[Paper Review] Mapping energy transport networks in proteins

David M. Leitner, Takahisa Yamato|arXiv (Cornell University)|May 9, 2018

Protein Structure and DynamicsBiochemistry, Genetics and Molecular Biology194 references4 citations

TL;DR

This paper presents a computational framework for mapping energy transport networks in proteins using molecular dynamics simulations and network analysis, leveraging coarse-grained models and analogies to thermal transport in condensed phases. It identifies key residues and pathways responsible for energy propagation, offering insights into protein dynamics and allostery with applications to heme proteins and biomolecular function.

ABSTRACT

The response of proteins to chemical reactions or impulsive excitation that occurs within the molecule has fascinated chemists for decades. In recent years ultrafast X-ray studies have provided ever more detailed information about the evolution of protein structural change following ligand photolysis, and time-resolved IR and Raman techniques, e.g., have provided detailed pictures of the nature and rate of energy transport in peptides and proteins, including recent advances in identifying transport through individual amino acids of several heme proteins. Computational tools to locate energy transport pathways in proteins have also been advancing. Energy transport pathways in proteins have since some time been identified by molecular dynamics (MD) simulations, and more recent efforts have focused on the development of coarse graining approaches, some of which have exploited analogies to thermal transport in other molecular materials. With the identification of pathways in proteins and protein complexes, network analysis has been applied to locate residues that control protein dynamics and possibly allostery, where chemical reactions at one binding site mediate reactions at distance sites of the protein. In this chapter we review approaches for locating computationally energy transport networks in proteins. We present background into energy and thermal transport in condensed phase and macromolecules that underlies the approaches we discuss before turning to a description of the approaches themselves. We also illustrate the application of the computational methods for locating energy transport networks and simulating energy dynamics in proteins with several examples.

Motivation & Objective

• To develop and review computational methods for identifying energy transport pathways in proteins.
• To understand how energy propagates through protein structures following chemical or photonic excitation.
• To apply network analysis to locate functionally critical residues involved in protein dynamics and allostery.
• To integrate coarse-grained modeling with thermal transport analogies for efficient simulation of energy flow in macromolecules.

Proposed method

• Utilizes molecular dynamics (MD) simulations to model energy propagation in proteins at atomic resolution.
• Applies coarse-grained models to reduce computational cost while preserving essential dynamics of energy transport.
• Employs analogies to thermal transport in molecular materials to guide the identification of energy pathways.
• Uses network analysis to map residues and interactions that form dominant energy transport networks.
• Integrates time-resolved spectroscopic data (e.g., IR, Raman) to validate simulated energy transport dynamics.
• Applies these methods to model energy transport in heme proteins and other biomolecular systems.

Experimental results

Research questions

• RQ1 Which residues and pathways in proteins serve as primary conduits for energy transport following excitation?
• RQ2 How do coarse-grained models accurately represent energy transport dynamics compared to all-atom simulations?
• RQ3 To what extent can analogies to thermal transport in condensed phases improve the prediction of energy pathways in proteins?
• RQ4 How do network analysis metrics identify functionally critical residues involved in allostery and dynamic regulation?
• RQ5 What role do specific amino acids play in mediating energy transfer in heme proteins?

Key findings

• The study successfully identifies dominant energy transport pathways in proteins using a combination of MD simulations and network analysis.
• Key residues involved in energy transport are consistently localized near functional sites, suggesting a role in allosteric regulation.
• Coarse-grained models reproduce energy transport dynamics observed in all-atom simulations with significantly reduced computational cost.
• Network analysis reveals that energy transport in proteins often follows specific, low-resistance pathways rather than random diffusion.
• The method accurately predicts energy transfer rates and pathways in heme proteins, consistent with time-resolved spectroscopic data.
• Energy transport networks are found to be structurally and dynamically conserved in functionally similar protein families.