Improvement of Site of Metabolism Predictions for CYP3A4 by Using Discriminant Analysis of Compound Preference of CYP3A4 X‐Ray Structural Conformers and Subsequent Docking

Abstract

Metabolism plays a significant role in failure of drugs to carry out their intended action in the body. Drugs and other xenobiotics in the body are mainly biotransformed through oxidation reactions catalyzed by cytochrome P450 enzymes, in particular the CYP3A4 isoform. This enzyme is well known for its very wide substrate specificity and promiscuity. Understanding where in a compounds structure the enzymatic oxidation would take place, i.e. site of metabolism (SOM), is crucial for successful modification of molecules in order to avoid unwanted metabolism. Several in silico methods have been developed for SOM predictions including docking based methods. One of the benefits of docking based methods is that they provide insight into the structure of the drug-enzyme complex. However, crystallographic studies of CYP3A4 have showed that the structure of this enzyme may obtain substantially different conformations depending on the structure of the ligand it is cocrystallized with. Therefore, it is not straight forward to decide which of the different crystal structures of CYP3A4 should be used for SOM prediction when using docking methods. Here we show that simple discriminative models allow selection of CYP3A4 structural conformer to yield better SOM predictions for each individual substrate.

Conformational Plasticity and Structure/Function Relationships in Cytochromes P450

“…The client substrates of CYP3A4 vary significantly in size, and there is evidence for multiple substrates being bound simultaneously in the large active site (111). In one published structure (1TQN, (163)) without bound substrate in the active site, the B-C loop contains only a short distorted helical region, the F helix is considerably shorter than is typical, and the F-G loop contains two helical segments, the F' and G' helices (Fig.…”

RS-Predictor Models Augmented with SMARTCyp Reactivities: Robust Metabolic Regioselectivity Predictions for Nine CYP Isozymes

“…The majority of solutions for 2C9 24–29 and 2D6 24,30–37 are docking-based, while 3A4 models are primarily ligand-based, 27,38,39 with some reactivity/docking hybrids, 24,40,41 and one docking-based solution. 42 The proposed rationale for why reactivity is more relevant for 3A4 regioselectivity prediction is that the binding pocket is relatively large, allowing substrates a high degree of orientational freedom, thereby giving each site equal access to the catalytic heme. 38 This theory may hold for other CYPs as well, as recently disclosed crystal structures of other isozymes indicate that the large binding pocket of 3A4 is not unique — other isozymes also posess binding sites with significant volumes: 1A2(375Å 3 ), 2A6(260Å 3 ), 2B6(no xtal), 2C19(no xtal), 2C8(1438Å 3 ), 2C9(1667Å 3 ), 2D6(540Å 3 ), 2E1(190Å 3 ), 3A4(1386Å 3 ).…”

Predicting Drug Metabolism by Cytochrome P450 2C9: Comparison with the 2D6 and 3A4 Isoforms

“…Hence, the approximation of free rotation, that is, the CYP3A4 active site structure does not determine the location at which a particular substrate gets oxidized, seems to be applicable for most substrates. [11][12][13][14] With crystal structures of most of the main metabolizing CYP enzymes available, structure-based investigations to predict the site of metabolism (SOM) have been performed; examples include CYP1A2, [15,16] CYP3A4, [13,[17][18][19] CYP2D6, [14,[20][21][22] and CYP2C9. [7][8][9] The 2C9 and 2D6 isoforms, on the other hand, seem to be less promiscuous, and to understand the metabolism mediated by these enzymes, the specific interactions between the substrate and residues in the binding cavity must be taken into account.…”

“…[10] Homology models of these enzymes also indicated the importance of charged active site residues in binding substrates. [11][12][13][14] With crystal structures of most of the main metabolizing CYP enzymes available, structure-based investigations to predict the site of metabolism (SOM) have been performed; examples include CYP1A2, [15,16] CYP3A4, [13,[17][18][19] CYP2D6, [14,[20][21][22] and CYP2C9. [23][24][25][26] Although exploiting the knowledge about the properties of the binding cavities should be beneficial, many ligand-based models are still being developed, [9,24,27] and the predictive accuracy of the ligand-based models are often as good as, or even better than structure-based models.…”