Computational study of missense mutations in phenylalanine hydroxylase

Area of Science:

• Biochemistry
• Genetics
• Computational Biology

Background:

• Hyperphenylalaninemia (HPA) is a common inherited metabolic disorder caused by phenylalanine hydroxylase (PAH) gene mutations.
• Mutations in the PAH gene lead to varying phenotypes, from classical phenylketonuria (PKU) to non-PKU HPA.
• Despite being monogenic, PKU genotypes can present diverse in vivo phenotypes, suggesting unknown contributing factors.

Purpose of the Study:

• To computationally analyze the impact of missense mutations in homozygous individuals with HPA.
• To investigate the relationship between PAH gene mutations and their resulting clinical phenotypes.
• To differentiate between non-PKU HPA/mild PKU and classical PKU/mild PKU genotypes based on structural impact.

Main Methods:

• Utilized the BIOPKU database for 34 selected homozygous PAH genotypes.
• Performed in silico analysis and molecular dynamics simulations (3 μs total).
• Employed programs like SNPs3D, Polyphen-2, and SIFT for mutation prediction.

Main Results:

• Successfully distinguished 32 out of 34 mutations into two phenotypic groups (non-PKU HPA/mild PKU vs. classical PKU/mild PKU) using simulations.
• Molecular dynamics simulations revealed the structural impact of missense mutations.
• Ionic strength was identified as a factor that can modulate simulation outcomes.
• SNPs3D, Polyphen-2, and SIFT predictions were insufficient to differentiate mild and severe PKU phenotypes.

Conclusions:

• In silico analysis combined with molecular dynamics simulations is effective in predicting HPA phenotype severity based on PAH gene mutations.
• The structural impact of missense mutations provides insights into genotype-phenotype correlations in HPA.
• Further research is needed to identify factors influencing the variability of PKU phenotypes.