Stochastic Mechanochemical Description of a Bioinspired Polymerization Process.

Area of Science:

• Biophysics
• Polymer Chemistry
• Theoretical Chemistry

Background:

• Enzyme-catalyzed polymerization is crucial in biological and industrial processes.
• Understanding the interplay between enzyme mechanics and chemical kinetics is essential for controlling polymerization outcomes.

Purpose of the Study:

• To theoretically investigate enzyme-catalyzed polymerization kinetics.
• To model the coupling between enzyme mechanics and chemical reaction rates.
• To predict polymerization behavior and polydispersity.

Main Methods:

• Developed a structural model of an enzyme as a Brownian particle sliding along a polymer chain.
• Employed a stochastic approach to describe polymerization kinetics.
• Utilized a numerical methodology to solve the Langevin equation.

Main Results:

• Predicted sudden polymerization arrest and decreased polydispersity with increasing polymer length.
• Identified four distinct kinetic regimes.
• Demonstrated the manifestation of mechanics/chemistry coupling in one regime.
• Showed that mechanical variables can be evaluated through chemical analysis.

Conclusions:

• The coupling of mechanics and chemistry significantly impacts enzyme-catalyzed polymerization.
• The model provides insights into controlling polymer chain length and polydispersity.
• Proposed a device to reduce technical polydispersity in polymerization processes.