Combined in Silico Prediction Methods, Molecular Dynamic Simulation, and Molecular Docking of FOXG1 Missense Mutations: Effect on FoxG1 Structure and Its Interactions with DNA and Bmi-1 Protein.
J Mol Neurosci
; 72(8): 1695-1705, 2022 Aug.
Article
in En
| MEDLINE
| ID: mdl-35654936
ABSTRACT
FoxG1 encoded by FOXG1 gene is a transcriptional factor interacting with the DNA of targeted genes as well as with several proteins to regulate the forebrain development. Mutations in the FOXG1 gene have been shown to cause a wide spectrum of brain disorders, including the congenital variant of Rett syndrome. In this study, the direct sequencing of FOXG1 gene revealed a novel c.645C > A (F215L) variant in the patient P1 and a de novo known one c.755G > A (G252D) in the patient P2. To investigate the putative impact of FOXG1 missense variants, a computational pipeline by the application of in silico prediction methods, molecular dynamic simulation, and molecular docking approaches was used. Bioinformatics analysis and molecular dynamics simulation have demonstrated that F215L and G252D variants found in the DNA binding domain are highly deleterious mutations that may cause the protein structure destabilization. On the other hand, molecular docking revealed that F215L mutant is likely to have a great impact on destabilizing the protein structure and the disruption of the Bmi-1 binding site quite significantly. Regarding G252D mutation, it seems to abolish the ability of FoxG1 to bind DNA target, affecting the transcriptional regulation of targeted genes. Our study highlights the usefulness of combined computational approaches, molecular dynamic simulation, and molecular docking for a better understanding of the dysfunctional effects of FOXG1 missense mutations and their role in the etiopathogenesis as well as in the genotype-phenotype correlation.
Key words
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Main subject:
Mutation, Missense
/
Molecular Dynamics Simulation
Type of study:
Prognostic_studies
/
Risk_factors_studies
Language:
En
Journal:
J Mol Neurosci
Journal subject:
BIOLOGIA MOLECULAR
/
NEUROLOGIA
Year:
2022
Document type:
Article
Affiliation country:
Túnez