Computational Design of Novel CD117-Specific RNA Aptamers for GBM Therapy

Overview

Glioblastoma multiforme (GBM), an aggressive brain tumor, is the deadliest human cancer with a median survival of 3-4 months without treatment and 12-15 months even with surgery and chemoradiotherapy. Aptamers are an emerging class of single-stranded DNA/RNA drugs that outweigh conventional cancer treatments due to their minimal toxicity to healthy cells, reduced risk of adverse immune responses like anaphylaxis, and effective blood brain barrier (BBB) permeability and entry into the brain. Using bioinformatics, this project designed novel RNA aptamers that inactivate CD117, a GBM-causative membrane protein, by creating novel mutations in previously discovered aptamers to enhance their binding. Molecular docking was used to evaluate the binding strength of four previously identified CD117-targeting aptamers (V15, V5, W3, and H5/V36), that directly correlates with their efficacy as CD117 inhibitors. V15 was revealed to have the highest binding affinity, indicated by its low binding energy (-300.65 kcal/mol), suggesting it best inactivates CD117 receptor function. Five novel mutants (M1-M5) of V15 were then created via in-silico mutagenesis and subjected to molecular docking, and it was revealed that two of these, M1 (-304.99 kcal/mol) and M3 (-355.96 kcal/mol) bound even more strongly to CD117. Analysis with molecular dynamics showed that M3 exhibited lower RMSD and Rg fluctuations (RMSD: 0.021 nm; Rg: 0.064 nm) than M1 (RMSD: 0.092 nm; Rg: 0.081 nm), which indicates M3 forms a more structurally stable complex with CD117, optimal for its inactivation. Additional molecular docking assays with M3 and target proteins revealed M3 effectively binds to BBB proteins that increase permeability, indicating it can successfully enter the brain. Yet, it also binds strongly to ribonuclease T2, a hydrolytic RNA-degrading enzyme, indicating high degradation risks. Overall, this study presents M3 as a promising treatment for GBM though structural optimizations are needed to minimize ribonuclease-mediated degradation before conducting laboratory assays and clinical testing.