The CYP-nsSNP Database And Theoretical Study Of Cyp-mediated Drug Metabolism

The cytochrome P450 superfamily (CYP) is a group of heme-containing monooxygenases which perform many necessary functions in the human body. As the major drug-metabolizing enzymes, CYP enzymes are responsible for the metabolism of a large number of drugs. In addition, CYP enzymes are subject to genetic polymorphism resulting in the inter-individual difference in drug-metabolizing ability. Thus, the main focus of recent CYP research includes the CYP-mediated drug metabolism, the substrate specificity of different CYP isoenzymes, the influences of different genetic polymorphisms on function of CYP enzymes and the possible mechanism for changing enzymatic activity of CYP due to mutation of amino acid. Here we carried out four independent experiments focused on the effect of non-synonymous single nucleotide polymorphism (nsSNP) on the enzymatic activity of CYP and the substrate selectivity of different CYP isoenzymes. These studies and their conclusions are briefly described below.1. A database named CYP-nsSNP was constructed through collecting the relevant data from the published references. The CYP-nsSNP is used to organize the available data regarding effect of nsSNPs on function of CYP proteins and to provide the reliable information for theoretical investigation of the role of amino acids in CYP function.2. The effect of a surface mutation F186L on CYP1A2 structure and function was explored using the molecular dynamics simulation and molecular docking as well as other structure-based methods. In this study, the long-range effect of surface mutation was comprehensively investigated from the point of view of protein structure and motions. Additionally, the method of protein motion combined with substrate channel was firstly applied to reveal the relationship between structure and function of CYP protein. Based on results from this study, we can provide a rational explanation for the decrease in enzymatic activity caused by mutation. In addition, we also propose a new mechanism for alosteric regulation of enzyme induced by mutation through changing the access channels and protein conformations.3. The substrate selectivity of different CYP isoenzymes was investigated using the machine learning methods based on the structure of CYP substrates. The genetic algorithm was combined with the artificial neural network and multi-label K nearest neighbour method to construct the single-label multi-class and multi-label multi-class classification models. Compared with the traditional models, two models reflect the more realistic CYP-mediated drugs metabolism in the human body. After appropriate evaluation, both models exhibited more than 80% of predictive accuracy.4. Integrating the information about both protein and compounds, we constructed a structural model specific to CYP1A2 active site using the comparative molecular field analysis. Based on such a model, we can investigate the detailed role of residues lining the CYP1A2 active site in substrate binding. Therefore, such analysis is useful for the rational drug design and enzyme modification by providing the detailed and reliable information about protein-ligand interactions.