Computational Screening of Clinical Drug Libraries for Neurofibromin Inhibition: A Molecular Docking and Dynamics Study for Neurofibromatosis Therapy

Introduction: Neurofibromatosis type 1 (NF1) is a genetic disorder characterized by the development of benign tumors due to mutations in the NF1 gene, which encodes the tumor suppressor neurofibromin. This study aimed to identify novel inhibitors of neurofibromin through drug repurposing of clinical trial compounds from the Zinc15 database. Method: Utilizing advanced in silico techniques, we conducted molecular docking via PyRx and molecular dynamics simulations with GROMACS. Among the compounds analyzed, ZINC000261527152 (Tetrodotoxin) emerged as a promising candidate due to its binding affinity to NF1. Tetrodotoxin formed stable conventional and carbon-hydrogen bonds with key residues, including GLU 981, GLY 984, GLN 985, SER 1030, SER 1561, and ASN 1563. Molecular dynamics simulations confirmed the stability of the Tetrodotoxin- NF1 complex, with favorable RMSD, RMSF, radius of gyration (Rg), and solvent- accessible surface area (SASA) values over a 100 ns simulation period. Result: These results suggest that Tetrodotoxin could effectively inhibit neurofibromin, presenting a novel therapeutic approach for neurofibromatosis. However, despite the promising computational findings, further experimental validation through in vitro and in vivo studies is essential to confirm the efficacy and safety of Tetrodotoxin as a treatment for NF1. Conclusion: This research underscores the utility of computational drug repurposing methodologies and their role in accelerating the discovery of novel treatments for genetic disorders, particularly neurofibromatosis, thereby potentially improving patient outcomes and quality of life.