1
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Pierro JD, Ahir BK, Baker NC, Kleinstreuer NC, Xia M, Knudsen TB. Computational model for fetal skeletal defects potentially linked to disruption of retinoic acid signaling. Front Pharmacol 2022; 13:971296. [PMID: 36172177 PMCID: PMC9511990 DOI: 10.3389/fphar.2022.971296] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2022] [Accepted: 07/21/2022] [Indexed: 11/13/2022] Open
Abstract
All-trans retinoic acid (ATRA) gradients determine skeletal patterning morphogenesis and can be disrupted by diverse genetic or environmental factors during pregnancy, leading to fetal skeleton defects. Adverse Outcome Pathway (AOP) frameworks for ATRA metabolism, signaling, and homeostasis allow for the development of new approach methods (NAMs) for predictive toxicology with less reliance on animal testing. Here, a data-driven model was constructed to identify chemicals associated with both ATRA pathway bioactivity and prenatal skeletal defects. The phenotype data was culled from ToxRefDB prenatal developmental toxicity studies and produced a list of 363 ToxRefDB chemicals with altered skeletal observations. Defects were classified regionally as cranial, post-cranial axial, appendicular, and other (unspecified) features based on ToxRefDB descriptors. To build a multivariate statistical model, high-throughput screening bioactivity data from >8,070 chemicals in ToxCast/Tox21 across 10 in vitro assays relevant to the retinoid signaling system were evaluated and compared to literature-based candidate reference chemicals in the dataset. There were 48 chemicals identified for effects on both in vivo skeletal defects and in vitro ATRA pathway targets for computational modeling. The list included 28 chemicals with prior evidence of skeletal defects linked to retinoid toxicity and 20 chemicals without prior evidence. The combination of thoracic cage defects and DR5 (direct repeats of 5 nucleotides for RAR/RXR transactivation) disruption was the most frequently occurring phenotypic and target disturbance, respectively. This data model provides valuable AOP elucidation and validates current mechanistic understanding. These findings also shed light on potential avenues for new mechanistic discoveries related to ATRA pathway disruption and associated skeletal dysmorphogenesis due to environmental exposures.
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Affiliation(s)
- Jocylin D. Pierro
- Center for Computational Toxicology and Exposure (CCTE), Computational Toxicology and Bioinformatics Branch (CTBB), Office of Research and Development (ORD), U.S. Environmental Protection Agency (USEPA), Research Triangle Park, NC, United States
| | - Bhavesh K. Ahir
- Eurofins Medical Device Testing, Lancaster, PA, United States
| | - Nancy C. Baker
- Scientific Computing and Data Curation Division (SCDCD), Leidos Contractor, Center for Computational Toxicology and Exposure (CCTE), USEPA/ORD, Research Triangle Park, NC, United States
| | - Nicole C. Kleinstreuer
- Interagency Center for the Evaluation of Alternative Toxicological Methods (NICEATM), National Toxicology Program, National Institutes of Health, Research Triangle Park, NC, United States
| | - Menghang Xia
- Division for Pre-Clinical Innovation, National Center for Advancing Translational Sciences, National Institutes of Health, Bethesda, MD, United States
| | - Thomas B. Knudsen
- Center for Computational Toxicology and Exposure (CCTE), Computational Toxicology and Bioinformatics Branch (CTBB), Office of Research and Development (ORD), U.S. Environmental Protection Agency (USEPA), Research Triangle Park, NC, United States
- *Correspondence: Thomas B. Knudsen, , orcid.org/0000-0002-5036-596x
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2
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Martin MM, Baker NC, Boyes WK, Carstens KE, Culbreth ME, Gilbert ME, Harrill JA, Nyffeler J, Padilla S, Friedman KP, Shafer TJ. An expert-driven literature review of "negative" chemicals for developmental neurotoxicity (DNT) in vitro assay evaluation. Neurotoxicol Teratol 2022; 93:107117. [PMID: 35908584 DOI: 10.1016/j.ntt.2022.107117] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2022] [Revised: 06/27/2022] [Accepted: 07/18/2022] [Indexed: 11/26/2022]
Abstract
To date, approximately 200 chemicals have been tested in US Environmental Protection Agency (EPA) or Organization for Economic Co-operation and Development (OECD) developmental neurotoxicity (DNT) guideline studies, leaving thousands of chemicals without traditional animal information on DNT hazard potential. To address this data gap, a battery of in vitro DNT new approach methodologies (NAMs) has been proposed. Evaluation of the performance of this battery will increase the confidence in its use to determine DNT chemical hazards. One approach to evaluate DNT NAM performance is to use a set of chemicals to evaluate sensitivity and specificity. Since a list of chemicals with potential evidence of in vivo DNT has been established, this study aims to develop a curated list of "negative" chemicals for inclusion in a "DNT NAM evaluation set". A workflow, including a literature search followed by an expert-driven literature review, was used to systematically screen 39 chemicals for lack of DNT effect. Expert panel members evaluated the scientific robustness of relevant studies to inform chemical categorizations. Following review, the panel discussed each chemical and made categorical determinations of "Favorable", "Not Favorable", or "Indeterminate" reflecting acceptance, lack of suitability, or uncertainty given specific limitations and considerations, respectively. The panel determined that 10, 22, and 7 chemicals met the criteria for "Favorable", "Not Favorable", and "Indeterminate", for use as negatives in a DNT NAM evaluation set. Ultimately, this approach not only supports DNT NAM performance evaluation but also highlights challenges in identifying large numbers of negative DNT chemicals.
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Affiliation(s)
- Melissa M Martin
- Rapid Assay Development Branch, Biomolecular and Computational Toxicology Division, CCTE/ORD, U.S. Environmental Protection Agency, Research Triangle Park, NC 27711, USA
| | - Nancy C Baker
- Leidos, Research Triangle Park, Research Triangle Park, NC 27711, USA
| | - William K Boyes
- Neurological and Endocrine Toxicology Branch, Public Health and Integrated Toxicology Division, CPHEA/ORD, U.S. Environmental Protection Agency, Research Triangle Park, NC 27711, USA
| | - Kelly E Carstens
- Rapid Assay Development Branch, Biomolecular and Computational Toxicology Division, CCTE/ORD, U.S. Environmental Protection Agency, Research Triangle Park, NC 27711, USA
| | - Megan E Culbreth
- Rapid Assay Development Branch, Biomolecular and Computational Toxicology Division, CCTE/ORD, U.S. Environmental Protection Agency, Research Triangle Park, NC 27711, USA
| | - Mary E Gilbert
- Neurological and Endocrine Toxicology Branch, Public Health and Integrated Toxicology Division, CPHEA/ORD, U.S. Environmental Protection Agency, Research Triangle Park, NC 27711, USA
| | - Joshua A Harrill
- Rapid Assay Development Branch, Biomolecular and Computational Toxicology Division, CCTE/ORD, U.S. Environmental Protection Agency, Research Triangle Park, NC 27711, USA
| | - Johanna Nyffeler
- Rapid Assay Development Branch, Biomolecular and Computational Toxicology Division, CCTE/ORD, U.S. Environmental Protection Agency, Research Triangle Park, NC 27711, USA; Oak Ridge Institute for Science and Education (ORISE), Oak Ridge, TN, USA
| | - Stephanie Padilla
- Rapid Assay Development Branch, Biomolecular and Computational Toxicology Division, CCTE/ORD, U.S. Environmental Protection Agency, Research Triangle Park, NC 27711, USA
| | - Katie Paul Friedman
- Computational Toxicology & Bioinformatics Branch, Biomolecular and Computational Toxicology Division, CCTE/ORD, U.S. Environmental Protection Agency, Research Triangle Park, NC 27711, USA
| | - Timothy J Shafer
- Rapid Assay Development Branch, Biomolecular and Computational Toxicology Division, CCTE/ORD, U.S. Environmental Protection Agency, Research Triangle Park, NC 27711, USA.
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3
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Baker NC, Pierro JD, Taylor LW, Knudsen TB. Identifying candidate reference chemicals for in vitro testing of the retinoid pathway for predictive developmental toxicity. ALTEX 2022; 40:217–236. [PMID: 35796328 PMCID: PMC10765368 DOI: 10.14573/altex.2202231] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/23/2022] [Accepted: 06/21/2022] [Indexed: 11/23/2022]
Abstract
Evaluating chemicals for potential in vivo toxicity based on their in vitro bioactivity profile is an important step toward animal- free testing. A compendium of reference chemicals and data describing their bioactivity on specific molecular targets, cellular pathways, and biological processes is needed to bolster confidence in the predictive value of in vitro hazard detection. Endogenous signaling by all-trans retinoic acid (ATRA) is an important pathway in developmental processes and toxicities. Employing data extraction methods and advanced literature extraction tools, we assembled a set of candidate reference chemicals with demonstrated activity on ten protein family targets in the retinoid system. The compendium was culled from Protein Data Bank, ChEMBL, ToxCast/Tox21, and the biomedical literature in PubMed. Finally, we performed a case study on one chemical in our collection, citral, an inhibitor of endogenous ATRA production, to determine whether the literature supports an adverse outcome pathway explaining the compound’s developmental toxicity initiated by disruption of the retinoid pathway. We also deliver an updated Abstract Sifter tool populated with these reference compounds and complex search terms designed to query the literature for the downstream consequences to support concordance with targeted retinoid pathway disruption.
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Affiliation(s)
| | - Jocylin D. Pierro
- Center for Computational Toxicology and Exposure, U.S. Environmental Protection Agency, Research Triangle Park, NC, USA
| | - Laura W. Taylor
- Center for Computational Toxicology and Exposure, U.S. Environmental Protection Agency, Research Triangle Park, NC, USA
| | - Thomas B. Knudsen
- Center for Computational Toxicology and Exposure, U.S. Environmental Protection Agency, Research Triangle Park, NC, USA
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4
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Bevington C, Williams AJ, Guider C, Baker NC, Meyer B, Babich MA, Robinson S, Jones A, Phillips KA. Development of a Flame Retardant and an Organohalogen Flame Retardant Chemical Inventory. Sci Data 2022. [PMCID: PMC9192637 DOI: 10.1038/s41597-022-01351-0] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022] Open
Abstract
There have been many attempts to compile comprehensive lists of flame retardants. However, this goal has proven challenging due to the heterogeneity of compounds that can be used as flame retardants coupled with changes in formulation chemistry over time. Flame retardants have been the focus of many recent existing hazard, exposure, and risk assessments. These assessments have been class-based or for individual chemical substances. Here, diverse sets of publicly available data sources from governmental organizations and the open literature were compiled to develop an inventory of chemicals used as flame retardants and organohalogen flame retardants. The chemical substances from these data sources were mapped to appropriate chemical identifiers via manual curation and deduplicated. Despite different data sources containing a large number of overlapping chemical substances, compiling information from multiple data sources was found to increase the breadth of potential flame retardant chemistries. The flame retardant and organohalogen flame retardant inventories were developed as a resource for scientists interested in better understanding properties of flame retardant and organohalogen flame retardant classes. Measurement(s) | chemical use information | Technology Type(s) | manual and automated literature collection |
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Piersma AH, Baker NC, Daston GP, Flick B, Fujiwara M, Knudsen TB, Spielmann H, Suzuki N, Tsaioun K, Kojima H. Pluripotent Stem Cell Assays: Modalities and Applications For Predictive Developmental Toxicity. Curr Res Toxicol 2022; 3:100074. [PMID: 35633891 PMCID: PMC9130094 DOI: 10.1016/j.crtox.2022.100074] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2022] [Revised: 04/21/2022] [Accepted: 05/09/2022] [Indexed: 12/02/2022] Open
Abstract
A systematic scoping review of the literature evaluated the embryonic stem cell test (EST). 1533 publications included 18 publications testing 10 or more compounds in human or mouse EST. Selected case examples included 5-fluorouracil, thalidomide, and caffeine. Applicability, limitations, and recommendations for further work are discussed.
This manuscript provides a review focused on embryonic stem cell-based models and their place within the landscape of alternative developmental toxicity assays. Against the background of the principles of developmental toxicology, the wide diversity of alternative methods using pluripotent stem cells developed in this area over the past half century is reviewed. In order to provide an overview of available models, a systematic scoping review was conducted following a published protocol with inclusion criteria, which were applied to select the assays. Critical aspects including biological domain, readout endpoint, availability of standardized protocols, chemical domain, reproducibility and predictive power of each assay are described in detail, in order to review the applicability and limitations of the platform in general and progress moving forward to implementation. The horizon of innovative routes of promoting regulatory implementation of alternative methods is scanned, and recommendations for further work are given.
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6
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Klein JJ, Baker NC, Foil DH, Zorn KM, Urbina F, Puhl AC, Ekins S. Correction to "Using Bibliometric Analysis and Machine Learning to Identify Compounds Binding to Sialidase-1". ACS Omega 2021; 6:16253. [PMID: 34179670 PMCID: PMC8223413 DOI: 10.1021/acsomega.1c02785] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/28/2021] [Indexed: 06/13/2023]
Abstract
[This corrects the article DOI: 10.1021/acsomega.0c05591.].
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Zurlinden TJ, Saili KS, Rush N, Kothiya P, Judson RS, Houck KA, Hunter ES, Baker NC, Palmer JA, Thomas RS, Knudsen TB. Profiling the ToxCast Library With a Pluripotent Human (H9) Stem Cell Line-Based Biomarker Assay for Developmental Toxicity. Toxicol Sci 2021; 174:189-209. [PMID: 32073639 DOI: 10.1093/toxsci/kfaa014] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022] Open
Abstract
The Stemina devTOX quickPredict platform is a human pluripotent stem cell-based assay that predicts the developmental toxicity potential based on changes in cellular metabolism following chemical exposure [Palmer, J. A., Smith, A. M., Egnash, L. A., Conard, K. R., West, P. R., Burrier, R. E., Donley, E. L. R., and Kirchner, F. R. (2013). Establishment and assessment of a new human embryonic stem cell-based biomarker assay for developmental toxicity screening. Birth Defects Res. B Dev. Reprod. Toxicol. 98, 343-363]. Using this assay, we screened 1065 ToxCast phase I and II chemicals in single-concentration or concentration-response for the targeted biomarker (ratio of ornithine to cystine secreted or consumed from the media). The dataset from the Stemina (STM) assay is annotated in the ToxCast portfolio as STM. Major findings from the analysis of ToxCast_STM dataset include (1) 19% of 1065 chemicals yielded a prediction of developmental toxicity, (2) assay performance reached 79%-82% accuracy with high specificity (> 84%) but modest sensitivity (< 67%) when compared with in vivo animal models of human prenatal developmental toxicity, (3) sensitivity improved as more stringent weights of evidence requirements were applied to the animal studies, and (4) statistical analysis of the most potent chemical hits on specific biochemical targets in ToxCast revealed positive and negative associations with the STM response, providing insights into the mechanistic underpinnings of the targeted endpoint and its biological domain. The results of this study will be useful to improving our ability to predict in vivo developmental toxicants based on in vitro data and in silico models.
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Affiliation(s)
| | | | | | | | | | | | - E Sidney Hunter
- National Health and Environmental Effects Research Laboratory (NHEERL), Office of Research and Development (ORD), U.S. Environmental Protection Agency (USEPA), Research Triangle Park, North Carolina
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Klein J, Baker NC, Foil DH, Zorn KM, Urbina F, Puhl AC, Ekins S. Using Bibliometric Analysis and Machine Learning to Identify Compounds Binding to Sialidase-1. ACS Omega 2021; 6:3186-3193. [PMID: 33553934 PMCID: PMC7860073 DOI: 10.1021/acsomega.0c05591] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/16/2020] [Accepted: 01/05/2021] [Indexed: 05/20/2023]
Abstract
Rare diseases impact hundreds of millions of individuals worldwide. However, few therapies exist to treat the rare disease population because financial resources are limited, the number of patients affected is low, bioactivity data is often nonexistent, and very few animal models exist to support preclinical development efforts. Sialidosis is an ultrarare lysosomal storage disorder in which mutations in the NEU1 gene result in the deficiency of the lysosomal enzyme sialidase-1. This enzyme catalyzes the removal of sialic acid moieties from glycoproteins and glycolipids. Therefore, the defective or deficient protein leads to the buildup of sialylated glycoproteins as well as several characteristic symptoms of sialidosis including visual impairment, ataxia, hepatomegaly, dysostosis multiplex, and developmental delay. In this study, we used a bibliometric tool to generate links between lysosomal storage disease (LSD) targets and existing bioactivity data that could be curated in order to build machine learning models and screen compounds in silico. We focused on sialidase as an example, and we used the data curated from the literature to build a Bayesian model which was then used to score compound libraries and rank these molecules for in vitro testing. Two compounds were identified from in vitro testing using microscale thermophoresis, namely sulfameter (K d 2.15 ± 1.02 μM) and mexenone (K d 8.88 ± 4.02 μM), which validated our approach to identifying new molecules binding to this protein, which could represent possible drug candidates that can be evaluated further as potential chaperones for this ultrarare lysosomal disease for which there is currently no treatment. Combining bibliometric and machine learning approaches has the ability to assist in curating small molecule data and model building, respectively, for rare disease drug discovery. This approach also has the capability to identify new compounds that are potential drug candidates.
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Affiliation(s)
- Jennifer
J. Klein
- Collaborations
Pharmaceuticals, Inc., 840 Main Campus Drive, Lab 3510, Raleigh, North Carolina 27606, United States
| | - Nancy C. Baker
- ParlezChem, 123 W Union Street, Hillsborough, North Carolina 27278, United States
| | - Daniel H. Foil
- Collaborations
Pharmaceuticals, Inc., 840 Main Campus Drive, Lab 3510, Raleigh, North Carolina 27606, United States
| | - Kimberley M. Zorn
- Collaborations
Pharmaceuticals, Inc., 840 Main Campus Drive, Lab 3510, Raleigh, North Carolina 27606, United States
| | - Fabio Urbina
- Collaborations
Pharmaceuticals, Inc., 840 Main Campus Drive, Lab 3510, Raleigh, North Carolina 27606, United States
| | - Ana C. Puhl
- Collaborations
Pharmaceuticals, Inc., 840 Main Campus Drive, Lab 3510, Raleigh, North Carolina 27606, United States
| | - Sean Ekins
- Collaborations
Pharmaceuticals, Inc., 840 Main Campus Drive, Lab 3510, Raleigh, North Carolina 27606, United States
- . Phone: 215-687-1320
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Franzosa JA, Bonzo JA, Jack J, Baker NC, Kothiya P, Witek RP, Hurban P, Siferd S, Hester S, Shah I, Ferguson SS, Houck KA, Wambaugh JF. High-throughput toxicogenomic screening of chemicals in the environment using metabolically competent hepatic cell cultures. NPJ Syst Biol Appl 2021; 7:7. [PMID: 33504769 PMCID: PMC7840683 DOI: 10.1038/s41540-020-00166-2] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2020] [Accepted: 10/15/2020] [Indexed: 01/30/2023] Open
Abstract
The ToxCast in vitro screening program has provided concentration-response bioactivity data across more than a thousand assay endpoints for thousands of chemicals found in our environment and commerce. However, most ToxCast screening assays have evaluated individual biological targets in cancer cell lines lacking integrated physiological functionality (such as receptor signaling, metabolism). We evaluated differentiated HepaRGTM cells, a human liver-derived cell model understood to effectively model physiologically relevant hepatic signaling. Expression of 93 gene transcripts was measured by quantitative polymerase chain reaction using Fluidigm 96.96 dynamic arrays in response to 1060 chemicals tested in eight-point concentration-response. A Bayesian framework quantitatively modeled chemical-induced changes in gene expression via six transcription factors including: aryl hydrocarbon receptor, constitutive androstane receptor, pregnane X receptor, farnesoid X receptor, androgen receptor, and peroxisome proliferator-activated receptor alpha. For these chemicals the network model translates transcriptomic data into Bayesian inferences about molecular targets known to activate toxicological adverse outcome pathways. These data also provide new insights into the molecular signaling network of HepaRGTM cell cultures.
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Affiliation(s)
- Jill A Franzosa
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. EPA, Research Triangle Park, NC, 27711, USA
| | - Jessica A Bonzo
- Cell Biology, Biosciences Division, Thermo Fisher Scientific, Frederick, MD, 21703, USA
| | - John Jack
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. EPA, Research Triangle Park, NC, 27711, USA
| | | | - Parth Kothiya
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. EPA, Research Triangle Park, NC, 27711, USA
| | - Rafal P Witek
- Cell Biology, Biosciences Division, Thermo Fisher Scientific, Frederick, MD, 21703, USA
| | | | | | - Susan Hester
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. EPA, Research Triangle Park, NC, 27711, USA
| | - Imran Shah
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. EPA, Research Triangle Park, NC, 27711, USA
| | - Stephen S Ferguson
- Division of National Toxicology Program, National Institutes of Environmental Health Sciences of National Institutes of Health, Durham, NC, 27709, USA
| | - Keith A Houck
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. EPA, Research Triangle Park, NC, 27711, USA
| | - John F Wambaugh
- Center for Computational Toxicology and Exposure, Office of Research and Development, U.S. EPA, Research Triangle Park, NC, 27711, USA.
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10
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Knudsen TB, Pierro JD, Baker NC. Retinoid signaling in skeletal development: Scoping the system for predictive toxicology. Reprod Toxicol 2021; 99:109-130. [DOI: 10.1016/j.reprotox.2020.10.014] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2020] [Revised: 10/15/2020] [Accepted: 10/27/2020] [Indexed: 02/06/2023]
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Abstract
New approach methodologies (NAMs) refer to any non-animal technology, methodology, approach, or combination thereof that can be used to provide information on chemical hazard and risk assessment that avoids the use of intact animals. A spectrum of in silico models is needed for the integrated analysis of various domains in toxicology to improve predictivity and reduce animal testing. This review focuses on in silico approaches, computer models, and computational intelligence for developmental and reproductive toxicity (predictive DART), providing a means to measure toxicodynamics in simulated systems for quantitative prediction of adverse outcomes phenotypes.
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Affiliation(s)
- Thomas B. Knudsen
- Center for Computational Toxicology and Exposure (CCTE), Biomolecular and Computational Toxicology Division (BCTD), Computational Toxicology and Bioinformatics Branch (CTBB), Office of Research and Development (ORD), U.S. Environmental Protection Agency (USEPA), Research Triangle Park NC 27711,Corresponding author:
| | - Richard M. Spencer
- General Dynamics, Contractor, Environmental Modeling and Visualization Laboratory (EMVL), US EPA/ORD, Research Triangle Park NC 27711
| | - Jocylin D. Pierro
- Center for Computational Toxicology and Exposure (CCTE), Biomolecular and Computational Toxicology Division (BCTD), Computational Toxicology and Bioinformatics Branch (CTBB), Office of Research and Development (ORD), U.S. Environmental Protection Agency (USEPA), Research Triangle Park NC 27711
| | - Nancy C. Baker
- Leidos Contractor, Center for Computational Toxicology and Exposure (CCTE), Scientific Computing and Data Curation Division (SCDCD), USEPA/ORD, Research Triangle Park NC 27711
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Heusinkveld HJ, Staal YCM, Baker NC, Daston G, Knudsen TB, Piersma A. An ontology for developmental processes and toxicities of neural tube closure. Reprod Toxicol 2020; 99:160-167. [PMID: 32926990 PMCID: PMC10083840 DOI: 10.1016/j.reprotox.2020.09.002] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2020] [Revised: 08/12/2020] [Accepted: 09/08/2020] [Indexed: 02/07/2023]
Abstract
In recent years, the development and implementation of animal-free approaches to chemical and pharmaceutical hazard and risk assessment has taken off. Alternative approaches are being developed starting from the perspective of human biology and physiology. Neural tube closure is a vital step that occurs early in human development. Correct closure of the neural tube depends on a complex interplay between proteins along a number of protein concentration gradients. The sensitivity of neural tube closure to chemical disturbance of signalling pathways such as the retinoid pathway, is well known. To map the pathways underlying neural tube closure, literature data on the molecular regulation of neural tube closure were collected. As the process of neural tube closure is highly conserved in vertebrates, the extensive literature available for the mouse was used whilst considering its relevance for humans. Thus, important cell compartments, regulatory pathways, and protein interactions essential for neural tube closure under physiological circumstances were identified and mapped. An understanding of aberrant processes leading to neural tube defects (NTDs) requires detailed maps of neural tube embryology, including the complex genetic signals and responses underlying critical cellular dynamical and biomechanical processes. The retinoid signaling pathway serves as a case study for this ontology because of well-defined crosstalk with the genetic control of neural tube patterning and morphogenesis. It is a known target for mechanistically-diverse chemical structures that disrupt neural tube closure The data presented in this manuscript will set the stage for constructing mathematical models and computer simulation of neural tube closure for human-relevant AOPs and predictive toxicology.
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Affiliation(s)
- Harm J Heusinkveld
- Centre for Health Protection, National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands.
| | - Yvonne C M Staal
- Centre for Health Protection, National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands
| | | | - George Daston
- Global Product Stewardship, The Procter & Gamble Company, Cincinnati, OH USA
| | - Thomas B Knudsen
- Center for Computational Toxicology and Exposure, U.S. Environmental Protection Agency, Research Triangle Park NC 27711, USA
| | - Aldert Piersma
- Centre for Health Protection, National Institute for Public Health and the Environment (RIVM), Bilthoven, the Netherlands
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13
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Zurlinden TJ, Saili KS, Rush N, Kothiya P, Judson RS, Houck KA, Hunter ES, Baker NC, Palmer JA, Thomas RS, Knudsen TB. Corrigendum to: "Profiling the ToxCast Library With a Pluripotent Human (H9) Stem Cell Line-Based Biomarker Assay for Developmental Toxicity". Toxicol Sci 2020; 177:301. [PMID: 32529217 DOI: 10.1093/toxsci/kfaa064] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
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14
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Schymanski EL, Baker NC, Williams AJ, Singh RR, Trezzi JP, Wilmes P, Kolber PL, Kruger R, Paczia N, Linster CL, Balling R. Connecting environmental exposure and neurodegeneration using cheminformatics and high resolution mass spectrometry: potential and challenges. Environ Sci Process Impacts 2019; 21:1426-1445. [PMID: 31305828 DOI: 10.1039/c9em00068b] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Connecting chemical exposures over a lifetime to complex chronic diseases with multifactorial causes such as neurodegenerative diseases is an immense challenge requiring a long-term, interdisciplinary approach. Rapid developments in analytical and data technologies, such as non-target high resolution mass spectrometry (NT-HR-MS), have opened up new possibilities to accomplish this, inconceivable 20 years ago. While NT-HR-MS is being applied to increasingly complex research questions, there are still many unidentified chemicals and uncertainties in linking exposures to human health outcomes and environmental impacts. In this perspective, we explore the possibilities and challenges involved in using cheminformatics and NT-HR-MS to answer complex questions that cross many scientific disciplines, taking the identification of potential (small molecule) neurotoxicants in environmental or biological matrices as a case study. We explore capturing literature knowledge and patient exposure information in a form amenable to high-throughput data mining, and the related cheminformatic challenges. We then briefly cover which sample matrices are available, which method(s) could potentially be used to detect these chemicals in various matrices and what remains beyond the reach of NT-HR-MS. We touch on the potential for biological validation systems to contribute to mechanistic understanding of observations and explore which sampling and data archiving strategies may be required to form an accurate, sustained picture of small molecule signatures on extensive cohorts of patients with chronic neurodegenerative disorders. Finally, we reflect on how NT-HR-MS can support unravelling the contribution of the environment to complex diseases.
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Affiliation(s)
- Emma L Schymanski
- Environmental Cheminformatics Group, Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, 6 Avenue du Swing, L-4367 Belvaux, Luxembourg.
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Baker NC, Sipes NS, Franzosa J, Belair DG, Abbott BD, Judson RS, Knudsen TB. Characterizing cleft palate toxicants using ToxCast data, chemical structure, and the biomedical literature. Birth Defects Res 2019; 112:19-39. [PMID: 31471948 DOI: 10.1002/bdr2.1581] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2019] [Revised: 07/23/2019] [Accepted: 07/24/2019] [Indexed: 12/11/2022]
Abstract
Cleft palate has been linked to both genetic and environmental factors that perturb key events during palatal morphogenesis. As a developmental outcome, it presents a challenging, mechanistically complex endpoint for predictive modeling. A data set of 500 chemicals evaluated for their ability to induce cleft palate in animal prenatal developmental studies was compiled from Toxicity Reference Database and the biomedical literature, which included 63 cleft palate active and 437 inactive chemicals. To characterize the potential molecular targets for chemical-induced cleft palate, we mined the ToxCast high-throughput screening database for patterns and linkages in bioactivity profiles and chemical structural descriptors. ToxCast assay results were filtered for cytotoxicity and grouped by target gene activity to produce a "gene score." Following unsuccessful attempts to derive a global prediction model using structural and gene score descriptors, hierarchical clustering was applied to the set of 63 cleft palate positives to extract local structure-bioactivity clusters for follow-up study. Patterns of enrichment were confirmed on the complete data set, that is, including cleft palate inactives, and putative molecular initiating events identified. The clusters corresponded to ToxCast assays for cytochrome P450s, G-protein coupled receptors, retinoic acid receptors, the glucocorticoid receptor, and tyrosine kinases/phosphatases. These patterns and linkages were organized into preliminary decision trees and the resulting inferences were mapped to a putative adverse outcome pathway framework for cleft palate supported by literature evidence of current mechanistic understanding. This general data-driven approach offers a promising avenue for mining chemical-bioassay drivers of complex developmental endpoints where data are often limited.
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Affiliation(s)
| | - Nisha S Sipes
- NIEHS Division of the National Toxicology Program, Research Triangle Park, North Carolina
| | - Jill Franzosa
- IOAA CSS, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina
| | - David G Belair
- NHEERL, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina
| | - Barbara D Abbott
- NHEERL, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina
| | - Richard S Judson
- National Center for Computational Toxicology, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina
| | - Thomas B Knudsen
- National Center for Computational Toxicology, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina
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Piersma AH, Baker NC, Burgoon LD, Daston G, Knudsen TB, Staal YC. An AOP-based ontology for spina bifida caused by disturbance in retinoic acid signaling. Reprod Toxicol 2018. [DOI: 10.1016/j.reprotox.2018.06.077] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/28/2022]
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Saili KS, Zurlinden TJ, Schwab AJ, Silvin A, Baker NC, Hunter ES, Ginhoux F, Knudsen TB. Blood-brain barrier development: Systems modeling and predictive toxicology. Birth Defects Res 2018; 109:1680-1710. [PMID: 29251840 DOI: 10.1002/bdr2.1180] [Citation(s) in RCA: 37] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2017] [Accepted: 11/12/2017] [Indexed: 01/17/2023]
Abstract
The blood-brain barrier (BBB) serves as a gateway for passage of drugs, chemicals, nutrients, metabolites, and hormones between vascular and neural compartments in the brain. Here, we review BBB development with regard to the microphysiology of the neurovascular unit (NVU) and the impact of BBB disruption on brain development. Our focus is on modeling these complex systems. Extant in silico models are available as tools to predict the probability of drug/chemical passage across the BBB; in vitro platforms for high-throughput screening and high-content imaging provide novel data streams for profiling chemical-biological interactions; and engineered human cell-based microphysiological systems provide empirical models with which to investigate the dynamics of NVU function. Computational models are needed that bring together kinetic and dynamic aspects of NVU function across gestation and under various physiological and toxicological scenarios. This integration will inform adverse outcome pathways to reduce uncertainty in translating in vitro data and in silico models for use in risk assessments that aim to protect neurodevelopmental health.
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Affiliation(s)
- Katerine S Saili
- National Center for Computational Toxicology (NCCT); U.S. Environmental Protection Agency, Office of Research and Development, Research Triangle Park, North Carolina 27711
| | - Todd J Zurlinden
- National Center for Computational Toxicology (NCCT); U.S. Environmental Protection Agency, Office of Research and Development, Research Triangle Park, North Carolina 27711
| | - Andrew J Schwab
- National Health and Environmental Effects Research Laboratory (NHEERL), U.S. Environmental Protection Agency, Office of Research and Development, Research Triangle Park, North Carolina 27711
| | - Aymeric Silvin
- Singapore Immunology Network (SIgN), Agency for Science, Technology and Research (A*STAR), 138648, Singapore
| | - Nancy C Baker
- Leidos, contractor to NCCT, Research Triangle Park, North Carolina 27711
| | - E Sidney Hunter
- National Health and Environmental Effects Research Laboratory (NHEERL), U.S. Environmental Protection Agency, Office of Research and Development, Research Triangle Park, North Carolina 27711
| | - Florent Ginhoux
- Singapore Immunology Network (SIgN), Agency for Science, Technology and Research (A*STAR), 138648, Singapore
| | - Thomas B Knudsen
- National Center for Computational Toxicology (NCCT); U.S. Environmental Protection Agency, Office of Research and Development, Research Triangle Park, North Carolina 27711
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Baker NC, Ekins S, Williams AJ, Tropsha A. A bibliometric review of drug repurposing. Drug Discov Today 2018; 23:661-672. [PMID: 29330123 DOI: 10.1016/j.drudis.2018.01.018] [Citation(s) in RCA: 123] [Impact Index Per Article: 20.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2017] [Revised: 11/06/2017] [Accepted: 01/04/2018] [Indexed: 11/15/2022]
Abstract
We have conducted a bibliometric review of drug repurposing by scanning >25 million papers in PubMed and using text-mining methods to gather, count and analyze chemical-disease therapeutic relationships. We find that >60% of the ∼35,000 drugs or drug candidates identified in our study have been tried in more than one disease, including 189 drugs that have been tried in >300 diseases each. Whereas in the majority of cases these drugs were applied in therapeutic areas close to their original use, there have been striking, and perhaps instructive, successful attempts of drug repurposing for unexpected, novel therapeutic areas.
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Affiliation(s)
- Nancy C Baker
- Laboratory for Molecular Modeling, UNC Eshelman School of Pharmacy, UNC Chapel Hill, Chapel Hill, NC 27599, USA; ParlezChem, 123 W Union Street, Hillsborough, NC 27278, USA.
| | - Sean Ekins
- Collaborations Pharmaceuticals, 840 Main Campus Drive, Lab 3510, Raleigh, NC 27606, USA
| | | | - Alexander Tropsha
- Laboratory for Molecular Modeling, UNC Eshelman School of Pharmacy, UNC Chapel Hill, Chapel Hill, NC 27599, USA; Kazan Federal University, Kazan 420008, Russia
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Williams AJ, Grulke CM, Edwards J, McEachran AD, Mansouri K, Baker NC, Patlewicz G, Shah I, Wambaugh JF, Judson RS, Richard AM. The CompTox Chemistry Dashboard: a community data resource for environmental chemistry. J Cheminform 2017; 9:61. [PMID: 29185060 PMCID: PMC5705535 DOI: 10.1186/s13321-017-0247-6] [Citation(s) in RCA: 529] [Impact Index Per Article: 75.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2017] [Accepted: 11/18/2017] [Indexed: 11/10/2022] Open
Abstract
Despite an abundance of online databases providing access to chemical data, there is increasing demand for high-quality, structure-curated, open data to meet the various needs of the environmental sciences and computational toxicology communities. The U.S. Environmental Protection Agency's (EPA) web-based CompTox Chemistry Dashboard is addressing these needs by integrating diverse types of relevant domain data through a cheminformatics layer, built upon a database of curated substances linked to chemical structures. These data include physicochemical, environmental fate and transport, exposure, usage, in vivo toxicity, and in vitro bioassay data, surfaced through an integration hub with link-outs to additional EPA data and public domain online resources. Batch searching allows for direct chemical identifier (ID) mapping and downloading of multiple data streams in several different formats. This facilitates fast access to available structure, property, toxicity, and bioassay data for collections of chemicals (hundreds to thousands at a time). Advanced search capabilities are available to support, for example, non-targeted analysis and identification of chemicals using mass spectrometry. The contents of the chemistry database, presently containing ~ 760,000 substances, are available as public domain data for download. The chemistry content underpinning the Dashboard has been aggregated over the past 15 years by both manual and auto-curation techniques within EPA's DSSTox project. DSSTox chemical content is subject to strict quality controls to enforce consistency among chemical substance-structure identifiers, as well as list curation review to ensure accurate linkages of DSSTox substances to chemical lists and associated data. The Dashboard, publicly launched in April 2016, has expanded considerably in content and user traffic over the past year. It is continuously evolving with the growth of DSSTox into high-interest or data-rich domains of interest to EPA, such as chemicals on the Toxic Substances Control Act listing, while providing the user community with a flexible and dynamic web-based platform for integration, processing, visualization and delivery of data and resources. The Dashboard provides support for a broad array of research and regulatory programs across the worldwide community of toxicologists and environmental scientists.
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Affiliation(s)
- Antony J. Williams
- National Center for Computational Toxicology, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC USA
| | - Christopher M. Grulke
- National Center for Computational Toxicology, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC USA
| | - Jeff Edwards
- National Center for Computational Toxicology, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC USA
| | | | - Kamel Mansouri
- National Center for Computational Toxicology, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC USA
- Oak Ridge Institute for Science and Education, Oak Ridge, TN USA
- ScitoVation LLC, Research Triangle Park, NC USA
| | | | - Grace Patlewicz
- National Center for Computational Toxicology, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC USA
| | - Imran Shah
- National Center for Computational Toxicology, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC USA
| | - John F. Wambaugh
- National Center for Computational Toxicology, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC USA
| | - Richard S. Judson
- National Center for Computational Toxicology, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC USA
| | - Ann M. Richard
- National Center for Computational Toxicology, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC USA
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Ndiwane AN, Baker NC, Makosky A, Reidy P, Guarino AJ. Use of Simulation to Integrate Cultural Humility Into Advanced Health Assessment for Nurse Practitioner Students. J Nurs Educ 2017; 56:567-571. [DOI: 10.3928/01484834-20170817-11] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2016] [Accepted: 03/29/2017] [Indexed: 11/20/2022]
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Abstract
Morphogenetic events are driven by cell-generated physical forces and complex cellular dynamics. To improve our capacity to predict developmental effects from chemical-induced cellular alterations, we built a multicellular agent-based model in CompuCell3D that recapitulates the cellular networks and collective cell behavior underlying growth and fusion of the mammalian secondary palate. The model incorporated multiple signaling pathways (TGFβ, BMP, FGF, EGF, and SHH) in a biological framework to recapitulate morphogenetic events from palatal outgrowth through midline fusion. It effectively simulated higher-level phenotypes (e.g., midline contact, medial edge seam (MES) breakdown, mesenchymal confluence, and fusion defects) in response to genetic or environmental perturbations. Perturbation analysis of various control features revealed model functionality with respect to cell signaling systems and feedback loops for growth and fusion, diverse individual cell behaviors and collective cellular behavior leading to physical contact and midline fusion, and quantitative analysis of the TGF/EGF switch that controls MES breakdown-a key event in morphogenetic fusion. The virtual palate model was then executed with theoretical chemical perturbation scenarios to simulate switch behavior leading to a disruption of fusion following chronic (e.g., dioxin) and acute (e.g., retinoic acid) chemical exposures. This computer model adds to similar systems models toward an integrative "virtual embryo" for simulation and quantitative prediction of adverse developmental outcomes following genetic perturbation and/or environmental disruption.
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Affiliation(s)
- M Shane Hutson
- Department of Physics & Astronomy, Department of Biological Sciences and Vanderbilt Institute for Integrative Biosystem Research & Education, Vanderbilt University , Nashville, Tennessee 37235, United States.,Oak Ridge Institute for Science & Education , Oak Ridge, Tennessee 37832, United States
| | - Maxwell C K Leung
- Oak Ridge Institute for Science & Education , Oak Ridge, Tennessee 37832, United States
| | - Nancy C Baker
- Leidos , Research Triangle Park, Durham, North Carolina 27711 United States
| | - Richard M Spencer
- Leidos , Research Triangle Park, Durham, North Carolina 27711 United States
| | - Thomas B Knudsen
- National Center for Computational Toxicology, Office of Research & Development, U.S. Environmental Protection Agency , Research Triangle Park, Durham, North Carolina 27711, United States
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Leung MC, Phuong J, Baker NC, Sipes NS, Klinefelter GR, Martin MT, McLaurin KW, Setzer RW, Darney SP, Judson RS, Knudsen TB. Systems Toxicology of Male Reproductive Development: Profiling 774 Chemicals for Molecular Targets and Adverse Outcomes. Environ Health Perspect 2016; 124:1050-61. [PMID: 26662846 PMCID: PMC4937872 DOI: 10.1289/ehp.1510385] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/24/2015] [Accepted: 11/24/2015] [Indexed: 05/21/2023]
Abstract
BACKGROUND Trends in male reproductive health have been reported for increased rates of testicular germ cell tumors, low semen quality, cryptorchidism, and hypospadias, which have been associated with prenatal environmental chemical exposure based on human and animal studies. OBJECTIVE In the present study we aimed to identify significant correlations between environmental chemicals, molecular targets, and adverse outcomes across a broad chemical landscape with emphasis on developmental toxicity of the male reproductive system. METHODS We used U.S. EPA's animal study database (ToxRefDB) and a comprehensive literature analysis to identify 774 chemicals that have been evaluated for adverse effects on male reproductive parameters, and then used U.S. EPA's in vitro high-throughput screening (HTS) database (ToxCastDB) to profile their bioactivity across approximately 800 molecular and cellular features. RESULTS A phenotypic hierarchy of testicular atrophy, sperm effects, tumors, and malformations, a composite resembling the human testicular dysgenesis syndrome (TDS) hypothesis, was observed in 281 chemicals. A subset of 54 chemicals with male developmental consequences had in vitro bioactivity on molecular targets that could be condensed into 156 gene annotations in a bipartite network. CONCLUSION Computational modeling of available in vivo and in vitro data for chemicals that produce adverse effects on male reproductive end points revealed a phenotypic hierarchy across animal studies consistent with the human TDS hypothesis. We confirmed the known role of estrogen and androgen signaling pathways in rodent TDS, and importantly, broadened the list of molecular targets to include retinoic acid signaling, vascular remodeling proteins, G-protein coupled receptors (GPCRs), and cytochrome P450s. CITATION Leung MC, Phuong J, Baker NC, Sipes NS, Klinefelter GR, Martin MT, McLaurin KW, Setzer RW, Darney SP, Judson RS, Knudsen TB. 2016. Systems toxicology of male reproductive development: profiling 774 chemicals for molecular targets and adverse outcomes. Environ Health Perspect 124:1050-1061; http://dx.doi.org/10.1289/ehp.1510385.
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Affiliation(s)
- Maxwell C.K. Leung
- Oak Ridge Institute for Science and Education, Oak Ridge, Tennessee
- National Center for Computational Toxicology, U.S. Environmental Protection Agency (EPA), Research Triangle Park, North Carolina
- Address correspondence to M.C.K. Leung, U.S. Environmental Protection Agency, 109 T.W. Alexander Dr., Research Triangle Park, NC 27711 USA. Telephone: (919) 541-2721. E-mail: , or T.B. Knudsen, U.S. Environmental Protection Agency, 109 T.W. Alexander Dr., Research Triangle Park, NC 27711 USA. Telephone: (919) 541-9776. E-mail:
| | - Jimmy Phuong
- National Center for Computational Toxicology, U.S. Environmental Protection Agency (EPA), Research Triangle Park, North Carolina
| | | | - Nisha S. Sipes
- Oak Ridge Institute for Science and Education, Oak Ridge, Tennessee
- National Center for Computational Toxicology, U.S. Environmental Protection Agency (EPA), Research Triangle Park, North Carolina
| | - Gary R. Klinefelter
- National Health and Environmental Effects Research Laboratory, U.S. EPA, Research Triangle Park, North Carolina
| | - Matthew T. Martin
- National Center for Computational Toxicology, U.S. Environmental Protection Agency (EPA), Research Triangle Park, North Carolina
| | - Keith W. McLaurin
- Oak Ridge Institute for Science and Education, Oak Ridge, Tennessee
- National Center for Computational Toxicology, U.S. Environmental Protection Agency (EPA), Research Triangle Park, North Carolina
| | - R. Woodrow Setzer
- National Center for Computational Toxicology, U.S. Environmental Protection Agency (EPA), Research Triangle Park, North Carolina
| | - Sally Perreault Darney
- National Health and Environmental Effects Research Laboratory, U.S. EPA, Research Triangle Park, North Carolina
| | - Richard S. Judson
- National Center for Computational Toxicology, U.S. Environmental Protection Agency (EPA), Research Triangle Park, North Carolina
| | - Thomas B. Knudsen
- National Center for Computational Toxicology, U.S. Environmental Protection Agency (EPA), Research Triangle Park, North Carolina
- Address correspondence to M.C.K. Leung, U.S. Environmental Protection Agency, 109 T.W. Alexander Dr., Research Triangle Park, NC 27711 USA. Telephone: (919) 541-2721. E-mail: , or T.B. Knudsen, U.S. Environmental Protection Agency, 109 T.W. Alexander Dr., Research Triangle Park, NC 27711 USA. Telephone: (919) 541-9776. E-mail:
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Baker NC, Fourches D, Tropsha A. Drug Side Effect Profiles as Molecular Descriptors for Predictive Modeling of Target Bioactivity. Mol Inform 2015; 34:160-70. [DOI: 10.1002/minf.201400134] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2014] [Accepted: 12/16/2014] [Indexed: 11/05/2022]
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Knudsen TB, Sipes NS, Kleinstreuer NC, Rountree MR, Baker NC, Spencer RM, Chandler KJ, Padilla S, Tal T, Hunter ES. Computational toxicology and in silico modeling of embryogenesis. Reprod Toxicol 2012. [DOI: 10.1016/j.reprotox.2012.05.022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
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Garcerant D, Rubiano L, Blanco V, Martinez J, Baker NC, Craft N. Possible links between sickle cell crisis and pentavalent antimony. Am J Trop Med Hyg 2012; 86:1057-61. [PMID: 22665619 DOI: 10.4269/ajtmh.2012.11-0683] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022] Open
Abstract
For over 60 years, pentavalent antimony (Sb(v)) has been the first-line treatment of leishmaniasis. Sickle cell anemia is a disease caused by a defect in red blood cells, which among other things can cause vasooclusive crisis. We report the case of a 6-year-old child with leishmaniasis who during treatment with meglumine antimoniate developed a sickle cell crisis (SCC). No previous reports describing the relationship between antimonial drugs and sickle cell disease were found. Reviews of both the pathophysiology of SCC and the mechanism of action of Sb(v) revealed that a common pathway (glutathione) may have resulted in the SCC. ChemoText, a novel database created to predict chemical-protein-disease interactions, was used to perform a more expansive and systematic review that was able to support the association between glutathione, Sb(v), and SCC. Although suggestive evidence to support the hypothesis, additional research at the bench would be needed to prove Sb(v) caused the SCC.
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Affiliation(s)
- Daniel Garcerant
- CIDEIM: Centro Internacional De Entrenamiento E Investigaciones Médicas (International Center for Medical Research and Training), Cali, Colombia.
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Baker NC, Hemminger BM. Mining connections between chemicals, proteins, and diseases extracted from Medline annotations. J Biomed Inform 2010; 43:510-9. [PMID: 20348023 PMCID: PMC2902698 DOI: 10.1016/j.jbi.2010.03.008] [Citation(s) in RCA: 37] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2009] [Revised: 02/15/2010] [Accepted: 03/22/2010] [Indexed: 10/19/2022]
Abstract
The biomedical literature is an important source of information about the biological activity and effects of chemicals. We present an application that extracts terms indicating biological activity of chemicals from Medline records, associates them with chemical name and stores the terms in a repository called ChemoText. We describe the construction of ChemoText and then demonstrate its utility in drug research by employing Swanson's ABC discovery paradigm. We reproduce Swanson's discovery of a connection between magnesium and migraine in a novel approach that uses only proteins as the intermediate B terms. We validate our methods by using a cutoff date and evaluate them by calculating precision and recall. In addition to magnesium, we have identified valproic acid and nitric oxide as chemicals which developed links to migraine. We hypothesize, based on protein annotations, that zinc and retinoic acid may play a role in migraine. The ChemoText repository has promise as a data source for drug discovery.
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Affiliation(s)
- Nancy C Baker
- School of Information and Library Science, University of North Carolina, Chapel Hill, NC, USA.
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Baker NC, Cerone SB, Gaze N, Knapp TR. The effect of type of thermometer and length of time inserted on oral temperature measurements of afebrile subjects. Nurs Res 1984; 33:109-11. [PMID: 6560422] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/05/2023]
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Baker NC. Nurses as news. Nurs Health Care 1982; 3:132-3, 137. [PMID: 6918796] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
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Baker NC, Hart CA. Building support for the circulator issue. AORN J 1982; 35:722-31. [PMID: 6917734 DOI: 10.1016/s0001-2092(07)63922-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
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Baker NC, Hart C. Nurses in action. Nurs Health Care 1981; 2:130-2. [PMID: 6906613] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
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