Empirical Regioselectivity Models for Human Cytochromes P450 3A4, 2D6, and 2C9

Sheridan, Robert P.; Korzekwa, Kenneth R.; Torres, Rhonda A.; Walker, Matthew J.

doi:10.1021/jm0613471

Cited by 103 publications

(136 citation statements)

References 21 publications

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“…for predicting sites of metabolism on the substrate, have been based on mechanistic information relating to the substrate-enzyme interaction. An alternative approach, entirely QSAR-based and not simulating specific mechanisms and/or using explicit models of active sites, was proposed by Sheridan et al (2007) for predicting CYP450 (3A4, 2D6, 2C9) sites of the metabolism The model was based on a dataset consisting of 532 diverse molecules (316 for CYP3A4, 124 for CYP2D6, and 92 for CYP2C9), collected mainly from the literature, but including also some proprietary in-house data. An external test set of 25 compounds was also used.…”

mentioning

confidence: 99%

Applicability of QSAR analysis to the evaluation of the toxicological relevance of metabolites and degradates of pesticide active substances for dietary risk assessment

2010

EFSA Supporting Publications

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confidence: 99%

Applicability of QSAR analysis to the evaluation of the toxicological relevance of metabolites and degradates of pesticide active substances for dietary risk assessment

2010

EFSA Supporting Publications

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“…Sheridan et al used the random forest (RF) method, and their descriptors included structural descriptors, SASA and topological descriptors to develop SOM prediction models for CYP3A4, 2D6, and 2C9. The predictive power of this model is comparable with that of MetaSite (Sheridan et al 2007). Zheng et al calculated quantum chemical descriptors to characterize atom reactivity and used the SVM method to develop six CYP SOM prediction models for major metabolic reaction types.…”

Section: Som Predictionmentioning

confidence: 61%

In silicoADME/T modelling for rational drug design

Wang

Xing

Yue

et al. 2015

Quart. Rev. Biophys.

262

155

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Abstract. In recent decades, in silico absorption, distribution, metabolism, excretion (ADME), and toxicity (T) modelling as a tool for rational drug design has received considerable attention from pharmaceutical scientists, and various ADME/T-related prediction models have been reported. The high-throughput and low-cost nature of these models permits a more streamlined drug development process in which the identification of hits or their structural optimization can be guided based on a parallel investigation of bioavailability and safety, along with activity. However, the effectiveness of these tools is highly dependent on their capacity to cope with needs at different stages, e.g. their use in candidate selection has been limited due to their lack of the required predictability. For some events or endpoints involving more complex mechanisms, the current in silico approaches still need further improvement. In this review, we will briefly introduce the development of in silico models for some physicochemical parameters, ADME properties and toxicity evaluation, with an emphasis on the modelling approaches thereof, their application in drug discovery, and the potential merits or deficiencies of these models. Finally, the outlook for future ADME/T modelling based on big data analysis and systems sciences will be discussed.

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“…6 The fact that the enzyme induces the binding suggests that it is relevant to use the protein structures to predict how drug compounds are metabolized. This is probably why only few studies of pure ligand-based models on SOM prediction for CYP2D6 exist, 7 and structural information of protein has been included for these purposes. de Groot and co-workers combined structural models of CYP2D6 and pharmacophore modeling with AM1 energies of intermediates and products to predict the SOMs.…”

Section: * S Supporting Informationmentioning

confidence: 99%

Ligand-Based Site of Metabolism Prediction for Cytochrome P450 2D6

Rydberg

Olsen

2011

ACS Med. Chem. Lett.

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A ligand-based method based on the SMARTCyp approach that predicts the sites of cytochrome P450 2D6-mediated metabolism of druglike molecules has been developed. The method uses only two descriptors besides the reactivity from SMARTCyp: the distance to a protonated nitrogen atom and the distance to the end of the molecule. Hence, the site of metabolism is predicted directly from the 2D structure of a molecule, without requiring calculation of electronic properties or generation of 3D structures. Testing on an independent test set gives an area under the curve value of 0.94, and a site of metabolism is found among the top two ranked atoms for 91% of the compounds. KEYWORDS: CYP2D6, cytochrome P450, drug metabolism C ytochrome P450 (CYP) constitutes an ubiquitous family of enzymes, and from a drug perspective, its most important function is to metabolize drug compounds. In the development of drugs, it is important at an early stage to be able to identify the site of metabolism (SOM) of the lead compounds to be able to guide the development of compounds with a desirable pharmacokinetic profile.The CYP 3A4 isoform is the most important enzyme in the degradation of drug compounds and metabolize about 50% of them. CYP 3A4 is promiscuous and is capable of converting both small and large compounds, and crystal structures have shown that the volume of the active site can change dramatically upon binding of ligands. 1−3 This is probably also why it is possible to use ligand-based models to predict how a druglike compound is metabolized for CYP 3A4, because binding in this flexible pocket is not too restrictive, and thus, the intrinsic reactivity plays a significant role. For example, it was possible with the SMARTCyp method, 4,5 which primarily takes the intrinsic reactivity into account, to predict a SOM within the top two ranked atoms for 81% of the compounds within a set of 361 druglike compounds. 5 The second most drug-metabolizing CYP enzyme, the 2D6 isoform, is more selective in its recognition of the substrates. Generally, many medium-sized amines are metabolized, however, not many of them by N-dealkylation of amines but rather further away from this functional group. The crystal structure of CYP 2D6 reveals that a there are two negatively charged amino acids in the upper part of the binding cavity of 2D6, that is, Glu216 and Asp301, which may facilitate the binding of the positively charged parts of the substrates. 6 The fact that the enzyme induces the binding suggests that it is relevant to use the protein structures to predict how drug compounds are metabolized. This is probably why only few studies of pure ligand-based models on SOM prediction for CYP2D6 exist, 7 and structural information of protein has been included for these purposes. de Groot and co-workers combined structural models of CYP2D6 and pharmacophore modeling with AM1 energies of intermediates and products to predict the SOMs. 8,9 Later studies have shown the importance of including water molecules and using ensembles of protein struct...

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Empirical Regioselectivity Models for Human Cytochromes P450 3A4, 2D6, and 2C9

Cited by 103 publications

References 21 publications

Applicability of QSAR analysis to the evaluation of the toxicological relevance of metabolites and degradates of pesticide active substances for dietary risk assessment

Applicability of QSAR analysis to the evaluation of the toxicological relevance of metabolites and degradates of pesticide active substances for dietary risk assessment

In silicoADME/T modelling for rational drug design

Ligand-Based Site of Metabolism Prediction for Cytochrome P450 2D6

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