AptaBLE: A Deep Learning Platform for Aptamer Generation and Analysis
Abstract
Abstract Aptamers are single-stranded oligonucleotides that bind molecular targets with high affinity and specificity. However, their discovery remains time-consuming, expensive, and susceptible to experimental biases. Here we present AptaBLE, a deep learning framework for predicting aptamer-protein binding. Additionally, we demonstrate two de novo generation methods that produce novel aptamers with desired specificity profiles and K d ’s as low as 31 nM to-date. AptaBLE represents a significant advance towards therapeutic and diagnostic aptamer development.
Fields of Study & Subjects
Advanced biosensing and bioanalysis techniques
RNA and protein synthesis mechanisms
Monoclonal and Polyclonal Antibodies Research
Publication details
- Journal / source
- bioRxiv (Cold Spring Harbor Laboratory)
- Publisher
- openRxiv
- Publication date
- 7 January 2026
- Document type
- Preprint