Raphael I. Benhamou; Blessy M. Suresh; Yuquan Tong; Wesley G. Cochrane; Valerie Cavett; Simon Vezina-Dawod; Daniel Abegg; Jessica L. Childs-Disney; Alexander Adibekian; Brian M. Paegel; Matthew D. Disney
Proc. Natl. Acad. Sci. USA, 2022, 119(6), e2114971119
https://doi.org/10.1073/pnas.2114971119

Abstract

Nature evolves molecular interaction networks through persistent perturbation and selection, in stark contrast to drug discovery, which evaluates candidates one at a time by screening. Here, nature’s highly parallel ligand-target search paradigm is recapitulated in a screen of a DNA-encoded library (DEL; 73,728 ligands) against a library of RNA structures (4,096 targets). In total, the screen evaluated ∼300 million interactions and identified numerous bona fide ligand–RNA three-dimensional fold target pairs. One of the discovered ligands bound a 5′GAG/3′CCC internal loop that is present in primary microRNA-27a (pri-miR-27a), the oncogenic precursor of microRNA-27a. The DEL-derived pri-miR-27a ligand was cell active, potently and selectively inhibiting pri-miR-27a processing to reprogram gene expression and halt an otherwise invasive phenotype in triple-negative breast cancer cells. By exploiting evolutionary principles at the earliest stages of drug discovery, it is possible to identify high-affinity and selective target–ligand interactions and predict engagements in cells that short circuit disease pathways in preclinical disease models.