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Hakura A, Awogi T, Shiragiku T, Ohigashi A, Yamamoto M, Kanasaki K, Oka H, Dewa Y, Ozawa S, Sakamoto K, Kato T, Yamamura E. Bacterial mutagenicity test data: collection by the task force of the Japan pharmaceutical manufacturers association. Genes Environ 2021; 43:41. [PMID: 34593056 PMCID: PMC8482598 DOI: 10.1186/s41021-021-00206-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2021] [Accepted: 07/07/2021] [Indexed: 12/04/2022] Open
Abstract
Background Ames test is used worldwide for detecting the bacterial mutagenicity of chemicals. In silico analyses of bacterial mutagenicity have recently gained acceptance by regulatory agencies; however, current in silico models for prediction remain to be improved. The Japan Pharmaceutical Manufacturers Association (JPMA) organized a task force in 2017 in which eight Japanese pharmaceutical companies had participated. The purpose of this task force was to disclose a piece of pharmaceutical companies’ proprietary Ames test data. Results Ames test data for 99 chemicals of various chemical classes were collected for disclosure in this study. These chemicals are related to the manufacturing process of pharmaceutical drugs, including reagents, synthetic intermediates, and drug substances. The structure-activity (mutagenicity) relationships are discussed in relation to structural alerts for each chemical class. In addition, in silico analyses of these chemicals were conducted using a knowledge-based model of Derek Nexus (Derek) and a statistics-based model (GT1_BMUT module) of CASE Ultra. To calculate the effectiveness of these models, 89 chemicals for Derek and 54 chemicals for CASE Ultra were selected; major exclusions were the salt form of four chemicals that were tested both in the salt and free forms for both models, and 35 chemicals called “known” positives or negatives for CASE Ultra. For Derek, the sensitivity, specificity, and accuracy were 65% (15/23), 71% (47/66), and 70% (62/89), respectively. The sensitivity, specificity, and accuracy were 50% (6/12), 60% (25/42), and 57% (31/54) for CASE Ultra, respectively. The ratio of overall disagreement between the CASE Ultra “known” positives/negatives and the actual test results was 11% (4/35). In this study, 19 out of 28 mutagens (68%) were detected with TA100 and/or TA98, and 9 out of 28 mutagens (32%) were detected with either TA1535, TA1537, WP2uvrA, or their combination. Conclusion The Ames test data presented here will help avoid duplicated Ames testing in some cases, support duplicate testing in other cases, improve in silico models, and enhance our understanding of the mechanisms of mutagenesis. Supplementary Information The online version contains supplementary material available at 10.1186/s41021-021-00206-1.
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Affiliation(s)
- Atsushi Hakura
- Global Drug Safety, Eisai Co., Ltd., 5-1-3 Tokodai, Tsukuba, Ibaraki, 300-2635, Japan.
| | - Takumi Awogi
- Manufacturing Process Development Department, Otsuka Pharmaceutical Co., Ltd., 224-18 Hiraishi-Ebisuno, Kawauchi-cho, Tokushima-shi, Tokushima, 771-0182, Japan
| | - Toshiyuki Shiragiku
- Tokushima Research Institute, Otsuka Pharmaceutical Co., Ltd., 463-10 Kagasuno, Kawauchi-cho, Tokushima-shi, Tokushima, 771-0192, Japan
| | - Atsushi Ohigashi
- Process Chemistry Labs, Astellas Pharma Inc., 160-2 Akahama, Takahagi, Ibaraki, 318-0001, Japan
| | - Mika Yamamoto
- Drug Safety Research Labs, Astellas Pharma Inc., 21 Miyukigaoka, Tsukuba, Ibaraki, 305-8585, Japan
| | - Kayoko Kanasaki
- Laboratory for Drug Discovery and Development, Shionogi & Co., Ltd., 3-1-1 Futaba-cho, Osaka, Toyonaka-shi, 561-0825, Japan
| | - Hiroaki Oka
- Toxicology Laboratory, Taiho pharmaceutical Co., Ltd., 224-2 Ebisuno, Hiraishi, Kawauchi-cho, Tokushima, 771-0194, Japan
| | - Yasuaki Dewa
- Toxicology Research Laboratory, Kyorin Pharmaceutical Co., Ltd., 1848 Nogi, Nogi-machi, Shimotsuga-gun, Tochigi, 329-0114, Japan
| | - Shunsuke Ozawa
- Toxicology Research Laboratory, Kyorin Pharmaceutical Co., Ltd., 1848 Nogi, Nogi-machi, Shimotsuga-gun, Tochigi, 329-0114, Japan
| | - Kouji Sakamoto
- Drug Safety, Taisho Pharmaceutical Co., Ltd., 1-403, Yoshino-cho, Kita-ku, Saitama-shi, 331-9530, Japan
| | - Tatsuya Kato
- Safety Research Laboratories, Mitsubishi Tanabe Pharma Co., 2-2-50 Kawagishi, Toda-shi, Saitama, 335-8505, Japan
| | - Eiji Yamamura
- Safety Research Laboratories, Mitsubishi Tanabe Pharma Co., 2-2-50 Kawagishi, Toda-shi, Saitama, 335-8505, Japan
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Shamovsky I, Ripa L, Narjes F, Bonn B, Schiesser S, Terstiege I, Tyrchan C. Mechanism-Based Insights into Removing the Mutagenicity of Aromatic Amines by Small Structural Alterations. J Med Chem 2021; 64:8545-8563. [PMID: 34110134 DOI: 10.1021/acs.jmedchem.1c00514] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Aromatic and heteroaromatic amines (ArNH2) are activated by cytochrome P450 monooxygenases, primarily CYP1A2, into reactive N-arylhydroxylamines that can lead to covalent adducts with DNA nucleobases. Hereby, we give hands-on mechanism-based guidelines to design mutagenicity-free ArNH2. The mechanism of N-hydroxylation of ArNH2 by CYP1A2 is investigated by density functional theory (DFT) calculations. Two putative pathways are considered, the radicaloid route that goes via the classical ferryl-oxo oxidant and an alternative anionic pathway through Fenton-like oxidation by ferriheme-bound H2O2. Results suggest that bioactivation of ArNH2 follows the anionic pathway. We demonstrate that H-bonding and/or geometric fit of ArNH2 to CYP1A2 as well as feasibility of both proton abstraction by the ferriheme-peroxo base and heterolytic cleavage of arylhydroxylamines render molecules mutagenic. Mutagenicity of ArNH2 can be removed by structural alterations that disrupt geometric and/or electrostatic fit to CYP1A2, decrease the acidity of the NH2 group, destabilize arylnitrenium ions, or disrupt their pre-covalent transition states with guanine.
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3
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A pharma-wide approach to address the genotoxicity prediction of primary aromatic amines. ACTA ACUST UNITED AC 2018. [DOI: 10.1016/j.comtox.2018.06.002] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
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Computational identification of structural factors affecting the mutagenic potential of aromatic amines: study design and experimental validation. Arch Toxicol 2018; 92:2369-2384. [PMID: 29779177 DOI: 10.1007/s00204-018-2216-x] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2018] [Accepted: 05/03/2018] [Indexed: 01/03/2023]
Abstract
A grid-based, alignment-independent 3D-SDAR (three-dimensional spectral data-activity relationship) approach based on simulated 13C and 15N NMR chemical shifts augmented with through-space interatomic distances was used to model the mutagenicity of 554 primary and 419 secondary aromatic amines. A robust modeling strategy supported by extensive validation including randomized training/hold-out test set pairs, validation sets, "blind" external test sets as well as experimental validation was applied to avoid over-parameterization and build Organization for Economic Cooperation and Development (OECD 2004) compliant models. Based on an experimental validation set of 23 chemicals tested in a two-strain Salmonella typhimurium Ames assay, 3D-SDAR was able to achieve performance comparable to 5-strain (Ames) predictions by Lhasa Limited's Derek and Sarah Nexus for the same set. Furthermore, mapping of the most frequently occurring bins on the primary and secondary aromatic amine structures allowed the identification of molecular features that were associated either positively or negatively with mutagenicity. Prominent structural features found to enhance the mutagenic potential included: nitrobenzene moieties, conjugated π-systems, nitrothiophene groups, and aromatic hydroxylamine moieties. 3D-SDAR was also able to capture "true" negative contributions that are particularly difficult to detect through alternative methods. These include sulphonamide, acetamide, and other functional groups, which not only lack contributions to the overall mutagenic potential, but are known to actively lower it, if present in the chemical structures of what otherwise would be potential mutagens.
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5
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Bezençon O, Heidmann B, Siegrist R, Stamm S, Richard S, Pozzi D, Corminboeuf O, Roch C, Kessler M, Ertel EA, Reymond I, Pfeifer T, de Kanter R, Toeroek-Schafroth M, Moccia LG, Mawet J, Moon R, Rey M, Capeleto B, Fournier E. Discovery of a Potent, Selective T-type Calcium Channel Blocker as a Drug Candidate for the Treatment of Generalized Epilepsies. J Med Chem 2017; 60:9769-9789. [PMID: 29116786 DOI: 10.1021/acs.jmedchem.7b01236] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/17/2023]
Abstract
We report here the discovery and pharmacological characterization of N-(1-benzyl-1H-pyrazol-3-yl)-2-phenylacetamide derivatives as potent, selective, brain-penetrating T-type calcium channel blockers. Optimization focused mainly on solubility, brain penetration, and the search for an aminopyrazole metabolite that would be negative in an Ames test. This resulted in the preparation and complete characterization of compound 66b (ACT-709478), which has been selected as a clinical candidate.
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Affiliation(s)
- Olivier Bezençon
- Chemistry, Biology and Pharmacology & Pre-clinical Development, Drug Discovery, Idorsia Pharmaceuticals Ltd. , Hegenheimermattweg 91, CH-4123 Allschwil, Switzerland
| | - Bibia Heidmann
- Chemistry, Biology and Pharmacology & Pre-clinical Development, Drug Discovery, Idorsia Pharmaceuticals Ltd. , Hegenheimermattweg 91, CH-4123 Allschwil, Switzerland
| | - Romain Siegrist
- Chemistry, Biology and Pharmacology & Pre-clinical Development, Drug Discovery, Idorsia Pharmaceuticals Ltd. , Hegenheimermattweg 91, CH-4123 Allschwil, Switzerland
| | - Simon Stamm
- Chemistry, Biology and Pharmacology & Pre-clinical Development, Drug Discovery, Idorsia Pharmaceuticals Ltd. , Hegenheimermattweg 91, CH-4123 Allschwil, Switzerland
| | - Sylvia Richard
- Chemistry, Biology and Pharmacology & Pre-clinical Development, Drug Discovery, Idorsia Pharmaceuticals Ltd. , Hegenheimermattweg 91, CH-4123 Allschwil, Switzerland
| | - Davide Pozzi
- Chemistry, Biology and Pharmacology & Pre-clinical Development, Drug Discovery, Idorsia Pharmaceuticals Ltd. , Hegenheimermattweg 91, CH-4123 Allschwil, Switzerland
| | - Olivier Corminboeuf
- Chemistry, Biology and Pharmacology & Pre-clinical Development, Drug Discovery, Idorsia Pharmaceuticals Ltd. , Hegenheimermattweg 91, CH-4123 Allschwil, Switzerland
| | - Catherine Roch
- Chemistry, Biology and Pharmacology & Pre-clinical Development, Drug Discovery, Idorsia Pharmaceuticals Ltd. , Hegenheimermattweg 91, CH-4123 Allschwil, Switzerland
| | - Melanie Kessler
- Chemistry, Biology and Pharmacology & Pre-clinical Development, Drug Discovery, Idorsia Pharmaceuticals Ltd. , Hegenheimermattweg 91, CH-4123 Allschwil, Switzerland
| | - Eric A Ertel
- Chemistry, Biology and Pharmacology & Pre-clinical Development, Drug Discovery, Idorsia Pharmaceuticals Ltd. , Hegenheimermattweg 91, CH-4123 Allschwil, Switzerland
| | - Isabelle Reymond
- Chemistry, Biology and Pharmacology & Pre-clinical Development, Drug Discovery, Idorsia Pharmaceuticals Ltd. , Hegenheimermattweg 91, CH-4123 Allschwil, Switzerland
| | - Thomas Pfeifer
- Chemistry, Biology and Pharmacology & Pre-clinical Development, Drug Discovery, Idorsia Pharmaceuticals Ltd. , Hegenheimermattweg 91, CH-4123 Allschwil, Switzerland
| | - Ruben de Kanter
- Chemistry, Biology and Pharmacology & Pre-clinical Development, Drug Discovery, Idorsia Pharmaceuticals Ltd. , Hegenheimermattweg 91, CH-4123 Allschwil, Switzerland
| | - Michael Toeroek-Schafroth
- Chemistry, Biology and Pharmacology & Pre-clinical Development, Drug Discovery, Idorsia Pharmaceuticals Ltd. , Hegenheimermattweg 91, CH-4123 Allschwil, Switzerland
| | - Luca G Moccia
- Chemistry, Biology and Pharmacology & Pre-clinical Development, Drug Discovery, Idorsia Pharmaceuticals Ltd. , Hegenheimermattweg 91, CH-4123 Allschwil, Switzerland
| | - Jacques Mawet
- Chemistry, Biology and Pharmacology & Pre-clinical Development, Drug Discovery, Idorsia Pharmaceuticals Ltd. , Hegenheimermattweg 91, CH-4123 Allschwil, Switzerland
| | - Richard Moon
- Chemistry, Biology and Pharmacology & Pre-clinical Development, Drug Discovery, Idorsia Pharmaceuticals Ltd. , Hegenheimermattweg 91, CH-4123 Allschwil, Switzerland
| | - Markus Rey
- Chemistry, Biology and Pharmacology & Pre-clinical Development, Drug Discovery, Idorsia Pharmaceuticals Ltd. , Hegenheimermattweg 91, CH-4123 Allschwil, Switzerland
| | - Bruno Capeleto
- Chemistry, Biology and Pharmacology & Pre-clinical Development, Drug Discovery, Idorsia Pharmaceuticals Ltd. , Hegenheimermattweg 91, CH-4123 Allschwil, Switzerland
| | - Elvire Fournier
- Chemistry, Biology and Pharmacology & Pre-clinical Development, Drug Discovery, Idorsia Pharmaceuticals Ltd. , Hegenheimermattweg 91, CH-4123 Allschwil, Switzerland
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6
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Pennington LD, Moustakas DT. The Necessary Nitrogen Atom: A Versatile High-Impact Design Element for Multiparameter Optimization. J Med Chem 2017; 60:3552-3579. [PMID: 28177632 DOI: 10.1021/acs.jmedchem.6b01807] [Citation(s) in RCA: 182] [Impact Index Per Article: 26.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
There is a continued desire in biomedical research to reduce the number and duration of design cycles required to optimize lead compounds into high-quality chemical probes or safe and efficacious drug candidates. The insightful application of impactful molecular design elements is one approach toward achieving this goal. The replacement of a CH group with a N atom in aromatic and heteroaromatic ring systems can have many important effects on molecular and physicochemical properties and intra- and intermolecular interactions that can translate to improved pharmacological profiles. In this Perspective, the "necessary nitrogen atom" is shown to be a versatile high-impact design element for multiparameter optimization, wherein ≥10-, 100-, or 1000-fold improvement in a variety of key pharmacological parameters can be realized.
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Affiliation(s)
- Lewis D Pennington
- Medicinal Chemistry and ‡Modeling and Informatics, Alkermes, Plc , 852 Winter Street, Waltham, Massachusetts 02451-1420, United States
| | - Demetri T Moustakas
- Medicinal Chemistry and ‡Modeling and Informatics, Alkermes, Plc , 852 Winter Street, Waltham, Massachusetts 02451-1420, United States
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7
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Borosky GL. Mutagenicity of heteroaromatic amines: Computational study on the influence of methyl substituents. J Mol Graph Model 2016; 69:92-102. [PMID: 27592197 DOI: 10.1016/j.jmgm.2016.08.010] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2016] [Revised: 08/18/2016] [Accepted: 08/27/2016] [Indexed: 10/21/2022]
Abstract
Quantum mechanical calculations were performed to elucidate the factors determining the variations in mutagenic activity within groups of isomeric heteroaromatic amines that differ in the position of methyl substituents. Formation energies for noncovalent complexes and covalent DNA adducts were evaluated by means of high level quantum chemical methods. According to the computational results in this work, covalent adduct stability is proposed to influence the relative mutagenicities of structurally related heterocyclic amines. The stability of covalent C8-dG DNA adducts was found to be mainly determined by π-stacking interactions between the fused ring system of the heteroaromatic amines and the flanking nucleobases. Relative mutagenicity of amines of very related structure is proposed to be regulated by both nitrenium ion and covalent adduct stabilities.
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Affiliation(s)
- Gabriela L Borosky
- INFIQC, CONICET and Departamento de Matemática y Física, Facultad de Ciencias Químicas, Universidad Nacional de Córdoba, Ciudad Universitaria, Córdoba 5000, Argentina.
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8
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Brack W, Ait-Aissa S, Burgess RM, Busch W, Creusot N, Di Paolo C, Escher BI, Mark Hewitt L, Hilscherova K, Hollender J, Hollert H, Jonker W, Kool J, Lamoree M, Muschket M, Neumann S, Rostkowski P, Ruttkies C, Schollee J, Schymanski EL, Schulze T, Seiler TB, Tindall AJ, De Aragão Umbuzeiro G, Vrana B, Krauss M. Effect-directed analysis supporting monitoring of aquatic environments--An in-depth overview. THE SCIENCE OF THE TOTAL ENVIRONMENT 2016; 544:1073-118. [PMID: 26779957 DOI: 10.1016/j.scitotenv.2015.11.102] [Citation(s) in RCA: 219] [Impact Index Per Article: 27.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/14/2015] [Revised: 11/20/2015] [Accepted: 11/20/2015] [Indexed: 05/18/2023]
Abstract
Aquatic environments are often contaminated with complex mixtures of chemicals that may pose a risk to ecosystems and human health. This contamination cannot be addressed with target analysis alone but tools are required to reduce this complexity and identify those chemicals that might cause adverse effects. Effect-directed analysis (EDA) is designed to meet this challenge and faces increasing interest in water and sediment quality monitoring. Thus, the present paper summarizes current experience with the EDA approach and the tools required, and provides practical advice on their application. The paper highlights the need for proper problem formulation and gives general advice for study design. As the EDA approach is directed by toxicity, basic principles for the selection of bioassays are given as well as a comprehensive compilation of appropriate assays, including their strengths and weaknesses. A specific focus is given to strategies for sampling, extraction and bioassay dosing since they strongly impact prioritization of toxicants in EDA. Reduction of sample complexity mainly relies on fractionation procedures, which are discussed in this paper, including quality assurance and quality control. Automated combinations of fractionation, biotesting and chemical analysis using so-called hyphenated tools can enhance the throughput and might reduce the risk of artifacts in laboratory work. The key to determining the chemical structures causing effects is analytical toxicant identification. The latest approaches, tools, software and databases for target-, suspect and non-target screening as well as unknown identification are discussed together with analytical and toxicological confirmation approaches. A better understanding of optimal use and combination of EDA tools will help to design efficient and successful toxicant identification studies in the context of quality monitoring in multiply stressed environments.
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Affiliation(s)
- Werner Brack
- UFZ Helmholtz Centre for Environmental Research, Permoserstraße 15, 04318 Leipzig, Germany; RWTH Aachen University, Worringerweg 1, 52074 Aachen, Germany
| | - Selim Ait-Aissa
- Institut National de l'Environnement Industriel et des Risques INERIS, BP2, 60550 Verneuil-en-Halatte, France
| | - Robert M Burgess
- US Environmental Protection Agency, Office of Research and Development, National Health and Environmental Effects Research Laboratory, Atlantic Ecology Division, Narragansett, RI, USA
| | - Wibke Busch
- UFZ Helmholtz Centre for Environmental Research, Permoserstraße 15, 04318 Leipzig, Germany
| | - Nicolas Creusot
- Institut National de l'Environnement Industriel et des Risques INERIS, BP2, 60550 Verneuil-en-Halatte, France
| | | | - Beate I Escher
- UFZ Helmholtz Centre for Environmental Research, Permoserstraße 15, 04318 Leipzig, Germany; Eberhard Karls University Tübingen, 72074 Tübingen, Germany
| | - L Mark Hewitt
- Water Science and Technology Directorate, Environment Canada, 867 Lakeshore Road, Burlington, Ontario L7S 1A1, Canada
| | - Klara Hilscherova
- Masaryk University, Research Centre for Toxic Compounds in the Environment (RECETOX), Kamenice 753/5, 625 00 Brno, Czech Republic
| | - Juliane Hollender
- Eawag, Swiss Federal Institute of Aquatic Science and Technology, 8600 Dübendorf, Switzerland
| | - Henner Hollert
- RWTH Aachen University, Worringerweg 1, 52074 Aachen, Germany
| | - Willem Jonker
- VU University, BioMolecular Analysis Group, Amsterdam, The Netherlands
| | - Jeroen Kool
- VU University, BioMolecular Analysis Group, Amsterdam, The Netherlands
| | - Marja Lamoree
- VU Amsterdam, Institute for Environmental Studies, Amsterdam, The Netherlands
| | - Matthias Muschket
- UFZ Helmholtz Centre for Environmental Research, Permoserstraße 15, 04318 Leipzig, Germany
| | - Steffen Neumann
- Leibniz Institute of Plant Biochemistry, Halle (Saale), Germany
| | - Pawel Rostkowski
- NILU - Norwegian Institute for Air Research, Instituttveien 18, 2007 Kjeller, Norway
| | | | - Jennifer Schollee
- Eawag, Swiss Federal Institute of Aquatic Science and Technology, 8600 Dübendorf, Switzerland
| | - Emma L Schymanski
- Eawag, Swiss Federal Institute of Aquatic Science and Technology, 8600 Dübendorf, Switzerland
| | - Tobias Schulze
- UFZ Helmholtz Centre for Environmental Research, Permoserstraße 15, 04318 Leipzig, Germany
| | | | - Andrew J Tindall
- WatchFrag, Bâtiment Genavenir 3, 1 Rue Pierre Fontaine, 91000 Evry, France
| | | | - Branislav Vrana
- Masaryk University, Research Centre for Toxic Compounds in the Environment (RECETOX), Kamenice 753/5, 625 00 Brno, Czech Republic
| | - Martin Krauss
- UFZ Helmholtz Centre for Environmental Research, Permoserstraße 15, 04318 Leipzig, Germany
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9
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Gallampois CMJ, Schymanski EL, Krauss M, Ulrich N, Bataineh M, Brack W. Multicriteria approach to select polyaromatic river mutagen candidates. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2015; 49:2959-68. [PMID: 25635928 DOI: 10.1021/es503640k] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/10/2023]
Abstract
The identification of unknown compounds remains one of the most challenging tasks to link observed toxic effects in complex environmental mixtures to responsible toxicants in effect-directed analysis (EDA). Here, a workflow is presented based on nontarget liquid chromatography-high resolution mass spectrometry (LC-HRMS) starting with molecular formulas determined in a previous study. A compound database search (ChemSpider) was performed to retrieve candidates for each formula. Subsequently, the number of candidates was reduced by applying MS-, physical-chemical, and chromatography-based selection criteria including HRMS/MS fragmentation and plausibility, ionization efficiency with different ion sources and detection modes, acid/base behavior, octanol/water partitioning, retention time prediction and finally toxic effects (mutagenicity caused by aromatic amines). The workflow strongly decreased the number of possible candidates and resulted in the tentative identification of possible mutagens and the positive identification of the nonmutagen benzyl(diphenyl) phosphine oxide in a mutagenic fraction. The positive identification of mutagens was hampered by a lack of commercially available standards. The workflow is an innovative and promising approach and forms an excellent basis for possible further advancements.
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Affiliation(s)
- Christine M J Gallampois
- UFZ - Helmholtz Centre for Environmental Research , Department of Effect-Directed Analysis, Permoserstr. 15, D-04318 Leipzig, Germany
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Zhang M, Eismin R, Kenttämaa H, Xiong H, Wu Y, Burdette D, Urbanek R. Identification of 2-Aminothiazolobenzazepine Metabolites in Human, Rat, Dog, and Monkey Microsomes by Ion-Molecule Reactions in Linear Quadrupole Ion Trap Mass Spectrometry. Drug Metab Dispos 2014; 43:358-66. [DOI: 10.1124/dmd.114.061978] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
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11
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Aza follow-ups to BI 207524, a thumb pocket 1 HCV NS5B polymerase inhibitor. Part 1: Mitigating the genotoxic liability of an aniline metabolite. Bioorg Med Chem Lett 2014; 25:1135-9. [PMID: 25575656 DOI: 10.1016/j.bmcl.2014.12.028] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2014] [Revised: 12/06/2014] [Accepted: 12/09/2014] [Indexed: 11/22/2022]
Abstract
A series of heterocyclic aza-analogs of BI 207524 (2), a potent HCV NS5B polymerase thumb pocket 1 inhibitor, was investigated with the goal to reduce the liability associated with the release of a genotoxic aniline metabolite in vivo. Analog 4, containing a 2-aminopyridine aniline isostere that is negative in the Ames test was identified, and was found to provide comparable GT1a/1b potency to 2. Although the cross-species PK profile, poor predicted human liver distribution of analog 4 and allometry principles projected high doses to achieve a strong antiviral response in patients, this work has provided a path forward toward the design of novel thumb pocket 1 NS5B polymerase inhibitors with improved safety profiles.
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12
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Leach AG, McCoull W, Bailey A, Barton P, Mee C, Rosevere E. Experimental Testing of Quantum Mechanical Predictions of Mutagenicity: Aminopyrazoles. Chem Res Toxicol 2013; 26:703-9. [DOI: 10.1021/tx3005136] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Andrew G. Leach
- AstraZeneca, Alderley Park,
Macclesfield, Cheshire SK10 4TG, United Kingdom
| | - William McCoull
- AstraZeneca, Alderley Park,
Macclesfield, Cheshire SK10 4TG, United Kingdom
| | - Andrew Bailey
- AstraZeneca, Alderley Park,
Macclesfield, Cheshire SK10 4TG, United Kingdom
| | - Peter Barton
- AstraZeneca, Alderley Park,
Macclesfield, Cheshire SK10 4TG, United Kingdom
| | - Christine Mee
- AstraZeneca, Alderley Park,
Macclesfield, Cheshire SK10 4TG, United Kingdom
| | - Eleanor Rosevere
- AstraZeneca, Alderley Park,
Macclesfield, Cheshire SK10 4TG, United Kingdom
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13
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Kalliokoski T, Kramer C, Vulpetti A, Gedeck P. Comparability of mixed IC₅₀ data - a statistical analysis. PLoS One 2013; 8:e61007. [PMID: 23613770 PMCID: PMC3628986 DOI: 10.1371/journal.pone.0061007] [Citation(s) in RCA: 187] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2013] [Accepted: 03/05/2013] [Indexed: 11/19/2022] Open
Abstract
The biochemical half maximal inhibitory concentration (IC50) is the most commonly used metric for on-target activity in lead optimization. It is used to guide lead optimization, build large-scale chemogenomics analysis, off-target activity and toxicity models based on public data. However, the use of public biochemical IC50 data is problematic, because they are assay specific and comparable only under certain conditions. For large scale analysis it is not feasible to check each data entry manually and it is very tempting to mix all available IC50 values from public database even if assay information is not reported. As previously reported for Ki database analysis, we first analyzed the types of errors, the redundancy and the variability that can be found in ChEMBL IC50 database. For assessing the variability of IC50 data independently measured in two different labs at least ten IC50 data for identical protein-ligand systems against the same target were searched in ChEMBL. As a not sufficient number of cases of this type are available, the variability of IC50 data was assessed by comparing all pairs of independent IC50 measurements on identical protein-ligand systems. The standard deviation of IC50 data is only 25% larger than the standard deviation of Ki data, suggesting that mixing IC50 data from different assays, even not knowing assay conditions details, only adds a moderate amount of noise to the overall data. The standard deviation of public ChEMBL IC50 data, as expected, resulted greater than the standard deviation of in-house intra-laboratory/inter-day IC50 data. Augmenting mixed public IC50 data by public Ki data does not deteriorate the quality of the mixed IC50 data, if the Ki is corrected by an offset. For a broad dataset such as ChEMBL database a Ki- IC50 conversion factor of 2 was found to be the most reasonable.
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Affiliation(s)
- Tuomo Kalliokoski
- Global Discovery Chemistry, Novartis Institutes for Biomedical Research, Basel, Switzerland
- * E-mail: (TK); (CK)
| | - Christian Kramer
- Global Discovery Chemistry, Novartis Institutes for Biomedical Research, Basel, Switzerland
- * E-mail: (TK); (CK)
| | - Anna Vulpetti
- Global Discovery Chemistry, Novartis Institutes for Biomedical Research, Basel, Switzerland
| | - Peter Gedeck
- Global Discovery Chemistry, Novartis Institutes for Biomedical Research, Basel, Switzerland
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Content S, Dupont T, Fédou NM, Smith JD, Twiddle SJR. Optimization of the Manufacturing Route to PF-610355 (1): Synthesis of Intermediate 5. Org Process Res Dev 2013. [DOI: 10.1021/op300341n] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- Stéphane Content
- Chemical
Research and Development, Pfizer Global Research and Development, Ramsgate Road, Sandwich,
Kent, U.K., CT13 9NJ
| | - Thomas Dupont
- Chemical
Research and Development, Pfizer Global Research and Development, Ramsgate Road, Sandwich,
Kent, U.K., CT13 9NJ
| | - Nicolas M. Fédou
- Chemical
Research and Development, Pfizer Global Research and Development, Ramsgate Road, Sandwich,
Kent, U.K., CT13 9NJ
| | - Julian D. Smith
- Chemical
Research and Development, Pfizer Global Research and Development, Ramsgate Road, Sandwich,
Kent, U.K., CT13 9NJ
| | - Steven J. R. Twiddle
- Chemical
Research and Development, Pfizer Global Research and Development, Ramsgate Road, Sandwich,
Kent, U.K., CT13 9NJ
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15
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Naven RT, Greene N, Williams RV. Latest advances in computational genotoxicity prediction. Expert Opin Drug Metab Toxicol 2012; 8:1579-87. [DOI: 10.1517/17425255.2012.724059] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
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16
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Shamovsky I, Ripa L, Blomberg N, Eriksson LA, Hansen P, Mee C, Tyrchan C, O'Donovan M, Sjö P. Theoretical Studies of Chemical Reactivity of Metabolically Activated Forms of Aromatic Amines toward DNA. Chem Res Toxicol 2012; 25:2236-52. [DOI: 10.1021/tx300313b] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
Affiliation(s)
- Igor Shamovsky
- Department of Medicinal Chemistry, R&I iMed, AstraZeneca R&D, Pepparedsleden 1, S-431 83 Mölndal, Sweden
| | - Lena Ripa
- Department of Medicinal Chemistry, R&I iMed, AstraZeneca R&D, Pepparedsleden 1, S-431 83 Mölndal, Sweden
| | - Niklas Blomberg
- Department of Medicinal Chemistry, R&I iMed, AstraZeneca R&D, Pepparedsleden 1, S-431 83 Mölndal, Sweden
| | - Leif A. Eriksson
- Department of Chemistry and Molecular Biology, University of Gothenburg, S-412 96 Göteborg, Sweden
| | - Peter Hansen
- Department of Medicinal Chemistry, R&I iMed, AstraZeneca R&D, Pepparedsleden 1, S-431 83 Mölndal, Sweden
| | - Christine Mee
- Genetic Toxicology, AstraZeneca R&D, Alderley Park, Macclesfield, Cheshire, SK10 4TG, United Kingdom
| | - Christian Tyrchan
- Department of Medicinal Chemistry, CVGI iMed, AstraZeneca R&D, Pepparedsleden 1, S-431 83 Mölndal, Sweden
| | - Mike O'Donovan
- Genetic Toxicology, AstraZeneca R&D, Alderley Park, Macclesfield, Cheshire, SK10 4TG, United Kingdom
| | - Peter Sjö
- Department of Medicinal Chemistry, R&I iMed, AstraZeneca R&D, Pepparedsleden 1, S-431 83 Mölndal, Sweden
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17
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Birch AM, Groombridge S, Law R, Leach AG, Mee CD, Schramm C. Rationally Designing Safer Anilines: The Challenging Case of 4-Aminobiphenyls. J Med Chem 2012; 55:3923-33. [DOI: 10.1021/jm3001295] [Citation(s) in RCA: 39] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Alan M. Birch
- AstraZeneca Pharmaceuticals, Mereside, Alderley Park,
Macclesfield, SK10 4TG, U.K
| | - Sam Groombridge
- AstraZeneca Pharmaceuticals, Mereside, Alderley Park,
Macclesfield, SK10 4TG, U.K
| | - Robert Law
- AstraZeneca Pharmaceuticals, Mereside, Alderley Park,
Macclesfield, SK10 4TG, U.K
| | - Andrew G. Leach
- AstraZeneca Pharmaceuticals, Mereside, Alderley Park,
Macclesfield, SK10 4TG, U.K
| | - Christine D. Mee
- AstraZeneca Pharmaceuticals, Mereside, Alderley Park,
Macclesfield, SK10 4TG, U.K
| | - Carolin Schramm
- AstraZeneca Pharmaceuticals, Mereside, Alderley Park,
Macclesfield, SK10 4TG, U.K
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18
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Benigni R, Bossa C. Flexible use of QSAR models in predictive toxicology: a case study on aromatic amines. ENVIRONMENTAL AND MOLECULAR MUTAGENESIS 2012; 53:62-69. [PMID: 22329023 DOI: 10.1002/em.20683] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/31/2023]
Abstract
Over the last years, predictive toxicology approaches based on Structure-Activity Relationships have emerged as fundamental tools in the regulatory assessments of chemicals, especially in those programs where regulatory constraints and assessment schemes limit the amount of data available from experimental test methods. Both the qualitative (e.g., Structural Alerts) and the quantitative (Quantitative Structure-Activity Relationships, QSAR) approach can play important roles. However, the two approaches are not familiar to the same extent to the regulators that most often use only the qualitative approach, so that the potentiality of the more sophisticated QSAR approach is neglected. In fact, QSAR is a very flexible tool that allows the user to modulate its response according to different goals and requirements. Here, we present a non-naïve approach to the use of a QSAR relative to a dichotomous biological activity (such as mutagen/nonmutagen), and we show how the user can maximize alternatively the reliability of the prediction of negative compounds (i.e., safe chemicals) or that of positive chemicals (i.e., chemicals that pose high hazard). Because of the environmental and industrial importance of the class of aromatic amines, we apply the approach to a previously published QSAR on the Salmonella typhimurium mutagenicity of these chemicals.
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Affiliation(s)
- Romualdo Benigni
- Environment and Health Department, Istituto Superiore di Sanità, Viale Regina Elena 299, Roma, Italy.
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19
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McCarren P, Springer C, Whitehead L. An investigation into pharmaceutically relevant mutagenicity data and the influence on Ames predictive potential. J Cheminform 2011; 3:51. [PMID: 22107807 PMCID: PMC3277490 DOI: 10.1186/1758-2946-3-51] [Citation(s) in RCA: 42] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2011] [Accepted: 11/22/2011] [Indexed: 11/29/2022] Open
Abstract
Background In drug discovery, a positive Ames test for bacterial mutation presents a significant hurdle to advancing a drug to clinical trials. In a previous paper, we discussed success in predicting the genotoxicity of reagent-sized aryl-amines (ArNH2), a structure frequently found in marketed drugs and in drug discovery, using quantum mechanics calculations of the energy required to generate the DNA-reactive nitrenium intermediate (ArNH:+). In this paper we approach the question of what molecular descriptors could improve these predictions and whether external data sets are appropriate for further training. Results In trying to extend and improve this model beyond this quantum mechanical reaction energy, we faced considerable difficulty, which was surprising considering the long history and success of QSAR model development for this test. Other quantum mechanics descriptors were compared to this reaction energy including AM1 semi-empirical orbital energies, nitrenium formation with alternative leaving groups, nitrenium charge, and aryl-amine anion formation energy. Nitrenium formation energy, regardless of the starting species, was found to be the most useful single descriptor. External sets used in other QSAR investigations did not present the same difficulty using the same methods and descriptors. When considering all substructures rather than just aryl-amines, we also noted a significantly lower performance for the Novartis set. The performance gap between Novartis and external sets persists across different descriptors and learning methods. The profiles of the Novartis and external data are significantly different both in aryl-amines and considering all substructures. The Novartis and external data sets are easily separated in an unsupervised clustering using chemical fingerprints. The chemical differences are discussed and visualized using Kohonen Self-Organizing Maps trained on chemical fingerprints, mutagenic substructure prevalence, and molecular weight. Conclusions Despite extensive work in the area of predicting this particular toxicity, work in designing and publishing more relevant test sets for compounds relevant to drug discovery is still necessary. This work also shows that great care must be taken in using QSAR models to replace experimental evidence. When considering all substructures, a random forest model, which can inherently cover distinct neighborhoods, built on Novartis data and previously reported external data provided a suitable model.
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Affiliation(s)
- Patrick McCarren
- Novartis Institutes for Biomedical Research, 100 Technology Square, Cambridge, MA 02139, USA.
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Marchant CA. Computational toxicology: a tool for all industries. WILEY INTERDISCIPLINARY REVIEWS-COMPUTATIONAL MOLECULAR SCIENCE 2011. [DOI: 10.1002/wcms.100] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Affiliation(s)
- Carol A. Marchant
- Lhasa Limited, 22‐23 Blenheim Terrace, Woodhouse Lane, Leeds LS2 9HD, UK
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21
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Shamovsky I, Ripa L, Börjesson L, Mee C, Nordén B, Hansen P, Hasselgren C, O’Donovan M, Sjö P. Explanation for Main Features of Structure–Genotoxicity Relationships of Aromatic Amines by Theoretical Studies of Their Activation Pathways in CYP1A2. J Am Chem Soc 2011; 133:16168-85. [DOI: 10.1021/ja206427u] [Citation(s) in RCA: 58] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Affiliation(s)
- Igor Shamovsky
- Department of Medicinal Chemistry, R&I iMed, AstraZeneca R&D, Pepparedsleden 1, S-431 83 Mölndal, Sweden
| | - Lena Ripa
- Department of Medicinal Chemistry, R&I iMed, AstraZeneca R&D, Pepparedsleden 1, S-431 83 Mölndal, Sweden
| | - Lena Börjesson
- Department of Medicinal Chemistry, R&I iMed, AstraZeneca R&D, Pepparedsleden 1, S-431 83 Mölndal, Sweden
| | - Christine Mee
- Genetic Toxicology, AstraZeneca R&D, Alderley Park, Macclesfield, Cheshire SK10 4TG, United Kingdom
| | - Bo Nordén
- Department of Medicinal Chemistry, R&I iMed, AstraZeneca R&D, Pepparedsleden 1, S-431 83 Mölndal, Sweden
| | - Peter Hansen
- Department of Medicinal Chemistry, R&I iMed, AstraZeneca R&D, Pepparedsleden 1, S-431 83 Mölndal, Sweden
| | | | - Mike O’Donovan
- Genetic Toxicology, AstraZeneca R&D, Alderley Park, Macclesfield, Cheshire SK10 4TG, United Kingdom
| | - Peter Sjö
- Department of Medicinal Chemistry, R&I iMed, AstraZeneca R&D, Pepparedsleden 1, S-431 83 Mölndal, Sweden
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