EMBL-EBI Powerpoint Presentation

Total Page:16

File Type:pdf, Size:1020Kb

EMBL-EBI Powerpoint Presentation Chemical Resources – ChEMBL Anne Hersey – ChEMBL Group EBI is an Outstation of the European Molecular Biology Laboratory. Overview of Talk • ChEMBL Content • ChEMBL Use Cases • UniChem Opportunity for hands-on use of ChEMBL tomorrow afternoon 2 What is ChEMBL • Open access database for drug discovery • Freely available (searchable and downloadable) • Content: • Bioactivity data manually extracted from the primary medicinal chemistry literature from journals such as J. Med. Chem. • Deposited data e.g. neglected disease screening, GSK kinase set • Subset of data from PubChem • Bioactivity data is associated with a biological target and a chemical structure • Compounds are stored in a structure searchable format • Protein targets are linked to protein sequences in UniProt • Updated regularly with new data • Secure searching (https://www.ebi.ac.uk/chembldb ) 3 Accessing ChEMBL Data Pipeline Pilot and knime protocols that use these webservices are available on forum pages 4 ChEMBL Database Content ChEMBL_14 Compounds: 1,213,239 Activities: 10,129,256 Publications: 46,133 Targets: 9,003 Targets 5918 proteins Compounds* organisms 517261 to 1213239 1475 1433 cell lines •Increase of >200,000 compds from literature since ChEMBL01 •~1% overlap between ChEMBL literature and PubChem compds 5 * Includes PubChem Compounds Organisation of ChEMBL Data Activities Compounds • Type (e.g IC50) • Values Targets • Units • Type • Sequence • Organism • Names Assays • Properties • Experimental detail 6 ChEMBL Compounds • Chemical structures in journal articles are drawn as .mol files • If the stereochemistry is known it is drawn as a specific enantiomer • Tautomers of the same compound are not treated as separate compounds. The form shown is as in the paper • Other “rules” for standardising NO2 groups, HCl salts etc Based on FDA Substance Registration System User's Guide http://www.fda.gov/ForIndustry/DataStandards/SubstanceRegistrationSystem- UniqueIngredientIdentifierUNII/default.htm • Identifying unique compounds is done using Standard InChI • Salts and parent molecules are grouped together for displaying bioactivity data although activity data is recorded against the specific salt 7 ChEMBL Assays – Binding, Functional, ADMET Binding Assays • Assays which directly measure the binding of a compound to a particular target (e.g., competition binding assays with a radioligand) Functional Assays • Whole organism assays (e.g., anti-infectives/parasitics) • Cell-based assay over-expressing target (e.g., GPCR Calcium mobilisation) ADMET Assays • Absorption, Distribution, Metabolism, Excretion,Toxicity (e.g t1/2 in rat) 8 ChEMBL Targets: Protein Protein complex Protein family Nucleic Acid e.g., PDE5 e.g., Nicotinic acetylcholine receptor e.g., Muscarinic receptors e.g., DNA Cell Line Tissue Sub-cellular Fraction Organism e.g., HEK293 cells e.g., Nervous e.g., Mitochondria e.g., Drosophila 9 ChEMBL Activities • Bioactivity value for a particular compound in a specific assay against a specific target e.g. data for Imatinib (Gleevec, CHEMBL941) 10 Use Cases • Use Case 1 • Interested in a specific compound (or substructure) • Which compounds are similar • Which targets do they bind to • What are their potential liabilities • Use Case 2 • Interested in a specific target • Identify compounds that bind to that target • What data is available on these compounds • Select compounds with good potency/good drug-like properties to start synthetic project • If there is no data for compounds binding to my protein is there data for closely related members of the same family? 11 Searching by Target in ChEMBL Find target by name, BLAST search or target tree Identify Potent Compounds IC50<10nM 12 Bioactivity Data download data 13 Compound Activity values Assay details Target details Refs structures 13 Information on a Target – Target Report Card 14 Compound Searching in ChEMBL 86 similar at >=90% 15 Also sub-structure searches Filter on Lipinski Rule of Five etc Chart View 16 Compound Search – Compound Report Card 17 Searching Assays 18 Marketed Drugs Export to Excel Export SDF UniChem http://chembl.blogspot.com/2011/11/unichem.html 20 Multiple EBI Resources hold Compound Structure Data - Maintaining links between DBs is a manual/time consuming for each source. - Business rules for constructing identifiers not consistent – users confused. „10003‟ „RIBOSTAMYCIN‟ „CHEMBL221572‟ EU_OPENSCREEN „EU-?????‟ etc ? „RIO‟ ??‟ 21 UniChem: a resource overlaying EBI chemistry resources EU_OPENSCREEN etc, etc… Uses standard InChI to compare chemical structures across databases Enables tracking of „id-to-structure‟ assignments over time All EBI DBs share the benefit of maintained links between chemistry resources 22 Additional benefits of UniChem: Maintained links to external sources are shared. EU_OPENSCREEN etc - All EBI DBs share the benefits of maintained links to external resources. - The „mapping service‟ will be opened for use by external users. 23 UniChem - Sources 24 24 UniChem – InChi or identifier searching 25 UniChem – InChi or Identifier Searching InChi Searching Identifier Searching 26 UniChem – Source Mapping 27 Useful information Other ChEMBL Resources If you would like help: [email protected] For ChEMBL news and data releases subscribe to: http://listserver.ebi.ac.uk/mailman/listinfo/chembl- announce ChEMBL Paper (NAR 2011) ChEMBL Blog: http://chembl.blogspot.com 28 Acknowledgements ChEMBL Group John Overington Collaborators Anne Hersey Imperial Cancer Research, University of Anna Gaulton Dundee, University of Cambridge, Mark Davies Sanger Centre, University of Maryland, NCBI, TDR, IUPHAR, Bayer-Schering, Jon Chambers Pfizer, GSK, Schering-Plough, MMV, Louisa Bellis Novartis, St Jude Children‟s Research Kazuyoshi Ikeda Hospital Patricia Bento Shaun McGlinchey EMBL-EBI colleagues Yvonne Light Felix Krueger Former Inpharmatica colleagues Ben Stauch Ruth Akhtar Francis Atkinson Rita Santos ChEMBL Hands-on Use Case 1 • Search for target by name (Adenosine A2a) • Select human target • Look at Target Report Card • Return to Target Search Results (back button) and tick just the human target • Filter bioactivity data for Ki<10nM • Sort the data by value • Output data to EXCEL • Select and copy a few CHEMBL_IDs • Paste into Compound Search - List Search • View all data on compounds 30 https://www.ebi.ac.uk/chembldb ChEMBL Hands-on Use Case 2 • Search by compound name (sildenafil) • Look at data on parent and salt • Look at links to crystal structure and clinical trials data • Select sildenafil structure and use as query • Go to compound search page • Do similarity search >=85% • Go to graph view of data • Filter by compound properties e.g logP<5 and Mol Wt<500 • Look at bioactivity data on new dataset 31 https://www.ebi.ac.uk/chembldb ChEMBL Hands-on Use Case 3 • Get FASTA sequence for IRAK2 from Uniprot http://www.uniprot.org/ • Paste sequence into ChEMBL – Protein Target Search • Sort results by BLAST Score • View bioactivity data on 3 most similar proteins (IRAK1, IRAK3, IRAK4) • Look at target report card for IRAK4. Look at database links for this protein e.g. PDBe • Select the few most ligand efficient compounds that bind to this target and view the data 32 ChEMBL Hands-on Use Case 4 • Search for assays that contain the word “Alzheimer” • Sort on activity counts • Look at document report card for assay Use Case 5 • Browse drugs • Filter on oral • Show download to excel • Drug approvals • Show links to blog 33 https://www.ebi.ac.uk/chembldb Answers 34 Use Case 1 35 36 37 Paste CHEMBL IDs 38 39 Use Case 2 40 41 42 43 Use Case 3 44 http://www.uniprot.org Protein Sequence of Interest e.g from UniProt http://www.uniprot.org Sort by BLAST Score Data on IRAK1,IRAK3 and 45 IRAK4 but not IRAK2 IRAK1, IRAK3 and IRAK4 data 46 47 Use Case 4 48 Use Case 5 49 50 .
Recommended publications
  • EPA's Dsstox Database: History of Development of a Curated Chemistry
    EPA Public Access Author manuscript Comput Toxicol. Author manuscript; available in PMC 2021 January 07. About author manuscripts | Submit a manuscript Published in final edited form as: EPA Author Manuscript Author EPA Manuscript Author EPA Comput Toxicol Manuscript Author . EPA 2019 November 1; 12: . doi:10.1016/j.comtox.2019.100096. EPA’s DSSTox database: History of development of a curated chemistry resource supporting computational toxicology research Christopher M. Grulkea, Antony J. Williamsa, Inthirany Thillanadarajahb, Ann M. Richarda,* aNational Center for Computational Toxicology, Office of Research & Development, US Environmental Protection Agency, Mail Drop D143-02, Research Triangle Park, NC 27711, USA bSenior Environmental Employment Program, US Environmental Protection Agency, Research Triangle Park, NC 27711, USA Abstract The US Environmental Protection Agency’s (EPA) Distributed Structure-Searchable Toxicity (DSSTox) database, launched publicly in 2004, currently exceeds 875 K substances spanning hundreds of lists of interest to EPA and environmental researchers. From its inception, DSSTox has focused curation efforts on resolving chemical identifier errors and conflicts in the public domain towards the goal of assigning accurate chemical structures to data and lists of importance to the environmental research and regulatory community. Accurate structure-data associations, in turn, are necessary inputs to structure-based predictive models supporting hazard and risk assessments. In 2014, the legacy, manually curated DSSTox_V1 content was migrated to a MySQL data model, with modern cheminformatics tools supporting both manual and automated curation processes to increase efficiencies. This was followed by sequential auto-loads of filtered portions of three public datasets: EPA’s Substance Registry Services (SRS), the National Library of Medicine’s ChemID, and PubChem.
    [Show full text]
  • The ELIXIR Core Data Resources: ​Fundamental Infrastructure for The
    Supplementary Data: The ELIXIR Core Data Resources: fundamental infrastructure ​ for the life sciences The “Supporting Material” referred to within this Supplementary Data can be found in the Supporting.Material.CDR.infrastructure file, DOI: 10.5281/zenodo.2625247 (https://zenodo.org/record/2625247). ​ ​ Figure 1. Scale of the Core Data Resources Table S1. Data from which Figure 1 is derived: Year 2013 2014 2015 2016 2017 Data entries 765881651 997794559 1726529931 1853429002 2715599247 Monthly user/IP addresses 1700660 2109586 2413724 2502617 2867265 FTEs 270 292.65 295.65 289.7 311.2 Figure 1 includes data from the following Core Data Resources: ArrayExpress, BRENDA, CATH, ChEBI, ChEMBL, EGA, ENA, Ensembl, Ensembl Genomes, EuropePMC, HPA, IntAct /MINT , InterPro, PDBe, PRIDE, SILVA, STRING, UniProt ● Note that Ensembl’s compute infrastructure physically relocated in 2016, so “Users/IP address” data are not available for that year. In this case, the 2015 numbers were rolled forward to 2016. ● Note that STRING makes only minor releases in 2014 and 2016, in that the interactions are re-computed, but the number of “Data entries” remains unchanged. The major releases that change the number of “Data entries” happened in 2013 and 2015. So, for “Data entries” , the number for 2013 was rolled forward to 2014, and the number for 2015 was rolled forward to 2016. The ELIXIR Core Data Resources: fundamental infrastructure for the life sciences ​ 1 Figure 2: Usage of Core Data Resources in research The following steps were taken: 1. API calls were run on open access full text articles in Europe PMC to identify articles that ​ ​ mention Core Data Resource by name or include specific data record accession numbers.
    [Show full text]
  • Annual Scientific Report 2013 on the Cover Structure 3Fof in the Protein Data Bank, Determined by Laponogov, I
    EMBL-European Bioinformatics Institute Annual Scientific Report 2013 On the cover Structure 3fof in the Protein Data Bank, determined by Laponogov, I. et al. (2009) Structural insight into the quinolone-DNA cleavage complex of type IIA topoisomerases. Nature Structural & Molecular Biology 16, 667-669. © 2014 European Molecular Biology Laboratory This publication was produced by the External Relations team at the European Bioinformatics Institute (EMBL-EBI) A digital version of the brochure can be found at www.ebi.ac.uk/about/brochures For more information about EMBL-EBI please contact: [email protected] Contents Introduction & overview 3 Services 8 Genes, genomes and variation 8 Molecular atlas 12 Proteins and protein families 14 Molecular and cellular structures 18 Chemical biology 20 Molecular systems 22 Cross-domain tools and resources 24 Research 26 Support 32 ELIXIR 36 Facts and figures 38 Funding & resource allocation 38 Growth of core resources 40 Collaborations 42 Our staff in 2013 44 Scientific advisory committees 46 Major database collaborations 50 Publications 52 Organisation of EMBL-EBI leadership 61 2013 EMBL-EBI Annual Scientific Report 1 Foreword Welcome to EMBL-EBI’s 2013 Annual Scientific Report. Here we look back on our major achievements during the year, reflecting on the delivery of our world-class services, research, training, industry collaboration and European coordination of life-science data. The past year has been one full of exciting changes, both scientifically and organisationally. We unveiled a new website that helps users explore our resources more seamlessly, saw the publication of ground-breaking work in data storage and synthetic biology, joined the global alliance for global health, built important new relationships with our partners in industry and celebrated the launch of ELIXIR.
    [Show full text]
  • 1 Effects Ethinyl Estradiol Ethinyl Estradiol & Its Effects On
    1 Effects Ethinyl Estradiol Ethinyl Estradiol & Its Effects on Cardiovascular Health Mary Eilert Lourdes University Spring 2019 BIO 490 Section A Dr. Anjali Gray 2 Effects Ethinyl Estradiol ABSTRACT Combined hormonal birth control regulates the menstrual cycle in women by manipulating the hormonal level. Combined hormonal contraception utilizes progestin and Ethinyl estradiol, which are synthetics of progesterone and estrogen. These synthetic hormones help regulate ovulation in women and in turn menstruation. Venous thromboembolism (VTE), stroke, and myocardial infarction are all risk factors when taking combined hormonal contraception due to the chemical composition of Ethinyl estradiol. Ethinyl estradiol’s binding mechanism to an estrogen receptor causes clots and therefore a risk for cardiovascular disease. The dosage of Ethinyl estradiol is related to an increased risk for VTE, stroke, and myocardial infarction. Due to the increased threat to cardiovascular health, physicians should screen patient health history carefully when prescribing combined hormonal birth control. Analyzing the risk Ethinyl estradiol poses to cardiovascular health in women can be used to determine if combined hormonal birth control is the ideal choice for contraception. 3 Effects Ethinyl Estradiol INTRODUCTION Birth control, a contraceptive, is frequently prescribed to women of varying ages throughout the United States. Birth control can be used for its primary use as a contraceptive or prescribed as a means of lessening symptoms of reproductive diseases, such as endometriosis. Birth control comes in various forms and methods. Intrauterine devices (IUDs) and birth control implants are forms which are implanted into the women and rely on the release of hormones to regulate the menstrual cycle (Planned Parenthood).
    [Show full text]
  • Routes of Oxytocin Administration for the Prevention of Postpartum Haemorrhage After Vaginal Birth
    WHO recommendation on Routes of oxytocin administration for the prevention of postpartum haemorrhage after vaginal birth WHO recommendation on Routes of oxytocin administration for the prevention of postpartum haemorrhage after vaginal birth WHO recommendation on routes of oxytocin administration for the prevention of postpartum haemorrhage after vaginal birth ISBN 978-92-4-001392-6 (electronic version) ISBN 978-92-4-001393-3 (print version) © World Health Organization 2020 Some rights reserved. This work is available under the Creative Commons Attribution- NonCommercial-ShareAlike 3.0 IGO licence (CC BY-NC-SA 3.0 IGO; https://creativecommons.org/ licenses/by-nc-sa/3.0/igo). Under the terms of this licence, you may copy, redistribute and adapt the work for non-commercial purposes, provided the work is appropriately cited, as indicated below. In any use of this work, there should be no suggestion that WHO endorses any specific organization, products or services. The use of the WHO logo is not permitted. If you adapt the work, then you must license your work under the same or equivalent Creative Commons licence. If you create a translation of this work, you should add the following disclaimer along with the suggested citation: “This translation was not created by the World Health Organization (WHO). WHO is not responsible for the content or accuracy of this translation. The original English edition shall be the binding and authentic edition”. Any mediation relating to disputes arising under the licence shall be conducted in accordance with the mediation rules of the World Intellectual Property Organization (http://www.wipo.int/amc/en/ mediation/rules/).
    [Show full text]
  • Hypermutation of DPYD Deregulates Pyrimidine Metabolism and Promotes Malignant Progression Lauren Edwards, Rohit Gupta, and Fabian Volker Filipp
    Published OnlineFirst November 25, 2015; DOI: 10.1158/1541-7786.MCR-15-0403 Genomics Molecular Cancer Research Hypermutation of DPYD Deregulates Pyrimidine Metabolism and Promotes Malignant Progression Lauren Edwards, Rohit Gupta, and Fabian Volker Filipp Abstract New strategies are needed to diagnose and target human the background mutation rate. Structural analysis of the DPYD melanoma. To this end, genomic analyses was performed to protein dimer reveals a potential hotspot of recurring somatic assess somatic mutations and gene expression signatures using mutations in the ligand-binding sites as well as the interfaces of a large cohort of human skin cutaneous melanoma (SKCM) protein domains that mediated electron transfer. Somatic muta- patients from The Cancer Genome Atlas (TCGA) project to tions of DPYD are associated with upregulation of pyrimidine identify critical differences between primary and metastatic degradation, nucleotide synthesis, and nucleic acid processing tumors. Interestingly, pyrimidine metabolism is one of the major while salvage and nucleotide conversion is downregulated in pathways to be significantly enriched and deregulated at the TCGA SKCM. transcriptional level in melanoma progression. In addition, dihy- dropyrimidine dehydrogenase (DPYD) and other important Implications: At a systems biology level, somatic mutations of pyrimidine-related genes: DPYS, AK9, CAD, CANT1, ENTPD1, DPYD cause a switch in pyrimidine metabolism and promote NME6, NT5C1A, POLE, POLQ, POLR3B, PRIM2, REV3L, and gene expression of pyrimidine enzymes toward malignant pro- UPP2 are significantly enriched in somatic mutations relative to gression. Mol Cancer Res; 14(2); 196–206. Ó2015 AACR. Introduction Pyrimidine synthesis is a key metabolic bottleneck important for DNA replication in tumor cells and, therefore, represents a Cancer cells take advantage of distinct metabolic pathways valuable diagnostic and therapeutic target.
    [Show full text]
  • Chebi: a Chemistry Ontology and Database
    de Matos et al. Journal of Cheminformatics 2010, 2(Suppl 1):P6 http://www.jcheminf.com/content/2/S1/P6 POSTER PRESENTATION Open Access ChEBI: a chemistry ontology and database Paula de Matos*, A Dekker, M Ennis, Janna Hastings, K Haug, S Turner, Christoph Steinbeck From 5th German Conference on Cheminformatics: 23. CIC-Workshop Goslar, Germany. 8-10 November 2009 The bioinformatics community has developed a policy and identifier. A complete version is available with all of open access and open data since its inception. This is the ChEBI data properties such as synonyms, cross- contrary to chemoinformatics which has traditionally references, SMILES and InChI. Furthermore cross-refer- been a closed-access area. In 2004, two complementary ences in ChEBI have been extended to include BRENDA open access databases were initiated by the bioinfor- the enzyme database, NMRShiftDB the database for matics community, ChEBI [1] and PubChem. PubChem organic structures and their nuclear magnetic resonance serves as automated repository on the biological activ- (nmr) spectra, Rhea the biochemical reaction database ities of small molecules and ChEBI (Chemical Entities of and IntEnz the enzyme nomenclature database. Biological Interest) as a manually annotated database of ChEBI is available at http://www.ebi.ac.uk/chebi. molecular entities focused on ‘small’ chemical com- pounds. Although ChEBI is reasonably compact contain- Published: 4 May 2010 ing just over 18,000 entities, it provides a wide range of data items such as chemical nomenclature, an ontology References and chemical structures. The ChEBI database has a 1. Degtyarenko K, de Matos P, Ennis M, Hastings J, Zbinden M, McNaught A, strong focus on quality with exceptional efforts afforded Alcántara R, Darsow M, Guedj M, Ashburner M: ChEBI: a database and ontology for chemical entities of biological interest.
    [Show full text]
  • Industry Programme EMBL-EBI and Industry
    The European Bioinformatics Institute . Cambridge Industry Programme EMBL-EBI and Industry Our Industry Programme is unique. It is a forum for interaction and knowledge exchange for those working at the forefront of applied bioinformatics, in over 20 major companies with global R&D activities. The programme focuses on precompetitive collaboration, open-source software and informatics standards, which have become essential to improving efficiency and reducing costs for the world’s bioindustries. The European Bioinformatics Institute (EMBL-EBI) is a global leader in the storage, annotation, interrogation and dissemination of large datasets of relevance to the bioindustries. We help companies realise the potential of ‘big data’ by combining our unique expertise with their own R&D knowledge, significantly enhancing their ability to exploit high-dimensional data to create value for their business. We see data as a critical tool that can accelerate research and development. Our mission is to provide opportunities for scientists across sectors to make the best possible use of public and proprietary data. This can help companies reduce costs, enhance product selection and validation and streamline their decision-making processes. Companies with large R&D capacity must ensure high data quality and integrate licensed information with both public and proprietary data. At EMBL-EBI, we help companies build publicly available data into their local infrastructure so they can add proprietary and licensed information in a secure way. Going forward, we see our interactions with our industry partners growing stronger, as the quality of data continues to rise. Through our programme and efforts such as the Innovative Medicines Initiative and the Pistoia Alliance, we support pre- competitive research collaborations, promote the uptake and utility of open-source software, and steer the development of data standards.
    [Show full text]
  • Inchi in the Wild: an Assessment of Inchikey Searching in Google Christopher Southan
    Southan Journal of Cheminformatics 2013, 5:10 http://www.jcheminf.com/content/5/1/10 REVIEW Open Access InChI in the wild: an assessment of InChIKey searching in Google Christopher Southan Abstract While chemical databases can be queried using the InChI string and InChIKey (IK) the latter was designed for open- web searching. It is becoming increasingly effective for this since more sources enhance crawling of their websites by the Googlebot and consequent IK indexing. Searchers who use Google as an adjunct to database access may be less familiar with the advantages of using the IK as explored in this review. As an example, the IK for atorvastatin retrieves ~200 low-redundancy links from a Google search in 0.3 of a second. These include most major databases and a very low false-positive rate. Results encompass less familiar but potentially useful sources and can be extended to isomer capture by using just the skeleton layer of the IK. Google Advanced Search can be used to filter large result sets. Image searching with the IK is also effective and complementary to open-web queries. Results can be particularly useful for less-common structures as exemplified by a major metabolite of atorvastatin giving only three hits. Testing also demonstrated document-to-document and document-to-database joins via structure matching. The necessary generation of an IK from chemical names can be accomplished using open tools and resources for patents, papers, abstracts or other text sources. Active global sharing of local IK-linked information can be accomplished via surfacing in open laboratory notebooks, blogs, Twitter, figshare and other routes.
    [Show full text]
  • The EPA Comptox Dashboard and Underpinning Software Architecture – a Platform for Data Integration for Environmental Chemistry
    http://www.orcid.org/0000-0002-2668-4821 The EPA CompTox Chemistry Dashboard and Underpinning Software Architecture – a platform for data integration for environmental chemistry data Antony Williams1, Chris Grulke1, Daniel Chang2, Kristan Markey2 and Jeff Edwards1 1. National Center for Computational Toxicology, U.S. Environmental Protection Agency, RTP, NC 2. Office of Pollution Prevention and Toxics, U.S. Environmental Protection Agency, Washington, DC 3. Office of Science Coordination and Policy, U.S. Environmental Protection Agency, Washington, DC The views expressed in this presentation are those of the author and do not necessarily reflect the views or policies of the U.S. EPA August 2017 ACS Fall Meeting, Washington, DC The CompTox Chemistry Dashboard PRIMARY GOALS • Deliver a web-based application serving up the chemistry related data used by our team • Provide public access to the results of over a decade of curation work reviewing environmental chemistry data • Provide access to the results of our QSAR modeling work • Deliver a central hub to link together websites of interest • All data to be available as Open Data for download/reuse SECONDARY GOAL • Develop a cheminformatics architecture to serve as a high quality chemical foundation for all NCCT tools and data The CompTox Chemistry Dashboard: An Overview • A publicly accessible website delivering access: – ~760,000 chemicals and related property data – Links to other agency websites and public data resources – “Literature” searches for chemicals using public resources – Integration
    [Show full text]
  • Comptox Chemicals Dashboard Version 3/2019
    CompTox Chemicals Dashboard v3 and invitroDB v3.1 http://comptox.epa.gov/dashboard Katie Paul Friedman and Antony Williams National Center for Computational Toxicology Disclaimer: The views expressed in this presentation are those of the author(s) and do not necessarily represent the views or policies of the U.S. Environmental Protection Agency, nor does mention of trade names or products represent endorsement for use. Overview of changes since August 2018 release • Data • 875k chemicals total. An additional 110k chemical substances added • InvitroDBv3.1 – including updated assay descriptions • ToxVal v7 data integrated – includes enormous curation effort • New OPERA predictions • New User Interface elements • Reworked tables across the application • Reworked multiple chemical results page • Navigating concentration response plots for all AEIDs in invitroDB_v3 data, not just the EDSP21 assays • Enhanced batch search capabilities QC Notes for Chemicals Accessing QC Notes for Chemicals Examples • Toxaphene • Antimycin A • Safflower Oil pKa experimental data added – no predictions A new “Structure Zoom” • On-click hover all over the dashboard as well as structure thumbnail Reworked multiple results page Reworked multiple results page • Use Ctrl to select multiple display • Improved visual cues for loading large lists of chemicals • Loading of Large lists RETAINS ordering Batch Search • New Search input - DTXCID • New Search Outputs Related Substance Relationships Bioactivity Data • Summary data now has “enhanced tables” • EDSP21 subset of assays has grown • Toxcast/Tox21 “all data” has been integrated • PubChem data widget – no change • Subset of ToxCast ”Models” – extended to include “COMPARA” data Tables Reworked – Column Selection • Ability to select columns to show added for tables –Bioactivity most important – Pick your own preferred display Assay Annotations Filled a Lot of Gaps! Previous data gaps Data gap filled Toxcast: Models – COMPARA added “EDSP Subset” • New assays added – expanded all subsets.
    [Show full text]
  • EMBL-EBI) Wellcome Genome Campus Hinxton, Cambridge CB10 1SD United Kingdom
    European Bioinformatics Institute (EMBL-EBI) Wellcome Genome Campus Hinxton, Cambridge CB10 1SD United Kingdom y www.ebi.ac.uk/industry EMBL-EBI is part of the European Molecular Biology Laboratory (EMBL) C +44 (0)1223 494 154 P +44 (0)1223 494 468 EMBL member states: Austria, Belgium, Croatia, Czech Republic, Denmark, E [email protected] Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Israel, Italy, Luxembourg, Malta, Netherlands, Norway, Portugal, Slovakia, Spain, Sweden, T @emblebi Switzerland, United Kingdom. Associate member states: Argentina, Australia F /EMBLEBI Y EMBLmedia You can download this brochure at www.ebi.ac.uk/about/our-impact The European Bioinformatics Institute . Cambridge Industry Programme EMBL-EBI and Industry Our Industry Programme is unique in the world. It is a forum for interaction and knowledge exchange for those working at the forefront of applied bioinformatics, in over 20 major companies with global R&D activities. The programme focuses on precompetitive collaboration, open-source software and informatics standards, which have become essential to improving efficiency and reducing costs for the world’s bioindustries. The European Bioinformatics Institute (EMBL-EBI) is a global leader in the storage, annotation, interrogation and dissemination of large datasets of relevance to the bioindustries. We help companies realise the potential of ‘big data’ by combining our unique expertise with their own R&D knowledge, significantly enhancing their ability to exploit high-dimensional data to create value for their business. We see data as a critical tool that can accelerate research and development. Our mission is to provide opportunities for scientists across sectors to make the best possible use of public and proprietary data.
    [Show full text]