Transformative Utility of InChIKey Searching in the Mother of all Databases
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Transformative Utility of InChIKey Searching in the Mother of all Databases

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From BioIT Workshop "A Bar Code for Chemical Structures: Using the InChI to Transform Connectivity between Chemistry, Biology, Biomedicine and Drug Discovery" ...

From BioIT Workshop "A Bar Code for Chemical Structures: Using the InChI to Transform Connectivity between Chemistry, Biology, Biomedicine and Drug Discovery"

http://figshare.com/articles/BioIT_Workshop_2014_Chem_Bio_via_InChI/1063314

Update June. Workshop attendees had access to all the slide sets via CHI. Some are on slideshare (e.g. from Antony Williams) but I have merged the sets into a PDF in the figshare link above.


Abstract: Google indexing of the InChIKey (IK) has turned the web into a de facto chemical database with well over 50 million unique entries (PMID:23399051). The first block of the IK encodes molecular skeleton that can be used to give maximum recall of related structures. For example, Google searching XUKUURHRXDUEBC from atorvastatin displays ~200 low-redundancy links in ~0.3 sec with a low false-positive rate . These include most major databases and less familiar but valuable sources. The simplicity of the IK makes it useful for those less familiar with chemical searching. Advanced Google Search can be used to filter results, image searching gives complementary coverage and there are also hits in Google Scholar. IK searching thus becomes powerfully enabling for reciprocal document-to-database joins from legacy text tombs including over 50 years of biology < > chemistry. Open tools such as chemicalize.org can generate of IKs from patents, papers, abstracts or web pages. Open Drug Discovery data on tested, synthesized or even proposed compounds, can be globally connected in real-time by surfacing IKs in open laboratory notebooks, Wikis, blogs, Twitter, figshare etc. Following the ChemSpider precedent the IUPHAR/GTP database offers users IK Google searches from all ligand entries including peptides.

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  • IinChIKeys - estimate of PubChem + ChemSpider in Google – but PubChem currently has a backlog for Key scrapingThe ROF + 250-800 is a very approximate circumscription of the property space that has some possibility of bioactivityProbably a proportion of vendor structures may have never been committed to textThere are some virtuals “out there” including some patent-extractions but difficult to estimate
  • Only Nature Chemical Biology and Nature Chemistry have direct links from the journal document to PubChemGiven todays technology the major patent offices could put links in the PDFs but are unlikely to do so
  • IinChIKeys - estimate of PubChem + ChemSpider in Google – but PubChem currently has a backlog for Key scrapingThe ROF + 250-800 is a very approximate circumscription of the property space that has some possibility of bioactivityProbably a proportion of vendor structures may have never been committed to textThere are some virtuals “out there” including some patent-extractions but difficult to estimate
  • The CID links straight throught to chemicalize and will just re-extract the whole patent in a few seconds The 413 gave 358 hits in pub chem
  • From manual cross-checking between the individual example structures and the IC50 table the Excel sheet can be populated
  • Can upload CID lists and download as a saved and public collection
  • We can start of with patent linksNote in this case numbered image capture, as oposed to the IUPAC listing, was important to manually collate the structure against the correct IC50
  • Need to assess what representational types are being used in the documentEg. Some patents are image-only (but SureChem is pulling most of these out)Then select tools and sources for the job ´Decide how to store your structures locally The default batch search is an upload to PubChemThe default individual search is the InChIKey against Google
  • InChIkey search picks up instantly This was just a choice of one of the activesSo this connects PubChem and figshare
  • Self explanatoryNote my blog post was indexed

Transformative Utility of InChIKey Searching in the Mother of all Databases Transformative Utility of InChIKey Searching in the Mother of all Databases Presentation Transcript

  • www.guidetopharmacology.org The transformative utility of InChIKey searching in the Mother of all Databases (a.k.a. Google) Chris Southan IUPHAR/BPS Guide to PHARMACOLOGY Web portal Group, Centre for Integrative Physiology, School of Biomedical Sciences, University of Edinburgh, Hugh Robson Building, Edinburgh, EH8 9XD, UK. cdsouthan@hotmail.com 1
  • Outline • Introduction: the atorvastatin example • Chem-to-bio context • IK stats and estimates • Extracting IKs from documents • IK database-to-database • Open Source malaria drug discovery as a testbed • Caveats and future prospects 2
  • The precedent InChI as a web index for molecules “We have now discovered, serendipitously, that these InChIs have been comprehensively and accurately indexed by the Google search engine. From preliminary exploration it appears that every known document in which an InChI appears has been indexed and that all are retrievable by standard queries with virtually 100% precision. This means that standard Web-based indexers, without any alteration, are capable of acting as completely precise chemical search engines. Although we have many years of developing chemistry on the web, this was an unexpected and very welcome finding” Murray-Rust et al. 2004 http://lists.w3.org/Archives/Public/public-swls- ws/2004Oct/att-0019/ 3
  • IK example: atorvastatin and metabolites 4
  • Fast and clean results 5 parent para-hydroxy ortho-hydroxy
  • Inner layer XUKUURHRXDUEBC image search 6
  • Making the chem < > bio join Biochemistry Medicinal chemistry Toxicology Chemical biology Systems pharmacology Metabolomics Drug discovery Pharmacology Chemogenomics InChIKey 7
  • Getting biology out of text-tombs is not easy; Getting chemistry out is even more difficult 8
  • Why chem < > bio joining is difficult • The majority of chemistry embedded in biological reports is specified as semantic names or images • The MeSH to PubChem connectivity is patchy • Biologists use sequence database accession numbers, ontologies and gene names widely but chemists rarely use open chemical database IDs • Most bioactive chemistry in text does not have direct connectivity to databases (unlike GenBank/RefSeq/UniProt < > PubMed) • Nat.Chem.Biol. is the only bio-journal that mandates PubChem reciprocal linking • Most authors don’t engage with surfacing and connectivity (e.g. becoming PubChem submitters and/or figshare data depositors) • Chemists and biologists tend not to communicate easily • GenBank started in 1982, PubChem in 2004 • Inventors/authors under-cite their own medicinal chemistry patents 9
  • So how many IKs has Google indexed ? • PubChem ~ 50 million • ChemSpider ~ 30 million • PubChem from patents (all sources) ~ 15 million • PubChem journal sources (PubMed + ChEMBL) ~ 1 million • Web sources outside the above (no idea) • Open ELNs (no idea) Guestimate 60 million-ish 10
  • Databases < > documents: IK Googling facilitates reciprocal linking Abstracts Patents Papers 15 mill 0.2 mill (mainly MeSH) 0.9 mill (ChEMBL) 12K 11
  • IKs with data-supported bioactivity (>biology) • GVKBIO Online Structure Activity Relationship Database (GOSTAR ) = 6.3 million with SAR data from patents and literature (not tagged in PubChem) • Thomson Pharma = 4.2 million selected examples from patents and literature • PubChem BioAssay “active” = 0.93 million • ChEMBL (in PubChem) = 0.88 million • Thomson Pharma (2013 only) = 0.27 million • PubMed = 0.23 million • MeSH “pharmacology” = 12,719 • INN or USAN = 10,707 • Union of last two above = 19,334 intersect = 4,092 • Prous (Thomson) Drugs of the Future = 7,218 • DrugBank approved (via SIDs) = 1,504 Guestimate for chemistry with a useful level of solubility, stability, specificity and potency (e.g. < 250 nM) in biological systems ~ 0.5 million IKs (but of course we also need low potency and inactives for controls and SAR) 12
  • IKs and the representational hextet used in documents and databases 13
  • Extracting IKs from documents: OPSIN 14
  • Extracting IKs from documents: chemicalize.org 15
  • Extracting IKs from documents OSRA 16
  • Extracting IKs from documents: sketchers 17
  • IK call-outs in dbs: extending the link reach 18
  • Modified peptides/big stuff: connection where similarity struggles http://www.guidetopharmacology.org/GRAC/LigandDisplayForwar d?ligandId=2532 19
  • OSM drug discovery: test bed for open data surfacing and connecting chem > bio • Team are exploring chemistry surfacing/sharing in real time (e.g. ELNs, Wiki,Github, ChEMBLMalaria for project updates) • Converted to IK utility (after the necessary evangelizing) • Global antimalarial drug R&D (open and closed) exemplifies full range of connectivity issues that IK surfacing can potentially ameliorate 20
  • Actively unlocking IK connections 21
  • Name > structure > biology: missing links 22
  • Where the IK connects…… 23
  • Chemicalize.org: 413 strucs/IKs fromWO2011086531 CID 53311393 -> 24
  • WO2011086531 >chemicalize.org > SAR IC50s > figshare surfaces and connects (e.g. PubChem) 25
  • Share structures via open MyNCBI http://www.ncbi.nlm.nih.gov/sites/myncbi/collections/public/1zWhcobieZbIo uGfUdsdbHek5/. 26
  • DIY surfacing of name < > IK connections 27
  • Caveats and risks for IK Googling • Ranking heuristics are opaque and change • Results shift on short time scales (i.e. irreproducible) • NoAPI (or good search result set parsers) • Don’t ignore corroborative searches in well-structured databases • Searching common IKs is not generally useful (but can filter) • No good for similarity searching on their own (but you can intersperse with similarity approaches) • In the relentless war between good and evil (Google verses the SEO Dark Side) dodgy chemical suppliers are always pushing • There may be future risks of common chemistry swamping • Names, SMILES or even IUPAC strings may sometimes give Google hits where the IK misses (because its not there) 28
  • What does the future hold /need ? • For manual searching Googling the IK is the “first stop shop” • InChI world-domination is proceeding • Inexorable increase in full-text, open access journals and crawled open repositories (e.g. figshare) • Journals must encourage author chemistry mark-up to include the IK • More biologists getting into chemistry connections and databases • Boutique bioactive chemistry databases becoming more discoverable • SureChEMBL will improve image handling and get crawled • RSC Journal Archive > ChemSpider • ContentMine (Murry-Rust et. al.) 100 million facts, including journal-extracted chemical structure streaming • More Open (Source) Drug Discovery > Google crawled ELNs with IKs • Wider community use of Chemicalize.org for targeted extractions • New IK via source expansion in ChemSpider and PubChem 29
  • Thanks and Questions 30
  • Extras 31
  • Abstract Abstract: Google indexing of the InChIKey (IK) has turned the web into a de facto chemical database with well over 50 million unique entries (PMID:23399051). The first block of the IK encodes molecular skeleton that can be used to give maximum recall of related structures. For example, Google searching XUKUURHRXDUEBC from atorvastatin displays ~200 low-redundancy links in ~0.3 sec with a low false- positive rate . These include most major databases and less familiar but valuable sources. The simplicity of the IK makes it useful for those less familiar with chemical searching. Advanced Google Search can be used to filter results, image searching gives complementary coverage and there are also hits in Google Scholar. IK searching thus becomes powerfully enabling for reciprocal document-to-database joins from legacy text tombs including over 50 years of biology < > chemistry. Open tools such as chemicalize.org can generate of IKs from patents, papers, abstracts or web pages. Open Drug Discovery data on tested, synthesized or even proposed compounds, can be globally connected in real-time by surfacing IKs in open laboratory notebooks, Wikis, blogs, Twitter, figshare etc. Following the ChemSpider precedent the IUPHAR/GTP database offers users IK Google searches from all ligand entries including peptides. 32
  • Patent SAR fromWO2011086531: Collating activities via SureChemOpen CID 53311393 > 33
  • Triaging document or webpage chemistry • Identify the structure specification types – Semantic names (all sources) – Code names (press releases, papers and abstracts) – IUPAC names (papers, patents and abstracts) – Images (papers, patents, & Google images) – SMILES (open lab books) – InChi strings (open lab books) – SDF files (open lab books, & github) Convert these to a structure (e.g. SDF, SMILES, InChI) then: – Search InChIKey in Google – Search major databases – Compare extracted sets for intersects and diffs – Extend exact match connectivity with similarity searching 34
  • Orthogonal joining 35
  • Triage example: a new antimalaria The MMV390048 code name is linked to an image in press reports but is PubChem and PubMed -ve 36