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AptaBLE: A Deep Learning Platform for Aptamer Generation and Analysis

Sawan Patel, Keith Fraser, Dhanush Gandavadi, Abhisek Dwivedy, Xing Wang, Fred Zhangzhi Peng, Pranam Chatterjee, Sherwood Yao

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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.

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