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Identifier 000441002
Title Correlation between CYP2D6 genetic variants and their metabolic activity insight from molecular dynamics simulations
Alternative Title Συσχέτιση των γενετικών παραλλαγών του CYP2D6 με τη μεταβολική τους δραστηριότητα μέσω προσομοιώσεων Μοριακής Δυναμικής
Author Κοτζάμπαση, Δανάη Μαρία
Thesis advisor Ποταμιάς, Γεώργιος
Reviewer Δασκαλάκης, Βαγγέλης
Ηλιόπουλος, Ιωάννης
Abstract Cytochrome P450s enzyme belongs to the superfamily of heme-containing proteins, responsible for metabolizing more than 90% of clinical drugs. One of the most significant enzymes in this family, Cytochrome P450 2D6 (CYP2D6), metabolizes ~25% of the clinically used drugs including crucial and commonly administered drugs such as antidepressants, chemotherapeutics, beta-blockers and opioids. Variations in CYP2D6, a highly polymorphic loci in the genome, could alter its activity influencing the efficacy and toxicity of numerous drugs. More than 100 haplotypes (star alleles) of the drug metabolizing enzyme CYP2D6 have been reported in the Pharmacogene Variation Consortium (PharmVar, www.pharmvar.org), resulting in wide intraindividual variability in drug metabolism activity and changes of the drug plasma concentration. The complete connecting link between the genetic variants and the metabolizer phenotype is still an open and challenging question. Our main objective was to investigate the key factors that determine the metabolizer phenotype by exploiting and appropriately employing molecular dynamics (MD) methods. MD is an elaborate computational method that enables the prediction of the time evolution of atomic positions within interacting systems of molecules. To this end, we have probed the dynamics of numerous CYP2D6 variants, as enzyme models with normal and no function, at all-atom resolution. We concluded that changes in residue b-factors and Dynamical Cross-correlation analysis could be used as markers in the discrimination of the two classes of metabolizing activity. Molecular docking analysis between CYP2D6 variants and BACE1 inhibitor confirmed our observations and highlighted the role of helix I and of K-K’ loop and their relative movement in the activity of the enzyme. Classical MD runs on the CYP2D6 *1 (wild-type) were used for identifying the important residues for the protein conformational space using Markov State Modeling. Based on these residues and using the data from the tICA/MSM analysis, a dataset for each variant has been produced which was then used to build a prediction model for the metabolizer phenotype. This is the first time such a tool has been developed. Results of this work are of great importance for areas like Personalized Medicine, Adverse Drug Reaction (ADR) prediction and drug discovery.
Language English
Subject Cytochrome P450
Drug metabolism
Κυτόχρωμα P450
Μεταβολισμός φαρμάκων
Issue date 2021-07-30
Collection   School/Department--School of Medicine--Department of Medicine--Post-graduate theses
  Type of Work
Permanent Link https://elocus.lib.uoc.gr//dlib/d/6/1/metadata-dlib-1625559221-687912-7290.tkl Bookmark and Share
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