Computational analysis reveals temperature-induced stabilization of FAST-PETase

Area of Science:

• Biotechnology
• Enzyme Engineering
• Computational Biology

Background:

• Poly(ethyleneterephthalate) (PET) constitutes over 10% of global solid waste.
• Wildtype PETases have limited activity and thermal stability for industrial plastic depolymerization.
• FAST-PETase, engineered using machine learning, shows enhanced functionality, activity, stability, and tolerance.

Purpose of the Study:

• To elucidate the molecular mechanisms behind FAST-PETase's improved thermal stability.
• To compare the dynamics of wildtype IsPETase (WT-PETase) and FAST-PETase.
• To identify thermolabile regions in WT-PETase and understand how mutations affect them.

Main Methods:

• Comparative Constraint Network Analysis (CNAnalysis).
• Molecular Dynamics (MD) simulations at 30°C and 50°C.
• Physical energy calculations to determine the free energy of unfolding (ΔG(stability)).

Main Results:

• Identified thermolabile sequence stretches in WT-PETase.
• FAST-PETase mutations targeted these critical regions, reducing backbone flexibility at elevated temperatures.
• In-silico and physical energy calculations indicated decreased free energy of unfolding and increased rigidity at higher temperatures for FAST-PETase.

Conclusions:

• FAST-PETase achieves enhanced thermal stability through temperature-dependent conformational changes that rigidify the enzyme.
• Findings provide insights into rational protein engineering for thermostability.
• Contributes to understanding the thermal adaptation of thermophilic enzymes.