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

The myotonic dystrophy type 1 drug development pipeline: 2022 edition

The beginning of the 20th decade has witnessed an increase in drug development programs for myotonic dystrophy type 1 (DM1). We have collected nearly 20 candidate drugs with accomplished preclinical and clinical phases, updating our previous drug development pipeline review with new entries and relevant milestones for pre-existing candidates. Three interventional first-in-human clinical trials got underway with distinct drug classes, namely AOC 1001 and DYNE-101 nucleic acid-based therapies, and the small molecule pitolisant, which joins the race toward market authorization with other repurposed drugs, including tideglusib, metformin, or mexiletine, already in clinical evaluation. Furthermore, newly disclosed promising preclinical data for several additional nucleic-acid therapeutic candidates and a CRISPR-based approach, as well as the advent into the pipeline of novel therapeutic programs, increase the plausibility of success in the demanding task of providing valid treatments to patients with DM1.

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.

Targeting strategies for modulating pre-mRNA splicing with small molecules: Recent advances

The concept of using small molecules to therapeutically modulate pre-mRNA splicing was validated with the US Food and Drug Administration (FDA) approval of Evrysdi® (risdiplam) in 2020. Since then, efforts have continued unabated toward the discovery of new splicing-modulating drugs. However, the drug development world has evolved in the 10 years since risdiplam precursors were first identified in high-throughput screening (HTS). Now, new mechanistic insights into RNA-processing pathways and regulatory networks afford increasingly feasible targeted approaches. In this review, organized into classes of biological target, we compile and summarize small molecules discovered, devised, and developed since 2020 to alter pre-mRNA splicing.