Master equation model to predict energy transport pathways in proteins

Area of Science:

• Biophysics
• Computational Biology

Background:

• Time-resolved experiments and molecular dynamics simulations enable monitoring vibrational energy flow in biomolecules.
• A master equation model was previously proposed to describe this energy transport, parameterized for low temperatures.

Purpose of the Study:

• To extend the master equation model's applicability to general proteins at room temperature.
• To introduce a new parameterization based on extensive nonequilibrium molecular dynamics simulations.
• To identify and analyze vibrational energy transport pathways in proteins.

Main Methods:

• Developed a new parameterization for a master equation model using extensive nonequilibrium molecular dynamics simulations.
• Proposed a new scaling rule for contact-mediated energy transport.
• Utilized Monte Carlo Markov chain simulations to identify energy transport pathways.

Main Results:

• Backbone transport is the fastest channel for vibrational energy flow (0.5-1 ps), described by a diffusive scaling rule.
• Contact transport (e.g., via hydrogen bonds) is slower at room temperature (6-30 ps).
• A new inverse square distance scaling rule accurately describes contact transport, validated in the PDZ3 protein.

Conclusions:

• The refined master equation model, with structure-dependent scaling rules, offers a simple and general method for predicting protein energy transport.
• Backbone and contact transport pathways compete, influencing overall energy flow dynamics.
• The model facilitates understanding energy dissipation mechanisms in proteins.