Glutaryl-CoA Dehydrogenase Misfolding in Glutaric Acidemia Type 1

Use of the Novel Site-Directed Enzyme Enhancement Therapy (SEE-Tx) Drug Discovery Platform to Identify Pharmacological Chaperones for Glutaric Acidemia Type 1

Allosteric regulators acting as pharmacological chaperones hold promise for innovative therapeutics since they target noncatalytic sites and stabilize the folded protein without competing with the natural substrate, resulting in a net gain of function. Exogenous allosteric regulators are typically more selective than active site inhibitors and can be more potent than competitive inhibitors when the natural substrate levels are high. To identify novel structure-targeted allosteric regulators (STARs) that bind to and stabilize the mitochondrial enzyme glutaryl-CoA dehydrogenase (GCDH), the computational site-directed enzyme enhancement therapy (SEE-Tx) technology was applied. SEE-Tx is an innovative drug discovery platform with the potential to identify drugs for treating protein misfolding disorders, such as glutaric acidemia type 1 (GA1) disease. Putative allosteric regulators were discovered using structure- and ligand-based virtual screening methods and validated using orthogonal biophysical and biochemical assays. The computational approach presented here could be used to discover allosteric regulators of other protein misfolding disorders.

Compilation of Genotype and Phenotype Data in GCDH-LOVD for Variant Classification and Further Application

Glutaric aciduria type 1 (GA-1) is a rare but treatable autosomal-recessive neurometabolic disorder of lysin metabolism caused by biallelic pathogenic variants in glutaryl-CoA dehydrogenase gene (GCDH) that lead to deficiency of GCDH protein. Without treatment, this enzyme defect causes a neurological phenotype characterized by movement disorder and cognitive impairment. Based on a comprehensive literature search, we established a large dataset of GCDH variants using the Leiden Open Variation Database (LOVD) to summarize the known genotypes and the clinical and biochemical phenotypes associated with GA-1. With these data, we developed a GCDH-specific variation classification framework based on American College of Medical Genetics and Genomics and the Association for Molecular Pathology guidelines. We used this framework to reclassify published variants and to describe their geographic distribution, both of which have practical implications for the molecular genetic diagnosis of GA-1. The freely available GCDH-specific LOVD dataset provides a basis for diagnostic laboratories and researchers to further optimize their knowledge and molecular diagnosis of this rare disease.