Rapid Application Development using InforSense Open Workflow and Oracle Chemistry Cartridge Technologies

Transcription

1 Rapid Application Development using InforSense Open Workflow and Oracle Chemistry Cartridge Technologies Anthony C. Arvanites Lead Discovery Informatics

2 Company Introduction Founded: 1999 Platform: Combining chemical and genetic screening to discover drugs Number of Scientists: 20 Areas of Focus: CNS, Parasitic diseases, Drug rescue Business Model: Organic growth - grants & partnership

3 What are Chemical Data Cartridges? An additional component that can be added to extend the functionality of Oracle to handle chemical objects like other standard data types within an industry-standard SQL framework. Store, index, manipulate and search chemical objects, such as molecules and reactions, directly within Oracle databases. Oracle Server

4 Sample SQL Statements SELECT mol FROM moltable WHERE CsCartridge.Molecule Contains(mol,'Nc1cc(O)c(C(O)=O)cc1','','')=1; SELECT mol from moltable WHERE CsCartridge.MoleculeContains(mol,'Nc1cc(O)c(C(O)=O)cc1','','similar= yes,simthreshold=80')=1; Query data using structural matching or similarity Calculate derived properties such as molecular weight and chemical formula Calculate molecular descriptors or chemical fingerprints Import and export external representations, such as MDL mol files or Smiles strings Each Chemical Cartridge has there own list of features: Daylight DayCart, MDL Direct, CambridgeSoft, Accelrys DS Accord, IDBS ChemXtra

5 InforSense 2.0: Oracle Edition IOE -- accelerates productivity by accessing Oracle 10g analytics via the intuitive InforSense workflow-based visual analytics environment Workflow-based analytics Real-time in-database analysis Select, connect and execute data, analysis, visualization components to build analytical processes Deploy analytical processes as web services/applications Quick integration of 3rd party Oracle solution Oracle Components Data Processing Data Mining Statistics, Blast, Text

6 InforSense as an Integration Platform Inforsense IOE platform can be an interface that connects the latest database technology, the chemical data cartridge combined with the power of oracle 10g analytics, to be an ideal rapid application development platform. Existing derive or search & replace components can be used to call chemical cartridge operators

7 DayCart Component Prototype Using Existing IOE nodes operator contains ( smiles1 IN VARCHAR2_OR_CLOB, smiles2 IN VARCHAR2_OR_CLOB ) => NUMBER operator smi2cansmi ( smiles IN VARCHAR2_OR_CLOB, type IN NUMBER ) => VARCHAR2_OR_CLOB Type is either 0 or 1, for unique or absolute SMILES operator tanimoto ( fp_or_smi1 IN VARCHAR2_OR_CLOB, fp_or_smi2 IN VARCHAR2_OR_CLOB ) => NUMBER

8 CambridgeSoft s Oracle Cartridge Based Structure to Name or Name to Structure Conversion CSCARTRIDGE.CONVERTCDX.CD XTONAME (STRUCTURE) CSCARTRIDGE.MOLECULECONTAI NS (STRUCTURE, Query,'','') Expression Editor Built into Oracle Derive Node Can be used with analyzing unstructured data (text-mining) with Oracle Text or Inforsense s TextScense

9 Prototype of Reusable DayCart Service Nodes Drag, Drop and Connect to build workflows Reusable Service nodes Quickly integrate new cartridge functionality (e.g. DayCart v4.9 s conversion toolkit ) Build and deploy custom solutions in less than a day Components can be programmed using Java

10 Examples of the Daylight DayCart Components Daylight Contrib code : MOL2SMI and SMI2MOL vcs_desalt and vcs_normalize operators Remove molecular fragments found in c$dcischem.salts SMIRKS-based structure normalization on input Smiles based on c$dcischem.transform Access Dayprop via Dayproptalk from DayCart exact, graph, blob and role index creation Substructure Match and Filter Operators exact, contains Similarity Operators tanimoto, euclid, Tversky Generate Daylight Fingerprints Operator smi2fp User able to define min, max and number of bits

11 Chemical Warehouse / Modeling Application Chemical Warehouse Capability of integrating with other in-house chemical databases (e.g. compound repository, subscription databases, virtual collections ) Easily create / modify using a visual programming environment Capability of performing external or in-database data-mining analytics Support chemical registrations Capability of integrating with other databases (e.g. BioAssay, Activity Base) Modeling Predictive ADME models Deployment of application to benefit bench scientists Oracle Data Mining Support Vector Machine (SVM) model Decision Tree Classification models Blood Brain Barrier Permeation(1670 compounds classified BBB+ or BBB-) P-glycoprotein (PgP), Human Intestinal Absorption (HIA), Torsades de Pointes (TdP)

12 Data Entry and Processing of Commercial Databases using DayCart Creating a compound warehouse: Collect individual database files from compound vendors Data entry and processing in using an oracle based chemical cartridge & IOE Generate Indexes using Components or use SQL Plus Deploy via a web portal

13 Creating a chemical warehouse via in-database processing Six commercial cleaned compound vendor databases are being preprocessed to unionize matching data columns (e.g. structure, CAS number, name, availability) creating a master chemical data warehouse within Oracle. DayCart structure Indexing (exact, role, graph, blob) was performed to enable fast structure searching on over 1 million compounds.

14 MDL & Daylight Similarity Searching Workflow query results Execute chemical searches using different chemical cartridges in one reusable and deployable workflow Link results to tables or views that access compound plate or biological data

15 Oracle Data Mining Blood Brain Barrier Model Launch Oracle Data Miner from within KDE Blood Brain Barrier dataset in SD format is converted into Daylight Smiles via contrib code and imported into an Oracle table. The dataset is joined with a repository of molecular descriptors and used to produce an SVM model all within the Oracle database. Published evaluation metrics are used to determine the efficiency of the model.

16 Predictive ADME solution using Oracle Data Mining A wrapped reusable service node Blood Brain Barrier (oracle SVM) P-glycoprotein (KDE Decision Tree) Human Intestinal Absorption (Weka Decision Tree) Torsades de Points (libsvm) J. Chem. Inf. Comput. Sci., Vol. 44, pg (2004) Effect of Molecular Descriptor Feature Selection in Support Vector Machine Classification of Pharmacokinetic and Toxicological Properties of Chemical Agents. J. Chem. Inf. Comput. Sci., Vol. 44, No.4 (2004), Prediction of P-Glycoprotein Substrates by a Support Vector Machine Approach. J. Chem. Inf. Comput. Sci.,Vol. 38, (1998) Prediction of Human Intestinal Absorption of Drug Compounds from Molecular Structure. J. Chem. Inf. Comput. Sci., Vol. 44, No.1 (2004) Blood-Brain Barrier Permeation Models: Discrimination between Potential CNS and Non-CNS Drugs Including P- Glycoprotein Substrates.

17 Deploying an application within InforSense

18 A Deployed Solution for Internal R&D

19 Questions? InforSense s workflow technology will be used as a rapid application development platform within Cambria Biosciences so that custom solutions can be deployed to staff scientists.