"Be sustainable": EOSC-Life recommendations for implementation of FAIR principles in life science data handling

The main goals and challenges for the life science communities in the Open Science framework are to increase reuse and sustainability of data resources, software tools, and workflows, especially in large-scale data-driven research and computational analyses. Here, we present key findings, procedures, effective measures and recommendations for generating and establishing sustainable life science resources based on the collaborative, cross-disciplinary work done within the EOSC-Life (European Open Science Cloud for Life Sciences) consortium. Bringing together 13 European life science research infrastructures, it has laid the foundation for an open, digital space to support biological and medical research. Using lessons learned from 27 selected projects, we describe the organisational, technical, financial and legal/ethical challenges that represent the main barriers to sustainability in the life sciences. We show how EOSC-Life provides a model for sustainable data management according to FAIR (findability, accessibility, interoperability, and reusability) principles, including solutions for sensitive- and industry-related resources, by means of cross-disciplinary training and best practices sharing. Finally, we illustrate how data harmonisation and collaborative work facilitate interoperability of tools, data, solutions and lead to a better understanding of concepts, semantics and functionalities in the life sciences.

FAIR+E pathogen data for surveillance and research: lessons from COVID-19

The COVID-19 pandemic has exemplified the importance of interoperable and equitable data sharing for global surveillance and to support research. While many challenges could be overcome, at least in some countries, many hurdles within the organizational, scientific, technical and cultural realms still remain to be tackled to be prepared for future threats. We propose to (i) continue supporting global efforts that have proven to be efficient and trustworthy toward addressing challenges in pathogen molecular data sharing; (ii) establish a distributed network of Pathogen Data Platforms to (a) ensure high quality data, metadata standardization and data analysis, (b) perform data brokering on behalf of data providers both for research and surveillance, (c) foster capacity building and continuous improvements, also for pandemic preparedness; (iii) establish an International One Health Pathogens Portal, connecting pathogen data isolated from various sources (human, animal, food, environment), in a truly One Health approach and following FAIR principles. To address these challenging endeavors, we have started an ELIXIR Focus Group where we invite all interested experts to join in a concerted, expert-driven effort toward sustaining and ensuring high-quality data for global surveillance and research.

POS0403 DYNAMIC CHANGES IN AUTOREACTIVE MEMORY B CELLS IN RHEUMATOID ARTHRITIS: KEY TO UNDERSTANDING IMMUNOLOGICAL DISEASE ACTIVITY

Background

Rheumatoid arthritis (RA) patients with autoantibodies against citrullinated antigens (ACPA) are characterized by poor chances to achieve sustained DMARD free remission. We have previously observed that autoreactive ACPA-expressing memory B cells (MBC) display an activated phenotype and frequently maintain this state of activation even in patients in clinical remission in whom joint inflammation is absent through treatment. Conceptually, these observations could reflect ongoing immunological activity. In fact, they indicate that most current therapeutic interventions do not induce immunological remission and could explain why disease frequently flares when treatment is stopped. ACPA-expressing MBC display the phenotype of recent germinal centre emigrants, actively proliferating (Ki-67 positive), expressing CD95 and co-stimulatory markers CD80 and CD86, and the signature cytokine IL-8.[1] Notably, in autoantibody-positive individuals with arthralgia that did not progress to inflammatory arthritis within 2 years, the autoreactive B cells were readily detectable in the circulation and proliferated but lacked, in most cases, the upregulation of CD80 seen at the onset of disease. Now, we studied these autoreactive B cells longitudinally in the ‘at-risk’ phase of clinically suspect arthralgia (CSA) and in a population of patients in sustained (>1 year) drug-free remission (SDFR).

Objectives

To define dynamic changes of the ACPA-expressing B cell compartment throughout clinical disease stages with the aim to evaluate this response as a possibly predictive biomarker of immunological disease activity.

Methods

ACPA-expressing MBC were identified by flow cytometry in peripheral blood of RA patients with chronic disease or at disease-onset (treatment-naïve), in ACPA-positive CSA patients ‘at-risk’ for RA, and in patients in SDFR. B cells were characterized by a combination of markers to classify B cell subpopulations and activation- and germinal centre related markers. Tetanus-toxoid-specific B cells were analysed in the same individuals as antigen-specific comparators.

Results

In patients in SDFR, significantly less autoreactive B cells expressed CD80 compared to active disease, while they persistently showed signs of proliferation, similar to the phenotype observed in CSA patients that did not progress to RA. ACPA-specific plasmablasts (defined as CD20-CD27hi) were practically absent in SDFR and CSA non-progressors, while they were readily detectable in patients with RA at disease onset, during treatment, and in CSA-individuals that later progressed to RA. Notably, two arthralgia patients that developed RA within one year showed high CD80 expression in the autoreactive MBC compartment already in the ‘at-risk’ phase, whereas patients that so far did not progress to RA during the time of follow-up, showed less CD80-positive autoreactive MBC.

Conclusion

The phenotype of autoreactive B cells is dynamic in different disease phases of RA. By studying extremes of clinical phenotypes (‘at-risk’ phase, disease onset, SDFR), we found evidence for dynamic expression of CD80 by ACPA-expressing MBC in relation to clinical disease stage. Intriguingly, CD80-positive B cells, but not CD80-negative B cells, have been shown to be able to differentiate into antibody secreting cells in mice.[2] Our finding that plasmablasts were practically absent in ACPA-positive arthralgia patients that did not progress to RA and in SDFR would fit with this notion and suggests that in SDFR autoreactive MBC lack, although actively proliferating, triggers that induce CD80 upregulation, differentiation to plasmablasts and, possibly, their active participation in processes causing joint inflammation. Based on this observation, it is possible that induction of this CD80lo phenotype in autoreactive MBC may be an important step towards achieving immunological remission, a conceptual proxy for cure.

References

[1]H. Kristyanto et al., Sci Transl Med12, (2020).

[2]G. V. Zuccarino-Catania et al., Nat Immunol15, 631-637 (2014).

Disclosure of Interests

None declared.

eTRANSAFE: Building a sustainable framework to share reproducible drug safety knowledge with the public domain

Integrative drug safety research in translational health informatics has rapidly evolved and included data that are drawn in from many resources, combining diverse data that are either reused from (curated) repositories, or newly generated at source. Each resource is mandated by different sets of metadata rules that are imposed on the incoming data. Combination of the data cannot be readily achieved without interference of data stewardship and the top-down policy guidelines that supervise and inform the process for data combination to aid meaningful interpretation and analysis of such data.

The eTRANSAFE Consortium's effort to drive integrative drug safety research at a large scale hereby present the lessons learnt and the proposal of solution at the guidelines in practice at this Innovative Medicines Initiative (IMI) project. Recommendations in these guidelines were compiled from feedback received from key stakeholders in regulatory agencies, EFPIA companies, and academic partners. The research reproducibility guidelines presented in this study lay the foundation for a comprehensive data sharing and knowledge management plans accounting for research data management in the drug safety space - FAIR data sharing guidelines, and the model verification guidelines as generic deliverables that best practices that can be reused by other scientific community members at large.

FAIR data sharing is a dynamic landscape that rapidly evolves with fast-paced technology advancements. The research reproducibility in drug safety guidelines introduced in this study provides a reusable framework that can be adopted by other research communities that aim to integrate public and private data in biomedical research space.

The COVID-19 Data Portal: accelerating SARS-CoV-2 and COVID-19 research through rapid open access data sharing

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic will be remembered as one of the defining events of the 21st century. The rapid global outbreak has had significant impacts on human society and is already responsible for millions of deaths. Understanding and tackling the impact of the virus has required a worldwide mobilisation and coordination of scientific research. The COVID-19 Data Portal (https://www.covid19dataportal.org/) was first released as part of the European COVID-19 Data Platform, on April 20th 2020 to facilitate rapid and open data sharing and analysis, to accelerate global SARS-CoV-2 and COVID-19 research. The COVID-19 Data Portal has fortnightly feature releases to continue to add new data types, search options, visualisations and improvements based on user feedback and research. The open datasets and intuitive suite of search, identification and download services, represent a truly FAIR (Findable, Accessible, Interoperable and Reusable) resource that enables researchers to easily identify and quickly obtain the key datasets needed for their COVID-19 research.

AB0022 AUTOREACTIVE B CELLS IN RHEUMATOID ARTHRITIS DISPLAY AN ACTIVATED PHENOTYPE OF RECENT ANTIGEN EXPOSURE

Background:

Rheumatoid arthritis, in particular ACPA+ RA, is characterized by frequent disease flares and poor chances to achieve DMARD-free sustained remission. Recently, we have shown that ACPA-expressing memory B cells (MBC) remain in a persistently activated state throughout disease, even in patients in DMARD-induced clinical remission.(1) The reasons why the ACPA B cell response is continuously activated are unknown, as well as why the response does not revert to a resting, ‘quiescent’ state. We hypothesized that continuous antigen exposure in germinal centres drives ACPA B cell activation, leading to a ‘recent germinal centre emigrant’ phenotype of these cells in the circulation.

Objectives:

To understand whether the activated phenotype of ACPA-expressing B cells could be induced by recent antigen exposure, to thereby discern the processes of immune activation that remain active in patients even in clinical remission and to argue whether these processes could be targets for therapeutic intervention.

Methods:

ACPA-expressing B cells were identified in peripheral blood of RA patients by flow cytometry during different stages of disease and characterized by a panel of activation- and germinal centre related markers (CD80, CD86, CD32, CD95, Ki-67). In addition, three healthy donors received a TT booster vaccination. TT-specific MBC were identified in blood at different timepoints (before vaccination and up to 22 weeks after vaccination) and analysed phenotypically over time.

Results:

The majority of ACPA-expressing B cells strongly expressed CD95 and the co-stimulatory marker CD80. A part was also positive for the proliferation marker Ki-67 (on average 30%), and most cells downregulated the inhibitory marker CD32. TT-specific MBC adopted a comparable phenotype after booster vaccination, but most markers returned to the pre-vaccination expression level gradually over time. These effects were antigen-dependent because the phenotype of TT-negative B cells remained unchanged. The phenotypic composition of the proliferating ACPA-positive B cell pool most closely corresponded to a stimulation history of 1-2 weeks after antigen exposure. Notably, none of the Ki-67 negative ACPA-specific MBC showed phenotypic quiescence, indicating either a short life-time (in circulation) after antigen encounter or persistent additional factors of activation.

Figure 1.

Ki-67 expression on ACPA-specific MBC in RA (A) and on TT-specific MBC in 3 healthy donors before and after booster vaccination (B).

Conclusion:

ACPA-expressing MBC phenotypically resemble TT-specific MBC after recent (1-2 weeks) booster vaccination, reflecting the phenotype of recent germinal centre emigrants, and remain activated, whereas TT-specific MBC lose this marker profile over time. These observations suggest that ACPA-expressing MBC either home to tissue or survive shortly in the circulation, or that additional factors drive or program these cells to persistent activation. Transcriptomic profiling and analysis of the homing marker profile may help to answer these questions. Furthermore, it will be important to understand the association of persistent activation of ACPA-expressing B cells in clinical remission and the risk for disease flares upon treatment discontinuation.

References:

[1]Kristyanto H, Blomberg NJ, Slot LM, van der Voort EIH, Kerkman PF, Bakker A, et al. Persistently activated, proliferative memory autoreactive B cells promote inflammation in rheumatoid arthritis. Sci Transl Med. 2020;12(570).

Disclosure of Interests:

Nienke Blomberg: None declared, Hendy Kristyanto: None declared, Thomas Huizinga Grant/research support from: Gilead, Rene Toes: None declared, Hans Ulrich Scherer Grant/research support from: Pfizer, Lilly, Sanofi, BMS

The eTRANSAFE Project on Translational Safety Assessment through Integrative Knowledge Management: Achievements and Perspectives

eTRANSAFE is a research project funded within the Innovative Medicines Initiative (IMI), which aims at developing integrated databases and computational tools (the eTRANSAFE ToxHub) that support the translational safety assessment of new drugs by using legacy data provided by the pharmaceutical companies that participate in the project. The project objectives include the development of databases containing preclinical and clinical data, computational systems for translational analysis including tools for data query, analysis and visualization, as well as computational models to explain and predict drug safety events.

ELIXIR-EXCELERATE: establishing Europe's data infrastructure for the life science research of the future

A new inter-governmental research infrastructure, ELIXIR, aims to unify bioinformatics resources and life science data across Europe, thereby facilitating their mining and (re-)use.

The ELIXIR Core Data Resources: fundamental infrastructure for the life sciences

Supplementary data are available at Bioinformatics online.

Connecting data, tools and people across Europe: ELIXIR's response to the COVID-19 pandemic

ELIXIR, the European research infrastructure for life science data, provides open access to data, tools and workflows in the response to the COVID-19 pandemic. ELIXIR's 23 nodes have reacted swiftly to support researchers in their combined efforts against the pandemic setting out three joint priorities: 1. Connecting national COVID-19 data platforms to create federated European COVID-19 Data Spaces; 2. Fostering good data management to make COVID-19 data open, FAIR and reusable over the long term; 3. Providing open tools, workflows and computational resources to drive reproducible and collaborative science. ELIXIR's strategy is based on the support given by our national nodes - collectively spanning over 200 institutes - to research projects and on partnering with community initiatives to drive development and adoption of good data practice and community driven standards. ELIXIR Nodes provide support activities locally and internationally, from provisioning compute capabilities to helping collect viral sequence data from hospitals. Some Nodes have prioritised access to their national cloud and compute facilities for all COVID-19 research projects, while others have developed tools to search, access and share all data related to the pandemic in a national healthcare setting.

Towards a European health research and innovation cloud (HRIC)

The European Union (EU) initiative on the Digital Transformation of Health and Care (Digicare) aims to provide the conditions necessary for building a secure, flexible, and decentralized digital health infrastructure. Creating a European Health Research and Innovation Cloud (HRIC) within this environment should enable data sharing and analysis for health research across the EU, in compliance with data protection legislation while preserving the full trust of the participants. Such a HRIC should learn from and build on existing data infrastructures, integrate best practices, and focus on the concrete needs of the community in terms of technologies, governance, management, regulation, and ethics requirements. Here, we describe the vision and expected benefits of digital data sharing in health research activities and present a roadmap that fosters the opportunities while answering the challenges of implementing a HRIC. For this, we put forward five specific recommendations and action points to ensure that a European HRIC: i) is built on established standards and guidelines, providing cloud technologies through an open and decentralized infrastructure; ii) is developed and certified to the highest standards of interoperability and data security that can be trusted by all stakeholders; iii) is supported by a robust ethical and legal framework that is compliant with the EU General Data Protection Regulation (GDPR); iv) establishes a proper environment for the training of new generations of data and medical scientists; and v) stimulates research and innovation in transnational collaborations through public and private initiatives and partnerships funded by the EU through Horizon 2020 and Horizon Europe.

Leveraging European infrastructures to access 1 million human genomes by 2022

Human genomics is undergoing a step change from being a predominantly research-driven activity to one driven through health care as many countries in Europe now have nascent precision medicine programmes. To maximize the value of the genomic data generated, these data will need to be shared between institutions and across countries. In recognition of this challenge, 21 European countries recently signed a declaration to transnationally share data on at least 1 million human genomes by 2022. In this Roadmap, we identify the challenges of data sharing across borders and demonstrate that European research infrastructures are well-positioned to support the rapid implementation of widespread genomic data access.

Registered access: authorizing data access

The Global Alliance for Genomics and Health (GA4GH) proposes a data access policy model-"registered access"-to increase and improve access to data requiring an agreement to basic terms and conditions, such as the use of DNA sequence and health data in research. A registered access policy would enable a range of categories of users to gain access, starting with researchers and clinical care professionals. It would also facilitate general use and reuse of data but within the bounds of consent restrictions and other ethical obligations. In piloting registered access with the Scientific Demonstration data sharing projects of GA4GH, we provide additional ethics, policy and technical guidance to facilitate the implementation of this access model in an international setting.

Identifiers for the 21st century: How to design, provision, and reuse persistent identifiers to maximize utility and impact of life science data

In many disciplines, data are highly decentralized across thousands of online databases (repositories, registries, and knowledgebases). Wringing value from such databases depends on the discipline of data science and on the humble bricks and mortar that make integration possible; identifiers are a core component of this integration infrastructure. Drawing on our experience and on work by other groups, we outline 10 lessons we have learned about the identifier qualities and best practices that facilitate large-scale data integration. Specifically, we propose actions that identifier practitioners (database providers) should take in the design, provision and reuse of identifiers. We also outline the important considerations for those referencing identifiers in various circumstances, including by authors and data generators. While the importance and relevance of each lesson will vary by context, there is a need for increased awareness about how to avoid and manage common identifier problems, especially those related to persistence and web-accessibility/resolvability. We focus strongly on web-based identifiers in the life sciences; however, the principles are broadly relevant to other disciplines.

General guidelines for biomedical software development

Most bioinformatics tools available today were not written by professional software developers, but by people that wanted to solve their own problems, using computational solutions and spending the minimum time and effort possible, since these were just the means to an end. Consequently, a vast number of software applications are currently available, hindering the task of identifying the utility and quality of each. At the same time, this situation has hindered regular adoption of these tools in clinical practice. Typically, they are not sufficiently developed to be used by most clinical researchers and practitioners. To address these issues, it is necessary to re-think how biomedical applications are built and adopt new strategies that ensure quality, efficiency, robustness, correctness and reusability of software components. We also need to engage end-users during the development process to ensure that applications fit their needs. In this review, we present a set of guidelines to support biomedical software development, with an explanation of how they can be implemented and what kind of open-source tools can be used for each specific topic.

General guidelines for biomedical software development

Most bioinformatics tools available today were not written by professional software developers, but by people that wanted to solve their own problems, using computational solutions and spending the minimum time and effort possible, since these were just the means to an end. Consequently, a vast number of software applications are currently available, hindering the task of identifying the utility and quality of each. At the same time, this situation has hindered regular adoption of these tools in clinical practice. Typically, they are not sufficiently developed to be used by most clinical researchers and practitioners. To address these issues, it is necessary to re-think how biomedical applications are built and adopt new strategies that ensure quality, efficiency, robustness, correctness and reusability of software components. We also need to engage end-users during the development process to ensure that applications fit their needs. In this review, we present a set of guidelines to support biomedical software development, with an explanation of how they can be implemented and what kind of open-source tools can be used for each specific topic.

Identifying ELIXIR Core Data Resources

The core mission of ELIXIR is to build a stable and sustainable infrastructure for biological information across Europe. At the heart of this are the data resources, tools and services that ELIXIR offers to the life-sciences community, providing stable and sustainable access to biological data. ELIXIR aims to ensure that these resources are available long-term and that the life-cycles of these resources are managed such that they support the scientific needs of the life-sciences, including biological research.

ELIXIR Core Data Resources are defined as a set of European data resources that are of fundamental importance to the wider life-science community and the long-term preservation of biological data. They are complete collections of generic value to life-science, are considered an authority in their field with respect to one or more characteristics, and show high levels of scientific quality and service. Thus, ELIXIR Core Data Resources are of wide applicability and usage.

This paper describes the structures, governance and processes that support the identification and evaluation of ELIXIR Core Data Resources. It identifies key indicators which reflect the essence of the definition of an ELIXIR Core Data Resource and support the promotion of excellence in resource development and operation. It describes the specific indicators in more detail and explains their application within ELIXIR’s sustainability strategy and science policy actions, and in capacity building, life-cycle management and technical actions. The identification process is currently being implemented and tested for the first time. The findings and outcome will be evaluated by the ELIXIR Scientific Advisory Board in March 2017.

Establishing the portfolio of ELIXIR Core Data Resources and ELIXIR Services is a key priority for ELIXIR and publicly marks the transition towards a cohesive infrastructure.

Identifying ELIXIR Core Data Resources

The core mission of ELIXIR is to build a stable and sustainable infrastructure for biological information across Europe. At the heart of this are the data resources, tools and services that ELIXIR offers to the life-sciences community, providing stable and sustainable access to biological data. ELIXIR aims to ensure that these resources are available long-term and that the life-cycles of these resources are managed such that they support the scientific needs of the life-sciences, including biological research. ELIXIR Core Data Resources are defined as a set of European data resources that are of fundamental importance to the wider life-science community and the long-term preservation of biological data. They are complete collections of generic value to life-science, are considered an authority in their field with respect to one or more characteristics, and show high levels of scientific quality and service. Thus, ELIXIR Core Data Resources are of wide applicability and usage. This paper describes the structures, governance and processes that support the identification and evaluation of ELIXIR Core Data Resources. It identifies key indicators which reflect the essence of the definition of an ELIXIR Core Data Resource and support the promotion of excellence in resource development and operation. It describes the specific indicators in more detail and explains their application within ELIXIR's sustainability strategy and science policy actions, and in capacity building, life-cycle management and technical actions. The identification process is currently being implemented and tested for the first time. The findings and outcome will be evaluated by the ELIXIR Scientific Advisory Board in March 2017. Establishing the portfolio of ELIXIR Core Data Resources and ELIXIR Services is a key priority for ELIXIR and publicly marks the transition towards a cohesive infrastructure.

Making sense of big data in health research: Towards an EU action plan

Medicine and healthcare are undergoing profound changes. Whole-genome sequencing and high-resolution imaging technologies are key drivers of this rapid and crucial transformation. Technological innovation combined with automation and miniaturization has triggered an explosion in data production that will soon reach exabyte proportions. How are we going to deal with this exponential increase in data production? The potential of "big data" for improving health is enormous but, at the same time, we face a wide range of challenges to overcome urgently. Europe is very proud of its cultural diversity; however, exploitation of the data made available through advances in genomic medicine, imaging, and a wide range of mobile health applications or connected devices is hampered by numerous historical, technical, legal, and political barriers. European health systems and databases are diverse and fragmented. There is a lack of harmonization of data formats, processing, analysis, and data transfer, which leads to incompatibilities and lost opportunities. Legal frameworks for data sharing are evolving. Clinicians, researchers, and citizens need improved methods, tools, and training to generate, analyze, and query data effectively. Addressing these barriers will contribute to creating the European Single Market for health, which will improve health and healthcare for all Europeans.

Patterns of database citation in articles and patents indicate long-term scientific and industry value of biological data resources

Data from open access biomolecular data resources, such as the European Nucleotide Archive and the Protein Data Bank are extensively reused within life science research for comparative studies, method development and to derive new scientific insights. Indicators that estimate the extent and utility of such secondary use of research data need to reflect this complex and highly variable data usage. By linking open access scientific literature, via Europe PubMedCentral, to the metadata in biological data resources we separate data citations associated with a deposition statement from citations that capture the subsequent, long-term, reuse of data in academia and industry.  We extend this analysis to begin to investigate citations of biomolecular resources in patent documents. We find citations in more than 8,000 patents from 2014, demonstrating substantial use and an important role for data resources in defining biological concepts in granted patents to both academic and industrial innovators. Combined together our results indicate that the citation patterns in biomedical literature and patents vary, not only due to citation practice but also according to the data resource cited. The results guard against the use of simple metrics such as citation counts and show that indicators of data use must not only take into account citations within the biomedical literature but also include reuse of data in industry and other parts of society by including patents and other scientific and technical documents such as guidelines, reports and grant applications.

The ELIXIR channel in F1000Research

ELIXIR, the European life science infrastructure for biological information, is a unique initiative to consolidate Europe's national centres, services, and core bioinformatics resources into a single, coordinated infrastructure. ELIXIR brings together Europe's major life-science data archives and connects these with national bioinformatics infrastructures  - the ELIXIR Nodes. This editorial introduces the ELIXIR channel in F1000Research; the aim of the channel is to collect and present ELIXIR's scientific and operational output, engage with the broad life science community and encourage discussion on proposed infrastructure solutions. Submissions will be assessed by the ELIXIR channel Advisory Board to ensure they are relevant to ELIXIR community, and subjected to F1000Research open peer review process.

[A Randomized Controlled Trial on the Effect of Earmuffs on Intermittent Hypoxia and Bradycardia in Preterm Infants]

BACKGROUND

Irregular breathing causing hypoxia and bradycardia is a common problem of preterm infants but its pathophysiology is incompletely understood. Agitation provoked by environmental noise may play a role. We wanted to know if earmuffs can at least halve the rate of intermittent hypoxia in premies.

PATIENTS AND METHODS

In this randomized controlled trial 31 infants (14 male; median [min.-max.] birth weight and gestational age: 1 323 g [560-1 990] and 30(1/7) weeks [25(5/7)-33(0/7)]) had the effect of earmuffs on the frequency of pulse oximeter desaturations (SpO(2) <80%) and bradycardia events (<80 beats per minute) tested, documented via a standard home monitor. Infants were measured 2 h each with or without earmuffs; the sequence of intervention was randomised. Measurement conditions were kept constant while a noise meter recorded sound pressure levels at a 1 Hz sampling rate.

RESULTS

Median sound pressure level was 46.8 dB(A). In a pre-study, ear muffs yielded a sound reduction by 7.2 dB. 19 infants had a total of 474 desaturations. The median (25.-75. percentile) number of desaturations was 1 (1-10.5) without, and 1 (1-10) with earmuffs. The amount of infants with at least one desaturation was equal in both treatment protocols. Only 7 bradycardias occurred.

CONCLUSION

The earmuffs had, in a rather quiet environment, no effect on intermittent hypoxia in these infants.

A quick guide for building a successful bioinformatics community

"Scientific community" refers to a group of people collaborating together on scientific-research-related activities who also share common goals, interests, and values. Such communities play a key role in many bioinformatics activities. Communities may be linked to a specific location or institute, or involve people working at many different institutions and locations. Education and training is typically an important component of these communities, providing a valuable context in which to develop skills and expertise, while also strengthening links and relationships within the community. Scientific communities facilitate: (i) the exchange and development of ideas and expertise; (ii) career development; (iii) coordinated funding activities; (iv) interactions and engagement with professionals from other fields; and (v) other activities beneficial to individual participants, communities, and the scientific field as a whole. It is thus beneficial at many different levels to understand the general features of successful, high-impact bioinformatics communities; how individual participants can contribute to the success of these communities; and the role of education and training within these communities. We present here a quick guide to building and maintaining a successful, high-impact bioinformatics community, along with an overview of the general benefits of participating in such communities. This article grew out of contributions made by organizers, presenters, panelists, and other participants of the ISMB/ECCB 2013 workshop "The 'How To Guide' for Establishing a Successful Bioinformatics Network" at the 21st Annual International Conference on Intelligent Systems for Molecular Biology (ISMB) and the 12th European Conference on Computational Biology (ECCB).

Big pharma screening collections: more of the same or unique libraries? The AstraZeneca-Bayer Pharma AG case

In this study, the screening collections of two major pharmaceutical companies (AstraZeneca and Bayer Pharma AG) have been compared using a 2D molecular fingerprint by a nearest neighborhood approach. Results revealed a low overlap between both collections in terms of compound identity and similarity. This emphasizes the value of screening multiple compound collections to expand the chemical space that can be accessed by high-throughput screening (HTS).

SARConnect: A Tool to Interrogate the Connectivity Between Proteins, Chemical Structures and Activity Data

The access and use of large-scale structure-activity relationships (SAR) is increasing as the range of targets and availability of bioactive compound-to-protein mappings expands. However, effective exploitation requires merging and normalisation of activity data, mappings to target classifications as well as visual display of chemical structure relationships. This work describes the development of the application "SARConnect" to address these issues. We discuss options for delivery and analysis of large-scale SAR data together with a set of use-cases to illustrate the design choices and utility. The main activity sources of ChEMBL,1 GOSTAR2 and AstraZeneca's internal system IBIS, had already been integrated in Chemistry Connect.3 For target relationships we selected human UniProtKB/Swiss-Prot4 as our primary source of a heuristic target classification. Similarly, to explore chemical relationships we combined several methods for framework and scaffold analysis into a unified, hierarchical classification where ease of navigation was the primary goal. An application was built on TIBCO Spotfire to retrieve data for visual display. Consequently, users can explore relationships between target, activity and structure across internal, external and commercial sources that encompass approximately 3 million compounds, 2000 human proteins and 10 million activity values. Examples showing the utility of the application are given.

Taking Open Innovation to the Molecular Level - Strengths and Limitations

The ever-growing availability of large-scale open data and its maturation is having a significant impact on industrial drug-discovery, as well as on academic and non-profit research. As industry is changing to an 'open innovation' business concept, precompetitive initiatives and strong public-private partnerships including academic research cooperation partners are gaining more and more importance. Now, the bioinformatics and cheminformatics communities are seeking for web tools which allow the integration of this large volume of life science datasets available in the public domain. Such a data exploitation tool would ideally be able to answer complex biological questions by formulating only one search query. In this short review/perspective, we outline the use of semantic web approaches for data and knowledge integration. Further, we discuss strengths and current limitations of public available data retrieval tools and integrated platforms.

Open PHACTS: semantic interoperability for drug discovery

Open PHACTS is a public-private partnership between academia, publishers, small and medium sized enterprises and pharmaceutical companies. The goal of the project is to deliver and sustain an 'open pharmacological space' using and enhancing state-of-the-art semantic web standards and technologies. It is focused on practical and robust applications to solve specific questions in drug discovery research. OPS is intended to facilitate improvements in drug discovery in academia and industry and to support open innovation and in-house non-public drug discovery research. This paper lays out the challenges and how the Open PHACTS project is hoping to address these challenges technically and socially.

Combinatorial library design from reagent pharmacophore fingerprints

Combinatorial and parallel chemical synthesis technologies are powerful tools in early drug discovery projects. Over the past couple of years an increased emphasis on targeted lead generation libraries and focussed screening libraries in the pharmaceutical industry has driven a surge in computational methods to explore molecular frameworks to establish new chemical equity. In this chapter we describe a complementary technique in the library design process, termed ProSAR, to effectively cover the accessible pharmacophore space around a given scaffold. With this method reagents are selected such that each R-group on the scaffold has an optimal coverage of pharmacophoric features. This is achieved by optimising the Shannon entropy, i.e. the information content, of the topological pharmacophore distribution for the reagents. As this method enumerates compounds with a systematic variation of user-defined pharmacophores to the attachment point on the scaffold, the enumerated compounds may serve as a good starting point for deriving a structure-activity relationship (SAR).

Physicochemical property profiles of marketed drugs, clinical candidates and bioactive compounds

We performed a comparison of several simple physicochemical properties between marketed drugs, clinical candidates and bioactive compounds using commercially available databases (GVKBIO, Hyderabad, India). In contrast to previous studies this comparison was performed at the individual target level. Confirming earlier studies this shows that marketed drugs have, on average and taken as a single set, lower physicochemical property values than the corresponding clinical candidates and bioactive compounds but that there is considerable variation between drug targets. This work complements earlier studies by using a much larger annotated dataset and confirms that there is a shift in physicochemical properties for targets with launched drugs and clinical candidates compared to bioactive compounds.

Structure-based organic synthesis of unnatural aeruginosin hybrids as potent inhibitors of thrombin

Based on X-ray crystallographic data of complexes of chlorodysinosin A with the enzyme thrombin, a series of analogs were synthesized varying the nature of the P(1), P(2), and P(3) pharmacophoric sites and the central octahydroindole carboxyamide core. In general, introduction of a hydrophobic substituent on the d-leucine amide residue dramatically improved the inhibition of the enzyme. This is rationalized based on a better fit of the P(3) subunit in the hydrophobic S(3) enzyme site. Single digit nanomolar inhibition expressed as IC(50) was observed for several analogs.

Development, interpretation and temporal evaluation of a global QSAR of hERG electrophysiology screening data

A 'global' model of hERG K(+) channel was built to satisfy three basic criteria for QSAR models in drug discovery: (1) assessment of the applicability domain, (2) assuring that model decisions can be interpreted by medicinal chemists and (3) assessment of model performance after the model was built. A combination of D-optimal onion design and hierarchical partial least squares modelling was applied to construct a global model of hERG blockade in order to maximize the applicability domain of the model and to enhance its interpretability. Additionally, easily interpretable hERG specific fragment-based descriptors were developed. Model performance was monitored, throughout a time period of 15 months, after model implementation. It was found that after this time duration a greater proportion of molecules were outside the model's applicability domain and that these compounds had a markedly higher average prediction error than those from molecules within the model's applicability domain. The model's predictive performance deteriorated within 4 months after building, illustrating the necessity of regular updating of global models within a drug discovery environment.

Total Synthesis and Structural Confirmation of Chlorodysinosin A

The first enantiocontrolled total synthesis of the marine sponge metabolite chlorodysinosin A is described. The structure and absolute configuration are identical to those of dysinosin A except for the presence of a novel 2S,3R-3-chloroleucine residue in the former. A concise stereocontrolled synthesis of the new chlorine-containing amino acid fragment was developed. An X-ray cocrystal structure of synthetic chlorodysinosin A with the enzyme thrombin confirms the structure and configuration assignment achieved through total synthesis. Within the aeruginosin family of natural products, chlorodysinosin A is the most potent inhibitor of the serine proteases thrombin, factor VIIa, and factor Xa, which are critical enzymes in the process leading to platelet aggregation and fibrin mesh formation in humans.

Multifingerprint Based Similarity Searches for Targeted Class Compound Selection

Molecular fingerprints are widely used for similarity-based virtual screening in drug discovery projects. In this paper we discuss the performance and the complementarity of nine two-dimensional fingerprints (Daylight, Unity, AlFi, Hologram, CATS, TRUST, Molprint 2D, ChemGPS, and ALOGP) in retrieving active molecules by similarity searching against a set of query compounds. For this purpose, we used biological data from HTS screening campaigns of four protein families (GPCRs, kinases, ion channels, and proteases). We have established threshold values for the similarity index (Tanimoto index) to be used as starting points for similarity searches. Based on the complementarities between the selections made by using different fingerprints we propose a multifingerprint approach as an efficient tool to balance the strengths and weaknesses of various fingerprints.

Structure of the PPARalpha and -gamma ligand binding domain in complex with AZ 242; ligand selectivity and agonist activation in the PPAR family

BACKGROUND

The peroxisome proliferator-activated receptors (PPAR) are ligand-activated transcription factors belonging to the nuclear receptor family. The roles of PPARalpha in fatty acid oxidation and PPARgamma in adipocyte differentiation and lipid storage have been characterized extensively. PPARs are activated by fatty acids and eicosanoids and are also targets for antidyslipidemic drugs, but the molecular interactions governing ligand selectivity for specific subtypes are unclear due to the lack of a PPARalpha ligand binding domain structure.

RESULTS

We have solved the crystal structure of the PPARalpha ligand binding domain (LBD) in complex with the combined PPARalpha and -gamma agonist AZ 242, a novel dihydro cinnamate derivative that is structurally different from thiazolidinediones. In addition, we present the crystal structure of the PPARgamma_LBD/AZ 242 complex and provide a rationale for ligand selectivity toward the PPARalpha and -gamma subtypes. Heteronuclear NMR data on PPARalpha in both the apo form and in complex with AZ 242 shows an overall stabilization of the LBD upon agonist binding. A comparison of the novel PPARalpha/AZ 242 complex with the PPARgamma/AZ 242 complex and previously solved PPARgamma structures reveals a conserved hydrogen bonding network between agonists and the AF2 helix.

CONCLUSIONS

The complex of PPARalpha and PPARgamma with the dual specificity agonist AZ 242 highlights the conserved interactions required for receptor activation. Together with the NMR data, this suggests a general model for ligand activation in the PPAR family. A comparison of the ligand binding sites reveals a molecular explanation for subtype selectivity and provides a basis for rational drug design.