Building innovative drug discovery alliances. Knime Desktop tools for chemists

Transcription

1 Building innovative drug discovery alliances Knime Desktop tools for chemists Evotec AG, Knime desktop tools for chemists, May 2011

2 Agenda Knime Getting project data from Excel spreadsheets Getting project data from IJC databases Getting public data from databases Enumerating libraries of compounds Getting data from other databases Knime Server Knime node development Conclusions 1

3 A KNIME Solution The Multi-Purpose Tool in the MedChem Toolkit 2

4 KNIME The Multi-Purpose Tool in the MedChem Toolkit 3

5 Knime Workbench 4

6 Agenda Knime Getting project data from Excel spreadsheets Getting project data from IJC databases Getting public data from databases Enumerating libraries of compounds Getting data from other databases Knime Server Knime node development Conclusions 5

7 Extracting data from Excel Loading into IJC Project compound data is kept on an Excel spreadsheet Data is filtered and prepared for loading into an IJC database Additional calculations are carried out during the workflow 6

8 Agenda Knime Getting project data from Excel spreadsheets Getting project data from IJC databases Getting public data from databases Enumerating libraries of compounds Getting data from other databases Knime Server Knime node development Conclusions 7

9 Using InstantJChem databases Projects keep their data in Oracle Every project uses InstantJChem for their project data Project members can easily view and query their data Easy for project members to load new data and maintain old data Two schemas; one for project data, one for project ideas Additional properties can be calculated during data loading Shared Oracle database All data backed up Each project area is secure Only project members can see the data 8

10 Overview Shared IJC project database setup at Evotec Enterprise licenses for server use shared across Abingdon and Hamburg sites Dedicated IJC server at Abingdon with Oracle 10g and JChem cartridge One Oracle schema per drug discovery project containing project data (currently 40 live IJC shared projects) A project IJC schema is connected to each Oracle schema Built-in IJC security & roles used for user management Deployment to project users via web server URLs 9

11 Project Data Flow Drug Discovery IJC Project at Evotec Abingdon Medicinal Chemistry ADMET Compound Registration IJC JChem g Hamburg Opera Assays Counter Assays In Vivo 10

12 Extract data from IJC Project ideas database Project chemists add synthetic ideas to their IJC database Knime is used to extract the data that has been added that month The extracted data is presented in PowerPoint 11

13 Data Model Schema Editor view: Data Trees SAR data tree contains joined chemistry & biology tables, allowing many assay results for each assay type per compound structure Assay tables Relationships All Structures 1-n 1-n Structure table fields Bioassay ADMET assays 12

14 Creating SAR tables from databases Producing reports Project data can be queried and filtered easily Data from multiple tables can be used Additional properties can be calculated SAR table reports can be prepared from the filtered data 13

15 Extracting data from IJC Using activity data 14

16 Exporting data from multiple tables Easy data extraction from IJC 15

17 Agenda Knime Getting project data from Excel Getting project data from IJC databases Getting public data from databases Enumerating libraries of compounds Getting data from other databases Knime Server Knime node development Conclusions 16

18 Accessing public data Viewing ChEMBL data ChEMBL is a database of bioactive drug-like small molecules, it contains 2-D structures, calculated properties (e.g. logp, Molecular Weight, Lipinski Parameters, etc.) and abstracted bioactivities (e.g. binding constants, pharmacology and ADMET data 17

19 Accessing public data Viewing ChEMBL data through IJC 18

20 Searching the ChemBL database Easy access to ChEMBl data using Knime A simple workflow allows users to search the ChEMBl data Users don t need a username and password 19

21 Agenda Knime Getting data from Excel spreadsheets Getting project data from IJC databases Getting public data from databases Enumerating libraries of compounds Knime Server Knime node development Conclusions 20

22 Library enumeration An easy way for chemists to create compounds Chemists can quickly create a virtual library Calculate physical properties Select interesting compounds for further processing 21

23 Virtual Library Enumeration: CDK2 Example 22

24 Re-usable components Physical properties Parts of workflows can be re-used Often used operations can be bundled into meta nodes 23

25 Even more meta nodes! 24

26 Library enumeration and searching Check EVOsource for starting materials Enumerate a focused library Select the promising compounds Search in-house compound database for starting materials 25

27 Agenda Knime Getting data from Excel spreadsheets Getting project data from IJC databases Getting public data from databases Enumerating libraries of compounds Getting data from other databases Knime Server / Sharing Workflows Knime node development Conclusions 26

28 Search Compound database Retrieving hits from EVOsource Using a list of part ID s Get lists of suppliers that the compound can be bought from 27

29 Administration of the ELN Auditing users Connect to ELN database Carry out audits By project By user Regular Leavers Submitted, countersigned, Printed 28

30 Agenda Knime Getting project data from Excel Getting project data from IJC databases Getting data from public data sets Enumerating libraries of compounds Getting data from other databases Knime Server / Sharing Workflows Knime node development Conclusions 29

31 Knime Server Sharing workflows Workflows created by expert users Reports for other users 30

32 SharePoint Sharing workflows Using SharePoint to share workflows and tips 31

33 Agenda Knime Getting project data from Excel Getting project data from IJC databases Getting data from public data sets Enumerating libraries of compounds Getting data from other databases Knime server / Sharing Workflows Knime node development Conclusions 32

34 EVOnodes KNIME Development Projects Have developed KNIME nodes to run linux based CADD programs 33

35 EVOnodes Knime development projects Knime nodes to replace Evotec desktop modelling tool Allow integrating modelling tools in workflows 34

36 Agenda Knime Getting project data from Excel Getting project data from IJC databases Getting data from public data sets Enumerating libraries of compounds Getting data from other databases Knime Server / Sharing Workflows Knime node development Conclusions 35

37 Conclusions Why use Knime? On every chemists desktop Easy for chemists to tailor make database exports Easy for chemists to enumerate libraries Easy for chemists to generate tailor made reports from databases Simple for developers and computational chemists to extend Fun to work with! 36

38 Acknowledgements escience Ian Berry Catherine Reisser Mike Potterton Computational Chemistry Mike Mazanetz Michelle Szeto Discovery Chemistry Ed Walker Rich Jones Chris Stimson 37

39 Building innovative drug discovery alliances Your contact: Dr Bob Marmon Senior Applications Developer, escience +44.(0) (0)