The COVID-19 pandemic has highlighted an important role for drug repurposing. Quaternary ammonium compounds such as ammonium chloride, cetylpyridinium and miramistin represent widely accessible ...antiseptic molecules with well-known broad-spectrum antiviral activities and represent a repurposing opportunity as therapeutics against SARS-CoV-2.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OBVAL, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
•A bibliometric review of drug repurposing provides novel insights into the practice.•Some drugs have been tried in hundreds of diseases.•Even an old drug like chloroquine is actively being tested in ...new therapeutic applications.
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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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
The collection of chemical structure information and associated experimental data for quantitative structure–activity/property relationship (QSAR/QSPR) modeling is facilitated by an increasing number ...of public databases containing large amounts of useful data. However, the performance of QSAR models highly depends on the quality of the data and modeling methodology used. This study aims to develop robust QSAR/QSPR models for chemical properties of environmental interest that can be used for regulatory purposes. This study primarily uses data from the publicly available PHYSPROP database consisting of a set of 13 common physicochemical and environmental fate properties. These datasets have undergone extensive curation using an automated workflow to select only high-quality data, and the chemical structures were standardized prior to calculation of the molecular descriptors. The modeling procedure was developed based on the five Organization for Economic Cooperation and Development (OECD) principles for QSAR models. A weighted k-nearest neighbor approach was adopted using a minimum number of required descriptors calculated using PaDEL, an open-source software. The genetic algorithms selected only the most pertinent and mechanistically interpretable descriptors (2–15, with an average of 11 descriptors). The sizes of the modeled datasets varied from 150 chemicals for biodegradability half-life to 14,050 chemicals for logP, with an average of 3222 chemicals across all endpoints. The optimal models were built on randomly selected training sets (75%) and validated using fivefold cross-validation (CV) and test sets (25%). The CV Q
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of the models varied from 0.72 to 0.95, with an average of 0.86 and an R
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test value from 0.71 to 0.96, with an average of 0.82. Modeling and performance details are described in QSAR model reporting format and were validated by the European Commission’s Joint Research Center to be OECD compliant. All models are freely available as an open-source, command-line application called OPEn structure–activity/property Relationship App (OPERA). OPERA models were applied to more than 750,000 chemicals to produce freely available predicted data on the U.S. Environmental Protection Agency’s CompTox Chemistry Dashboard.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
In August 2015, the US Environmental Protection Agency (EPA) convened a workshop entitled “Advancing non-targeted analyses of xenobiotic chemicals in environmental and biological media.” The purpose ...of the workshop was to bring together the foremost experts in non-targeted analysis (NTA) to discuss the state-of-the-science for generating, interpreting, and exchanging NTA measurement data. During the workshop, participants discussed potential designs for a collaborative project that would use EPA resources, including the ToxCast library of chemical substances, the DSSTox database, and the CompTox Chemicals Dashboard, to evaluate cutting-edge NTA methods. That discussion was the genesis of
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PA’s
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on-
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argeted
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nalysis
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ollaborative
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rial (ENTACT). Nearly 30 laboratories have enrolled in ENTACT and used a variety of chromatography, mass spectrometry, and data processing approaches to characterize ten synthetic chemical mixtures, three standardized media (human serum, house dust, and silicone band) extracts, and thousands of individual substances. Initial results show that nearly all participants have detected and reported more compounds in the mixtures than were intentionally added, with large inter-lab variability in the number of reported compounds. A comparison of gas and liquid chromatography results shows that the majority (45.3%) of correctly identified compounds were detected by only one method and 15.4% of compounds were not identified. Finally, a limited set of true positive identifications indicates substantial differences in observable chemical space when employing disparate separation and ionization techniques as part of NTA workflows. This article describes the genesis of ENTACT, all study methods and materials, and an analysis of results submitted to date.
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DOBA, EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, IZUM, KILJ, KISLJ, MFDPS, NLZOH, NUK, OBVAL, OILJ, PILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UILJ, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Despite an abundance of online databases providing access to chemical data, there is increasing demand for
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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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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
There is an increasing need for comparable and harmonized retention times (t R) in liquid chromatography (LC) among different laboratories, to provide supplementary evidence for the identity of ...compounds in high-resolution mass spectrometry (HRMS)-based suspect and nontarget screening investigations. In this study, a rigorously tested, flexible, and less system-dependent unified retention time index (RTI) approach for LC is presented, based on the calibration of the elution pattern. Two sets of 18 calibrants were selected for each of ESI+ and ESI-based on the maximum overlap with the retention times and chemical similarity indices from a total set of 2123 compounds. The resulting calibration set, with RTI set to range between 1 and 1000, was proposed as the most appropriate RTI system after rigorous evaluation, coordinated by the NORMAN network. The validation of the proposed RTI system was done externally on different instrumentation and LC conditions. The RTI can also be used to check the reproducibility and quality of LC conditions. Two quantitative structure–retention relationship (QSRR)-based models were built based on the developed RTI systems, which assist in the removal of false-positive annotations. The applicability domains of the QSRR models allowed completing the identification process with higher confidence for substances within the domain, while indicating those substances for which results should be treated with caution. The proposed RTI system was used to improve confidence in suspect and nontarget screening and increase the comparability between laboratories as demonstrated for two examples. All RTI-related calculations can be performed online at http://rti.chem.uoa.gr/.
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IJS, KILJ, NUK, PNG, UL, UM
The core goal of cheminformatics is to efficiently store robust and accurate chemical information and make it accessible for drug discovery, environmental analysis, and the development of prediction ...models including quantitative structure–activity relationships (QSAR). The U.S. Environmental Protection Agency (EPA) has developed a web-based application, the CompTox Chemicals Dashboard, which provides access to a compilation of data generated within the agency and sourced from public databases and literature and to utilities for real-time QSAR prediction and chemical read-across. While the vast majority of online tools only allow interrogation of chemicals one at a time, the Dashboard provides a batch search feature that allows for the sourcing of data based on thousands of chemical inputs at one time, by chemical identifier (e.g., names, Chemical Abstract Service registry numbers, or InChIKeys), or by mass or molecular formulas. Chemical information that can then be sourced via the batch search includes chemical identifiers and structures; intrinsic, physicochemical and fate and transport properties; in vitro and in vivo toxicity data; and the presence in environmentally relevant lists. We outline how to use the batch search feature and provide an overview regarding the type of information that can be sourced by considering a series of typical-use questions.
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IJS, KILJ, NUK, PNG, UL, UM
Tens-of-thousands of chemicals are registered in the U.S. for use in countless processes and products. Recent evidence suggests that many of these chemicals are measureable in environmental and/or ...biological systems, indicating the potential for widespread exposures. Traditional public health research tools, including in vivo studies and targeted analytical chemistry methods, have been unable to meet the needs of screening programs designed to evaluate chemical safety. As such, new tools have been developed to enable rapid assessment of potentially harmful chemical exposures and their attendant biological responses. One group of tools, known as "non-targeted analysis" (NTA) methods, allows the rapid characterization of thousands of never-before-studied compounds in a wide variety of environmental, residential, and biological media. This article discusses current applications of NTA methods, challenges to their effective use in chemical screening studies, and ways in which shared resources (e.g., chemical standards, databases, model predictions, and media measurements) can advance their use in risk-based chemical prioritization. A brief review is provided of resources and projects within EPA's Office of Research and Development (ORD) that provide benefit to, and receive benefits from, NTA research endeavors. A summary of EPA's Non-Targeted Analysis Collaborative Trial (ENTACT) is also given, which makes direct use of ORD resources to benefit the global NTA research community. Finally, a research framework is described that shows how NTA methods will bridge chemical prioritization efforts within ORD. This framework exists as a guide for institutions seeking to understand the complexity of chemical exposures, and the impact of these exposures on living systems.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
One approach to speed up drug discovery is to examine new uses for existing approved drugs, so-called ‘drug repositioning’ or ‘drug repurposing’, which has become increasingly popular in recent ...years. Analysis of the literature reveals many examples of US Food and Drug Administration-approved drugs that are active against multiple targets (also termed promiscuity) that can also be used to therapeutic advantage for repositioning for other neglected and rare diseases. Using proof-of-principle examples, we suggest here that with current
in silico technologies and databases of the structures and biological activities of chemical compounds (drugs) and related data, as well as close integration with
in vitro screening data, improved opportunities for drug repurposing will emerge for neglected or rare/orphan diseases.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
Monitored contaminants in drinking water represent a small portion of the total compounds present, many of which may be relevant to human health. To understand the totality of human exposure to ...compounds in drinking water, broader monitoring methods are imperative. In an effort to more fully characterize the drinking water exposome, point-of-use water filtration devices (Brita® filters) were employed to collect time-integrated drinking water samples in a pilot study of nine North Carolina homes. A suspect screening analysis was performed by matching high resolution mass spectra of unknown features to molecular formulas from EPA's DSSTox database. Candidate compounds with those formulas were retrieved from the EPA's CompTox Chemistry Dashboard, a recently developed data hub for approximately 720,000 compounds. To prioritize compounds into those most relevant for human health, toxicity data from the US federal collaborative Tox21 program and the EPA ToxCast program, as well as exposure estimates from EPA's ExpoCast program, were used in conjunction with sample detection frequency and abundance to calculate a “ToxPi” score for each candidate compound. From ∼15,000 molecular features in the raw data, 91 candidate compounds were ultimately grouped into the highest priority class for follow up study. Fifteen of these compounds were confirmed using analytical standards including the highest priority compound, 1,2-Benzisothiazolin-3-one, which appeared in 7 out of 9 samples. The majority of the other high priority compounds are not targets of routine monitoring, highlighting major gaps in our understanding of drinking water exposures. General product-use categories from EPA's CPCat database revealed that several of the high priority chemicals are used in industrial processes, indicating the drinking water in central North Carolina may be impacted by local industries.
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•Drinking water was sampled using point-of-use filters to adsorb organic contaminants.•Suspect screening and non-targeted analyses were performed on the samples.•A novel method for the prioritization of candidate compounds is introduced.•Several high-priority compounds were confirmed using analytical standards.•Product use categories revealed general sources that may be impacting drinking water.
This manuscript advances suspect screening and non-targeted analysis through various data processing tools and reports several concerning compounds found in drinking water.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
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