ArticleMetabolic brain disease2018
Computational insights of K1444N substitution in GAP-related domain of NF1 gene associated with neurofibromatosis type 1 disease: a molecular modeling and dynamics approach.
Article in Metabolic brain disease, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
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7 citing papers in PubMed, 1 synthesis or guideline pooled it, 27 citations in OpenAlex.
- Deciphering the Role of Filamin B Calponin-Homology Domain in Causing the Larsen Syndrome, Boomerang Dysplasia, and Atelosteogenesis Type I Spectrum Disorders via a Computational Approach.Molecules (Basel, Switzerland) · 2020Pooled it
- Identification and structural characterization of a pathogenic ARSA missense variant in two consanguineous families from Jammu and Kashmir (India) with late infantile metachromatic leukodystrophy.Molecular biology reports · 2023Article
- Exome sequence analysis of rare frequency variants in Late-Onset Alzheimer Disease.Metabolic brain disease · 2023Article
- Investigating the structural impacts of a novel missense variant identified with whole exome sequencing in an Egyptian patient with propionic acidemia.Molecular genetics and metabolism reports · 2020Article
- Article
- Impact of missense mutations in survival motor neuron protein (SMN1) leading to Spinal Muscular Atrophy (SMA): A computational approach.Metabolic brain disease · 2018Article
- Computational modelling approaches as a potential platform to understand the molecular genetics association between Parkinson's and Gaucher diseases.Metabolic brain disease · 2018Article
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Authors and funding
5 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The NF1 gene encodes for neurofibromin protein, which is ubiquitously expressed, but most highly in the central nervous system. Non-synonymous SNPs (nsSNPs) in the NF1 gene were found to be associated with Neurofibromatosis Type 1 disease, which is characterized by the growth of tumors along nerves in the skin, brain, and other parts of the body. In this study, we used several in silico predictions tools to analyze 16 nsSNPs in the RAS-GAP domain of neurofibromin, the K1444N (K1423N) mutation was predicted as the most pathogenic. The comparative molecular dynamic simulation (MDS; 50 ns) between the wild type and the K1444N (K1423N) mutant suggested a significant change in the electrostatic potential. In addition, the RMSD, RMSF, Rg, hydrogen bonds, and PCA analysis confirmed the loss of flexibility and increase in compactness of the mutant protein. Further, SASA analysis revealed exchange between hydrophobic and hydrophilic residues from the core of the RAS-GAP domain to the surface of the mutant domain, consistent with the secondary structure analysis that showed significant alteration in the mutant protein conformation. Our data concludes that the K1444N (K1423N) mutant lead to increasing the rigidity and compactness of the protein. This study provides evidence of the benefits of the computational tools in predicting the pathogenicity of genetic mutations and suggests the application of MDS and different in silico prediction tools for variant assessment and classification in genetic clinics.
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