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.

Legacy data sharing to improve drug safety assessment: the eTOX project.

The sharing of legacy preclinical safety data among pharmaceutical companies and its integration with other information sources offers unprecedented opportunities to improve the early assessment of drug safety. Here, we discuss the experience of the eTOX project, which was established through the Innovative Medicines Initiative to explore this possibility.

Value of shared preclinical safety studies - The eTOX database.

A first analysis of a database of shared preclinical safety data for 1214 small molecule drugs and drug candidates extracted from 3970 reports donated by thirteen pharmaceutical companies for the eTOX project (www.etoxproject.eu) is presented. Species, duration of exposure and administration route data were analysed to assess if large enough subsets of homogenous data are available for building in silico predictive models. Prevalence of treatment related effects for the different types of findings recorded were analysed. The eTOX ontology was used to determine the most common treatment-related clinical chemistry and histopathology findings reported in the database. The data were then mined to evaluate sensitivity of established in vivo biomarkers for liver toxicity risk assessment. The value of the database to inform other drug development projects during early drug development is illustrated by a case study.

The eTOX data-sharing project to advance in silico drug-induced toxicity prediction.

The high-quality in vivo preclinical safety data produced by the pharmaceutical industry during drug development, which follows numerous strict guidelines, are mostly not available in the public domain. These safety data are sometimes published as a condensed summary for the few compounds that reach the market, but the majority of studies are never made public and are often difficult to access in an automated way, even sometimes within the owning company itself. It is evident from many academic and industrial examples, that useful data mining and model development requires large and representative data sets and careful curation of the collected data. In 2010, under the auspices of the Innovative Medicines Initiative, the eTOX project started with the objective of extracting and sharing preclinical study data from paper or pdf archives of toxicology departments of the 13 participating pharmaceutical companies and using such data for establishing a detailed, well-curated database, which could then serve as source for read-across approaches (early assessment of the potential toxicity of a drug candidate by comparison of similar structure and/or effects) and training of predictive models. The paper describes the efforts undertaken to allow effective data sharing intellectual property (IP) protection and set up of adequate controlled vocabularies) and to establish the database (currently with over 4000 studies contributed by the pharma companies corresponding to more than 1400 compounds). In addition, the status of predictive models building and some specific features of the eTOX predictive system (eTOXsys) are presented as decision support knowledge-based tools for drug development process at an early stage.

Inroads to predict in vivo toxicology-an introduction to the eTOX Project.

There is a widespread awareness that the wealth of preclinical toxicity data that the pharmaceutical industry has generated in recent decades is not exploited as efficiently as it could be. Enhanced data availability for compound comparison ("read-across"), or for data mining to build predictive tools, should lead to a more efficient drug development process and contribute to the reduction of animal use (3Rs principle). In order to achieve these goals, a consortium approach, grouping numbers of relevant partners, is required. The eTOX ("electronic toxicity") consortium represents such a project and is a public-private partnership within the framework of the European Innovative Medicines Initiative (IMI). The project aims at the development of in silico prediction systems for organ and in vivo toxicity. The backbone of the project will be a database consisting of preclinical toxicity data for drug compounds or candidates extracted from previously unpublished, legacy reports from thirteen European and European operation-based pharmaceutical companies. The database will be enhanced by incorporation of publically available, high quality toxicology data. Seven academic institutes and five small-to-medium size enterprises (SMEs) contribute with their expertise in data gathering, database curation, data mining, chemoinformatics and predictive systems development. The outcome of the project will be a predictive system contributing to early potential hazard identification and risk assessment during the drug development process. The concept and strategy of the eTOX project is described here, together with current achievements and future deliverables.

Diels-Alder reaction between cyclopentadiene and C60: an analysis of the performance of the ONIOM method for the study of chemical reactivity in fullerenes and nanotubes.

In this article, we theoretically analyze the Diels-Alder cycloaddition between cyclopentadiene and C60 for which experimental results on energy barriers and reaction energies are known. The comparison of the results obtained with the two-layered ONIOM approach using different partitions for the high- and low-level layers with those obtained employing the B3LYP/6-31G(d) method for the entire system allows us to conclude that the partition including a pyracylene unit of C60 in the description of the high-level layer is enough to get excellent results. Using this partition in the two-layered ONIOM approach, we have computed the energy barriers and reaction energies for this Diels-Alder reaction for different functionals, and we have compared them with experimental data. From this comparison, both the ONIOM2(M06-2X/6-31G(d):SVWN/STO-3G) and the M06-2X/6-31G(d)//ONIOM2(B3LYP/6-31G(d):SVWN/STO-3G) methods are recommended as reliable and computationally affordable approaches to be exploited for the study of the chemical reactivity of [6,6]-bonds in fullerenes and nanotubes.

A chemogenomic approach to drug discovery: focus on cardiovascular diseases.

References to individual protein targets and bioactive small molecules associated with cardiovascular diseases can be found in multiple bibliographic sources. From mining these sources, a highly curated list of 214 cardiovascular targets was collected and organised using functional classification schemes for the main protein families of therapeutic relevance, namely, enzymes, G-protein-coupled receptors, ion channels, and nuclear receptors. This list was then used to interrogate annotated chemical libraries and extract a chemical space of 44032 small molecules connected to 160 targets. Some of these bioactive ligands were also found to have affinity for an additional set of 421 proteins not linked originally to cardiovascular diseases, thus constituting a valuable indirect source to complete the cardiovascular target space and infer a potential off-cardiovascular target space.

Training multidisciplinary biomedical informatics students: three years of experience.

OBJECTIVE: The European INFOBIOMED Network of Excellence recognized that a successful education program in biomedical informatics should include not only traditional teaching activities in the basic sciences but also the development of skills for working in multidisciplinary teams. DESIGN: A carefully developed 3-year training program for biomedical informatics students addressed these educational aspects through the following four activities: (1) an internet course database containing an overview of all Medical Informatics and BioInformatics courses, (2) a BioMedical Informatics Summer School, (3) a mobility program based on a 'brokerage service' which published demands and offers, including funding for research exchange projects, and (4) training challenges aimed at the development of multi-disciplinary skills. MEASUREMENTS: This paper focuses on experiences gained in the development of novel educational activities addressing work in multidisciplinary teams. The training challenges described here were evaluated by asking participants to fill out forms with Likert scale based questions. For the mobility program a needs assessment was carried out. RESULTS: The mobility program supported 20 exchanges which fostered new BMI research, resulted in a number of peer-reviewed publications and demonstrated the feasibility of this multidisciplinary BMI approach within the European Union. Students unanimously indicated that the training challenge experience had contributed to their understanding and appreciation of multidisciplinary teamwork. CONCLUSION: The training activities undertaken in INFOBIOMED have contributed to a multi-disciplinary BMI approach. It is our hope that this work might provide an impetus for training efforts in Europe, and yield a new generation of biomedical informaticians.

Connecting small molecules to nuclear receptor pathways.

Many efforts are currently being made to connect small molecules to target proteins by extracting pharmacological data from bibliographic sources and storing them in annotated chemical libraries. Here, small molecules are further connected to biological pathways, with particular focus to pathways involving members of the nuclear receptor family. The results bring to light the relative importance for molecules on gaining selectivity at the target level, when the target has an intrinsic promiscuity at the pathway level, and highlight the implications for drug discovery to address current challenges related to poor drug efficacy and toxicity. Details on the main limitations encountered during the molecule-to-target-to-pathway annotation process are also discussed.

Applied information retrieval and multidisciplinary research: new mechanistic hypotheses in complex regional pain syndrome.

BACKGROUND: Collaborative efforts of physicians and basic scientists are often necessary in the investigation of complex disorders. Difficulties can arise, however, when large amounts of information need to reviewed. Advanced information retrieval can be beneficial in combining and reviewing data obtained from the various scientific fields. In this paper, a team of investigators with varying backgrounds has applied advanced information retrieval methods, in the form of text mining and entity relationship tools, to review the current literature, with the intention to generate new insights into the molecular mechanisms underlying a complex disorder. As an example of such a disorder the Complex Regional Pain Syndrome (CRPS) was chosen. CRPS is a painful and debilitating syndrome with a complex etiology that is still unraveled for a considerable part, resulting in suboptimal diagnosis and treatment. RESULTS: A text mining based approach combined with a simple network analysis identified Nuclear Factor kappa B (NFkappaB) as a possible central mediator in both the initiation and progression of CRPS. CONCLUSION: The result shows the added value of a multidisciplinary approach combined with information retrieval in hypothesis discovery in biomedical research. The new hypothesis, which was derived in silico, provides a framework for further mechanistic studies into the underlying molecular mechanisms of CRPS and requires evaluation in clinical and epidemiological studies.

Ligand-based approach to in silico pharmacology: nuclear receptor profiling.

Bioactive ligands are a valuable and increasingly accessible source of information about protein targets. On the basis of this statement, a list of 25 nuclear receptors was described by a series of bioactive ligands extracted directly from bibliographical sources, stored properly in an annotated chemical library, and mathematically represented using the recently reported SHED molecular descriptors. Analysis of this ligand information allowed for derivation of a threshold of nuclear receptor concern. If the similarity of one molecule to any of the molecules annotated to one particular nuclear receptor is below that threshold, the molecule receives an alert on the probability of having affinity below 10 microM for that nuclear receptor. On this basis, a linkage map was constructed that reveals the interaction network of nuclear receptors from the perspective of their active ligands. This ligand-based approach to nuclear receptor profiling was subsequently applied to four external chemical libraries of 10,000 molecules targeted to proteases, kinases, ion channels, and G protein-coupled receptors. The percentage of each library that returned an alert on at least one nuclear receptor was reasonably low and varied between 4.4 and 9.7%. In addition, ligand-based nuclear receptor profiling of a set of 2944 drugs provided an alert for 153 drugs. For some of them, namely, acitretin, telmisartan, phenyltoloxamine, tazarotene, and flumazenil, bibliographical evidence could be found indicating that those drugs may indeed have some potential off-target residual affinity for the nuclear receptors annotated. Overall, the present findings suggest that ligand-based approaches to protein family profiling appear as a promising means toward the establishment of novel tools for in silico pharmacology.

Chemical and biological profiling of an annotated compound library directed to the nuclear receptor family.

Nuclear receptors form a family of ligand-activated transcription factors that regulate a wide variety of biological processes and are thus generally considered relevant targets in drug discovery. We have constructed an annotated compound library directed to nuclear receptors (NRacl) as a means for integrating the chemical and biological data being generated within this family. Special care has been put in the appropriate storage of annotations by using hierarchical classification schemes for both molecules and nuclear receptors, which takes the ability to extract knowledge from annotated compound libraries to another level. Analysis of NRacl has ultimately led to the identification of scaffolds with highly promiscuous nuclear receptor profiles and to the classification of nuclear receptor groups with similar scaffold promiscuity patterns. This information can be exploited in the design of probing libraries for deorphanization activities as well as for devising screening batteries to address selectivity issues.

Theoretical study of the addition patterns of C60 fluorination: C60Fn (n = 1-60).

A systematic study is presented of addition patterns occurring upon fluorination of C60. We use the program SACHA, which increments the number of fluorine addends, tests all available addition sites within a given cutoff radius, and selects the most energetically stable structure for further addition on the basis of full AM1 optimizations for every isomer. The lowest energy structures are optimized at HF/3-21G level of theory. A number of distinct addition routes are predicted, based on octahedral, 'S', and 'T' addition patterns, leading both to experimentally observed C60F(n) isomers and to isomers not previously described in the literature. Furthermore the main addition routes were analyzed for C60F2n isomers, using ab initio global and local aromaticity calculations. For this, magnetizability and NICS calculations have been carried out at HF/3-21G level of theory. We show the possibility of using NICS to predict the next preferential addition site, matching the above-described addition routes.