Factors influencing rates and clearance in P450-mediated reactions: QSARs for substrates of the xenobiotic-metabolizing hepatic microsomal P450s

Designing QSARs for Parameters of High-Throughput Toxicokinetic Models Using Open-Source Descriptors

The intrinsic metabolic clearance rate (Cl_int) and the fraction of the chemical unbound in plasma (f_up) serve as important parameters for high-throughput toxicokinetic (TK) models, but experimental data are limited for many chemicals. Open-source quantitative structure-activity relationship (QSAR) models for both parameters were developed to offer reliable in silico predictions for a diverse set of chemicals regulated under the U.S. law, including pharmaceuticals, pesticides, and industrial chemicals. As a case study to demonstrate their utility, model predictions served as inputs to the TK component of a risk-based prioritization approach based on bioactivity/exposure ratios (BERs), in which a BER < 1 indicates that exposures are predicted to exceed a biological activity threshold. When applied to a subset of the Tox21 screening library (6484 chemicals), we found that the proportion of chemicals with BER <1 was similar using either in silico (1133/6484; 17.5%) or in vitro (148/848; 17.5%) parameters. Further, when considering only the chemicals in the Tox21 set with in vitro data, there was a high concordance of chemicals classified with either BER <1 or >1 using either in silico or in vitro parameters (767/848, 90.4%). Thus, the presented QSARs may be suitable for prioritizing the risk posed by many chemicals for which measured in vitro TK data are lacking.

The utilisation of structural descriptors to predict metabolic constants of xenobiotics in mammals

Quantitative structure-activity relationships (QSARs) were developed to predict the Michaelis-Menten constant (Km) and the maximum reaction rate (Vmax) of xenobiotics metabolised by four enzyme classes in mammalian livers: alcohol dehydrogenase (ADH), aldehyde dehydrogenase (ALDH), flavin-containing monooxygenase (FMO), and cytochrome P450 (CYP). Metabolic constants were gathered from the literature and a genetic algorithm was employed to select at most six predictors from a pool of over 2000 potential molecular descriptors using two-thirds of the xenobiotics in each enzyme class. The resulting multiple linear models were cross-validated using the remaining one-third of the compounds. The explained variances (R(2)adj) of the QSARs were between 50% and 80% and the predictive abilities (R(2)ext) between 50% and 60%, except for the Vmax QSAR of FMO with both R(2)adj and R(2)ext less than 30%. The Vmax values of FMO were independent of substrate chemical structure because the rate-limiting step of its catalytic cycle occurs before compound oxidation. For the other enzymes, Vmax was predominantly determined by functional groups or fragments and electronic properties because of the strong and chemical-specific interactions involved in the metabolic reactions. The most relevant predictors for Km were functional groups or fragments for the enzymes metabolising specific compounds (ADH, ALDH and FMO) and size and shape properties for CYP, likely because of the broad substrate specificity of CYP enzymes. The present study can be helpful to predict the Km and Vmax of four important oxidising enzymes in mammals and better understand the underlying principles of chemical transformation by liver enzymes.

Mechanistically-based QSARs to describe metabolic constants in mammals

Biotransformation is one of the processes which influence the bioaccumulation of chemicals. The enzymatic action of metabolism involves two processes, i.e. the binding of the substrate to the enzyme followed by a catalytic reaction, which are described by the Michaelis-Menten constant (Km) and the maximum rate (Vmax). Here, we developed Quantitative Structure-Activity Relationships (QSARs) for Log(1/Km) and LogVmax for substrates of four enzyme classes. We focused on oxidations catalysed by alcohol dehydrogenase (ADH), aldehyde dehydrogenase (ALDH), flavin-containing monooxygenase (FMO) and cytochrome P450 (CYP) in mammals. The chemicals investigated were xenobiotics, including alcohols, aldehydes, pesticides and drugs. We applied general linear models for this purpose, employing descriptors related to partitioning, geometric characteristics, and electronic properties of the substrates, which can be interpreted mechanistically. The explained variance of the QSARs varied between 20% and 70%, and it was larger for Log(1/Km) than for LogVmax. The increase of 1/Km with compound logP and size suggests that weak interactions are important, e.g. by substrate binding via desolvation processes. The importance of electronic factors for 1/Km was described in relation to the catalytic mechanism of the enzymes. Vmax was particularly influenced by electronic properties, such as dipole moment and energy of the lowest unoccupied molecular orbital. This can be explained by the nature of the catalysis, characterised by the cleavage and formation of covalent or ionic bonds (strong interactions). The present study may be helpful to understand the underlying principles of the chemical specific activity of four important oxidising enzymes.

QSARs for PBPK modelling of environmental contaminants

Physiologically-based pharmacokinetic (PBPK) models are increasingly finding use in risk assessment applications of data-rich compounds. However, it is a challenge to determine the chemical-specific parameters for these models, particularly in time- and resource-limiting situations. In this regard, SARs, QSARs and QPPRs are potentially useful for computing the chemical-specific input parameters of PBPK models. Based on the frequency of occurrence of molecular fragments (CH(3), CH(2), CH, C, C=C, H, benzene ring and H in benzene ring structure) and exposure conditions, the available QSAR-PBPK models facilitate the simulation of tissue and blood concentrations for some inhaled volatile organic chemicals. The application domain of existing QSARs for developing PBPK models is limited, due to lack of relevant data for diverse chemicals and mechanisms. Even though this approach is conceptually applicable to non-volatile and high molecular weight organics as well, it is more challenging to predict the other PBPK model parameters required for modelling the kinetics of these chemicals (particularly tissue diffusion coefficients, association constants for binding and oral absorption rates). As the level of our understanding of the mechanistic basis of toxicokinetic processes improves, QSARs to provide a priori predictions of key chemical-specific PBPK parameters can be developed to expedite the internal dose-based health risk assessments in data-poor situations.

Reduction of aliphatic nitroesters and N-nitramines by Enterobacter cloacae PB2 pentaerythritol tetranitrate reductase: quantitative structure-activity relationships

Enterobacter cloacae PB2 NADPH:pentaerythritol tetranitrate reductase (PETNR) performs the biodegradation of explosive organic nitrate esters via their reductive denitration. In order to understand the enzyme substrate specificity, we have examined the reactions of PETNR with organic nitrates (n = 15) and their nitrogen analogues, N-nitramines (n = 4). The reactions of these compounds with PETNR were accompanied by the release of 1-2 mol of nitrite per mole of compound, but were not accompanied by their redox cycling and superoxide formation. The reduction rate constants (k(cat)/K(m)) of inositol hexanitrate, diglycerol tetranitrate, erythritol tetranitrate, mannitol hexanitrate and xylitol pentanitrate were similar to those of the established PETNR substrates, PETN and glycerol trinitrate, whereas the reactivities of hexahydro-1,3,5-trinitro-1,3,5-triazine and octahydro-1,3,5,7-tetranitro-1,3,5,7-tetrazocine were three orders of magnitude lower. The log k(cat)/K(m) value of the compounds increased with a decrease in the enthalpy of formation of the hydride adducts [DeltaH(f)(R-O-N(OH)O(-)) or DeltaH(f)(R(1),R(2) > N-N(OH)O(-))], and with an increase in their lipophilicity (octanol/water partition coefficient, log P(ow)), and did not depend on their van der Waals' volumes. Hydrophobic organic nitroesters and hydrophilic N-nitramines compete for the same binding site in the reduced enzyme form. The role of the hydrophobic interaction of PETNR with glycerol trinitrate was supported by the positive dependence of glycerol trinitrate reactivity on the solution ionic strength. The discrimination of nitroesters and N-nitramines according to their log P(ow) values seems to be a specific feature of the Old Yellow Enzyme family of flavoenzymes.

Human cytochromes P450 in the metabolism of drugs: new molecular models of enzyme-substrate interactions

The overall predictive ability of molecular modelling, as applied to the cytochrome P450 (CYP) system, is analysed in the light of current developments in a variety of techniques, including X-ray crystallography, molecular biology, enzyme kinetics, molecular mechanics and dynamics, in relation to its relevance to drug metabolism in humans. This review demonstrates that it is possible to generate realistic models for the major human CYPs, which metabolise xenobiotics that compare favourably with crystal structures, and thus may be used to derive substrate binding energies that agree closely with experimental K(m) values obtained from enzyme kinetics.

A combination of 3D-QSAR, docking, local-binding energy (LBE) and GRID study of the species differences in the carcinogenicity of benzene derivatives chemicals

A combination of 3D-QSAR, docking, local-binding energy (LBE) and GRID methods was applied as a tool to study and predict the mechanism of action of 100 carcinogenic benzene derivatives. Two 3D-QSAR models were obtained: (i) model of mouse carcinogenicity on the basis of 100 chemicals (model 1) and (ii) model of the differences in mouse and rat carcinogenicity on the basis of 73 compounds (model 2). 3D-QSAR regression maps indicated the important differences in species carcinogenicity, and the molecular positions associated with them. In order to evaluate the role of P450 metabolic process in carcinogenicity, the following approaches were used. The 3D models of CYP2E1 for mouse and rat were built up. A docking study was applied and the important ligand-protein residues interactions and oxidation positions of the molecules were identified. A new approach for quantitative assessment of metabolism pathways was developed, which enabled us to describe the species differences in CYP2E1 metabolism, and how it can be related to differences in the carcinogenic potential for a subset of compounds. The binding energies of the important substituents (local-binding energy-LBE) were calculated, in order to quantitatively demonstrate the contribution of the substituents in metabolic processes. Furthermore, a computational procedure was used for determining energetically favourable binding sites (GRID examination) of the enzymes. The GRID procedure allowed the identification of some important differences, related to species metabolism in CYP2E1. Comparing GRID, 3D-QSAR maps and LBE results, a similarity was identified, indicating a relationship between P450 metabolic processes and the differences in the carcinogenicity.

Use ofin vitrotransporter assays to understand hepatic and renal disposition of new drug candidates

Hepatic and renal transporters contribute to the uptake, secretion and reabsorption of endogenous compounds, xenobiotics and their metabolites and have been implicated in drug-drug interactions and toxicities. Characterising the renal and hepatic disposition of drug candidates early in development would lead to more rational drug design, as chemotypes with 'ideal' pharmacokinetic characteristics could be identified and further refined. Because transporters are often organ specific, 'custom' transporter panels need to be identified for each major organ and chemotype to be evaluated, and appropriate studies planned. This review outlines the major renal and hepatic transporters and some of the in vitro transporter reagents, assays and processes that can be used to evaluate the renal and hepatic disposition of new chemical entities during drug discovery and development.

Quantitative structure-activity relationships (QSARs) within the cytochrome P450 system: QSARs describing substrate binding, inhibition and induction of P450s

Quantitative structure-activity relationships (QSARs) within substrates, inducers and inhibitors of cytochromes P450 involved in xenobiotic metabolism are reported, together with QSARs associated with induction, inhibition and metabolic rate. The importance of frontier orbitals and shape descriptors, such as planarity (estimated by the area/depth(2) parameter) and rectangularity (estimated by the length/width parameter) is discussed, particularly in the context of the COMPACT system which discriminates between several P450 families associated with the activation and detoxication of xenobiotics. The use of parameters, particularly those derived from homology modelling of mammalian (especially human) P450s that are involved in exogenous metabolism, in generating QSARs for P450 substrates is discussed in the context of explaining differences in the binding affinities of human P450 substrates which are pharmacologically active.

Molecular structural characteristics governing biocatalytic oxidation of PAHs with hemoglobin

Based on some fundamental quantum chemical descriptors computed by PM3 hamiltonian, two quantitative structure-activity relationship (QSAR) models for biocatalytic oxidation specific activity of unmodified and chemically modified hemoglobin in the oxidation of different polycyclic aromatic hydrocarbons (PAHs) in 15% acetonitrile were developed, respectively, using partial least squares analysis (PLS). The cross-validated Q(cum)(2) values for the two optimal QSAR models are 0.785 and 0.747, respectively, indicating a good predictive ability for biocatalytic oxidation specific activity of PAHs. The main factors affecting specific activity of PAHs are most positive net atomic charges on a hydrogen atom (q(H)(+)), largest negative atomic charge on a carbon atom (q(C)(-)), dipole moment (μ), the energy of the highest occupied molecular orbital (E(HOMO)), and (E(LUMO) - E(HOMO))(2). The biocatalytic oxidation specific activity of PAHs with big q(C)(-) and (E(LUMO) - E(HOMO))(2) values tends to be slow. Increasing q(H)(+), μ, and E(HOMO) values of PAHs leads to increase of specific activity.

Quantitative structure–activity relationships (QSARs) for substrates of human cytochromes P450 CYP2 family enzymes

The results of quantitative structure-activity relationship (QSAR) studies on substrates of human CYP2 family enzymes are reported, together with those of a small number of CYP2A6, CYP2C19 and CYP2D6 inhibitors. In general, there are good correlations (R = 0.90-0.99) between binding affinity (based on Km or KD values) and various parameters relating to active site interactions such as hydrogen bonding and pi-pi stacking. There is also evidence for the role of compound lipophilicity (as determined by either log P or log D7.4 values) in overall substrate binding affinity, and this could reflect the desolvation energy involved in substrate interaction within the enzyme active site. It is possible to estimate the substrate binding energy for a given P450 from a combination of energy terms relating to hydrogen bonding, pi-pi stacking, desolvation and loss in rotatable bond energy, which agree closely (R = 0.98) with experimental data based on either Km or KD values. Consequently, it is likely that active site interactions represent the major contributory factors to the overall binding affinities for human CYP2 family substrates and, therefore, their estimation is of potential importance for the development of new chemical entities (NCEs) as this can facilitate an assessment of likely metabolic clearance.

A quantitative structure-activity relationship analysis on a series of alkyl benzenes metabolized by human cytochrome p450 2E1

The results of quantitative structure-activity relationships for eight alkyl benzenes undergoing oxidative metabolism via human CYP2E1 are reported. Molecular orbital calculations via the AM1 method were employed for the generation of electronic structural descriptors against experimentally generated kinetic data for CYP2E1-mediated metabolism. The findings point to the importance of electronic structural properties of the molecules themselves, particularly the role of frontier orbitals, in determining rates of metabolism. Other factors appear to be responsible for the affinity of these substrates for the CYP2E1 enzyme however, such as its lipophilic character. The results are consistent with the interactive molecular modeling of these compounds within the putative active site of human CYP2E1 constructed from the CYP2C5 template, where it was found that pi-pi stacking interactions between aromatic rings are important for the binding of substrates to the CYP2E1 active site, together with contributions from desolvation entropy changes accompanying substrate binding.

P450 structures and oxidative metabolism of xenobiotics

This review focuses on the structural models for cytochrome P450, which are improving our knowledge and understanding of the P450 catalytic cycle, and the way in which substrates bind to the enzyme leading to catalytic conversion and subsequent formation of mono-oxygenated metabolites. Various stages in the P450 reaction cycle have now been investigated using X-ray crystallography and electronic structure calculations, whereas homology modeling of mammalian P450s is currently revealing important aspects of pharmaceutical and other xenobiotic metabolism mediated by P450 involvement. These features are explored in the current review on P450-based catalysis, which emphasizes the importance of structural modeling to our understanding of this enzyme's function. In addition, the results of various quantitative structure-activity relationships (QSAR) analyses on series of chemicals, which are metabolized via P450 enzymes, are presented such that the importance of electronic and other structural factors in explaining variations in rates of metabolism can be appreciated. As an important example of biocatalysis, the P450 system has a major future as an enzyme for use in many biotechnological applications, including biodegradation and bioremediation.

Baseline lipophilicity relationships in human cytochromes P450 associated with drug metabolism

From analyses of human P450 substrates and their physicochemical properties, it is apparent that baseline lipophilicity relationships exist for over 70 substrates of eight drug-metabolizing P450 enzymes from families CYP1, CYP2, and CYP3. Equations of the general form shown below result in all cases investigated thus far: deltaG(bind) = adeltaG(part) + b where a is the slope of the line which can be termed the hydrophobicity factor of the enzyme active site, possibly being related to the extent of hydrophobic amino acid residues lining the heme pocket; b is the intercept on the y axis and can be regarded as the sum of nonhydrophobic interactions between enzyme and substrate; deltaG(bind) is the free energy change for substrate binding to P450, based on the relationship deltaG(bind) = RTlnKm where Km is the Michaelis constant, and deltaG(part) is the free energy change for partitioning between n-octanol and water based on the relationship deltaG(part) = -RTlnP where P is the n-octanol/water partition coefficient. These findings facilitate the analysis of P450 enzyme-substrate binding interactions and provide information about the likely hydrophobic character of human P450 active site regions. This shows that there are common interactions for certain numbers of substrates in each case composed of hydrogen bonding and pi-pi stacking, the extent of which varies from one P450 enzyme to another.