49 research outputs found

    Computer modeling of dapsone-mediated heteroactivation of flurbiprofen metabolism by CYP2C9

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    The occurrence of atypical kinetics in cytochrome P450 reactions can confound in vitro determinations of a drug\u27s kinetic parameters. During drug development, inaccurate kinetic parameter estimates can lead to incorrect decisions about a lead compound\u27s potential for success. It has become widely accepted that in certain CYP subfamilies more than one molecule can occupy the active site simultaneously, in some cases resulting in enhanced substrate turnover (heteroactivation). However, the specific mechanism(s) by which dual-compound binding results in heteroactivation remain unclear. It is known that orientation of the substrate in the active site, as dictated by interactions with active site residues, plays a large role in metabolic outcome. Effector compounds have been shown in vitro to alter substrate position in the active site. Here, data obtained via in silico methods including docking, molecular dynamics, semi-empirical and ab initio quantum mechanics indicate that direct interaction between effector and substrate can play a role in stabilizing the substrate in an alternative conformation conducive to oxidation. In this study a high-throughput screening computer model of heteroactivation of flurbiprofen metabolism by CYP2C9 has been developed for the purpose of elucidating key interactions between substrate, effector, and enzyme responsible for heteroactivation in this system, as well as to predict as yet unknown activators

    Review of QSAR Models and Software Tools for predicting Biokinetic Properties

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    In the assessment of industrial chemicals, cosmetic ingredients, and active substances in pesticides and biocides, metabolites and degradates are rarely tested for their toxicologcal effects in mammals. In the interests of animal welfare and cost-effectiveness, alternatives to animal testing are needed in the evaluation of these types of chemicals. In this report we review the current status of various types of in silico estimation methods for Absorption, Distribution, Metabolism and Excretion (ADME) properties, which are often important in discriminating between the toxicological profiles of parent compounds and their metabolites/degradation products. The review was performed in a broad sense, with emphasis on QSARs and rule-based approaches and their applicability to estimation of oral bioavailability, human intestinal absorption, blood-brain barrier penetration, plasma protein binding, metabolism and. This revealed a vast and rapidly growing literature and a range of software tools. While it is difficult to give firm conclusions on the applicability of such tools, it is clear that many have been developed with pharmaceutical applications in mind, and as such may not be applicable to other types of chemicals (this would require further research investigation). On the other hand, a range of predictive methodologies have been explored and found promising, so there is merit in pursuing their applicability in the assessment of other types of chemicals and products. Many of the software tools are not transparent in terms of their predictive algorithms or underlying datasets. However, the literature identifies a set of commonly used descriptors that have been found useful in ADME prediction, so further research and model development activities could be based on such studies.JRC.DG.I.6-Systems toxicolog

    Computational prediction of metabolism: sites, products, SAR, P450 enzyme dynamics, and mechanisms.

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    Metabolism of xenobiotics remains a central challenge for the discovery and development of drugs, cosmetics, nutritional supplements, and agrochemicals. Metabolic transformations are frequently related to the incidence of toxic effects that may result from the emergence of reactive species, the systemic accumulation of metabolites, or by induction of metabolic pathways. Experimental investigation of the metabolism of small organic molecules is particularly resource demanding; hence, computational methods are of considerable interest to complement experimental approaches. This review provides a broad overview of structure- and ligand-based computational methods for the prediction of xenobiotic metabolism. Current computational approaches to address xenobiotic metabolism are discussed from three major perspectives: (i) prediction of sites of metabolism (SOMs), (ii) elucidation of potential metabolites and their chemical structures, and (iii) prediction of direct and indirect effects of xenobiotics on metabolizing enzymes, where the focus is on the cytochrome P450 (CYP) superfamily of enzymes, the cardinal xenobiotics metabolizing enzymes. For each of these domains, a variety of approaches and their applications are systematically reviewed, including expert systems, data mining approaches, quantitative structure-activity relationships (QSARs), and machine learning-based methods, pharmacophore-based algorithms, shape-focused techniques, molecular interaction fields (MIFs), reactivity-focused techniques, protein-ligand docking, molecular dynamics (MD) simulations, and combinations of methods. Predictive metabolism is a developing area, and there is still enormous potential for improvement. However, it is clear that the combination of rapidly increasing amounts of available ligand- and structure-related experimental data (in particular, quantitative data) with novel and diverse simulation and modeling approaches is accelerating the development of effective tools for prediction of in vivo metabolism, which is reflected by the diverse and comprehensive data sources and methods for metabolism prediction reviewed here. This review attempts to survey the range and scope of computational methods applied to metabolism prediction and also to compare and contrast their applicability and performance.JK, MJW, JT, PJB, AB and RCG thank Unilever for funding

    Minireview PHARMACOPHORE AND THREE-DIMENSIONAL QUANTITATIVE STRUCTURE ACTIVITY RELATIONSHIP METHODS FOR MODELING CYTOCHROME P450 ACTIVE SITES

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    This paper is available online at http://dmd.aspetjournals.org ABSTRACT: Structure activity relationships (SAR), three-dimensional structure activity relationships (3D-QSAR), and pharmacophores represent useful tools in understanding cytochrome P450 (CYP) active sites in the absence of crystal structures for these human enzymes. These approaches have developed over the last 30 years such that they are now being applied in numerous industrial and academic laboratories solely for this purpose. Such computational approaches have helped in understanding substrate and inhibitor binding to the major human CYPs 1A2, 2B6, 2C9, 2D6, 3A4 as well as other CYPs and additionally complement homology models for these enzymes. Similarly, these approaches may assist in our understanding of CYP induction. This review describes in detail the development of pharmacophores and 3D-QSAR techniques, which are now being more widely used for modeling CYPs; the review will also describe how such approaches are likely to further impact our active site knowledge of these omnipresent and important enzymes. By the end of the 1990s, several reviews had characterized the active site details and physicochemical properties of substrates for the major cytochrome P450 (CYP 1 ) enzymes. These reviews had been gathered from analysis of physicochemical data 1 Abbreviations used are: CYP or P450, cytochrome P450; CoMFA, comparative molecular field analysis; GOLPE, generating optimal linear PLS estimations; PLS, partial least squares; 3D-QSAR, three-dimensional quantitative structure-activity relationship; MS-WHIM, molecular surface weighted holistic invariant molecular. DMD 29:936-944, 2001 Printed in U.S.A. 936 intends to give an overview of the pharmacophore and 3D-QSAR models that have been used to describe P450s and indicate their varying degrees of success. 3D-QSAR and Pharmacophores The development of computational tools has paralleled that of in vitro approaches to understanding and characterizing CYPs. One of the first visual 3D-QSAR computational approaches was comparative molecular field analysis (CoMFA) Until recently, few CYP binding or active site models had been generated using enzyme kinetic data, and these focused primarily on inhibition. Now, however, a considerable number of CYP pharmacophores have appeared in the literature, which presents us with the opportunity to review what is known about several CYPs based on such computational analyses. CYP Models CYP1A2. CYP1A2 is an inducible member of the CYP superfamily, which can be inhibited by some selective serotonin reuptake inhibitors With regard to predicting substrates for CYP1A2, one study has suggested that they are generally neutral or protonated and that they possess a total interaction energy greater than ÏȘ40 kcal/mol and a molecular volume lower than 200 Å 3 CYP2A6. To date there has been no published CYP2A6 QSAR; however, the related mouse form, CYP2A5, has been studied. One group analyzed substrate requirements using a graphical method and concluded that bicyclic ring systems with an electron-rich moiety were essential for the 11 molecules analyzed CYP2B6. Many examples of xenobiotics metabolized in part by CYP2B6 have been identified and described in more detail This challenge was answered by The first quantitative QSAR for CYP2C9 was published in 1996 This model was validated by testing 14 new compounds that had K i values ranging from 0.1 to 48 M (Rao et al., 2000). While the initial training set contained mostly coumarin-containing compounds, this validation set contained mostly sulfonamides. Interestingly, the initial model predicted the affinity of the validation set reasonably well, predicting 13 of the 14 compounds within 1 log residual. Finally, when these compounds where included in the training set, the pharmacophore remained essentially the same. In separate experiments, conducted at the same time as the validation study described above, pharmacophore and PLS predictive models where constructed using Catalyst and PLS MS-WHIM, respectively To gain confidence in the pharmacophores generated for CYP2C9, an attempt was made to determine the specific amino acid residues that might be involved in establishing the pharmacophore. Initial docking of the 9(R)-11(S)-cyclocoumarol and visualizing the CoMFA field in a CYP2C9 homology model indicated that two phenylalanine residues, Phe 110 EKINS ET AL CYP2C19. One group has focused on obtaining substrate structure activity relationships for the polymorphic CYP2C19 using inhibitors of omeprazole 5-hydroxylation (Lock et al., 1998a,b). Using mainly benzodiazepines which are N-dealkylated and 3-hydroxylated, it was suggested that these sites and the carbonyl group were important for inhibition. Electron-withdrawing groups were found to further decrease inhibition. As yet, the data for the 14 compounds used in these two studies have not been used to produce a published 3D-QSAR. CYP2D6. Human CYP2D6 is a polymorphic member of the CYP superfamily and is absent in 5 to 9% of the Caucasian population as a result of a recessive inheritance of gene mutations The first substrate models were manual alignments based on substrates containing a basic nitrogen atom at either 5 Å Another small-molecule model for CYP2D6 was derived by The actual positions of the heme moiety and the I-helix containing Asp 301 [derived from a protein homology model of CYP2D6 Recently, a combined pharmacophore and homology model for CYP2D6 has been derived (de Groot et al., 1999a,b). This model consists of a set of two pharmacophores (one for O-dealkylation and oxidation reactions and a second one for N-dealkylation reactions catalyzed by CYP2D6) embedded in a protein homology model based on bacterial CYP crystal structures (de Groot et al., 1999a,b). This model for the first time combines the strengths of pharmacophore models (atom-atom overlap and reproducible starting points) and homology models (steric interactions and the possibility to identify amino acids involved in binding). This model correctly predicted the metabolism of a wide variety of compounds (de Groot et al., 1999a,b). An inhibitor model for CYP2D6 has also been derived. The template of this model was derived by fitting six strong reversible inhibitors of CYP2D6 onto each other . The basic nitrogen atoms were superimposed and the aromatic planes of these inhibitors were fitted coplanar. Consecutively, other inhibitors, such as derivatives of ajmalicine and quinidine, were fitted onto the derived template. The derived preliminary pharmacophore model consisted of a tertiary nitrogen atom (protonated at physiological pH) and a flat hydrophobic region. There also appeared to be two regions in which functional groups with lone pairs were allowed. In one of these regions, these groups caused enhanced inhibitory potency, which was not the case in yet another region . The overall criteria derived for this inhibitor-based small-molecule model were very similar to the criteria for the proposed substrate models of CYP2D6 P450 PHARMACOPHORE AND QSAR MODELS A set of 3D/4D-QSAR pharmacophore models has also been created for competitive inhibitors of CYP2D6 in a manner similar to that described for CYP2B6 and CYP2C9 using Catalyst CYP2E1. CYP2E1 is involved in the metabolism of many toxic and carcinogenic molecules such as low molecular weight solvents and anesthetics. Early on, it was suggested that the active site was restricted due to the limited size of known substrates. A graphical model of the active site topology was derived from reactions of human CYP2E1 with phenyldiazene, 2-naphthyl, and p-biphenylhydrazine. This work indicated that the active site was open above the pyrrole rings A and D of the heme for a height of 10 Å CYP3A4. Smith et al. have described in detail the CYP3A4 active site characteristics (as well as those of the other major mammalian CYPs) based on homology models built using soluble bacterial CYP structures as a template More recently, a pharmacophore for inhibitors of CYP3A4-mediated midazolam 1Ј-hydroxylase was developed that consisted of four features necessary for the inhibition of CYP3A4 To evaluate these 3D-QSAR models, the activity of molecules excluded from the training set was predicted and then compared with those observed by means of a 1 log residual. Eight molecules were selected from the literature with K i (apparent) values. Both of the CYP3A4 K i (apparent) Catalyst models predicted the K i values similarly. Seven of eight best fit predictions were within 1 log unit residual, for both models, and the correct rank ordering of three protease inhibitors was observed Using the same commercially available software, a Catalyst hypothesis for 38 CYP3A4 substrates was generated using literature K m data Analyses of the likely features of activators of CYP3A4 have also been undertaken, as three substrates (carbamazepine, nifedipine, and testosterone) within the 38-molecule training set used in the CYP3A4 pharmacophore were known CYP3A4 autoactivators. A common features analysis of these molecules using the HipHop function within Catalyst generated a pharmacophore illustrating three hydrophobic areas and one hydrogen bond acceptor. The hydrophobic areas were located 4.4 to 7.6 Å from the hydrogen bond acceptor feature, and the sites of metabolism were colocated. Therefore, hydrophobic interactions with the CYP3A4 active site may be more important than hydrogen bonding for these same CYP3A4 substrates CYP19 (Aromatase). The importance of CYPs that metabolize endogenous substrates can be demonstrated by aromatase, which catalyzes the metabolism of androstenedione to estrone, 16␣-hy- EKINS ET AL droxyandrostenedione to estriol, and testosterone to estradiol via the aromatization of the A ring and the removal of the C19 methyl group CYP51 (14␣-Demethylase)

    Molecular simulations on proteins of biomedical interest : A. Ligand-protein hydration B. Cytochrome P450 2D6 and 2C9 C. Myelin associated glycoprotein (MAG)

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    TOPIC 1: Water molecules mediating polar interactions in ligand–protein complexes contribute to both binding affinity and specificity. To account for such water molecules in computer-aided drug discovery, we performed an extensive search in the Cambridge Structural Database (CSD) to identify the geometrical criteria defining interactions of water molecules with ligand and protein. In addition, ab initio calculations were used to derive the propensity of ligand hydration. Based on these information we developed an algorithm (AcquaAlta) to reproduce water molecules bridging polar interactions between ligand and protein moieties. This approach was validated using 20 crystal structures and yielded a match of 76% between experimental and calculated water positions. The solvation algorithm was then applied to the docking of oligopeptides to the periplasmic oligopeptide binding protein A (OppA), supported by a pharmacophore-based alignment tool. TOPIC 2: Drug metabolism, toxicity, and interaction profile are major issues in the drug discovery and lead optimization processes. The Cytochromes P450 (CYPs) 2D6 and 2C9 are enzymes involved in the oxidative metabolism of a majority of the marketed drugs. By identifying the binding mode using pharmacophore pre-alignement and automated flexible docking, and quantifying the binding affinity by multi-dimensional QSAR, we validated a model family of 56 compounds (46 training, 10 test) and 85 (68 training, 17 test) for CYP2D6 and CYP2C9, respectively. The correlation with the experimental data (cross- validated r2 = 0.811 for CYP2D6 and 0.687 for CYP2C9) suggests that our approach is suited for predicting the binding affinity of compounds towards the CYP2D6 and CYP2C9. The models were challenged by Y-scrambling, and by testing an external dataset of binding compounds (15 compounds for CYP2D6 and 40 for CYP2C9) and not binding compounds (64 compounds for CYP2D6 and 56 for CYP2C9). TOPIC 3: After injury, neurites from mammalian adult central nervous systems are inhibited to regenerate by inhibitory proteins such as the myelin-associated glycoprotein (MAG). The block of MAG with potent glycomimetic antagonists could be a fruitful approach to enhance axon regeneration. Libraries of MAG antagonists were derived and synthesized starting from the (general) sialic acid moiety. The binding data were rationalized by docking studies, molecular dynamics simulations and free energy perturbations on a homology model of MAG. The pharmacokinetic profile (i.e. stability in cerebrospinal fluid, logD, and blood-brain barrier permeation) of these compounds has been thoroughly investigated to evaluate the drug-likeness of the identified antagonists
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