Computational design and biosensor applications of small molecule-sensing allosteric ribozymes

Area of Science:

• Synthetic Biology
• Computational Chemistry
• Molecular Biology

Background:

• Allosteric ribozymes offer precise molecular sensing capabilities.
• Developing efficient computational methods is crucial for designing complex RNA structures.
• Boolean logic functions in biological systems enable sophisticated molecular computing.

Purpose of the Study:

• To develop accurate and time-efficient computational methods for designing small molecule-sensing allosteric ribozymes.
• To engineer ribozymes functioning as NOT or YES Boolean logic gates.
• To create novel RNA sensors for applications in antibacterial drug discovery and gene expression control.

Main Methods:

• Computational modeling of secondary structures to fuse theophylline aptamers with extended hammerhead ribozymes.
• Computational modeling of 3D interactions to fuse minimal hammerhead ribozymes with bacterial guanine or adenine aptamers.
• Development of high-throughput compatible arrays based on purine RNA sensors.

Main Results:

• Engineered theophylline-sensing ribozymes with a high cleavage rate (1.3 min⁻¹) under physiological conditions.
• Achieved high specificity for theophylline, with no response to caffeine.
• Developed purine-sensing ribozymes and high-throughput screening arrays for antibacterial drug discovery.

Conclusions:

• Accurate and efficient computational design of allosteric ribozymes as Boolean logic gates is feasible.
• These engineered ribozymes serve as specific molecular sensors with potential in diverse applications.
• The developed RNA sensors are valuable tools for exogenous gene control, high-throughput screening, and molecular computing.