IDSite: An Accurate Approach to Predict P450-Mediated Drug Metabolism

Li, Jianing; Schneebeli, Severin T.; Bylund, Joseph H.; Farid, Ramy; Friesner, Richard A.

doi:10.1021/ct200462q

Cited by 49 publications

(55 citation statements)

References 42 publications

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“…If the distance was less than 3·5 Å, the site was considered to be exposed to the haem centre, and a quantum mechanics calculation was performed to obtain the hydrogen abstraction energy. To further consider the effect of protein flexibility during the ligand-binding process, Li et al reported a CYP-mediated SOM prediction model based on induced-fit docking, where the conformations were refined with the Protein Local Optimization Program (Li et al 2011b). The testing of the IDSite on CYP2D6 showed that the IDSite could recover 83% of the experimentally observed SOMs for 56 compounds with a low false positive rate.…”

Section: Som Predictionmentioning

confidence: 99%

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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Section: Som Predictionmentioning

confidence: 99%

In silicoADME/T modelling for rational drug design

Wang

Xing

Yue

et al. 2015

Quart. Rev. Biophys.

262

155

View full text Add to dashboard Cite

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“…Should a prediction only consider the atoms that are closest, or could any additional atoms also be considered? More elaborate geometric criteria may circumvent this problem [10].…”

Section: å Rulementioning

confidence: 99%

“…Interestingly, a very simple approach such as SMARTCyp (see Chapter 11), which is based solely on the intrinsic reactivity of potential SoMs, performs very well to predict the SoM of substrates of CYP1A2 and 3A4, but an orientational penalty needs to be included for isoforms 2C9 and 2D6 [11][12][13]. Ideally, a structure-based approach should be combined with an estimate of the intrinsic reactivity, which is the key idea behind approaches such as MetaSite [7], MLite [14], or IDSite [10]. The first of these approaches combines a quantum mechanical calculation to describe the reactivity with a fingerprint match between the substrate and the active site [7] (see Chapter 9).…”

Section: å Rulementioning

confidence: 99%

“…The first of these approaches combines a quantum mechanical calculation to describe the reactivity with a fingerprint match between the substrate and the active site [7] (see Chapter 9). MLite combines a docking approach with precalculated activation energies [14], and IDSite performs a flexible docking, with a local protein structure optimization and finally a density functional calculation [10].…”

Section: å Rulementioning

confidence: 99%

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Structure‐Based Methods for Predicting the Sites and Products of Metabolism

Oostenbrink

2014

Methods and Principles in Medicinal Chemistry

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IntroductionCytochrome P450s (CYPs) are heme-containing enzymes that can be found in virtually all organisms. In humans, the CYP superfamily constitutes the most important enzymes in drug metabolism (see Chapters 4-8).Various computational approaches to study CYP metabolism have been reported over the years [1][2][3][4], and depending on the question that is being addressed, different methods may be more or less appropriate. For instance, if the actual reaction mechanism of a particular substrate is to be studied, a quantum mechanical description explicitly describing the electrons that are responsible for bonds being broken and formed is required [5]. On the other hand, a classification of a large number of compounds in terms of their likelihood to show an interaction with a CYP may rather be performed by application of cheminformatics machine learning tools [6]. In almost all cases, the versatility of the enzymes, the diversity of the substrates and inhibitors, and the malleability of the active sites pose additional challenges to the computational approach at hand. This chapter focuses on structure-based approaches to study the metabolism of substrates by CYP enzymes. Rather than addressing the actual enzymatic reactions, as in Chapters 6 and 11, we will focus here on the preferred orientations of substrates in the active site of CYP enzymes as a crucial first step in the prediction of metabolism. Using mostly examples from our own work, we will highlight some of the possibilities and challenges in structure-based predictions of sites of metabolism (SoMs). 6 Å RuleThe basic concept behind structure-based prediction of metabolism by CYP enzymes is extremely simple. The crucial cofactor of the enzymes is a heme 243 Drug Metabolism Prediction, First Edition. Edited by Johannes Kirchmair.

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“…In addition to these solely ligand-based strategies, other computationally more demanding approaches to prediction SOMs include the protein environment via docking [64][65][66]. On the other hand also data-driven approaches were found to yield accurate results at a comparably low computational cost.…”

Section: Som Predictionmentioning

confidence: 99%

Precursors for cytochrome P450 profiling breath tests from an in silico screening approach

et al. 2014

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The family of cytochrome P450 enzymes (CYPs) is a major player in the metabolism of drugs and xenobiotics. Genetic polymorphisms and transcriptional regulation give a complex patientindividual CYP activity profile for each human being. Therefore, personalized medicine demands easy and non-invasive measurement of the CYP phenotype. Breath tests detect volatile organic compounds (VOCs) in the patients' exhaled air after administration of a precursor molecule. CYP breath tests established for individual CYP isoforms are based on the detection of 13 CO 2 or 14 CO 2 originating from CYP-catalyzed oxidative degradation reactions of isotopically labeled precursors.We present an in silico work-flow aiming at the identification of novel precursor molecules, likely to result in VOCs other than CO 2 upon oxidative degradation as we aim at label-free precursor molecules. The ligand-based work-flow comprises five parts: (1) CYP profiling was encoded as a decision tree based on 2D molecular descriptors derived from established models in the literature and validated against publicly available data extracted from the DrugBank. (2) Likely sites of metabolism were identified by reactivity and accessibility estimation for abstractable hydrogen radical. (3) Oxidative degradation reactions (O-and N-dealkylations) were found to be most promising in the release of VOCs. Thus, the CYP-catalyzed oxidative degradation reaction was encoded as SMIRKS (a programming language style to implement reactions based on the SMARTS description) to enumerate possible reaction products. (4) A quantitative structure property relation (QSPR) model aiming to predict the Henry constant H was derived from data for 488 organic compounds and identifies potentially VOCs amongst CYP reaction products.(5) A blacklist of naturally occurring breath components was implemented to identify marker molecules allowing straightforward detection within the exhaled air.

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IDSite: An Accurate Approach to Predict P450-Mediated Drug Metabolism

Cited by 49 publications

References 42 publications

In silicoADME/T modelling for rational drug design

In silicoADME/T modelling for rational drug design

Structure‐Based Methods for Predicting the Sites and Products of Metabolism

Precursors for cytochrome P450 profiling breath tests from an in silico screening approach

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