Computation-Enabled Structure-Based Discovery of Potent Binders for Small-Molecule Aptamers.

Area of Science:

• Biochemistry
• Computational Biology
• Drug Discovery

Background:

• Aptamers are nucleic acid-based binders with high affinity and specificity.
• Current methods for aptamer specificity characterization are limited.
• Exploring the chemical space of aptamer binders is crucial for practical applications.

Purpose of the Study:

• To develop a computational framework for identifying aptamer binders.
• To systematically explore aptamer-binding chemical space.
• To uncover aptamer versatility and enhance target specificity.

Main Methods:

• High-throughput, three-stage structure-based computational framework.
• Identification of potent binders for two model aptamers.
• Pocket mutation studies to tune aptamer specificity.

Main Results:

• An l-argininamide (L-Arm)-binding aptamer showed 31-fold higher affinity for retromer chaperone R55.
• Norfloxacin and difloxacin had >10-fold higher affinity for an ochratoxin A (OTA)-binding aptamer than OTA.
• Pocket mutations altered aptamer binding affinities for L-Arm and norfloxacin.

Conclusions:

• The computational framework effectively identifies potent aptamer binders.
• Aptamer-target interactions are more versatile than previously assumed.
• Findings advance nucleic acid-targeted drug discovery and aptamer specificity tuning.