Identification of Mutational Hot Spots for Substrate Diffusion: Application to Myoglobin

Area of Science:

• Biophysics
• Computational Biology
• Protein Engineering

Background:

• Understanding how small molecules access protein active sites is vital for enzyme and protein function.
• Designing or modifying proteins requires identifying mutation sites that influence substrate transport properties.
• Molecular simulations indicate multiple ligand access routes, complicating traditional analysis.

Purpose of the Study:

• To develop a method for identifying critical mutation sites that affect ligand diffusion rates.
• To apply this method to myoglobin to understand its substrate transport mechanisms.
• To validate the predictive power of the developed method against experimental data.

Main Methods:

• Utilized Markov State Models (MSMs) to capture the complexity of ligand diffusion processes.
• Developed a sensitivity analysis of the MSM rate matrix to identify key mutation locations.
• Applied the method to myoglobin, a well-characterized protein model.

Main Results:

• The sensitivity analysis successfully identified specific locations within myoglobin where mutations significantly impact ligand diffusion on-rates.
• Translating sensitivity parameters into CO binding rates upon mutation showed semi-quantitative correlation with experimental results.
• The model's predictions were further validated against explicit simulations of experimental mutants.

Conclusions:

• The developed MSM-based sensitivity analysis provides a powerful tool for predicting the effects of protein mutations on ligand transport.
• This approach aids in rational protein design by guiding the selection of mutation sites for desired functional alterations.
• The study validates the utility of MSMs and sensitivity analysis in understanding and engineering protein dynamics and function.