GRID‐Derived Molecular Interaction Fields for Predicting the Site of Metabolism in Human Cytochromes

Cruciani, Gabriele; Aristei, Yasmin; Vianello, Riccardo; Baroni, Massimo

doi:10.1002/3527607676.ch12

Cited by 3 publications

(4 citation statements)

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“…Rydberg et al also showed that active-site waters could exchange with bulk during 4 ns simulations of six mammalian CYPs. The mean number of waters and exchange pathways varied significantly between isoforms, consistent with the variability in active site volume …”

Section: The Cyp Superfamily Of Metabolizing Enzymessupporting

confidence: 55%

“…The mean number of waters and exchange pathways varied significantly between isoforms, consistent with the variability in active site volume. 99 …”

Section: The Cyp Superfamily Of Metabolizing Enzymesmentioning

confidence: 99%

“…98 The active site volume of CYP isoforms varies as a function of isoform. Cruciani et al 99 investigated the structural characteristics of the binding sites of various isoforms using GRID. They point out the remarkable differences of the active site volumes computed using a hydrogen probe.…”

Section: Enzymesmentioning

confidence: 99%

“…The mean number of waters and exchange pathways varied significantly between isoforms, consistent with the variability in active site volume. 99 MD simulations have also been utilized to study the effect of organic cosolvent molecules such as DMSO on the structure and dynamics of CYPs 134,135 for commercial exploitation, since many industrially important substrates are poorly soluble in water. Moreover, a series of 1 ns MD trajectories have been used to identify docking sites for CO binding to P450cam, rationalizing laser flash photolysis data.…”

Section: Enzymesmentioning

confidence: 99%

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Computational Prediction of Metabolism: Sites, Products, SAR, P450 Enzyme Dynamics, and Mechanisms

Kirchmair

Williamson

Tyzack

et al. 2012

J. Chem. Inf. Model.

256

219

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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.

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Section: The Cyp Superfamily Of Metabolizing Enzymessupporting

confidence: 55%

“…The mean number of waters and exchange pathways varied significantly between isoforms, consistent with the variability in active site volume. 99 …”

Section: The Cyp Superfamily Of Metabolizing Enzymesmentioning

confidence: 99%

Section: Enzymesmentioning

confidence: 99%

Section: Enzymesmentioning

confidence: 99%

See 2 more Smart Citations

Computational Prediction of Metabolism: Sites, Products, SAR, P450 Enzyme Dynamics, and Mechanisms

Kirchmair

Williamson

Tyzack

et al. 2012

J. Chem. Inf. Model.

256

219

View full text Add to dashboard Cite

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Abstract

Ölander¹,

Wiśniewski

Norén³

et al. 2016

Drug Metabolism Reviews

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Molecular field technology applied to virtual screening and finding the bioactive conformation

Cheeseright¹,

Mackey²,

Rose³

et al. 2007

Expert Opinion on Drug Discovery

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Virtual screening is being applied to reduce the high-throughput screening bottleneck in many pharmaceutical companies and to reduce compound wastage. Cresset's ligand-based virtual screening technology using molecular fields can facilitate rapid identification of novel chemotypes from biologically testing only 200 - 1000 compounds. Four molecular fields calculated using the interaction of different probe atoms with the ligand are sufficient to describe how a ligand binds to its protein. Compounds with similar fields to known active ligands are predicted to have a high probability of showing similar activity. As binding is related to field similarity, this property has been exploited further to predict the bioactive conformation of small sets of structurally diverse active ligands starting from the two-dimensional structures alone without knowledge of the target site structure.

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GRID‐Derived Molecular Interaction Fields for Predicting the Site of Metabolism in Human Cytochromes

Cited by 3 publications

References 0 publications

Computational Prediction of Metabolism: Sites, Products, SAR, P450 Enzyme Dynamics, and Mechanisms

Computational Prediction of Metabolism: Sites, Products, SAR, P450 Enzyme Dynamics, and Mechanisms

Abstract

Molecular field technology applied to virtual screening and finding the bioactive conformation

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