Infrequent metadynamics study of rare-event electrostatic channeling

Area of Science:

• Biochemistry
• Computational Chemistry
• Chemical Engineering

Background:

• Cascade reactions require efficient intermediate transport between steps, a challenge in artificial systems.
• Electrostatic channeling is effective in natural cascades but difficult to implement artificially.
• Poly-arginine peptides offer a potential solution for bridging enzymes in artificial cascades.

Purpose of the Study:

• To computationally investigate the transport mechanism of glucose-6-phosphate (G6P) using poly-arginine peptides.
• To compare the efficiency of poly-arginine bridges with poly-lysine bridges in artificial enzyme cascades.
• To determine the feasibility of using poly-arginine for electrostatic channeling of anionic intermediates.

Main Methods:

• Infrequent metadynamics (InMetaD) to calculate hopping activation energy.
• Umbrella sampling (US) to determine desorption energy.
• Kinetic Monte Carlo (KMC) modeling to estimate transport efficiency.

Main Results:

• G6P transport via hopping on poly-arginine is a rare event requiring significant energy.
• Poly-arginine peptides demonstrated potentially more efficient transport than poly-lysine.
• KMC simulations predicted a lag time of 6 seconds for poly-arginine vs. 59 seconds for poly-lysine.

Conclusions:

• Poly-arginine peptides may serve as improved bridge structures for electrostatic channeling in artificial enzyme cascades.
• This approach enhances intermediate transfer efficiency, crucial for multi-step synthesis.
• The findings pave the way for designing more efficient artificial chemical systems.