Background: Methyl CpG binding protein 2 (MeCP2) is essential for the normal function of mature neurons. Mutations in the MECP2 gene are the main cause of Rett syndrome (RTT). Gene mutations have been identified throughout the gene and the mutation effect is mainly correlated with its type and location.
Methods: In this study, a series of in silico algorithms were applied for analyzing the functional consequences of 3 novel gene missense mutations (D121A, S359Y, and P403S) and a rarely reported one with suspicious effect (R133H) on RettBASE. Besides, a ROC curve analysis was performed to investigate the critical factors affecting variant pathogenicity.
Results: (1) The ROC curve analysis for a retrieved set of MeCP2 variants showed that physicochemical characters do not significantly affect variant pathogenicity; (2) PREM PDI tool revealed that both D121A and R133H mainly contribute to disease progression via reducing MeCP2 affinity to DNA; (3) GPS v5.0 software indicated that P403S may correlate with altered protein phosphorylation; however, no defective protein interaction has been already documented. (4) The applied computational algorithms failed to explore any informative pathogenic mechanism for the S359Y variant.
Conclusion: The conducted approach might provide an efficient prediction model for the effect of MECP2 variants that are located in MBD and CTD.
Keywords: In silico analysis; MECP2; Missense mutation; Rett syndrome.
© 2022. The Author(s).