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Services | Research | Training | Industry Small Molecules Resources at the EBI Dr. Louisa Bellis Chemical Content Curator, ChEMBL Group EMBL-EBI, UK Bioinformatics.

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Presentation on theme: "Services | Research | Training | Industry Small Molecules Resources at the EBI Dr. Louisa Bellis Chemical Content Curator, ChEMBL Group EMBL-EBI, UK Bioinformatics."— Presentation transcript:

1 Services | Research | Training | Industry Small Molecules Resources at the EBI Dr. Louisa Bellis Chemical Content Curator, ChEMBL Group EMBL-EBI, UK Bioinformatics Resources for Immunologists 6 th September 2013

2 Agenda Introduction Small molecule resources ChEBI ChEMBL Searching and browsing Hands-on Exercises

3 Small Molecules within Bioinformatics Literature Nucleotide sequences Genomes Expressions Protein sequences Protein domains, families 3D structures Enzymes Small molecules Pathways Systems

4 Annotation of bioinformatics data Essential for capturing understanding and knowledge associated with core data Often captured in free text, which is easier to read and better for conveying understanding to a human audience, but… Difficult for computers to parse Quality varies from database to database Terminology used varies from annotator to annotator Towards annotation using standard vocabularies: ontologies within bioinformatics

5 Small Molecule Databases can be used to: Investigate historical compounds and associated bioactivity data. Create Structure-Activity Relationships (SARs) Direct synthesis Direct end product testing

6 ChEBI and ChEMBL

7 What is ChEBI? Chemical Entities of Biological Interest Freely available Focused on ‘small’ chemical entities (no proteins or nucleic acids) Illustrated dictionary of chemical nomenclature High quality, manually annotated Provides chemical ontology ~39,000 ChEBI 3* compounds Access ChEBI at


9 Visualisation caffeine 1,3,7-trimethylxanthine methyltheobromine Nomenclature Formula: C8H10N4O2 Charge: 0 Mass: 194.19 Chemical data metabolite CNS stimulant trimethylxanthines Ontology MSDchem: CFF KEGG DRUG: D00528 Database Xrefs Chemical Informatics InChI=1/C8H10N4O2/c1-10-4-9-6- 5(10)7(13)12(3)8(14)11(6)2/h4H,1-3H3 SMILES: CN1C(=O)N(C)c2ncn(C)c2C1=O ChEBI Data Overview





14 ChEBI Chemical Structures Chemical structure may be interactively explored using MarvinView applet Available in formats Image Molfile InChI and InChIKey SMILES


16 Automatic Cross-references


18 The ChEBI ontology Organised into three sub-ontologies, namely Molecular structure ontology Subatomic particle ontology Role ontology ( R )-adrenaline

19 Molecular structure ontology

20 Role ontology

21 ChEBI ontology relationships Generic ontology relationships Chemistry-specific relationships

22 Viewing ChEBI ontology

23 What is ChEMBL? Database of bioactive, drug-like small molecules. Store 2D structures, calculated properties (logP, mol weight, Lipinski etc) Contains abstracted bioactivity data, e.g. binding data and IC50, from multiple primary scientific journals Covers about 33 years of compound synthesis and testing Annotated FDA-approved drugs Access ChEMBL at

24 Data Statistics Focused towards compounds with drug-like properties by extraction from medicinal chemistry journals Includes small molecules (~92%) and peptides (~7%) Abstracted from 50,095 papers across 47 journals 1,487,579 compound records (~450,000 directly from PubChem) 1,295,510 distinct compound structures 11,420,351 activities (>6.0 million directly from PubChem) binding measurements, functional assays and ADMET 9,844 targets, with over 5,400 protein targets and over 2,440 human targets Deposition of PubChem Substances and Bioassay assays



27 > 10,000,000 bioactivities > 1,300,000 compounds ~30,000 distinct lead series ~15,000 candidates ~2,400 drugs Target Discovery Lead Discovery Lead Optimisation Preclinical Development Phase 1 Phase 2 Phase 3 Launch Target identification Microarray profiling Target validation Assay development Biochemistry Clinical/Animal disease models High-throughput Screening (HTS) Fragment-based screening Focused libraries Screening collection Medicinal Chemistry Structure-based drug design Selectivity screens ADMET screens Cellular/Animal disease models Pharmacokinetics Toxicology In vivo safety pharmacology Formulation Dose prediction PK tolerability Efficacy Safety & Efficacy Indication Discovery & expansion Med. Chem. SAR Clinical Candidates Drugs DiscoveryDevelopment Use Clinical Trials ChEMBL database

28 ChEMBL Target Types Molecular Non-molecular Nucleic acid ProteinCell-line Tissue Subcellular-fraction Organism Single Protein Protein Complex Protein Family DNA HEK293 cells Nervous Drosophila PDE5 Nicotinic acetylcholine receptor Muscarinic receptors Mitochondria


30 Clickable structure Structural Representations Drug Information


32 ChEMBL --> ChEBI Link:

33 ChemSpider Links: The link works both ways. They link TO ChemSpider and FROM ChemSpider. They link on Standard InChI

34 Wikipedia Links: We also have links with Wikipedia. These also use the Standard_Inchi as the common identifier. These links will link to the Compound Report Card in ChEMBL.

35 Searching and Browsing

36 Chemical names Common or trivial names are those that are highly used. Advantages of common names include simplicity, easy to pronounce, universally recognised The main disadvantage is ambiguity – the same common name may refer to more than one type of chemical. Fluorene Fluorine

37 Systematic names A systematic name is one which corresponds to the chemical structure such that the structure can be determined from the name, e.g. 1,2-dimethyl-naphthalene Software packages exist which can generate structures from the systematic names (e.g. ACD/Name, ChemOffice, MarvinSketch). More than one correct systematic name can be assigned to the same molecular structure, depending on the manner in which naming rules are applied (e.g. IUPAC names).

38 Examples of common and systematic names Common namesSystematic names caffeine guaranine theine 1,3,7-trimethyl-3,7-dihydro-1H- purine-2,6-dione 7-methyltheophylline 1,3,7-trimethyl-2,6- dioxopurine

39 The ChEBI web service Programmatic access to a ChEBI entry SOAP based Java implementation Clients currently available in Java and perl Methods include: getLiteEntity getCompleteEntity and getCompleteEntityByList getOntologyParents getOntologyChildren and getAllOntologyChildrenInPath getStructureSearch Documented at

40 Web services Allow users to create their own applications to query data User application

41 The ChEBI web service Programmatic access to a ChEBI entry SOAP based Java implementation Clients currently available in Java and perl Methods getLiteEntity getCompleteEntity and getCompleteEntityByList getOntologyParents getOntologyChildren and getAllOntologyChildrenInPath getStructureSearch Documented at

42 Web service client object model getLiteEntity getCompleteEntity getOntology (Parents and Children)

43 ChEMBL Web Services Programmatic access to the ChEMBL database Provide Java, Perl and Python scripts to help you get started with the ChEMBL RESTful Web Service API Can be used to bring back compounds, lists of compounds, images, targets and assays

44 Examples of Web Services


46 ChEBI simple and advanced text search Narrow to category AND, OR and BUT NOT

47 Search options Structure drawing tools

48 Search Results Hover-over for a larger structure Click to go to entry page

49 Types of structure search Identity – based on InChI Substructure – uses fingerprints to narrow search range, then performs full substructure search algorithm Similarity – based on Tanimoto coefficient calculated between the fingerprints InChI=1/H2O/h1H2 10101101110010110010 1010110111 0010110010 Tanimoto(a,b) = c / (a+b-c) = 4 / (4+7-4) = 0.57 a b

50 Browse via Periodic Table Molecular entities / Elements

51 Navigate via links in ontology Click to follow ontology links

52 ChEMBL Interface Searching: Keywords Compound name Trade Name Synonym Structure Exact match Substructure SMILES Single or a list of SMILES

53 Run substructure and similarity searches Keyword searches. Can use * as a wildcard Can search with a list of ChEMBL IDs, or Keywords or SMILES

54 Types of Compound Names To Use ChEMBL captures all compound names, compound keys and synonyms from the papers. Synonyms can be taken from the publications or are curated from other sources (e.g. NCBI website). Curated and extracted synonyms in ChEMBL_16 > 660,000 Types of synonyms captured include: Research codes FDA alternative names Trade Names (not for combinations of drugs) INN, BAN, JAN, USAN

55 Protein Sequence Search More precise method for identifying targets Input is a protein sequence of interest Uses BLAST* algorithm to perform pair-wise comparisons between input sequence and all proteins in the Target Dictionary, to find most closely related matches Results are scored according to similarity to input sequence (determined by number of amino acids that are identical or have similar properties) *Altschul SF et al., J Mol Biol. 215(3), p403-10 (1990).

56 Find a protein sequence of interest Select entry of interest Retrieve sequence in fasta format

57 Paste in a FASTA file and run a search to fetch matching targets


59 Can also browse using the Taxonomy

60 Family Tree browser Search box for keyword searching

61 Browse Drugs Tab Able to search the approved drugs using keywords


63 I want to find data and information on the target, IRAK4. I also want to find out about the compounds that have been tested against this target. But where would I start?....


65 Identifying Chemical Tools Search ChEMBL for protein of interest Simple text search against protein names/synonyms OR Browse protein family tree OR Sequence search using BLAST (can find related proteins) Identify compounds active against this protein Sort/filter by relevant activity types and potency E.g., retrieve compounds with IC50/Ki < 100nM Retrieve other data for these compounds Structures, chemical properties, other activities

66 Compound Properties and Selectivity ChEMBL stores a wide range of calculated compound properties (e.g., mol wt, logP, RO5 violations) Can be used to identify compounds most likely to have good in vivo properties (Absorption, Distribution, Metabolism, Excretion) Contains activity information against liability targets (e.g., cytochrome P450s, HERG K+ channel) If compounds have been tested in these assays, can avoid those with potential toxicity issues Contains data on a wide range of targets If compounds have been tested against multiple targets, can get an idea of their selectivity (important for validation studies)


68 The compound results can be downloaded as an *.SDFile.

69 The bioactivity data can be downloaded as *.XLS or a TAB file (tab-delimited) Activity types and values Assay details Literature references

70 You can use the standard Excel filtering options to filter the results

71 Downloads and programmatic access

72 Downloading ChEBI flavours All downloads come in two flavours 3 star only entries (manually annotated ChEBI entries) 2 and 3 star entries (manually annotated ChEBI, ChEMBL and user submissions)

73 Downloading ChEBI OBO file Use on OBO-edit SDF File Chemistry software compliant such as Bioclipse Flat file, tab delimited Import all the data into Excel Parse it into your own database structure Oracle binary dumps Import into an oracle database Generic SQL insert statements Import into MySQL or postgresql database

74 Downloading ChEMBL

75 Help and Feedback Email addresses for support queries and feedback General questions and feedback on ChEMBL interface: Reporting of data errors: General questions, support and feedback on ChEBI

76 Services | Research | Training | Industry Thank you

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