Macrocyclization of a Ligand Targeting a Toxic RNA Dramatically Improves Potency

Dynamic docking of small molecules targeting RNA CUG repeats causing myotonic dystrophy type 1

Expansion of RNA CUG repeats causes myotonic dystrophy type 1 (DM1). Once transcribed, the expanded CUG repeats strongly attract muscleblind-like 1 (MBNL1) proteins and disturb their functions in cells. Because of its unique structural form, expanded RNA CUG repeats are prospective drug targets, where small molecules can be utilized to target RNA CUG repeats to inhibit MBNL1 binding and ameliorate DM1-associated defects. In this contribution, we developed two physics-based dynamic docking approaches (DynaD and DynaD/Auto) and applied them to nine small molecules known to specifically target RNA CUG repeats. While DynaD uses a distance-based reaction coordinate to study the binding phenomenon, DynaD/Auto combines results of umbrella sampling calculations performed on 1 × 1 UU internal loops and AutoDock calculations to efficiently sample the energy landscape of binding. Predictions are compared with experimental data, displaying a positive correlation with correlation coefficient (R) values of 0.70 and 0.81 for DynaD and DynaD/Auto, respectively. Furthermore, we found that the best correlation was achieved with MM/3D-RISM calculations, highlighting the importance of solvation in binding calculations. Moreover, we detected that DynaD/Auto performed better than DynaD because of the use of prior knowledge about the binding site arising from umbrella sampling calculations. Finally, we developed dendrograms to present how bound states are connected to each other in a binding process. Results are exciting, as DynaD and DynaD/Auto will allow researchers to utilize two novel physics-based and computer-aided drug-design methodologies to perform in silico calculations on drug-like molecules aiming to target complex RNA loops.

Massively Parallel Optimization of the Linker Domain in Small Molecule Dimers Targeting a Toxic r(CUG) Repeat Expansion

RNA contributes to disease pathobiology and is an important therapeutic target. The downstream biology of disease-causing RNAs can be short-circuited with small molecules that recognize structured regions. The discovery and optimization of small molecules interacting with RNA is, however, challenging. Herein, we demonstrate a massively parallel one-bead-one-compound methodology, employed to optimize the linker region of a dimeric compound that binds the toxic r(CUG) repeat expansion [r(CUG)exp] causative of myotonic dystrophy type 1 (DM1). Indeed, affinity selection on a 331,776-member library allowed the discovery of a compound with enhanced potency both in vitro (10-fold) and in DM1-patient-derived myotubes (5-fold). Molecular dynamics simulations revealed additional interactions between the optimized linker and the RNA, resulting in ca. 10 kcal/mol lower binding free energy. The compound was conjugated to a cleavage module, which directly cleaved the transcript harboring the r(CUG)exp and alleviated disease-associated defects.