Publication details

Computational study of missense mutations in phenylalanine hydroxylase

Authors

RÉBLOVÁ Kamila KULHÁNEK Petr FAJKUSOVÁ Lenka

Year of publication 2015
Type Article in Periodical
Magazine / Source Journal of Molecular Modeling
MU Faculty or unit

Central European Institute of Technology

Citation
Web http://download.springer.com/static/pdf/105/art%253A10.1007%252Fs00894-015-2620-6.pdf?originUrl=http%3A%2F%2Flink.springer.com%2Farticle%2F10.1007%2Fs00894-015-2620-6&token2=exp=1441358136~acl=%2Fstatic%2Fpdf%2F105%2Fart%25253A10.1007%25252Fs00894-015-26
Doi http://dx.doi.org/10.1007/s00894-015-2620-6
Field Biochemistry
Keywords mutations; computations; MD simulations; genetic disease;
Attached files
Description Hyperphenylalaninemia (HPA) is one of the most common metabolic disorders. HPA, which is transmitted by an autosomal recessive mode of inheritance, is caused by mutations of the phenylalanine hydroxylase gene. Most mutations are missense and lead to reduced protein stability and/or impaired catalytic function. The impact of such mutations varies, ranging from classical phenylketonuria (PKU), mild PKU, to non-PKU HPA phenotypes. Despite the fact that HPA is a monogenic disease, clinical data show that one PKU genotype can be associated with more in vivo phenotypes, which indicates the role of other (still unknown) factors. To better understand the phenotype–genotype relationships, we analyzed computationally the impact of missense mutations in homozygotes stored in the BIOPKU database. A total of 34 selected homozygous genotypes was divided into two main groups according to their phenotypes: (A) genotypes leading to non-PKU HPA or combined phenotype non-PKU HPA/mild PKU and (B) genotypes leading to classical PKU, mild PKU or combined phenotype mild PKU/classical PKU. Combining in silico analysis and molecular dynamics simulations (in total 3000 ns) we described the structural impact of the mutations, which allowed us to separate 32 out of 34 mutations between groups A and B. Testing the simulation conditions revealed that the outcome of mutant simulations can be modulated by the ionic strength.We also employed programs SNPs3D, Polyphen-2, and SIFT but based on the predictions performed we were not able to discriminate mutations with mild and severe PKU phenotypes.
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