Computational biology and bioinformatics as tools towards a better understanding of phenylketonuria

Phenylketonuria (PKU) is an autosomal recessive disease that leads to severe mental retardation in humans if left untreated. In this classical inborn error of metabolism, the gene primarily affected is the PAH gene, which results in a protein with reduced enzyme activity that is not sufficient to hydroxylate phenylalanine to tyrosine. Understanding the background of diseases is crucial to medical research, with implications in diagnosis, treatment and drug development. The computational approach has been proven to be very powerful to understand how genetic variations modify the structure of biological macromolecules and to shed light on the structure-function relationships. Thus, in my thesis, to get insight into the structural basis of the PAH defects underlying the disease, I used computational methods as homology modelling, molecular dynamics simulations and molecular docking. Here, my current results contribute to elucidate specific aspects of PAH and PKU related to: (i) the conformational stability of disease-causing PAH mutants, (ii) the structural and dynamical features of the isolated ACT domain of the wild-type enzyme and of six mutants, (iii) the structural basis for the regulation of PAH, through the identification in silico of the putative allosteric L-Phe-binding site.