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Đukić-Ćosić D, Baralić K, Jorgovanović D, Živančević K, Javorac D, Stojilković N, Radović B, Marić Đ, Ćurčić M, Buha-Đorđević A, Bulat Z, Antonijević-Miljaković E, Antonijević B. 'In silico' toxicology methods in drug safety assessment. ARHIV ZA FARMACIJU 2021. [DOI: 10.5937/arhfarm71-32966] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/02/2022] Open
Abstract
While experimental animal investigation has historically been the most conventional approach conducted to assess drug safety and is currently considered the main method for determining drug toxicity, these studies are constricted by cost, time, and ethical approvals. Over the last 20 years, there have been significant advances in computational sciences and computer data processing, while knowledge of alternative techniques and their application has developed into a valuable skill in toxicology. Thus, the application of in silico methods in drug safety assessment is constantly increasing. They are very complex and are grounded on accumulated knowledge from toxicology, bioinformatics, biochemistry, statistics, mathematics, as well as molecular biology. This review will summarize current state-of-the-art scientific data on the use of in silico methods in toxicity testing, taking into account their shortcomings, and highlighting the strategies that should deliver consistent results, while covering the applications of in silico methods in preclinical trials and drug impurities toxicity testing.
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Coecke S, Ahr H, Blaauboer BJ, Bremer S, Casati S, Castell J, Combes R, Corvi R, Crespi CL, Cunningham ML, Elaut G, Eletti B, Freidig A, Gennari A, Ghersi-Egea JF, Guillouzo A, Hartung T, Hoet P, Ingelman-Sundberg M, Munn S, Janssens W, Ladstetter B, Leahy D, Long A, Meneguz A, Monshouwer M, Morath S, Nagelkerke F, Pelkonen O, Ponti J, Prieto P, Richert L, Sabbioni E, Schaack B, Steiling W, Testai E, Vericat JA, Worth A. Metabolism: A Bottleneck in In Vitro Toxicological Test Development. Altern Lab Anim 2019; 34:49-84. [PMID: 16522150 DOI: 10.1177/026119290603400113] [Citation(s) in RCA: 105] [Impact Index Per Article: 21.0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Affiliation(s)
- Sandra Coecke
- ECVAM, Institute for Health and Consumer Protection, European Commission Joint Research Centre, Ispra, Italy
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Ruiz P, Ingale K, Wheeler JS, Mumtaz M. 3D QSAR studies of hydroxylated polychlorinated biphenyls as potential xenoestrogens. CHEMOSPHERE 2016; 144:2238-2246. [PMID: 26598992 PMCID: PMC8211363 DOI: 10.1016/j.chemosphere.2015.11.004] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/28/2015] [Revised: 09/17/2015] [Accepted: 11/02/2015] [Indexed: 06/01/2023]
Abstract
Mono-hydroxylated polychlorinated biphenyls (OH-PCBs) are found in human biological samples and lack of data on their potential estrogenic activity has been a source of concern. We have extended our previous in silico 2D QSAR study through the application of advance techniques such as docking and 3D QSAR to gain insights into their estrogen receptor (ERα) binding. The results support our earlier findings that the hydroxyl group is the most important feature on the compounds; its position, orientation and surroundings in the structure are influential for the binding of OH-PCBs to ERα. This study has also revealed the following additional interactions that influence estrogenicity of these chemicals (a) the aromatic interactions of the biphenyl moieties with the receptor, (b) hydrogen bonding interactions of the p-hydroxyl group with key amino acids ARG394 and GLU353, (c) low or no electronegative substitution at para-positions of the p-hydroxyl group, (d) enhanced electrostatic interactions at the meta position on the B ring, and (e) co-planarity of the hydroxyl group on the A ring. In combination the 2D and 3D QSAR approaches have led us to the support conclusion that the hydroxyl group is the most important feature on the OH-PCB influencing the binding to estrogen receptors, and have enhanced our understanding of the mechanistic details of estrogenicity of this class of chemicals. Such in silico computational methods could serve as useful tools in risk assessment of chemicals.
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Affiliation(s)
- Patricia Ruiz
- Computational Toxicology and Methods Development Laboratory, Division of Toxicology and Human Health Sciences, Agency for Toxic Substances and Disease Registry, 1600 Clifton Road, MS-F57, Atlanta, GA, 30333, USA.
| | - Kundan Ingale
- VLife Sciences Tech. Pvt. Ltd., Plot No-05, Survey No 131/1b/2/11, Ram Indu Park, Baner Road, Pune, 411045, India
| | - John S Wheeler
- Computational Toxicology and Methods Development Laboratory, Division of Toxicology and Human Health Sciences, Agency for Toxic Substances and Disease Registry, 1600 Clifton Road, MS-F57, Atlanta, GA, 30333, USA
| | - Moiz Mumtaz
- Computational Toxicology and Methods Development Laboratory, Division of Toxicology and Human Health Sciences, Agency for Toxic Substances and Disease Registry, 1600 Clifton Road, MS-F57, Atlanta, GA, 30333, USA
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Sullivan KM, Manuppello JR, Willett CE. Building on a solid foundation: SAR and QSAR as a fundamental strategy to reduce animal testing. SAR AND QSAR IN ENVIRONMENTAL RESEARCH 2014; 25:357-365. [PMID: 24773450 DOI: 10.1080/1062936x.2014.907203] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/03/2023]
Abstract
The development of more efficient, ethical, and effective means of assessing the effects of chemicals on human health and the environment was a lifetime goal of Gilman Veith. His work has provided the foundation for the use of chemical structure for informing toxicological assessment by regulatory agencies the world over. Veith's scientific work influenced the early development of the SAR models in use today at the US Environmental Protection Agency. He was the driving force behind the Organisation for Economic Co-operation and Development QSAR Toolbox. Veith was one of a few early pioneers whose vision led to the linkage of chemical structure and biological activity as a means of predicting adverse apical outcomes (known as a mode of action, or an adverse outcome pathway approach), and he understood at an early stage the power that could be harnessed when combining computational and mechanistic biological approaches as a means of avoiding animal testing. Through the International QSAR Foundation he organized like-minded experts to develop non-animal methods and frameworks for the assessment of chemical hazard and risk for the benefit of public and environmental health. Avoiding animal testing was Gil's passion, and his work helped to initiate the paradigm shift in toxicology that is now rendering this feasible.
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Affiliation(s)
- K M Sullivan
- a Toxicology and Regulatory Testing , Physicians Committee for Responsible Medicine , 5100 Wisconsin Ave NW, Suite 400, Washington , DC , 20016 , USA
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Ruiz P, Myshkin E, Quigley P, Faroon O, Wheeler JS, Mumtaz MM, Brennan RJ. Assessment of hydroxylated metabolites of polychlorinated biphenyls as potential xenoestrogens: a QSAR comparative analysis∗. SAR AND QSAR IN ENVIRONMENTAL RESEARCH 2013; 24:393-416. [PMID: 23557136 DOI: 10.1080/1062936x.2013.781537] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/02/2023]
Abstract
Alternative methods, including quantitative structure-activity relationships (QSAR), are being used increasingly when appropriate data for toxicity evaluation of chemicals are not available. Approximately 40 mono-hydroxylated polychlorinated biphenyls (OH-PCBs) have been identified in humans. They represent a health and environmental concern because some of them have been shown to have agonist or antagonist interactions with human hormone receptors. This could lead to modulation of steroid hormone receptor pathways and endocrine system disruption. We performed QSAR analyses using available estrogenic activity (human estrogen receptor ER alpha) data for 71 OH-PCBs. The modelling was performed using multiple molecular descriptors including electronic, molecular, constitutional, topological, and geometrical endpoints. Multiple linear regressions and recursive partitioning were used to best fit descriptors. The results show that the position of the hydroxyl substitution, polarizability, and meta adjacent un-substituted carbon pairs at the phenolic ring contribute towards greater estrogenic activity for these chemicals. These comparative QSAR models may be used for predictive toxicity, and identification of health consequences of PCB metabolites that lack empirical data. Such information will help prioritize such molecules for additional testing, guide future basic laboratory research studies, and help the health/risk assessment community understand the complex nature of chemical mixtures.
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Affiliation(s)
- P Ruiz
- Division of Toxicology and Human Health Sciences, Agency for Toxic Substances and Disease Registry, Atlanta, USA.
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In Silico Methods for Toxicity Prediction. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2012; 745:96-116. [DOI: 10.1007/978-1-4614-3055-1_7] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/09/2023]
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Hewitt M, Ellison CM. Developing the Applicability Domain of In Silico Models: Relevance, Importance and Methods. IN SILICO TOXICOLOGY 2010. [DOI: 10.1039/9781849732093-00301] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/29/2023]
Abstract
The past two decades has seen the rapid growth in the development and utilisation of computational technologies to predict the toxicity of chemicals. Most notably, widespread pressure to both reduce and replace current animal testing regimes has led to in silico modelling becoming a widely utilised tool in toxicological screening. Unfortunately, given that computational models are open to misuse, there has been, and still is, significant reluctance to accept them for regulatory use. In an effort to combat this, the validation of both model and predictions is now at the forefront of research, with the concept of applicability domain being central to the validation process.
In this chapter the applicability domain concept is defined and numerous methods for its characterisation are detailed and explored with the aid of a case study example. These approaches are shown to span from relatively simple descriptor-based methods to more complex approaches based upon structural similarity or mechanism of action. Given the wealth of differing approaches available and the different information each method yields about the model, a stepwise scheme which considers numerous methods is recommended. With appreciation of model architecture and subsequent utilisation, this chapter shows that a robust and multifaceted applicability domain can be generated. Once defined, the applicability domain serves as a critical screening stage ensuring that a model is fit-for-purpose and predictions are made with maximal confidence.
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Affiliation(s)
- M. Hewitt
- School of Pharmacy and Chemistry, Liverpool John Moores University Byrom Street, Liverpool L3 3AF UK
| | - C. M. Ellison
- School of Pharmacy and Chemistry, Liverpool John Moores University Byrom Street, Liverpool L3 3AF UK
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Pérez-Garrido A, Helguera AM, Rodríguez FG, Cordeiro MNDS. QSAR models to predict mutagenicity of acrylates, methacrylates and alpha,beta-unsaturated carbonyl compounds. Dent Mater 2010; 26:397-415. [PMID: 20122717 DOI: 10.1016/j.dental.2009.11.158] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2009] [Revised: 09/08/2009] [Accepted: 11/26/2009] [Indexed: 11/17/2022]
Abstract
OBJECTIVE The purpose of this study is to develop a quantitative structure-activity relationship (QSAR) model that can distinguish mutagenic from non-mutagenic species with alpha,beta-unsaturated carbonyl moiety using two endpoints for this activity - Ames test and mammalian cell gene mutation test - and also to gather information about the molecular features that most contribute to eliminate the mutagenic effects of these chemicals. METHODS Two data sets were used for modeling the two mutagenicity endpoints: (1) Ames test and (2) mammalian cells mutagenesis. The first one comprised 220 molecules, while the second one 48 substances, ranging from acrylates, methacrylates to alpha,beta-unsaturated carbonyl compounds. The QSAR models were developed by applying linear discriminant analysis (LDA) along with different sets of descriptors computed using the DRAGON software. RESULTS For both endpoints, there was a concordance of 89% in the prediction and 97% confidentiality by combining the three models for the Ames test mutagenicity. We have also identified several structural alerts to assist the design of new monomers. SIGNIFICANCE These individual models and especially their combination are attractive from the point of view of molecular modeling and could be used for the prediction and design of new monomers that do not pose a human health risk.
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Affiliation(s)
- Alfonso Pérez-Garrido
- Enviromental Engineering and Toxicology Dpt., Catholic University of San Antonio, Guadalupe, Murcia, Spain.
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Puzyn T, Leszczynska D, Leszczynski J. Toward the development of "nano-QSARs": advances and challenges. SMALL (WEINHEIM AN DER BERGSTRASSE, GERMANY) 2009; 5:2494-509. [PMID: 19787675 DOI: 10.1002/smll.200900179] [Citation(s) in RCA: 139] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/03/2023]
Abstract
The most significant achievements and challenges relating to an application of quantitative structure-activity relationship (QSAR) approach in the risk assessment of nanometer-sized materials are highlighted. Recent advances are discussed in the context of "classical" QSAR methodology. The possible ways for the structural characterization of compounds existing at the nanoscale (at least one dimension of 100 nm or less) are briefly reviewed. The applicability of the existing toxicological data for developing QSAR models is evaluated. Finally, the existing models are presented. The need to develop new interpretative descriptors for the nanosystems is also highlighted. It is suggested that, due to high variability in the molecular structures and different mechanisms of toxicity, individual classes of nanoparticles should be modeled separately.
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Affiliation(s)
- Tomasz Puzyn
- Interdisciplinary Nanotoxicity Center, Department of Chemistry, Jackson State University, 1325 Lynch St, Jackson, MS 39217-0510, USA
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Hammerling U, Tallsjö A, Grafström R, Ilbäck NG. Comparative Hazard Characterization in Food Toxicology. Crit Rev Food Sci Nutr 2009; 49:626-69. [DOI: 10.1080/10408390802145617] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
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Abstract
In this final chapter a new perspective for the application of QSAR in the nanosciences is discussed. The role of nanomaterials is rapidly increasing in many aspects of everyday life. This is promoting a wide range of research needs related to both the design of new materials with required properties and performing a comprehensive risk assessment of the manufactured nanoparticles. The development of nanoscience also opens new areas for QSAR modelers. We have begun this contribution with a detailed discussion on the remarkable physical–chemical properties of nanomaterials and their specific toxicities. Both these factors should be considered as potential endpoints for further nano-QSAR studies. Then, we have highlighted the status and research needs in the area of molecular descriptors applicable to nanomaterials. Finally, we have put together currently available nano-QSAR models related to the physico-chemical endpoints of nanoparticles and their activity. Although we have observed many problems (i.e., a lack of experimental data, insufficient and inadequate descriptors), we do believe that application of QSAR methodology will significantly support nanoscience in the near future. Development of reliable nano-QSARs can be considered as the next challenging task for the QSAR community.
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Cronin M, Worth A. (Q)SARs for Predicting Effects Relating to Reproductive Toxicity. ACTA ACUST UNITED AC 2008. [DOI: 10.1002/qsar.200710118] [Citation(s) in RCA: 40] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
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Blagg J. Structure–Activity Relationships for In vitro and In vivo Toxicity. ANNUAL REPORTS IN MEDICINAL CHEMISTRY VOLUME 41 2006. [DOI: 10.1016/s0065-7743(06)41024-1] [Citation(s) in RCA: 43] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
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Combes R, Balls M. Intelligent testing strategies for chemicals testing -- a case of more haste, less speed? Altern Lab Anim 2005; 33:289-97. [PMID: 16180981 DOI: 10.1177/026119290503300302] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
The prospects for using (Q)SAR modelling, read-across (chemical) and other non-animal approaches as part of integrated testing strategies for chemical risk assessment, within the framework of the EU REACH legislation, are considered. The potential advantages and limitations of (Q)SAR modelling and read-across methods for chemical regulatory risk assessment are reviewed. It is concluded that it would be premature to base a testing strategy on chemical-based computational modelling approaches, until such time as criteria to validate them for their reliability and relevance by using independent and transparent procedures, have been agreed. This is mainly because of inherent problems in validating and accepting (Q)SARs for regulatory use in ways that are analogous to those that have been developed and applied for in vitro tests. Until this issue has been resolved, it is recommended that testing strategies should be developed which comprise the integrated use of computational and read-across approaches. These should be applied in a cautious and judicious way, in association with available tissue culture methods, and in conjunction with metabolism and biokinetic studies. Such strategies should be intelligently applied by being driven by exposure information (based on bioavailability, not merely on production volume) and hazard information needs, in preference to a tick-box approach. In the meantime, there should be increased efforts to develop improved (Q)SARs, expert systems and new in vitro methods, and, in particular, ways to expedite their validation and acceptance must be found and prospectively agreed with all major stakeholders.
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A topological sub-structural approach to the mutagenic activity in dental monomers. 3. Heterogeneous set of compounds. POLYMER 2005. [DOI: 10.1016/j.polymer.2005.01.064] [Citation(s) in RCA: 16] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
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