Herein, we investigated the scalability of 2DCS to study the RNA-binding capacity of a reasonably large subset of compounds found within the pharmaceutical industry and if the resulting data could be applied to a pre-determined target. To address scalability, we deployed various technologies to probe quickly over 60 million interactions between small molecules from the AstraZeneca compound library (n = 2947) and RNA folds. These studies defined not only the SMIRNAs themselves but also features within the small molecules and the bound RNAs that afford molecular recognition. We then applied our privileged RNA motif-small molecule interactions to enhance VEGFA expression. Upregulation of VEGFA is a promising strategy for management of diseases such as coronary artery disease, a significant societal burden with few therapeutic options.