RÉBLOVÁ, Kamila, Petr KULHÁNEK and Lenka FAJKUSOVÁ. Computational study of missense mutations in phenylalanine hydroxylase. Journal of Molecular Modeling. New York: SPRINGER, 2015, vol. 21, No 4, p. "nestránkováno", 10 pp. ISSN 1610-2940. doi:10.1007/s00894-015-2620-6.
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Basic information
Original name Computational study of missense mutations in phenylalanine hydroxylase
Name in Czech Počítačová studie missense mutací fenylalaninehydroxylázy
Authors RÉBLOVÁ, Kamila (203 Czech Republic, guarantor, belonging to the institution), Petr KULHÁNEK (203 Czech Republic, belonging to the institution) and Lenka FAJKUSOVÁ (203 Czech Republic, belonging to the institution).
Edition Journal of Molecular Modeling, New York, SPRINGER, 2015, 1610-2940.
Other information
Original language English
Type of outcome Article in a journal
Field of Study 10600 1.6 Biological sciences
Country of publisher United States of America
Confidentiality degree is not subject to a state or trade secret
Impact factor Impact factor: 1.438
RIV identification code RIV/00216224:14740/15:00083364
Organization unit Central European Institute of Technology
Doi http://dx.doi.org/10.1007/s00894-015-2620-6
UT WoS 000351477800004
Keywords in English mutations; computations; MD simulations; genetic disease;
Tags podil, rivok
Tags International impact, Reviewed
Changed by Changed by: Mgr. Eva Špillingová, učo 110713. Changed: 30. 3. 2016 13:41.
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.
ED1.1.00/02.0068, research and development projectName: CEITEC - central european institute of technology
EE2.3.20.0045, research and development projectName: Podpora profesního růstu a mezinárodní integrace výzkumných týmů v oblasti molekulární medicíny
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