RESUMO
During the past decades, there have been continuous attempts in the prediction of metabolism mediated by cytochrome P450s (CYP450s) 3A4, 2D6, and 2C9. However, it has indeed remained a huge challenge to accurately predict the metabolism of xenobiotics mediated by these enzymes. To address this issue, microsomal metabolic reaction system (MMRS)-a novel concept, which integrates information about site of metabolism (SOM) and enzyme-was introduced. By incorporating the use of multiple feature selection (FS) techniques (ChiSquared (CHI), InfoGain (IG), GainRatio (GR), Relief) and hybrid classification procedures (Kstar, Bayes (BN), K-nearest neighbours (IBK), C4.5 decision tree (J48), RandomForest (RF), Support vector machines (SVM), AdaBoostM1, Bagging), metabolism prediction models were established based on metabolism data released by Sheridan et al. Four major biotransformations, including aliphatic C-hydroxylation, aromatic C-hydroxylation, N-dealkylation and O-dealkylation, were involved. For validation, the overall accuracies of all four biotransformations exceeded 0.95. For receiver operating characteristic (ROC) analysis, each of these models gave a significant area under curve (AUC) value >0.98. In addition, an external test was performed based on dataset published previously. As a result, 87.7% of the potential SOMs were correctly identified by our four models. In summary, four MMRS-based models were established, which can be used to predict the metabolism mediated by CYP3A4, 2D6, and 2C9 with high accuracy.
Assuntos
Citocromo P-450 CYP2C9/metabolismo , Citocromo P-450 CYP2D6/metabolismo , Citocromo P-450 CYP3A/metabolismo , Modelos Teóricos , Preparações Farmacêuticas/metabolismo , Área Sob a Curva , Biotransformação , Humanos , Microssomos Hepáticos/enzimologia , Curva ROC , Máquina de Vetores de SuporteRESUMO
Dampness evil is the source of all diseases, which is easy to cause disease and promote aging, while aging could also promote the occurence and development of diseases. In this paper, the relationship between the dampness evil and aging would be discussed, to find the anti-aging active ingredients in traditional Chinese medicine (TCM), and analyze the anti-aging mechanism of dampness eliminating drug. Molecular docking technology was used, with aging-related mammalian target of rapamycin as the docking receptors, and chemical components of Fuling, Sangzhi, Mugua, Yiyiren and Houpo as the docking molecules, to preliminarily screen the anti-aging active ingredients in dampness eliminating drug. Through the comparison with active drugs already on the market (temsirolimus and everolimus), 12 kinds of potential anti-aging active ingredients were found, but their drug gability still needs further study. The docking results showed that various components in the dampness eliminating drug can play anti-aging activities by acting on mammalian target of rapamycin. This result provides a new thought and direction for the method of delaying aging by eliminating dampness.