Molecular docking simulations and GRID-independent molecular descriptor (GRIND) analysis to probe stereoselective interactions of CYP3A4 inhibitors

Comparative study of the interaction mechanism of astilbin, isoastilbin, and neoastilbin with CYP3A4

The interactions of human CYP3A4 with three selected isomer flavonoids, such as astilbin, isoastilbin and neoastilbin, were clarified using spectral analysis, molecular docking, and molecular dynamics simulation. During binding with the three flavonoids, the intrinsic fluorescence of CYP3A4 was statically quenched in static mode with nonradiative energy conversion. The fluorescence and ultraviolet/visible (UV/vis) data revealed that the three flavonoids had a moderate and stronger binding affinity with CYP3A4 due to the order of the Ka1 and Ka2 values ranging from 104 to 105  L·mol-1 . In addition, astilbin had the highest affinity with CYP3A4, then isoastilbin and neoastilbin, at the three experimental temperatures. Multispectral analysis confirmed that binding of the three flavonoids resulted in clear changes in the secondary structure of CYP3A4. It was found from fluorescence, UV/vis and molecular docking analyses that these three flavonoids strongly bound to CYP3A4 by means of hydrogen bonds and van der Waals forces. The key amino acids around the binding site were also elucidated. Furthermore, the stabilities of the three CYP3A4 complexes were evaluated using molecular dynamics simulation.

Interaction study of engeletin toward cytochrome P450 3A4 and 2D6 by multi-spectroscopy and molecular docking

The inhibitory effects of engeletin on the activities of human cytochrome P450 3A4 and 2D6 (CYP3A4 and CYP2D6) were investigated by enzyme kinetics, multi-spectroscopy and molecular docking. Engeletin was found to strongly inhibit CYP3A4 and CYP2D6, with the IC₅₀ of 1.32 μM and 2.87 μM, respectively. The inhibition modes of engeletin against CYP3A4 and CYP2D6 were a competitive type and a mixed type, respectively. The fluorescence of the two CYPs was quenched statically by engeletin, which was bound to CYP3A4 stronger than to CYP2D6 at the same temperature. Circular dichroism spectroscopy, three-dimensional fluorescence, ultraviolet-visible spectroscopy and synchronous fluorescence confirmed that the conformation and micro-environment of the two CYPs protein were changed after binding with engeletin. Molecular docking, ultraviolet-visible spectroscopy and the fluorescence data revealed that engeletin had strong binding affinity to the two CYPs through hydrogen and van der Waals forces. The findings here suggested that engeletin may cause the herb-drug interactions for its inhibition of CYP3A4 and CYP2D6 activities.

Computational prediction of cytochrome P450 inhibition and induction

Cytochrome P450 (CYP) enzymes play an important role in the phase I metabolism of many xenobiotics. Most drug-drug interactions (DDIs) associated with CYP are caused by either CYP inhibition or induction. The early detection of potential DDIs is highly desirable in the pharmaceutical industry because DDIs can cause serious adverse events, which can lead to poor patient health and drug development failures. Recently, many computational studies predicting CYP inhibition and induction have been reported. The current computational modeling approaches for CYP metabolism are classified as ligand- and structure-based; various techniques, such as quantitative structure-activity relationships, machine learning, docking, and molecular dynamic simulation, are involved in both the approaches. Recently, combining these two approaches have resulted in improvements in the prediction accuracy of DDIs. In this review, we present important, recent developments in the computational prediction of the inhibition of four clinically crucial CYP isoforms (CYP1A2, 2C9, 2D6, and 3A4) and three nuclear receptors (aryl hydrocarbon receptor, constitutive androstane receptor, and pregnane X receptor) involved in the induction of CYP1A2, 2B6, and 3A4, respectively.

Molecular Dynamics Simulation Framework to Probe the Binding Hypothesis of CYP3A4 Inhibitors

The Cytochrome P450 family of heme-containing proteins plays a major role in catalyzing phase I metabolic reactions, and the CYP3A4 subtype is responsible for the metabolism of many currently marketed drugs. Additionally, CYP3A4 has an inherent affinity for a broad spectrum of structurally diverse chemical entities, often leading to drug-drug interactions mediated by the inhibition or induction of the metabolic enzyme. The current study explores the binding of selected highly efficient CYP3A4 inhibitors by docking and molecular dynamics (MD) simulation protocols and their binding free energy calculated using the WaterSwap method. The results indicate the importance of binding pocket residues including Phe57, Arg105, Arg106, Ser119, Arg212, Phe213, Thr309, Ser312, Ala370, Arg372, Glu374, Gly481 and Leu483 for interaction with CYP3A4 inhibitors. The residue-wise decomposition of the binding free energy from the WaterSwap method revealed the importance of binding site residues Arg106 and Arg372 in the stabilization of all the selected CYP3A4-inhibitor complexes. The WaterSwap binding energies were further complemented with the MM(GB/PB)SA results and it was observed that the binding energies calculated by both methods do not differ significantly. Overall, our results could guide towards the use of multiple computational approaches to achieve a better understanding of CYP3A4 inhibition, subsequently leading to the design of highly specific and efficient new chemical entities with suitable ADMETox properties and reduced side effects.

Exploring the Chemical Space of Cytochrome P450 Inhibitors Using Integrated Physicochemical Parameters, Drug Efficiency Metrics and Decision Tree Models

The cytochrome P450s (CYPs) play a central role in the metabolism of various endogenous and exogenous compounds including drugs. CYPs are vulnerable to inhibition and induction which can lead to adverse drug reactions. Therefore, insights into the underlying mechanism of CYP450 inhibition and the estimation of overall CYP inhibitor properties might serve as valuable tools during the early phases of drug discovery. Herein, we present a large data set of inhibitors against five major metabolic CYPs (CYP1A2, CYP2C9, CYP2C19, CYP2D6 and CYP3A4) for the evaluation of important physicochemical properties and ligand efficiency metrics to define property trends across various activity levels (active, efficient and inactive). Decision tree models for CYP inhibition were developed with an accuracy >90% for both the training set and 10-folds cross validation. Overall, molecular weight (MW), hydrogen bond acceptors/donors (HBA/HBD) and lipophilicity (clogP/logPo/w) represent important physicochemical descriptors for CYP450 inhibitors. However, highly efficient CYP inhibitors show mean MW, HBA, HBD and logP values between 294.18–482.40,5.0–8.2,1–7.29 and 1.68–2.57, respectively. Our results might help in optimization of toxicological profiles associated with new chemical entities (NCEs), through a better understanding of inhibitor properties leading to CYP-mediated interactions.