A multidimensional computational exploration of congenital myasthenic syndrome causing mutations in human choline acetyltransferase

• Published in: Journal of cellular biochemistry 2021-08, Vol.122 (8), p.787-800
• Main Authors: Janežič, Matej, Dileep, Kalarickal V., Zhang, Kam Y. J.
• Format: Article
• Language: English
• Subjects: Acetyltransferase; Allosteric properties; Catalytic activity; Choline; choline acetyltransferase; Choline O-acetyltransferase; Computer applications; congenital myasthenic syndrome; Data search; Disruption; essential dynamics; Genotypes; Missense mutation; molecular dynamics; Mutation; mutations; Pathogenicity; Pathogens; Phenotypes; Phosphorylation; Protein structure; Secondary structure; sequence and structure analysis
• ISSN: 0730-2312; 1097-4644
• DOI: 10.1002/jcb.29913

Missense mutations of human choline acetyltransferase (CHAT) are mainly associated with congenital myasthenic syndrome (CMS). To date, several pathogenic mutations have been reported, but due to the rarity and genetic complexity of CMS and difficult genotype–phenotype correlations, the CHAT mutations, and their consequences are underexplored. In this study, we systematically sift through the available genetic data in search of previously unreported pathogenic mutations and use a dynamic in silico model to provide structural explanations for the pathogenicity of the reported deleterious and undetermined variants. Through rigorous multiparameter analyses, we conclude that mutations can affect CHAT through a variety of different mechanisms: by disrupting the secondary structure, by perturbing the P‐loop through long‐range allosteric interactions, by disrupting the domain connecting loop, and by affecting the phosphorylation process. This study provides the first dynamic look at how mutations affect the structure and catalytic activity in CHAT and highlights the need for further genomic research to better understand the pathology of CHAT. Choline acetyltransferase (CHAT) is chiefly associated with congenital myasthenia gravis, but the rareness and genetic complexity of the neuromuscular condition hinder genotype–phenotype correlations. In this study, we systematically sift through the available mutation data in search of novel pathogenic mutations and use a dynamic in silico model to provide structural explanations for the pathogenicity of reported deleterious and undetermined variants. This study represents the first dynamic look at how mutations affect the structure and catalytic activity in CHAT.