Fatemeh Vaghefi1 
, Farzaneh Motallebi1 , Niloufar Moradi1 , Teymoor Khosravi1 , Akram Vahidi1 , Nahid Rezaei1 , Morteza Oladnabi *2
, Farzaneh Motallebi1 , Niloufar Moradi1 , Teymoor Khosravi1 , Akram Vahidi1 , Nahid Rezaei1 , Morteza Oladnabi *2
1- Student Research Committee, Golestan University of Medical Sciences, Gorgan, Iran
2- Gorgan Congenital Malformations Research Center, Jorjani Clinical Sciences Research Institute, Golestan University of Medical Sciences, Gorgan, Iran; Ischemic Disorders Research Center, Golestan University of Medical Sciences, Gorgan, Iran ,oladnabidozin@yahoo.com
2- Gorgan Congenital Malformations Research Center, Jorjani Clinical Sciences Research Institute, Golestan University of Medical Sciences, Gorgan, Iran; Ischemic Disorders Research Center, Golestan University of Medical Sciences, Gorgan, Iran ,
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Discussion
The phenylalanine hydroxylase (PAH) gene encodes phenylalanine hydroxylase, an essential enzyme in the metabolism of phenylalanine that plays a vital role in multiple biochemical pathways, including tyrosine degradation, biogenic amine synthesis, and L-phenylalanine catabolism. This enzyme consists of three domains that regulate its activity; mutations - particularly in the catalytic domain - disrupt enzyme structure and function, thus leading to phenylketonuria (PKU). The catalytic domain is critical for the proper folding and stability of PAH, and mutations in the hotspot exon 6 can significantly reduce enzymatic activity (12). Our bioinformatics analysis with Clustal Omega and Consurf indicated that this domain is highly conserved across species, emphasizing its functional importance. Supporting this, over 80.82% of PAH mutations identified in Iranian PKU patients were found in these conserved regions.
In silico analyses provide valuable insights by predicting the impact of mutations on protein function, offering a rapid and cost-effective alternative to experimental methods (13). This study aimed to conduct an in-silico analysis of the PAH gene mutation profile in Iranian PKU patients. A total of 154 variants from 685 patients were examined, with 31.67% of cases involving consanguineous marriages, highlighting the significance of genetic screening in this population. Polymerase chain reaction (PCR) sequencing was the primary method in 71.5% of cases. Among 76 missense variants analyzed using six prediction programs, 63 were consistently classified as deleterious, indicating a high likelihood of pathogenicity. Heatmap analysis (Figure 6) revealed that most mutations were missense, many classified as pathogenic or likely pathogenic, implying significant potential harm to affected individuals.
Our data strongly suggest that a high proportion of the mutations are deleterious missense variants, predominantly in the catalytic domain, affecting the tetrahydrobiopterin (BH4) cofactor binding site. Key mutations included the addition of three Gly-Leu-Gln amino acids between exons 10 (Yellow region) and 11 (Light blue region), p.Pro 281Leu, p.Arg 261X, and p.Arg 261Gln (14,15). The Iranome database identified 20 missense variants in PAH. Supplementary 2 shows that the variant c.688G>A has the highest number of heterozygotes (13 individuals) and the highest frequency (0.03) in the Kurdish population. This specific mutation (c.688G>A, p.Val 230Ile) was selected for detailed docking analysis because it exhibited the highest frequency in the Kurdish population according to the Iranome database and fulfilled all three pathogenicity criteria in our workflow. Furthermore, previous reports have suggested its potential pathogenic role in Iranian PKU patients. Considering both its relatively high prevalence and predicted deleterious effect on enzyme function, this variant was chosen as a representative model for structural analysis.
This variant met all three criteria established in our pathogenicity workflow. Given the high rate of consanguineous marriages in Iran, we designed the workflow to assess its capability in identifying previously reported pathogenic mutations. Validation with c.688G>A showed accurate identification of this variant’s pathogenicity, consistent with its documented prevalence in Kurdish patients (15-17). This mutation leads to a critical loss of a catalytic site residue within the catalytic domain (Figure 1), resulting in reduced binding affinity for phenylalanine and diminished catalytic activity (18,19).
Among the reported variants in the Iranome database, there are 20 missense variants. As indicated in Supplementary 2, the variant c.688G>A has the highest number of heterozygotes (13 heterozygotes) and the highest frequency (0.03) in the Kurdish population. Notably, c.688G>A meets the three criteria upon which our workflow was designed. Given the high rate of consanguineous marriages in Iran, we designed this workflow to test its efficacy in identifying previously reported mutations that are confirmed to be pathogenic. To validate our algorithm, we examined the mutation c.688G>A and found that our workflow accurately identifies it as pathogenic. According to a study published in 2014, this mutation has been observed in patients from the Kurdish population (18), which aligns with the population in the Iranome database that exhibits the highest frequency. This mutation leads to a critical loss of a catalytic site residue within the catalytic domain (Figure 1), reducing binding affinity with phenylalanine and consequently decreasing catalytic activity (11).
Remarkably, despite these pronounced effects, the difference in the MolDock score between the wild-type and mutant proteins remains imperceptible. This subtle impact can be attributed to the missense mutation involving a single nucleotide alteration. Additionally, hydrogen bonds play a pivotal role in maintaining protein stability (20). To explore this, we assessed the number of hydrogen bonds present in both the mutant and wild-type PAH structures. The mutant structure exhibits a disruption in its intramolecular hydrogen bond network, with fewer hydrogen bonds observed compared to the wild-type. This reduction likely contributes to the overall loss of stability (Table 3). Therefore, the decrease in hydrogen bonds associated with the V230I mutation signifies a compromised protein stability resulting from the substitution of valine with isoleucine at the 230th residue of the PAH protein (21).
As phenylketonuria (PKU) is an autosomal recessive disorder, consanguineous marriages increase the likelihood of children inheriting two copies of a pathogenic variant in the PAH gene, potentially resulting in PKU. If both parents carry such a variant, the risk of their offspring developing the disorder increases due to consanguinity. This underscores the importance of genetic counseling for affected families.
Conclusion
This study provides a comprehensive in silico analysis of PAH gene mutations among Iranian patients with PKU, highlighting the exceptional genetic diversity and frequency of consanguinity within this population. Using integrated computational approaches - including 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 (PolyPhen-2), Mutation Taster, MUpro, and I-Mutant 2.0, alongside conservation analysis with Clustal Omega and Consurf - the pathogenicity and stability of 154 reported PAH variants were systematically evaluated. Our workflow enabled rapid, cost-effective screening and accurate prioritization of potentially deleterious mutations for further functional investigation.
Key findings reveal that 80.8% of PKU-causing mutations cluster in conserved regions, especially the catalytic domain, and that approximately half are missense variants. The rate of consanguineous marriage in the analyzed cohort was high (31.67%), underscoring the need for tailored genetic counseling programs. Docking analyses demonstrated that recurrent variants such as c.688G>A critically impair catalytic residues and destabilize the enzyme’s structure. Notably, the prevalence and impact of this variant were validated against the Iranome database, reinforcing its relevance across multiple ethnic groups.
While in silico approaches offer valuable predictions regarding the molecular and clinical effects of genetic variation, these findings require further confirmation through laboratory-based functional studies to establish direct impacts on phenotype and treatment outcomes. Building upon the compiled catalog of common PAH mutations, the development of rapid diagnostic tools - such as strip assay kits incorporating high-frequency variants like c.688G>A specific to regional populations - can facilitate efficient genetic screening and contribute to precision medicine in PKU care. Ultimately, integration of computational and experimental methods will enable clinicians to prescribe optimal treatment, improve prognoses, and reduce unnecessary interventions, particularly in populations with elevated consanguinity rates (22).
Acknowledgement
We extend our profound gratitude to the Medical Genetics Department at Golestan University of Medical Sciences for their unparalleled technical and scientific guidance. The real-world impact of this research stems directly from the synergistic contributions of all collaborators.
Funding sources
This study was financially supported by Golestan University of Medical Sciences (Grant Number: 113350).
Ethical statement
This study was performed in line with the principles of the Declaration of Helsinki. Approval was granted by the Ethics Committee of Golestan University of Medical Sciences (Code: IR.GOUMS.REC.1401.522).
Conflicts of interest
The authors declare no conflict of interest.
Author contributions
Fatemeh Vaghefi: Methodology, Investigation, Formal analysis, and Writing-Original draft; Farzaneh Motallebi: Methodology, Investigation, Formal analysis, and Writing-Original draft; Niloufar Moradi: Methodology and Writing-Original draft; Teymoor Khosravi: Visualization and Writing; Akram Vahidi: Writing-Review and Editing; Morteza Oladnabi: Conceptualization, Supervision, Writing-Review, Editing, Validation, and Data curation; Nahid Rezaie: Methodology.
Data availability statement
Data sharing is not applicable to this article, as no datasets were generated or analyzed during the current study.
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Introduction
Phenylalanine hydroxylase (PAH) is an enzyme that catalyzes the conversion of phenylalanine to tyrosine. Dysfunction of PAH causes phenylketonuria (PKU), a common hereditary metabolic disorder inherited in an autosomal recessive manner. PKU manifests in three clinical types: Classic PKU (cPKU, 62%), mild PKU (mPKU, 22%), and mild hyperphenylalaninemia (HPA, 16%) (1-3). Tetrahydrobiopterin (BH4) serves as a vital cofactor in this metabolic pathway. Mutations in genes involved in BH4 synthesis, including GTP cyclohydrolase (GTPCH), 6-pyruvoyl-tetrahydropterin synthase (PTPS), dihydropteridine reductase (DHPR), and pterin-4a-carbinolamine dehydratase (PCD), can also lead to PKU (2). Accurate molecular diagnosis is crucial for differentiating PAH gene defects from BH4-related metabolic abnormalities. Early diagnosis and treatment with a low-phenylalanine diet and phenylalanine-free supplements can prevent severe neurological and dermatological complications (4,5).
The PAH gene is located on chromosome 12 (12q22-q24.2), spans approximately 90 kb, and comprises 13 exons. It encodes a 452-amino acid protein (~52 kDa) (6). The severity of PKU correlates with residual enzyme activity, which depends on the mutation type and its impact on protein function. Globally, the incidence of PKU averages about 6.002 per 100,000 births but varies widely by region; for instance, European countries report rates near 1 in 10,000 births, whereas certain Middle Eastern populations, such as Iran, experience higher prevalence due in part to consanguinity and founder effects (2,3,7). In Iran, the PKU prevalence is approximately 1 in 1,000 live births, reflecting these genetic and demographic factors (5).
Despite this relatively high prevalence, studies exploring PAH gene mutations in the ethnically diverse Iranian population - comprising Persians (65%), Azeris (16%), and others (8) - are limited. To address this gap, we performed an in-silico analysis of PAH mutations in Iranian PKU patients. This study aims to characterize the frequency of variants registered in the Iranome database and evaluate their pathogenicity using multiple computational prediction tools and three-dimensional protein structural modeling. Furthermore, we introduce a novel bioinformatics workflow that integrates sequencing data analysis, variant annotation, and protein modeling to improve the accuracy of pathogenic variant prediction in this population. Our findings provide valuable insights into the genetic landscape of PKU in Iran and offer a framework for future research and clinical decision-making.
Methods
Variant identification and selection
We thoroughly searched for phenylalanine hydroxylase (PAH) gene variants in Iranian patients. The Scientific Information Database (SID) and several search engines, including PUBMED, Web of Science, Scopus, Cochrane Library, and Google Scholar, were utilized for this purpose. In both English and Farsi, the keywords "phenylketonuria," "Iran," "PAH gene," and "PKU" were used in the search strategy. Duplicate articles, studies involving non-Iranian patients, and papers lacking genetic testing were excluded from the collected data.
Predicting pathogenicity and stability of variants
Bioinformatics methods, such as the American College of Medical Genetics and Genomics (ACMG) criteria (https://franklin.genoox.com/clinical-db/), Combined Annotation Dependent Depletion (CADD; https://cadd.gs.washington.edu/), Sorting Intolerant From Tolerant (SIFT; https://sift.bii.a-star.edu.sg/), Polymorphism Phenotyping version 2 (PolyPhen-2; http://genetics.bwh.harvard.edu/pph2/), Functional Analysis through Hidden Markov Models (Fathmm; http://fathmm.biocompute.org.uk/), I-Mutant 2.0 (https://sls.cup.edu.in/imutant2/), and MUpro (https://mupro.proteomics.ics.uci.edu/) were used to study how pathogenic genetic changes can affect the stability of proteins in Iranian individuals with phenylketonuria.
Predicting putative pathogenic variants using the Iranome database
We used the Iranome Genomic Database (http://www.iranome.ir/) to search for possible detrimental changes in the PAH gene. Whole exome sequencing (WES) was conducted on 800 healthy individuals from eight major Iranian communities: Persians, Kurds, Lurs, Azeris, Baluchs, Iranian Arabs, Persian Gulf Islanders, and Turkmen. Among the more than 1.5 million variants identified in the database, over 300,000 were found to be unique (9). Six methods were employed to evaluate pathogenicity, including SIFT, PolyPhen-2, Mutation Taster, Mutation Assessor, FATHMM, and FATHMM MKL. The predictions for each variant are available on the Iranome website.
In this study, we developed a comprehensive workflow employing computational methods optimized for the Iranome database to investigate variants in the phenylalanine hydroxylase (PAH) gene associated with phenylketonuria (PKU). The workflow included the following steps:
Phenylalanine hydroxylase (PAH) is an enzyme that catalyzes the conversion of phenylalanine to tyrosine. Dysfunction of PAH causes phenylketonuria (PKU), a common hereditary metabolic disorder inherited in an autosomal recessive manner. PKU manifests in three clinical types: Classic PKU (cPKU, 62%), mild PKU (mPKU, 22%), and mild hyperphenylalaninemia (HPA, 16%) (1-3). Tetrahydrobiopterin (BH4) serves as a vital cofactor in this metabolic pathway. Mutations in genes involved in BH4 synthesis, including GTP cyclohydrolase (GTPCH), 6-pyruvoyl-tetrahydropterin synthase (PTPS), dihydropteridine reductase (DHPR), and pterin-4a-carbinolamine dehydratase (PCD), can also lead to PKU (2). Accurate molecular diagnosis is crucial for differentiating PAH gene defects from BH4-related metabolic abnormalities. Early diagnosis and treatment with a low-phenylalanine diet and phenylalanine-free supplements can prevent severe neurological and dermatological complications (4,5).
The PAH gene is located on chromosome 12 (12q22-q24.2), spans approximately 90 kb, and comprises 13 exons. It encodes a 452-amino acid protein (~52 kDa) (6). The severity of PKU correlates with residual enzyme activity, which depends on the mutation type and its impact on protein function. Globally, the incidence of PKU averages about 6.002 per 100,000 births but varies widely by region; for instance, European countries report rates near 1 in 10,000 births, whereas certain Middle Eastern populations, such as Iran, experience higher prevalence due in part to consanguinity and founder effects (2,3,7). In Iran, the PKU prevalence is approximately 1 in 1,000 live births, reflecting these genetic and demographic factors (5).
Despite this relatively high prevalence, studies exploring PAH gene mutations in the ethnically diverse Iranian population - comprising Persians (65%), Azeris (16%), and others (8) - are limited. To address this gap, we performed an in-silico analysis of PAH mutations in Iranian PKU patients. This study aims to characterize the frequency of variants registered in the Iranome database and evaluate their pathogenicity using multiple computational prediction tools and three-dimensional protein structural modeling. Furthermore, we introduce a novel bioinformatics workflow that integrates sequencing data analysis, variant annotation, and protein modeling to improve the accuracy of pathogenic variant prediction in this population. Our findings provide valuable insights into the genetic landscape of PKU in Iran and offer a framework for future research and clinical decision-making.
Methods
Variant identification and selection
We thoroughly searched for phenylalanine hydroxylase (PAH) gene variants in Iranian patients. The Scientific Information Database (SID) and several search engines, including PUBMED, Web of Science, Scopus, Cochrane Library, and Google Scholar, were utilized for this purpose. In both English and Farsi, the keywords "phenylketonuria," "Iran," "PAH gene," and "PKU" were used in the search strategy. Duplicate articles, studies involving non-Iranian patients, and papers lacking genetic testing were excluded from the collected data.
Predicting pathogenicity and stability of variants
Bioinformatics methods, such as the American College of Medical Genetics and Genomics (ACMG) criteria (https://franklin.genoox.com/clinical-db/), Combined Annotation Dependent Depletion (CADD; https://cadd.gs.washington.edu/), Sorting Intolerant From Tolerant (SIFT; https://sift.bii.a-star.edu.sg/), Polymorphism Phenotyping version 2 (PolyPhen-2; http://genetics.bwh.harvard.edu/pph2/), Functional Analysis through Hidden Markov Models (Fathmm; http://fathmm.biocompute.org.uk/), I-Mutant 2.0 (https://sls.cup.edu.in/imutant2/), and MUpro (https://mupro.proteomics.ics.uci.edu/) were used to study how pathogenic genetic changes can affect the stability of proteins in Iranian individuals with phenylketonuria.
Predicting putative pathogenic variants using the Iranome database
We used the Iranome Genomic Database (http://www.iranome.ir/) to search for possible detrimental changes in the PAH gene. Whole exome sequencing (WES) was conducted on 800 healthy individuals from eight major Iranian communities: Persians, Kurds, Lurs, Azeris, Baluchs, Iranian Arabs, Persian Gulf Islanders, and Turkmen. Among the more than 1.5 million variants identified in the database, over 300,000 were found to be unique (9). Six methods were employed to evaluate pathogenicity, including SIFT, PolyPhen-2, Mutation Taster, Mutation Assessor, FATHMM, and FATHMM MKL. The predictions for each variant are available on the Iranome website.
In this study, we developed a comprehensive workflow employing computational methods optimized for the Iranome database to investigate variants in the phenylalanine hydroxylase (PAH) gene associated with phenylketonuria (PKU). The workflow included the following steps:
- Exclusion of variants: To ensure statistical significance, we excluded variants with fewer than 10 heterozygous occurrences.
- CADD score threshold: Variants scoring below 20 on the CADD scale were eliminated, since this score signifies the potential harmful effects of a variant.
- Predictor consensus: Variants identified as pathogenic by fewer than 3 out of 6 web server predictors were eliminated to enhance the reliability of the findings.
By applying these criteria, we assessed the variants found in the Iranome database to identify those likely to be pathogenic and observable in patients.
Amino acid conservation analysis
A conservation analysis of the PAH protein was performed using two computational tools: The European Bioinformatics Institute (EBI) Clustal Omega Tool and ConSurf (ConSurf Server). PAH amino acid sequences from different species, including Gallus gallus, Macaca mulatta, Oryctolagus cuniculus, Homo sapiens, Bos taurus, Mus musculus, Felis catus, Equus asinus, Rattus norvegicus, and Pongo abelii, were obtained from UniProt (https://www.uniprot.org/). These sequences were uploaded to Clustal Omega to perform multiple sequence alignment, allowing evaluation of the evolutionary conservation of amino acids in the PAH protein across different species. The evolutionary conservation of amino acid and nucleotide residues was subsequently assessed using the ConSurf tool, which provides conservation ratings ranging from 1 (Denoting variable areas). High-scoring exposed residues are regarded as functional, whereas high-scoring buried residues are considered structural.
Molecular docking simulation
The impact of the detected variant on the function of the encoded protein, specifically the mutated form c.688G>A corresponding to V230I in the protein, was evaluated through docking simulations using Molegro Virtual Docker (MVD) version 6.0.1 software. The interaction between the phenylalanine hydroxylase enzyme and its substrate, phenylalanine, was examined. The Moldock scoring algorithm, implemented in MVD software, applies a piecewise linear potential and a re-ranking procedure to identify the most optimal protein-ligand complexes; a higher preference for these complexes is indicated by lower energy scores. For structural analysis, the crystal structure of the active site of the phenylalanine hydroxylase enzyme (PDB: 1PAH) and a modeled structure of the mutated protein were utilized. The mutated protein structure was generated using homology modeling via the SWISS-MODEL online platform (https://swissmodel.expasy.org/interactive). The quality of the homology model was evaluated using the Global Model Quality Estimation (GMQE) score provided by SWISS-MODEL, which ranges from 0 to 1 and predicts the expected accuracy of the modeled structure; higher GMQE scores indicate higher reliability. This metric was used to confirm the suitability of the mutant protein model for subsequent docking simulations.
Results
Variant identification and selection
Initial keyword research conducted across six search engines resulted in the identification of 8,414 manuscripts. After applying the inclusion criteria and removing duplicate studies, it was found that 23 of these papers reported homozygous variants in Iranian patients with phenylketonuria (PKU). We compiled a total of 154 variants from the filtered manuscripts, which included 76 missense mutations, 8 nonsense mutations, 5 silent mutations, 40 splice site mutations, 2 duplications, and 23 indel mutations. A comprehensive list of mutations, classified by marriage type, patient count, and genetic testing, is provided in Supplementary 1. Furthermore, the range of PAH mutations in Iran is graphically depicted in Figure 1.
Pathogenicity and stability of variants
The pathogenicity and stability of all missense variants were predicted using seven different bioinformatic tools. Table 1 displays the results of the pathogenicity and stability analysis of missense mutations. Furthermore, Table 2 describes the documented impacts of splice site, deletion, and duplication mutations on the protein.
Putative pathogenic variants revealed by the Iranome database
By searching for the phenylalanine hydroxylase (PAH) gene in the Iranome database, we were able to identify all variants, including deletions, duplications, splice region, intronic, and single nucleotide polymorphisms (SNPs). A total of 20 missense variants were discovered, with their respective maximum and minimum allele frequencies reported across various populations in Iran. Additionally, information on pathogenicity predictions and the number of heterozygotes can be found in Supplementary 2. After designing and implementing this workflow, we tested the variant c.688G>A to assess whether our criteria and workflow could predict its occurrence in the Kurdish population. The results demonstrated that our criteria functioned effectively, and the workflow successfully predicted that the variant c.688G>A would be observed in this population. This variant has been particularly identified among Kurdish patients, and its presence is supported by a 2019 study that reported a patient with phenylketonuria (PKU) carrying a homozygous mutation of c.688G>A. This prior documentation serves as a strong validation of our predictive criteria and underscores the reliability of our methodology in genetic assessments. The structural consequences of this mutation are illustrated in Figure 2.
Conservation study of amino acids
We performed a multiple sequence alignment of the PAH protein in H. sapiens with other species using Clustal Omega. This alignment allowed us to determine the corresponding positions in the PAH proteins of the ten species relative to those in the human PAH. Our findings, illustrated in Figure 3, reveal that 77.63% (n = 59) of the reported missense variants are conserved across the ten species analyzed. This conservation indicates significant evolutionary stability of these positions, suggesting that these mutations may play a crucial role in maintaining protein function across different organisms. Furthermore, the assessment of PAH amino acids utilizing the Consurf web server corroborated our results from Clustal Omega, reinforcing the reliability of our findings.
These data are visually represented in Figure 4. Additionally, the Consurf grade scores for each amino acid are detailed in Supplementary 3, providing further insights into the conservation of these residues.
Molecular docking findings
Figure 5 illustrates the docking study of both the intact protein and its mutated form (c.688G>A, corresponding to V230I in the protein) with phenylalanine serving as the ligand molecule. Significant involvement of residues SER349, ARG270, and SER350 from the wild-type protein, along with ARG270 and SER349 from the mutated protein, in hydrogen bond interactions with the ligand has been observed (10). The assessment of the ligand's binding affinity to the target protein was determined based on their MolDock scores. A comparative analysis of the results from both protein types is shown in Table 3. The MolDock scores for binding to phenylalanine differed slightly between the mutated and normal PAH proteins. It is noteworthy that the mutated protein showed a lower binding affinity for phenylalanine in comparison to the wild-type protein, leading to disrupted interactions and diminished catalytic activities of the PAH protein (11).
Amino acid conservation analysis
A conservation analysis of the PAH protein was performed using two computational tools: The European Bioinformatics Institute (EBI) Clustal Omega Tool and ConSurf (ConSurf Server). PAH amino acid sequences from different species, including Gallus gallus, Macaca mulatta, Oryctolagus cuniculus, Homo sapiens, Bos taurus, Mus musculus, Felis catus, Equus asinus, Rattus norvegicus, and Pongo abelii, were obtained from UniProt (https://www.uniprot.org/). These sequences were uploaded to Clustal Omega to perform multiple sequence alignment, allowing evaluation of the evolutionary conservation of amino acids in the PAH protein across different species. The evolutionary conservation of amino acid and nucleotide residues was subsequently assessed using the ConSurf tool, which provides conservation ratings ranging from 1 (Denoting variable areas). High-scoring exposed residues are regarded as functional, whereas high-scoring buried residues are considered structural.
Molecular docking simulation
The impact of the detected variant on the function of the encoded protein, specifically the mutated form c.688G>A corresponding to V230I in the protein, was evaluated through docking simulations using Molegro Virtual Docker (MVD) version 6.0.1 software. The interaction between the phenylalanine hydroxylase enzyme and its substrate, phenylalanine, was examined. The Moldock scoring algorithm, implemented in MVD software, applies a piecewise linear potential and a re-ranking procedure to identify the most optimal protein-ligand complexes; a higher preference for these complexes is indicated by lower energy scores. For structural analysis, the crystal structure of the active site of the phenylalanine hydroxylase enzyme (PDB: 1PAH) and a modeled structure of the mutated protein were utilized. The mutated protein structure was generated using homology modeling via the SWISS-MODEL online platform (https://swissmodel.expasy.org/interactive). The quality of the homology model was evaluated using the Global Model Quality Estimation (GMQE) score provided by SWISS-MODEL, which ranges from 0 to 1 and predicts the expected accuracy of the modeled structure; higher GMQE scores indicate higher reliability. This metric was used to confirm the suitability of the mutant protein model for subsequent docking simulations.
Results
Variant identification and selection
Initial keyword research conducted across six search engines resulted in the identification of 8,414 manuscripts. After applying the inclusion criteria and removing duplicate studies, it was found that 23 of these papers reported homozygous variants in Iranian patients with phenylketonuria (PKU). We compiled a total of 154 variants from the filtered manuscripts, which included 76 missense mutations, 8 nonsense mutations, 5 silent mutations, 40 splice site mutations, 2 duplications, and 23 indel mutations. A comprehensive list of mutations, classified by marriage type, patient count, and genetic testing, is provided in Supplementary 1. Furthermore, the range of PAH mutations in Iran is graphically depicted in Figure 1.
Pathogenicity and stability of variants
The pathogenicity and stability of all missense variants were predicted using seven different bioinformatic tools. Table 1 displays the results of the pathogenicity and stability analysis of missense mutations. Furthermore, Table 2 describes the documented impacts of splice site, deletion, and duplication mutations on the protein.
Putative pathogenic variants revealed by the Iranome database
By searching for the phenylalanine hydroxylase (PAH) gene in the Iranome database, we were able to identify all variants, including deletions, duplications, splice region, intronic, and single nucleotide polymorphisms (SNPs). A total of 20 missense variants were discovered, with their respective maximum and minimum allele frequencies reported across various populations in Iran. Additionally, information on pathogenicity predictions and the number of heterozygotes can be found in Supplementary 2. After designing and implementing this workflow, we tested the variant c.688G>A to assess whether our criteria and workflow could predict its occurrence in the Kurdish population. The results demonstrated that our criteria functioned effectively, and the workflow successfully predicted that the variant c.688G>A would be observed in this population. This variant has been particularly identified among Kurdish patients, and its presence is supported by a 2019 study that reported a patient with phenylketonuria (PKU) carrying a homozygous mutation of c.688G>A. This prior documentation serves as a strong validation of our predictive criteria and underscores the reliability of our methodology in genetic assessments. The structural consequences of this mutation are illustrated in Figure 2.
Conservation study of amino acids
We performed a multiple sequence alignment of the PAH protein in H. sapiens with other species using Clustal Omega. This alignment allowed us to determine the corresponding positions in the PAH proteins of the ten species relative to those in the human PAH. Our findings, illustrated in Figure 3, reveal that 77.63% (n = 59) of the reported missense variants are conserved across the ten species analyzed. This conservation indicates significant evolutionary stability of these positions, suggesting that these mutations may play a crucial role in maintaining protein function across different organisms. Furthermore, the assessment of PAH amino acids utilizing the Consurf web server corroborated our results from Clustal Omega, reinforcing the reliability of our findings.
These data are visually represented in Figure 4. Additionally, the Consurf grade scores for each amino acid are detailed in Supplementary 3, providing further insights into the conservation of these residues.
Molecular docking findings
Figure 5 illustrates the docking study of both the intact protein and its mutated form (c.688G>A, corresponding to V230I in the protein) with phenylalanine serving as the ligand molecule. Significant involvement of residues SER349, ARG270, and SER350 from the wild-type protein, along with ARG270 and SER349 from the mutated protein, in hydrogen bond interactions with the ligand has been observed (10). The assessment of the ligand's binding affinity to the target protein was determined based on their MolDock scores. A comparative analysis of the results from both protein types is shown in Table 3. The MolDock scores for binding to phenylalanine differed slightly between the mutated and normal PAH proteins. It is noteworthy that the mutated protein showed a lower binding affinity for phenylalanine in comparison to the wild-type protein, leading to disrupted interactions and diminished catalytic activities of the PAH protein (11).
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Table 1 (Continued)
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Table1 (Continued)
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Table1 (Continued)
.PNG) Table 2. Protein effects of splice site, deletion, and duplication mutations in PAH gene in Iranian PKU patients .PNG) .PNG) |
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Table 2 (Continued)
.PNG) .PNG) Figure 2. Tertiary structure of the c.688G>A (p.Val230Ile) mutation |
.PNG) .PNG) Figure 3. Amino acid conservation study of the PAH protein sequence using Clustal Omega across 10 different species (Green and red indicate conserved and non-conserved variants, respectively) |
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Table 3. The docking prediction results for the mutation in PAH gene using molegro virtual docker software
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Discussion
The phenylalanine hydroxylase (PAH) gene encodes phenylalanine hydroxylase, an essential enzyme in the metabolism of phenylalanine that plays a vital role in multiple biochemical pathways, including tyrosine degradation, biogenic amine synthesis, and L-phenylalanine catabolism. This enzyme consists of three domains that regulate its activity; mutations - particularly in the catalytic domain - disrupt enzyme structure and function, thus leading to phenylketonuria (PKU). The catalytic domain is critical for the proper folding and stability of PAH, and mutations in the hotspot exon 6 can significantly reduce enzymatic activity (12). Our bioinformatics analysis with Clustal Omega and Consurf indicated that this domain is highly conserved across species, emphasizing its functional importance. Supporting this, over 80.82% of PAH mutations identified in Iranian PKU patients were found in these conserved regions.
In silico analyses provide valuable insights by predicting the impact of mutations on protein function, offering a rapid and cost-effective alternative to experimental methods (13). This study aimed to conduct an in-silico analysis of the PAH gene mutation profile in Iranian PKU patients. A total of 154 variants from 685 patients were examined, with 31.67% of cases involving consanguineous marriages, highlighting the significance of genetic screening in this population. Polymerase chain reaction (PCR) sequencing was the primary method in 71.5% of cases. Among 76 missense variants analyzed using six prediction programs, 63 were consistently classified as deleterious, indicating a high likelihood of pathogenicity. Heatmap analysis (Figure 6) revealed that most mutations were missense, many classified as pathogenic or likely pathogenic, implying significant potential harm to affected individuals.
Our data strongly suggest that a high proportion of the mutations are deleterious missense variants, predominantly in the catalytic domain, affecting the tetrahydrobiopterin (BH4) cofactor binding site. Key mutations included the addition of three Gly-Leu-Gln amino acids between exons 10 (Yellow region) and 11 (Light blue region), p.Pro 281Leu, p.Arg 261X, and p.Arg 261Gln (14,15). The Iranome database identified 20 missense variants in PAH. Supplementary 2 shows that the variant c.688G>A has the highest number of heterozygotes (13 individuals) and the highest frequency (0.03) in the Kurdish population. This specific mutation (c.688G>A, p.Val 230Ile) was selected for detailed docking analysis because it exhibited the highest frequency in the Kurdish population according to the Iranome database and fulfilled all three pathogenicity criteria in our workflow. Furthermore, previous reports have suggested its potential pathogenic role in Iranian PKU patients. Considering both its relatively high prevalence and predicted deleterious effect on enzyme function, this variant was chosen as a representative model for structural analysis.
This variant met all three criteria established in our pathogenicity workflow. Given the high rate of consanguineous marriages in Iran, we designed the workflow to assess its capability in identifying previously reported pathogenic mutations. Validation with c.688G>A showed accurate identification of this variant’s pathogenicity, consistent with its documented prevalence in Kurdish patients (15-17). This mutation leads to a critical loss of a catalytic site residue within the catalytic domain (Figure 1), resulting in reduced binding affinity for phenylalanine and diminished catalytic activity (18,19).
Among the reported variants in the Iranome database, there are 20 missense variants. As indicated in Supplementary 2, the variant c.688G>A has the highest number of heterozygotes (13 heterozygotes) and the highest frequency (0.03) in the Kurdish population. Notably, c.688G>A meets the three criteria upon which our workflow was designed. Given the high rate of consanguineous marriages in Iran, we designed this workflow to test its efficacy in identifying previously reported mutations that are confirmed to be pathogenic. To validate our algorithm, we examined the mutation c.688G>A and found that our workflow accurately identifies it as pathogenic. According to a study published in 2014, this mutation has been observed in patients from the Kurdish population (18), which aligns with the population in the Iranome database that exhibits the highest frequency. This mutation leads to a critical loss of a catalytic site residue within the catalytic domain (Figure 1), reducing binding affinity with phenylalanine and consequently decreasing catalytic activity (11).
Remarkably, despite these pronounced effects, the difference in the MolDock score between the wild-type and mutant proteins remains imperceptible. This subtle impact can be attributed to the missense mutation involving a single nucleotide alteration. Additionally, hydrogen bonds play a pivotal role in maintaining protein stability (20). To explore this, we assessed the number of hydrogen bonds present in both the mutant and wild-type PAH structures. The mutant structure exhibits a disruption in its intramolecular hydrogen bond network, with fewer hydrogen bonds observed compared to the wild-type. This reduction likely contributes to the overall loss of stability (Table 3). Therefore, the decrease in hydrogen bonds associated with the V230I mutation signifies a compromised protein stability resulting from the substitution of valine with isoleucine at the 230th residue of the PAH protein (21).
As phenylketonuria (PKU) is an autosomal recessive disorder, consanguineous marriages increase the likelihood of children inheriting two copies of a pathogenic variant in the PAH gene, potentially resulting in PKU. If both parents carry such a variant, the risk of their offspring developing the disorder increases due to consanguinity. This underscores the importance of genetic counseling for affected families.
.PNG) Figure 6. Heatmaps illustrating genetic variations in the PAH gene based on the ClinVar database (a) and the findings of this study (b) |
Conclusion
This study provides a comprehensive in silico analysis of PAH gene mutations among Iranian patients with PKU, highlighting the exceptional genetic diversity and frequency of consanguinity within this population. Using integrated computational approaches - including 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 (PolyPhen-2), Mutation Taster, MUpro, and I-Mutant 2.0, alongside conservation analysis with Clustal Omega and Consurf - the pathogenicity and stability of 154 reported PAH variants were systematically evaluated. Our workflow enabled rapid, cost-effective screening and accurate prioritization of potentially deleterious mutations for further functional investigation.
Key findings reveal that 80.8% of PKU-causing mutations cluster in conserved regions, especially the catalytic domain, and that approximately half are missense variants. The rate of consanguineous marriage in the analyzed cohort was high (31.67%), underscoring the need for tailored genetic counseling programs. Docking analyses demonstrated that recurrent variants such as c.688G>A critically impair catalytic residues and destabilize the enzyme’s structure. Notably, the prevalence and impact of this variant were validated against the Iranome database, reinforcing its relevance across multiple ethnic groups.
While in silico approaches offer valuable predictions regarding the molecular and clinical effects of genetic variation, these findings require further confirmation through laboratory-based functional studies to establish direct impacts on phenotype and treatment outcomes. Building upon the compiled catalog of common PAH mutations, the development of rapid diagnostic tools - such as strip assay kits incorporating high-frequency variants like c.688G>A specific to regional populations - can facilitate efficient genetic screening and contribute to precision medicine in PKU care. Ultimately, integration of computational and experimental methods will enable clinicians to prescribe optimal treatment, improve prognoses, and reduce unnecessary interventions, particularly in populations with elevated consanguinity rates (22).
Acknowledgement
We extend our profound gratitude to the Medical Genetics Department at Golestan University of Medical Sciences for their unparalleled technical and scientific guidance. The real-world impact of this research stems directly from the synergistic contributions of all collaborators.
Funding sources
This study was financially supported by Golestan University of Medical Sciences (Grant Number: 113350).
Ethical statement
This study was performed in line with the principles of the Declaration of Helsinki. Approval was granted by the Ethics Committee of Golestan University of Medical Sciences (Code: IR.GOUMS.REC.1401.522).
Conflicts of interest
The authors declare no conflict of interest.
Author contributions
Fatemeh Vaghefi: Methodology, Investigation, Formal analysis, and Writing-Original draft; Farzaneh Motallebi: Methodology, Investigation, Formal analysis, and Writing-Original draft; Niloufar Moradi: Methodology and Writing-Original draft; Teymoor Khosravi: Visualization and Writing; Akram Vahidi: Writing-Review and Editing; Morteza Oladnabi: Conceptualization, Supervision, Writing-Review, Editing, Validation, and Data curation; Nahid Rezaie: Methodology.
Data availability statement
Data sharing is not applicable to this article, as no datasets were generated or analyzed during the current study.
References
1. Esfahani MS, Vallian S. A comprehensive study of phenylalanine hydroxylase gene mutations in the Iranian phenylketonuria patients. Eur J Med Genet. 2019;62(9):103559. [View at Publisher] [DOI] [PMID] [Google Scholar]
2. Alibakhshi R, Mohammadi A, Salari N, Khamooshian S, Kazeminia M, Moradi K. Spectrum of PAH gene mutations in 1547 phenylketonuria patients from Iran: a comprehensive systematic review. Metab Brain Dis. 2021;36(5):767-80. [View at Publisher] [DOI] [PMID] [Google Scholar]
3. Hillert A, Anikster Y, Belanger-Quintana A, Burlina A, Burton BK, Carducci C, et al. The genetic landscape and epidemiology of phenylketonuria. Am J Hum Genet. 2020;107(2):234-50. [View at Publisher] [DOI] [PMID] [Google Scholar]
4. Jaulent P, Charriere S, Feillet F, Douillard C, Fouilhoux A, Thobois S. Neurological manifestations in adults with phenylketonuria: new cases and review of the literature. J Neurol. 2020;267(2):531-42. [View at Publisher] [DOI] [PMID] [Google Scholar]
5. Jafarzadeh-Esfehani R, Vojdani S, Hashemian S, Mirinezhad M, Pourafshar M, Forouzanfar N, et al. Genetic variants of the phenylalanine hydroxylase gene in patients with phenylketonuria in the northeast of Iran. J Pediatr Endocrinol Metab. 2020;33(3):355-9. [View at Publisher] [DOI] [PMID] [Google Scholar]
6. Nemati H, Yousefi SK, Pourvatan N, Aparviz R, Farzaneh P, Koohpar ZK, et al. Mutation analysis of phenylketonuria in the north of Iran. Gene Reports. 2021;24:101196. [View at Publisher] [DOI] [Google Scholar]
7. Moghadam MR, Shojaei A, Babaei V, Rohani F, Ghazi F. Mutation analysis of phenylalanine hydroxylase gene in Iranian patients with phenylketonuria. Med J Islam Repub Iran. 2018;32(1):21. [View at Publisher] [DOI] [PMID] [Google Scholar]
8. Mehrjoo Z, Fattahi Z, Beheshtian M, Mohseni M, Poustchi H, Ardalani F, et al. Distinct genetic variation and heterogeneity of the Iranian population. PLoS Genet. 2019;15(9):e1008385. [View at Publisher] [DOI] [PMID] [Google Scholar]
9. Fattahi Z, Beheshtian M, Mohseni M, Poustchi H, Sellars E, Nezhadi SH, et al. Iranome: A catalog of genomic variations in the Iranian population. Hum Mutat. 2019;40(11):1968-84. [View at Publisher] [DOI] [PMID] [Google Scholar]
10. Maass A, Scholz J, Moser A. Modeled ligand‐protein complexes elucidate the origin of substrate specificity and provide insight into catalytic mechanisms of phenylalanine hydroxylase and tyrosine hydroxylase. Eur J Biochem. 2003;270(6):1065-75. [View at Publisher] [DOI] [PMID] [Google Scholar]
11. Khorrami M, Mahdavi M, Fakhr F, Kheirollahi M. A novel pathogenic variant in NAGLU (N-Acetyl-Alpha-Glucosaminidase) gene identified by targeted next-generation sequencing followed by in silico analysis. Iran J Child Neurol. 2019;13(4):173-83. [View at Publisher] [PMID] [Google Scholar]
12. Williams RA, Mamotte CD, Burnett JR. Phenylketonuria: an inborn error of phenylalanine metabolism. Clin Biochem Rev. 2008;29(1):31-41. [View at Publisher] [PMID] [Google Scholar]
13. Duarte AJ, Ribeiro D, Moreira L, Amaral O. In silico analysis of missense mutations as a first step in functional studies: Examples from two sphingolipidoses. Int J Mol Sci. 2018;19(11):3409. [View at Publisher] [DOI] [PMID] [Google Scholar]
14. Kumari P, Rameshwari R. In silico mutational analysis to identify the role and pathogenicity of BCL-w missense variants. J Genet Eng Biotechnol. 2022;20(1):120. [View at Publisher] [DOI] [PMID] [Google Scholar]
15. Carluccio C, Fraternali F, Salvatore F, Fornili A, Zagari A. Structural features of the regulatory ACT domain of phenylalanine hydroxylase. PLoS One. 2013;8(11):e79482. [View at Publisher] [DOI] [PMID] [Google Scholar]
16. Cerreto M, Cavaliere P, Carluccio C, Amato F, Zagari A, Daniele A, et al. Natural phenylalanine hydroxylase variants that confer a mild phenotype affect the enzyme's conformational stability and oligomerization equilibrium. Biochim Biophys Acta. 2011;1812(11):1435-45. [View at Publisher] [DOI] [PMID] [Google Scholar]
17. Eiken HG, Knappskog PM, Apold J, Flatmark T. PKU mutation G46S is associated with increased aggregation and degradation of the phenylalanine hydroxylase enzyme. Hum Mutat. 1996;7(3):228-38. [View at Publisher] [DOI] [PMID] [Google Scholar]
18. Alibakhshi R, Moradi K, Mohebbi Z, Ghadiri K. Mutation analysis of PAH gene in patients with PKU in western Iran and its association with polymorphisms: identification of four novel mutations. Metab Brain Dis. 2014;29(1):131-8. [View at Publisher] [DOI] [PMID] [Google Scholar]
19. Jalali H, Zamanfar D, Amirzadegan M, Ghadami F, Mahdavi M, Mahdavi MR. Mutation Analysis of PAH Gene in Phenylketonuria Patients from the North of Iran: Identification of Three Novel Pathogenic Variants. Int J Prev Med. 2024;15:22. [View at Publisher] [DOI] [PMID] [Google Scholar]
20. Lopez A, Havranek B, Papadantonakis GA, Islam SM. In silico screening and molecular dynamics simulation of deleterious PAH mutations responsible for phenylketonuria genetic disorder. Proteins. 2021;89(6):683-96. [View at Publisher] [DOI] [PMID] [Google Scholar]
21. Abdullahi SH, Moin AT, Uzairu A, Umar AB, Ibrahim MT, Usman MT, et al. Molecular docking studies of some benzoxazole and benzothiazole derivatives as VEGFR-2 target inhibitors: in silico design, MD simulation, pharmacokinetics and DFT studies. Intelligent Pharmacy. 2024;2(2):232-50. [View at Publisher] [DOI] [Google Scholar]
22. Sengupta M, Sarkar D, Ganguly K, Sengupta D, Bhaskar S, Ray K. In silico analyses of missense mutations in coagulation factor VIII: identification of severity determinants of haemophilia A. Haemophilia. 2015;21(5):662-9. [View at Publisher] [DOI] [PMID] [Google Scholar]
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