title: Insights into the proline hydroxylase (PHD) family, molecular evolution and its impact on human health.
abstract: PHDs (proline hydroxylases) are a small protein family found in all organisms, considered the central regulator of the molecular hypoxia response due to PHDs being completely inactivated under low oxygen concentration. At physiological oxygen concentration, PHDs drive the degradation of the HIF-1α (hypoxia-inducible factor 1-α), which is responsible for upregulating the expression of genes involved in the cellular response to hypoxia. Hypoxia is a common feature of most tumors, in particular during metastasis development. Indeed, cancer reacts by activating pathways promoting new blood vessel formation and activating strategies aimed to improve survival. In this scenario, the PHD family regulates the activation of HIF-1α and cell-cycle regulation. Several PHD mutations were found in cancer patients, underlining their importance for human health. Here, we propose a Bayesian model able to predict the pathological effect of human PHD mutations and their correlation with cancer outcome. The model was developed through an integrative in silico approach, where data collected from the literature has been coupled with sequence evolution and structural analysis. The model was used to assess 135 human PHD variants. Finally, bioinformatics characterization was used to demonstrate how few amino acid changes are able to explain the functional specialization of PHD family members and their physiological role in human health.
authors.affiliation: Department of Biomedical Sciences, University of Padua, Viale G. Colombo 3, 35121, Padova, Italy.
authors.forename: Giovanni
authors.initials: G
authors.lastname: Minervini
authors.affiliation: Department of Biomedical Sciences, University of Padua, Viale G. Colombo 3, 35121, Padova, Italy.
authors.forename: Federica
authors.initials: F
authors.lastname: Quaglia
authors.affiliation: Department of Biomedical Sciences, University of Padua, Viale G. Colombo 3, 35121, Padova, Italy. Electronic address: silvio.tosatto@unipd.it.
authors.forename: Silvio C E
authors.initials: SC
authors.lastname: Tosatto
mesh_terms: D001499:Bayes Theorem; D019143:Evolution, Molecular; D006801:Humans; D009154:Mutation; D064828:Prolyl Hydroxylases / Q000145:classification / Q000235:genetics*
chemical_list: D064828:Prolyl Hydroxylases
keywords: Bioinformatics; Cancer; Hydroxylation; Proline hydroxylase; Protein structure; Variants