We’re all SMILES! Building Chemical Semantic Web Services with SADI, ChEBI, and CHEMINF

ChEBI User Group Meeting:June 24, 2010 1

We’re all SMILES! Building Chemical Semantic Web Services

with SADI, ChEBI, and CHEMINF

Michel Dumontier, Ph.D.Associate Professor of Bioinformatics

Carleton University

Department of BiologySchool of Computer Science

Institute of BiochemistryOttawa Institute of Systems Biology

Ottawa-Carleton Institute of Biomedical Engineering


Syntactic Web…It takes a lot of digging to get answers


Surface web:167 terabytes

Deep web:91,000 terabytes

545-to-one

We need to get to the deep web

ChEBI User Group Meeting:June 24, 2010

and tap into the global web of structured knowledge

5


The Semantic Web is the new global web of knowledge

It is about standards for publishing, sharing and querying knowledge drawn from diverse sources

It makes possible the answeringsophisticated questions using

background knowledge

Goals

• Provision chemical data on the Web

• Find cheminformatic services that will consume the data

• Answer questions about chemicals by reasoning over essential chemical knowledge


Is caffeine a drug-like molecule?


Lipinski Rule of Five• Rule of thumb for druglikeness (orally active in humans)

(4 rules with multiples of 5)– Less than 500 Dalton– Less than 5 hydrogen bond donors– Less than 10 hydrogen bond acceptors– A partition coefficient value between -5 and 5

• We need a more formal (machine understandable) description



Formal Ontology as a Strategy


The Web Ontology Language (OWL) Has Explicit Semantics

Can therefore be used to capture knowledge in a machine understandable way

Lipinski Rule of Five• Empirically derived ruleset for druglikeness

(4 rules with multiples of 5)– Less than 500 Dalton– Less than 5 hydrogen bond donors– Less than 10 hydrogen bond acceptors– A partition coefficient value between -5 and 5

• A formal description using OWL:


To calculate these attributes, we need access to a computable representation

of the molecular structure


ball & stick model for caffeine

The chemical graph specifies the type and connectivity of atoms in molecules. It describes

a part of chemical structure

SMILES strings are common representations of the chemical graph


ball & stick model for caffeine

SMILES string for caffeine

Cn1cnc2n(C)c(=O)n(C)c(=O)c12

Chemical descriptors

• Chemical descriptors are data (quantities or values) that provide information about substances, molecular entities, and their parts (rings, atoms, bonds, etc).

• Sometimes they enumerate material parts, they quantify or describe qualities, functions or dispositions

• Often used to build Quantitative Structure Activity Relationships (QSAR) models

• Example descriptors :– Mass values– Partition coefficients– Heats of formation– Aromaticity values– Molecular formulas


The Chemical Information Ontology (CHEMINF)

• 100 chemical descriptors• 50 chemical qualities• Relates descriptors to their

specifications, the software that generated them (along with the running parameters, and the algorithms that they implement)

• Contributors: Nico Adams, Leonid Chepelev, Michel Dumontier, Janna Hastings, Egon Willighagen, Peter Murray-Rust, Cristoph Steinbeck


http://semanticchemistry.googlecode.com

CHEMINF provides the vocabulary to define an input (SMILES-annotated molecule) and an output

(molecule annotated with a descriptor)


Ultimately, the goal is to use an OWL reasoner to reason about the attributes to determine

whether the compound is drug-like


Semantic Automated Discovery and Integration

http://sadiframework.org

Mark Wilkinson, UBCMichel Dumontier, Carleton UniversityChristopher Baker, UNB

SADI is a framework to create Semantic Web services using OWL classes as service inputs and outputs

19ChEBI User Group Meeting:June 24, 2010

http://sadiframework.org/

SADI

• OWL classes in SADI are local to individual services

– They should uniquely specify the service input and outputs (they exactly have the right restrictions)

– one service’s world-view can conflict with another,but a client can use any or all

• maximize interoperability by reusing types and relations


Create code stubs using the ontology

• Publish the ontology to a web-accessible locationhttp://semanticscience.org/sadi/ontology/lipinskiserviceontology.owl

• Make sure that the class names are resolvable(easy when using the hash notation)

http://semanticscience.org/sadi/ontology/lipinskiserviceontology.owl#smiles-molecule

http://semanticscience.org/sadi/ontology/lipinskiserviceontology.owl#logp-molecule

http://semanticscience.org/sadi/ontology/lipinskiserviceontology.owl#hbdc-molecule

http://semanticscience.org/sadi/ontology/lipinskiserviceontology.owl#hdba-molecule

http://semanticscience.org/sadi/ontology/lipinskiserviceontology.owl#lipinksi-druglike-molecule

• Download/checkout the codehttp://sadiframework.org

• Run the code generator – specify the URIs that correspond to input and output types


Implement the functionality

• Java version – Uses Jena to manipulate the RDF graph– Uses Maven to build from command-line or Eclipse; Invokes

Jetty for service testing

• Chemistry– We used the Chemistry Development Kit (CDK) to implement 4

services


Working with the service (GET)

• Responds to a GET by providing the service description in RDF– conforms to Feta (BioMoby, myGrid)


curl http://cbrass.biordf.net/logpdc/logpc<rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:j.0="http://www.mygrid.org.uk/mygrid-moby-service#" > <rdf:Description rdf:about=""> <j.0:hasServiceDescriptionText>no description</j.0:hasServiceDescriptionText> <j.0:hasServiceNameText rdf:datatype="http://www.w3.org/2001/XMLSchema#string">logpc</j.0:hasServiceNameText> <j.0:hasOperation rdf:resource="#operation"/> <rdf:type rdf:resource="http://www.mygrid.org.uk/mygrid-moby-service#serviceDescription"/> </rdf:Description> <rdf:Description rdf:about="#input"> <j.0:objectType rdf:resource="http://semanticscience.org/sadi/ontology/lipinskiserviceontology.owl#smilesmolecule"/> <rdf:type rdf:resource="http://www.mygrid.org.uk/mygrid-moby-service#parameter"/> </rdf:Description> <rdf:Description rdf:about="#operation"> <j.0:outputParameter rdf:resource="#output"/> <j.0:inputParameter rdf:resource="#input"/> <rdf:type rdf:resource="http://www.mygrid.org.uk/mygrid-moby-service#operation"/> </rdf:Description> <rdf:Description rdf:about="#output"> <j.0:objectType rdf:resource="http://semanticscience.org/sadi/ontology/lipinskiserviceontology.owl#alogpsmilesmolecule"/> <rdf:type rdf:resource="http://www.mygrid.org.uk/mygrid-moby-service#parameter"/> </rdf:Description></rdf:RDF>

Working with the service (POST)

• Responds to a POST with service output (process an input file)


<rdf:Description rdf:about="http://semanticscience.org/sadi/ontology/caffeine.rdf#mdalogp"> <rdf:type rdf:resource="http://semanticscience.org/resource/CHEMINF_000251"/> <j.0:SIO_000300 rdf:datatype="http://www.w3.org/2001/XMLSchema#double">-0.4311000000000006</j.0:SIO_000300> </rdf:Description>

<rdf:RDF xmlns="http://semanticscience.org/sadi/ontology/caffeine.rdf#" xmlns:so="http://semanticscience.org/sadi/ontology/lipinskiserviceontology.owl#" xmlns:owl="http://www.w3.org/2002/07/owl#" xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:sio="http://semanticscience.org/resource/" xmlns:xsd="http://www.w3.org/2001/XMLSchema#"> <so:smilesmolecule rdf:about="http://semanticscience.org/sadi/ontology/caffeine.rdf#m"> <sio:SIO_000008 rdf:resource = "http://semanticscience.org/sadi/ontology/caffeine.rdf#msmiles"/> </so:smilesmolecule> <sio:CHEMINF_000018 rdf:about = "http://semanticscience.org/sadi/ontology/caffeine.rdf#msmiles"> <sio:SIO_000300 rdf:datatype="xsd:string">Cn1cnc2n(C)c(=O)n(C)c(=O)c12</sio:SIO_000300> </sio:CHEMINF_000018></rdf:RDF>

curl --data @caffeine.rdf http://cbrass.biordf.net/logpdc/logpc

Publish and Register the service


http://sadiframework.org/registry

Now what?



Semantic Health and Research Environment

SHARE is an application that execute (SPARQL) queries as workflows over SADI Services

“Reckoning”

dynamic discovery of instances of OWL classes through synthesis and invocation of a Web Service workflow capable of generating data described by the OWL class restrictions, followed by reasoning to classify the data

into that ontology

28ChEBI User Group Meeting:June 24, 2010


SPARQL is the new cool kid on the query block

SQL SPARQL

SHARE

• SPARQL engine– triple patterns are matched against service

descriptions

– knowledge base is dynamically populated

– queries can contain OWL classes, which are expanded to the required triple patterns

– query is optimized to minimize the number of service calls and the amount of data sent over the network


ChEBI has data!


Bio2RDF provides ChEBI in RDF



Bio2RDF now serving over 40 billion triples of linked biological data


An increasing amount of machine understandable chemical data


Dataset Source

ChEBI Bio2RDF

PubChem Bio2RDF

DrugBank Bio2RDF

KEGG Bio2RDF

PDB Bio2RDF

PharmGKB Bio2RDF

CTD Bio2RDF

TCM LODD

Medicare LODD

SIDER LODD

ChEMBL LODD

DailyMed LODD

Query for log p


Query: Is caffeine a drug-like molecule?



SADI

• Describe the input and output using OWL-DL classes

• Subject of input and output must be the same

• Web services indexed by predicates

• Biocatalogue will list SADI-compliant services

• Taverna plugin to work with SADI services

• Protégé 4.1 plugin to create SADI services

• Simplified migration path for existing web services (java, perl)

Benefits

• Data remains distributed – no warehouse!

• Data is not “exposed” as a SPARQL endpoint– greater provider-control over computational

resources

• Yet data appears to be a SPARQL endpoint… no modification of SPARQL or reasoner required.


Join Us!

• SADI and CardioSHARE are Open Source

• Come join us – we’re having a lot of fun!!

http://sadiframework.org



Acknowledgements

This research is supported by The Heart + Stroke Foundation of BC and Yukon, Microsoft Research, The Canadian Institutes of Health Research, The Natural Sciences and Engineering Research Council of Canada and CANARIE.

Leonid Chepelev (implementing the services)

Luke McCarthy (technical support)

Mark Wilkinson (vision and leadership)

CHEMINF Group

Janna HastingsNico AdamsEgon Willighagen

Technology

We’re all SMILES! Building Chemical Semantic Web Services with SADI, ChEBI, and CHEMINF