Apta FastZ: An Algorithm for the Rapid Identification of Aptamers with Defined Binding Affinities

Area of Science:

• Biomolecular Engineering
• Bioinformatics
• Biosensor Technology

Background:

• Real-time biomolecular monitoring necessitates biosensors utilizing affinity reagents like aptamers.
• Aptamers with moderate to low affinities offer optimal binding dynamics and signal gain for biosensors.
• Previous methods like Pro-SELEX used bioinformatics to select aptamers with specific affinities.

Purpose of the Study:

• To develop a faster algorithm, Apta FastZ, to enhance the Pro-SELEX workflow.
• To maintain the accuracy of aptamer affinity prediction while increasing computational speed.
• To reduce the overall time for aptamer discovery and validation.

Main Methods:

• Developed Apta FastZ, a rapid computational algorithm derived from AptaZ.
• Optimized Apta FastZ by considering the sparse nature of sequences from SELEX and minimizing sequence comparisons.
• Validated Apta FastZ predictions experimentally using myeloperoxidase aptamers.

Main Results:

• Apta FastZ demonstrated a 10 to 40-fold increase in computing speed compared to AptaZ.
• The algorithm maintained identical outcomes to AptaZ in predicting aptamer affinities.
• Bioinformatics analysis for large datasets was completed within 1-10 hours.
• Experimental validation showed a high linear correlation between Apta FastZ predicted scores and measured aptamer affinities.

Conclusions:

• Apta FastZ significantly accelerates the Pro-SELEX workflow for aptamer selection.
• The implementation of Apta FastZ enables the discovery of customized aptamers within 3 days.
• This advancement facilitates rapid development of aptamers for biosensor applications.