@TOME 3.0: Interfacing Protein Structure Modeling and Ligand Docking.

Knowledge of protein-ligand complexes is essential for efficient drug design. Virtual docking can bring important information on putative complexes but it is still far from being simultaneously fast and accurate. Receptors are flexible and adapt to the incoming small molecules while docking is highly sensitive to small conformational deviations. Conformation ensemble is providing a mean to simulate protein flexibility. However, modeling multiple protein structures for many targets is seldom connected to ligand screening in an efficient and straightforward manner. @TOME-3 is an updated version of our former pipeline @TOME-2, in which protein structure modeling is now directly interfaced with flexible ligand docking. Sequence-sequence profile comparisons identify suitable PDB templates for structure modeling and ligands from these templates are used to deduce binding sites to be screened. In addition, bound ligand can be used as pharmacophoric restraint during the virtual docking. The latter is performed by PLANTS while the docking poses are analysed through multiple chemoinformatics functions. This unique combination of tools allows rapid and efficient ligand docking on multiple receptor conformations in parallel. @TOME-3 is freely available on the web at https://atome.cbs.cnrs.fr.

Roadmap towards safe and sustainable advanced and innovative materials. (Outlook for 2024-2030).

The adoption of innovative advanced materials holds vast potential, contingent upon addressing safety and sustainability concerns. The European Commission advocates the integration of Safe and Sustainable by Design (SSbD) principles early in the innovation process to streamline market introduction and mitigate costs. Within this framework, encompassing ecological, social, and economic factors is paramount. The NanoSafety Cluster (NSC) delineates key safety and sustainability areas, pinpointing unresolved issues and research gaps to steer the development of safe(r) materials. Leveraging FAIR data management and integration, alongside the alignment of regulatory aspects, fosters informed decision-making and innovation. Integrating circularity and sustainability mandates clear guidance, ensuring responsible innovation at every stage. Collaboration among stakeholders, anticipation of regulatory demands, and a commitment to sustainability are pivotal for translating SSbD into tangible advancements. Harmonizing standards and test guidelines, along with regulatory preparedness through an exchange platform, is imperative for governance and market readiness. By adhering to these principles, the effective and sustainable deployment of innovative materials can be realized, propelling positive transformation and societal acceptance.

Knowledge infrastructure for integrated data management and analysis supporting new approach methods in predictive toxicology and risk assessment.

The EU-ToxRisk project (2016-2021) was a large European project working towards shifting toxicological testing away from animal tests, towards a toxicological assessment based on comprehensive mechanistic understanding of cause-consequence relationships of chemical adverse effects. More than 40 partners from scientific institutions, industry and regulators coordinated their work towards this goal in a six-year long programme. The breadth and variety of data and knowledge generated, presented a challenging data management landscape. Here, we describe our approach to data management as developed under EU-ToxRisk. The main building blocks of the data infrastructure are: 1) An easy-to-use, extensible data and metadata format; 2) A flexible system with protocols for data capture and sharing from the entire consortium; 3) A methods database for describing and reviewing data generation and processing protocols; 4) Data archiving using a sustainable resource; 5) Data transformation from the archive to the system that provides granular access; 6) Application Programming Interface (API) for access to individual data points; 7) Data exploration and analysis modules, based on a «web notebook¼ approach to executable data processing documentation; and 8) Knowledge portal that ties together all of the above and provides a collaboration space for information exchange across the consortium. This knowledge infrastructure is being extended and refined for the support of follow-up projects (RISK-HUNT3R, ASPIS cluster, European Open Science Cloud (2021-2026)).

Evaluation of the impact of iPSC differentiation protocols on transcriptomic signatures.

Human induced pluripotent stem cells (iPSC) have the potential to produce desired target cell types in vitro and allow for the high-throughput screening of drugs/chemicals at population level thereby minimising the cost of drug discovery and drug withdrawals after clinical trials. There is a substantial need for the characterisation of the iPSC derived models to better understand and utilise them for toxicological relevant applications. In our study, iPSC (SBAD2 or SBAD3 lines obtained from StemBANCC project) were differentiated towards toxicologically relevant cell types: alveolar macrophages, brain capillary endothelial cells, brain cells, endothelial cells, hepatocytes, lung airway epithelium, monocytes, podocytes and renal proximal tubular cells. A targeted transcriptomic approach was employed to understand the effects of differentiation protocols on these cell types. Pearson correlation and principal component analysis (PCA) separated most of the intended target cell types and undifferentiated iPSC models as distinct groups with a high correlation among replicates from the same model. Based on PCA, the intended target cell types could also be separated into the three germ layer groups (ectoderm, endoderm and mesoderm). Differential expression analysis (DESeq2) presented the upregulated genes in each intended target cell types that allowed the evaluation of the differentiation to certain degree and the selection of key differentiation markers. In conclusion, these data confirm the versatile use of iPSC differentiated cell types as standardizable and relevant model systems for in vitro toxicology.

Simplified Method for Removing Direct Oral Anticoagulant Interference in Mechanical Coagulation Test Systems-A Proof of Concept.

BACKGROUND: Direct oral anticoagulants (DOACs) cause unwanted interference in various hemostasis assays, including lupus anticoagulant (LA) testing, where false positive and false negative identification may occur. DOAC Stop (DS) is an activated charcoal (AC) product used to specifically and effectively adsorb DOACs from test plasma. This process normally requires plasma treatment, centrifugation and plasma separation prior to tests, but inexperienced operators may also inadvertently transfer residual AC particles, thereby potentially adversely affecting clot detection. METHODS: We hypothesized that residual DS might not be problematic for mechanical clot detection. We therefore investigated the potential impact of DS and a new DS liquid (DS-L) product on clotting tests using a mechanical clot detection system. Varying concentrations of DS were added to normal and abnormal plasmas with and without DOAC presence. Clotting tests including PT, APTT and dRVVT were performed directly in the analyzer without plasma/DS centrifugation. RESULTS: DS up to double the recommended treatment level had only minor effects on all test results, despite completely obscuring visibility in the plasma/reagent mix. This confirms that the centrifugation step may be able to be omitted when using mechanical detection systems. CONCLUSIONS: Should DS carryover into treated plasmas occur, this should not cause issues with testing performed on mechanical clot-sensing devices. Moreover, we hypothesize that DS can be used directly in these systems, without the need for centrifugation, thereby simplifying its many potential applications.

Capturing time-dependent activation of genes and stress-response pathways using transcriptomics in iPSC-derived renal proximal tubule cells.

Transcriptomic analysis is a powerful method in the utilization of New Approach Methods (NAMs) for identifying mechanisms of toxicity and application to hazard characterization. With this regard, mapping toxicological events to time of exposure would be helpful to characterize early events. Here, we investigated time-dependent changes in gene expression levels in iPSC-derived renal proximal tubular-like cells (PTL) treated with five diverse compounds using TempO-Seq transcriptomics with the aims to evaluate the application of PTL for toxicity prediction and to report on temporal effects for the activation of cellular stress response pathways. PTL were treated with either 50 µM amiodarone, 10 µM sodium arsenate, 5 nM rotenone, or 300 nM tunicamycin over a temporal time course between 1 and 24 h. The TGFß-type I receptor kinase inhibitor GW788388 (1 µM) was used as a negative control. Pathway analysis revealed the induction of key stress-response pathways, including Nrf2 oxidative stress response, unfolding protein response, and metal stress response. Early response genes per pathway were identified much earlier than 24 h and included HMOX1, ATF3, DDIT3, and several MT1 isotypes. GW788388 did not induce any genes within the stress response pathways above, but showed deregulation of genes involved in TGFß inhibition, including downregulation of CYP24A1 and SERPINE1 and upregulation of WT1. This study highlights the application of iPSC-derived renal cells for prediction of cellular toxicity and sheds new light on the temporal and early effects of key genes that are involved in cellular stress response pathways.

European Registry of Materials: global, unique identifiers for (undisclosed) nanomaterials.

Management of nanomaterials and nanosafety data needs to operate under the FAIR (findability, accessibility, interoperability, and reusability) principles and this requires a unique, global identifier for each nanomaterial. Existing identifiers may not always be applicable or sufficient to definitively identify the specific nanomaterial used in a particular study, resulting in the use of textual descriptions in research project communications and reporting. To ensure that internal project documentation can later be linked to publicly released data and knowledge for the specific nanomaterials, or even to specific batches and variants of nanomaterials utilised in that project, a new identifier is proposed: the European Registry of Materials Identifier. We here describe the background to this new identifier, including FAIR interoperability as defined by FAIRSharing, identifiers.org, Bioregistry, and the CHEMINF ontology, and show how it complements other identifiers such as CAS numbers and the ongoing efforts to extend the InChI identifier to cover nanomaterials. We provide examples of its use in various H2020-funded nanosafety projects.

The AOP-DB RDF: Applying FAIR Principles to the Semantic Integration of AOP Data Using the Research Description Framework.

Computational toxicology is central to the current transformation occurring in toxicology and chemical risk assessment. There is a need for more efficient use of existing data to characterize human toxicological response data for environmental chemicals in the US and Europe. The Adverse Outcome Pathway (AOP) framework helps to organize existing mechanistic information and contributes to what is currently being described as New Approach Methodologies (NAMs). AOP knowledge and data are currently submitted directly by users and stored in the AOP-Wiki (https://aopwiki.org/). Automatic and systematic parsing of AOP-Wiki data is challenging, so we have created the EPA Adverse Outcome Pathway Database. The AOP-DB, developed by the US EPA to assist in the biological and mechanistic characterization of AOP data, provides a broad, systems-level overview of the biological context of AOPs. Here we describe the recent semantic mapping efforts for the AOP-DB, and how this process facilitates the integration of AOP-DB data with other toxicologically relevant datasets through a use case example.

Towards a qAOP framework for predictive toxicology - Linking data to decisions.

The adverse outcome pathway (AOP) is a conceptual construct that facilitates organisation and interpretation of mechanistic data representing multiple biological levels and deriving from a range of methodological approaches including in silico, in vitro and in vivo assays. AOPs are playing an increasingly important role in the chemical safety assessment paradigm and quantification of AOPs is an important step towards a more reliable prediction of chemically induced adverse effects. Modelling methodologies require the identification, extraction and use of reliable data and information to support the inclusion of quantitative considerations in AOP development. An extensive and growing range of digital resources are available to support the modelling of quantitative AOPs, providing a wide range of information, but also requiring guidance for their practical application. A framework for qAOP development is proposed based on feedback from a group of experts and three qAOP case studies. The proposed framework provides a harmonised approach for both regulators and scientists working in this area.

An in vitro strategy using multiple human induced pluripotent stem cell-derived models to assess the toxicity of chemicals: A case study on paraquat.

Most OECD guidelines for chemical risk assessment include tests performed on animals, raising financial, ethical and scientific concerns. Thus, the development of human-based models for toxicity testing is highly encouraged. Here, we propose an in vitro multi-organ strategy to assess the toxicity of chemicals. Human induced pluripotent stem cells (hiPSCs)-derived models of the brain, blood-brain barrier, kidney, liver and vasculature were generated and exposed to paraquat (PQ), a widely employed herbicide with known toxic effects in kidneys and brain. The models showed differential cytotoxic sensitivity to PQ after acute exposure. TempO-Seq analysis with a set of 3565 probes revealed the deregulation of oxidative stress, unfolded protein response and estrogen receptor-mediated signaling pathways, in line with the existing knowledge on PQ mechanisms of action. The main advantages of this strategy are to assess chemical toxicity on multiple tissues/organs in parallel, exclusively in human cells, eliminating the interspecies bias, allowing a better evaluation of the differential sensitivity of the models representing the diverse organs, and increasing the chance to identify toxic compounds. Furthermore, although we focused on the mechanisms of action of PQ shared by the different models, this strategy would also allow for organ-specific toxicity testing, by including more cell type-specific probes for TempO-Seq analyses. In conclusion, we believe this strategy will participate in the further improvement of chemical risk assessment for human health.

Integrate mechanistic evidence from new approach methodologies (NAMs) into a read-across assessment to characterise trends in shared mode of action.

Read-across approaches often remain inconclusive as they do not provide sufficient evidence on a common mode of action across the category members. This read-across case study on thirteen, structurally similar, branched aliphatic carboxylic acids investigates the concept of using human-based new approach methods, such as in vitro and in silico models, to demonstrate biological similarity. Five out of the thirteen analogues have preclinical in vivo studies. Three out of them induced lipid accumulation or hypertrophy in preclinical studies with repeated exposure, which leads to the read-across hypothesis that the analogues can potentially induce hepatic steatosis. To confirm the selection of analogues, the expression patterns of the induced differentially expressed genes (DEGs) were analysed in a human liver model. With increasing dose, the expression pattern within the tested analogues got more similar, which serves as a first indication of a common mode of action and suggests differences in the potency of the analogues. Hepatic steatosis is a well-known adverse outcome, for which over 55 adverse outcome pathways have been identified. The resulting adverse outcome pathway (AOP) network, comprised a total 43 MIEs/KEs and enabled the design of an in vitro testing battery. From the AOP network, ten MIEs, early and late KEs were tested to systematically investigate a common mode of action among the grouped compounds. The targeted testing of AOP specific MIE/KEs shows that biological activity in the category decreases with side chain length. A similar trend was evident in measuring liver alterations in zebra fish embryos. However, activation of single MIEs or early KEs at in vivo relevant doses did not necessarily progress to the late KE "lipid accumulation". KEs not related to the read-across hypothesis, testing for example general mitochondrial stress responses in liver cells, showed no trend or biological similarity. Testing scope is a key issue in the design of in vitro test batteries. The Dempster-Shafer decision theory predicted those analogues with in vivo reference data correctly using one human liver model or the CALUX reporter assays. The case study shows that the read-across hypothesis is the key element to designing the testing strategy. In the case of a good mechanistic understanding, an AOP facilitates the selection of reliable human in vitro models to demonstrate a common mode of action. Testing DEGs, MIEs and early KEs served to show biological similarity, whereas the late KEs become important for confirmation, as progression from MIEs to AO is not always guaranteed.

Temporal transcriptomic alterations of cadmium exposed human iPSC-derived renal proximal tubule-like cells.

Cadmium is a well-studied environmental pollutant where the kidney and particularly the proximal tubule cells are especially sensitive as they are exposed to higher concentrations of cadmium than other tissues. Here we investigated the temporal transcriptomic alterations (TempO-Seq) of human induced pluripotent stem cell (iPSC)-derived renal proximal tubule-like (PTL) cells exposed to 5 µM cadmium chloride for 1, 2, 4, 8, 12, 16, 20, 24, 72 and 168 h. There was an early activation (within 4 h) of the metal and oxidative stress responses (metal-responsive transcription factor-1 (MTF1) and nuclear factor erythroid-2-related factor 2 (Nrf2) genes). The Nrf2 response returned to baseline within 24 h. The Activator Protein 1 (AP-1) regulated genes HSPA6 and FOSL-1 followed the Nrf2 time course. While the MTF1 genes also spiked at 4 h, they remained strongly elevated over the entire exposure period. The data and cell culture model utilised will be useful in further research aimed at the refinement of safe human exposure limits for cadmium, other metals and their mixtures.

Evaluation of a human iPSC-derived BBB model for repeated dose toxicity testing with cyclosporine A as model compound.

The blood-brain barrier (BBB) is a highly restrictive barrier that preserves central nervous system homeostasis and ensures optimal brain functioning. Using BBB cell assays makes it possible to investigate whether a compound is likely to compromise BBBs functionality, thereby probably resulting in neurotoxicity. Recently, several protocols to obtain human brain-like endothelial cells (BLECs) from induced pluripotent stem cells (iPSCs) have been reported. Within the framework of the European MSCA-ITN in3 project, we explored the possibility to use an iPSC-derived BBB model to assess the effects of repeated dose treatment with chemicals, using Cyclosporine A (CsA) as a model compound. The BLECs were found to exhibit important BBB characteristics up to 15 days after the end of the differentiation and could be used to assess the effects of repeated dose treatment. Although BLECs were still undergoing transcriptional changes over time, a targeted transcriptome analysis (TempO-Seq) indicated a time and concentration dependent activation of ATF4, XBP1, Nrf2 and p53 stress response pathways under CsA treatment. Taken together, these results demonstrate that this iPSC-derived BBB model and iPSC-derived models in general hold great potential to study the effects of repeated dose exposure with chemicals, allowing personalized and patient-specific studies in the future.

ELIXIR and Toxicology: a community in development.

Toxicology has been an active research field for many decades, with academic, industrial and government involvement. Modern omics and computational approaches are changing the field, from merely disease-specific observational models into target-specific predictive models. Traditionally, toxicology has strong links with other fields such as biology, chemistry, pharmacology and medicine. With the rise of synthetic and new engineered materials, alongside ongoing prioritisation needs in chemical risk assessment for existing chemicals, early predictive evaluations are becoming of utmost importance to both scientific and regulatory purposes. ELIXIR is an intergovernmental organisation that brings together life science resources from across Europe. To coordinate the linkage of various life science efforts around modern predictive toxicology, the establishment of a new ELIXIR Community is seen as instrumental. In the past few years, joint efforts, building on incidental overlap, have been piloted in the context of ELIXIR. For example, the EU-ToxRisk, diXa, HeCaToS, transQST, and the nanotoxicology community have worked with the ELIXIR TeSS, Bioschemas, and Compute Platforms and activities. In 2018, a core group of interested parties wrote a proposal, outlining a sketch of what this new ELIXIR Toxicology Community would look like. A recent workshop (held September 30th to October 1st, 2020) extended this into an ELIXIR Toxicology roadmap and a shortlist of limited investment-high gain collaborations to give body to this new community. This Whitepaper outlines the results of these efforts and defines our vision of the ELIXIR Toxicology Community and how it complements other ELIXIR activities.

Can an InChI for Nano Address the Need for a Simplified Representation of Complex Nanomaterials across Experimental and Nanoinformatics Studies?

Chemoinformatics has developed efficient ways of representing chemical structures for small molecules as simple text strings, simplified molecular-input line-entry system (SMILES) and the IUPAC International Chemical Identifier (InChI), which are machine-readable. In particular, InChIs have been extended to encode formalized representations of mixtures and reactions, and work is ongoing to represent polymers and other macromolecules in this way. The next frontier is encoding the multi-component structures of nanomaterials (NMs) in a machine-readable format to enable linking of datasets for nanoinformatics and regulatory applications. A workshop organized by the H2020 research infrastructure NanoCommons and the nanoinformatics project NanoSolveIT analyzed issues involved in developing an InChI for NMs (NInChI). The layers needed to capture NM structures include but are not limited to: core composition (possibly multi-layered); surface topography; surface coatings or functionalization; doping with other chemicals; and representation of impurities. NM distributions (size, shape, composition, surface properties, etc.), types of chemical linkages connecting surface functionalization and coating molecules to the core, and various crystallographic forms exhibited by NMs also need to be considered. Six case studies were conducted to elucidate requirements for unambiguous description of NMs. The suggested NInChI layers are intended to stimulate further analysis that will lead to the first version of a "nano" extension to the InChI standard.

Metadata Stewardship in Nanosafety Research: Community-Driven Organisation of Metadata Schemas to Support FAIR Nanoscience Data.

The emergence of nanoinformatics as a key component of nanotechnology and nanosafety assessment for the prediction of engineered nanomaterials (NMs) properties, interactions, and hazards, and for grouping and read-across to reduce reliance on animal testing, has put the spotlight firmly on the need for access to high-quality, curated datasets. To date, the focus has been around what constitutes data quality and completeness, on the development of minimum reporting standards, and on the FAIR (findable, accessible, interoperable, and reusable) data principles. However, moving from the theoretical realm to practical implementation requires human intervention, which will be facilitated by the definition of clear roles and responsibilities across the complete data lifecycle and a deeper appreciation of what metadata is, and how to capture and index it. Here, we demonstrate, using specific worked case studies, how to organise the nano-community efforts to define metadata schemas, by organising the data management cycle as a joint effort of all players (data creators, analysts, curators, managers, and customers) supervised by the newly defined role of data shepherd. We propose that once researchers understand their tasks and responsibilities, they will naturally apply the available tools. Two case studies are presented (modelling of particle agglomeration for dose metrics, and consensus for NM dissolution), along with a survey of the currently implemented metadata schema in existing nanosafety databases. We conclude by offering recommendations on the steps forward and the needed workflows for metadata capture to ensure FAIR nanosafety data.

Skin sensitization in silico protocol.

The assessment of skin sensitization has evolved over the past few years to include in vitro assessments of key events along the adverse outcome pathway and opportunistically capitalize on the strengths of in silico methods to support a weight of evidence assessment without conducting a test in animals. While in silico methods vary greatly in their purpose and format; there is a need to standardize the underlying principles on which such models are developed and to make transparent the implications for the uncertainty in the overall assessment. In this contribution, the relationship between skin sensitization relevant effects, mechanisms, and endpoints are built into a hazard assessment framework. Based on the relevance of the mechanisms and effects as well as the strengths and limitations of the experimental systems used to identify them, rules and principles are defined for deriving skin sensitization in silico assessments. Further, the assignments of reliability and confidence scores that reflect the overall strength of the assessment are discussed. This skin sensitization protocol supports the implementation and acceptance of in silico approaches for the prediction of skin sensitization.

The EU-ToxRisk method documentation, data processing and chemical testing pipeline for the regulatory use of new approach methods.

Hazard assessment, based on new approach methods (NAM), requires the use of batteries of assays, where individual tests may be contributed by different laboratories. A unified strategy for such collaborative testing is presented. It details all procedures required to allow test information to be usable for integrated hazard assessment, strategic project decisions and/or for regulatory purposes. The EU-ToxRisk project developed a strategy to provide regulatorily valid data, and exemplified this using a panel of > 20 assays (with > 50 individual endpoints), each exposed to 19 well-known test compounds (e.g. rotenone, colchicine, mercury, paracetamol, rifampicine, paraquat, taxol). Examples of strategy implementation are provided for all aspects required to ensure data validity: (i) documentation of test methods in a publicly accessible database; (ii) deposition of standard operating procedures (SOP) at the European Union DB-ALM repository; (iii) test readiness scoring accoding to defined criteria; (iv) disclosure of the pipeline for data processing; (v) link of uncertainty measures and metadata to the data; (vi) definition of test chemicals, their handling and their behavior in test media; (vii) specification of the test purpose and overall evaluation plans. Moreover, data generation was exemplified by providing results from 25 reporter assays. A complete evaluation of the entire test battery will be described elsewhere. A major learning from the retrospective analysis of this large testing project was the need for thorough definitions of the above strategy aspects, ideally in form of a study pre-registration, to allow adequate interpretation of the data and to ensure overall scientific/toxicological validity.

The effect of DOACs on laboratory tests and their removal by activated carbon to limit interference in functional assays.

We aimed to review the interfering effect of DOACs on tests for haemostatic function and then to discuss overcoming these with activated carbon (AC) products, thereby eliminating DOAC issues from test plasmas. Recent relevant articles were reviewed and are discussed. Laboratory tests for DOACs, lupus anticoagulant, factor assays and APC Resistance were carried out in such publications with and without an AC product on various instruments using reagents approved for diagnostic use in well-regulated clinical laboratories. All reports on this plasma pre-treatment by AC products agree that they extract DOACs from plasma samples with minimal effect on underlying clotting tests. The specific extraction of DOACs significantly reduced false positive lupus anticoagulant detection and provided more reliable results in clotting factor assays, APC resistance and other thrombophilia tests. Dabigatran and edoxaban seem to be adsorbed more thoroughly by AC from plasmas than rivaroxaban and apixaban. In summary, most of the AC products reviewed here appear to remove DOACs from test plasmas without significantly affecting underlying clotting tests and permit correct diagnosis of various haemostatic conditions despite the initial presence of DOACs. The application of such agents as a sample pre-treatment to overcome the effects of DOACs for routine coagulation testing is supported by the emerging literature.