostatic interactions
• Utilized physics-based predictions for protein dynamics
• Demonstrated improved accuracy in electrostatic interaction modeling
• Enhanced understanding of protein dynamics at coarse-grained levels
• Provided a practical solution for biomolecular model limitations