Background: Phenylketonuria (PKU) is the most prevalent inborn error of metabolism, resulting from a malfunction of the phenylalanine hydroxylase (PAH) enzyme. The diversity and high rate of consanguinity in the Iranian population provide an apt study sample for autosomal recessive disorders.
Methods: In this study, we investigated 154 mutations in the PAH gene reported in Iran using various computational approaches. We predicted the pathogenicity and stability of genetic variants through the use of the American College of Medical Genetics and Genomics (ACMG) criteria, Functional Analysis through Hidden Markov Models (Fathmm), Combined Annotation Dependent Depletion (CADD), Sorting Intolerant From Tolerant (SIFT), Polymorphism Phenotyping version 2 (POLY PHEN 2), Mutation Taster, MUpro, and I-Mutant 2.0. Additionally, we performed an analysis of amino acid conservation using Clustal Omega and Consurf web servers. Molegro Virtual Docker (MVD), an integrated platform, was also utilized to perform protein-ligand docking simulations. This research presents a novel method for predicting pathogenic variants in the Iranome database and examines the pathogenicity of mutations in the PKU gene, enhancing the understanding of the genetic landscape of PKU in Iran.
Results: The results of this study showed that 80.8% of mutations occur in conserved regions, especially the catalytic domain. About half of all reported mutations were missense. This research introduces a novel workflow that predicts the pathogenicity of variants present in the Iranome database. Furthermore, docking studies revealed that this variant exhibits a critical loss of a catalytic site residue within the catalytic domain. Also, the most common genetic test was polymerase chain reaction (PCR) sequencing, which accounts for 71.5% of cases.
Conclusion: This study delineates future directions for functional studies, genetic counseling, and the development of diagnostic tools (e.g., strip assay kit).