APDB: A Large-Scale Repository of Predicted 2D and 3D Aptamer Structures

Abstract

RNA aptamers are short, single-stranded oligonucleotides capable of folding into specific three-dimensional structures to bind diverse molecular targets with high affinity and specificity. In this study, we present a comprehensive computational analysis of a curated data set of over 150,000 RNA aptamers annotated with sequences, predicted secondary structures, molecular features, and minimum free energy (MFE) values. A total of 161 molecular descriptors were extracted, including pairing ratios, stem density, sequence complexity, and motif composition. Dimensionality reduction using Principal Component Analysis (PCA) and t-distributed Stochastic Neighbor Embedding (t-SNE) revealed distinct clustering patterns driven by MFE, GC/AU pairing composition, and secondary structure complexity. PCA indicated that aptamers with high AU content tend to occupy distinct structural space, while t-SNE highlighted concentrated regions of high GC pairing and stem density. A 3D surface plot of GC pairing, AU pairing, and MFE further demonstrated a nonlinear landscape, with folding stability changing in a bumpy, hill-like pattern as pairing ratios varied. These findings provide insights into how base-pairing composition influences aptamer folding stability and offer a framework for rational design. The resulting Aptamer Database (APDB) integrates these analyses into an interactive, scalable platform to support research in biosensing, therapeutics, and computational aptamer design (https://boron.ru.ac.za/database).