Identification of Pathogenic Missense Mutations of NF1 Using Computational Approaches

Abstract

Neurofibromatosis type 1 (NF1) is a prevalent autosomal dominant disorder caused by mutations in the NF1 gene, leading to multisystem disorders. Given the critical role of cysteine residues in protein stability and function, we aimed to identify key NF1 mutations affecting cysteine residues that significantly contribute to neurofibromatosis pathology. To identify the most critical mutations in the NF1 gene that contribute to the pathology of neurofibromatosis, we employed a sophisticated computational pipeline specifically designed to detect significant mutations affecting the NF1 gene. Our approach involved an exhaustive search of databases such as the Human Gene Mutation Database (HGMD), UniProt, and ClinVar for information on missense mutations associated with NF1. Our search yielded a total of 204 unique cysteine missense mutations. We then employed in silico prediction tools, including PredictSNP, iStable, and Align GVGD, to assess the impact of these mutations. Among the mutations, C379R, R1000C, and C1016Y stood out due to their deleterious effects on the biophysical properties of the neurofibromin protein, significantly destabilizing its structure. These mutations were subjected to further phenotyping analysis using SNPeffect 4.0, which predicted disturbances in the protein’s chaperone binding sites and overall structural stability. Furthermore, to directly visualize the impact of these mutations on protein structure, we utilized AlphaFold3 to simulate both the wild-type and mutant NF1 structures, revealing the significant effects of the R1000C mutation on the protein’s conformation. In conclusion, the identification of these mutations can play a pivotal role in advancing the field of precision medicine and aid in the development of effective drugs for associated diseases.