Dynamic web application for drug design researchDynamic web application for drug design research

M. Chapman1, N. MacCuish1, J. MacCuish1

J. Bradley2, J. Blankley3

1Mesa Analytics & Computing, Inc., Santa Fe, New Mexico, USA2Drexel University, Philadelphia, PA, USA

3Pfizer (retired), Ann Arbor, MI, USA

ABSTRACTABSTRACTThe dynamic Web application, WebFlowDD, introduces synthetic organic chemistry students to the world of drug design through a pharmaceutical industry workflow. Students and researchers have access to simple tasks that are commonplace in an industrial setting and have the opportunity to run a variety of freeware and Web-services as they tackle synthetic challenges in drug design. This poster focuses on WebFlowDD combined with Cheminformatics Virtual Classroom (ChemVC), an e-Learning environment for students to learn specific topics in drug discovery.

WebflowDD InterfaceWebflowDD Interface

WebflowDD InterfaceWebflowDD Interface Dashboard design with four expandable, dynamically

interactive panels Data panel allows for import and management of data for

the various tasks outlined in the Task panel View panel updates with views for any data imported from

the Data window or visualization dynamically generated from interaction with the Task panel

Task panel allows users to choose specific workflows of interest and leads them through a workflow

Analysis panel enables users to interact with Tasks that involve intermediate steps.

Dashboard design with four expandable, dynamically interactive panels

Data panel allows for import and management of data for the various tasks outlined in the Task panel

View panel updates with views for any data imported from the Data window or visualization dynamically generated from interaction with the Task panel

Task panel allows users to choose specific workflows of interest and leads them through a workflow

Analysis panel enables users to interact with Tasks that involve intermediate steps.

Dashboard DesignDashboard Design

WebFlowDD TasksWebFlowDD Tasks

Similarity Searching Visualize Common Substructures

(ChemTattooTM) Build QSAR Models Make predictions with pre-computed

models (internal or via web services)

Similarity Searching Visualize Common Substructures

(ChemTattooTM) Build QSAR Models Make predictions with pre-computed

models (internal or via web services)

Database Similarity SearchingDatabase Similarity Searching

SMILES can be pasted in as queries for Similarity SMILES can be pasted in as queries for Similarity Searching on databases local to the WebFlowDD Searching on databases local to the WebFlowDD server as well as hits can be used to interface with server as well as hits can be used to interface with ChemSpider or other on-line database services.ChemSpider or other on-line database services.

Interface to ChemSpiderInterface to ChemSpider

http://www.chemspider.com/http://www.chemspider.com/

Interface to Webservice ModelingInterface to Webservice Modeling

QSAR Models from a webservice provided by R. GuhaQSAR Models from a webservice provided by R. Guhaat Indiana University, enables users to generate a at Indiana University, enables users to generate a spectrum of QSAR Models from their imported data. spectrum of QSAR Models from their imported data. Models are built and results displayed in the View panel.Models are built and results displayed in the View panel.

Predictive ModelingPredictive Modeling

QSAR models, solubility models, etc. are created with computed parameters from CDK

Pre-computed models are menu available for predictions on new data sets

QSAR models, solubility models, etc. are created with computed parameters from CDK

Pre-computed models are menu available for predictions on new data sets

Predictive ModelingPredictive Modeling

Example Predictive Modeling workflow. Users chose a Example Predictive Modeling workflow. Users chose a parameter set to build a model. A SMILES is uploaded and parameter set to build a model. A SMILES is uploaded and a prediction generated from the pre-computed model. a prediction generated from the pre-computed model.

Lessons on www.chemvc.comLessons on www.chemvc.com

Users requiring more backgroundUsers requiring more backgroundfor workflow tasks, can look to ChemVCfor workflow tasks, can look to ChemVCfor related subject matter.for related subject matter.

AcknowledgementsAcknowledgements WebFlowDD is written in Python, Jython, Java and C++. It relies on several 3rd party Free/Open Source Software (FOSS) packages:

CDK -- the Chemistry Development Kit provides chemical properties and 2D depiction coordinates CherryPy -- WebFlowDD is built atop this web application framework Elixir -- an Object-Relational Mapper layer that sits atop SQLAlchemyexcanvas -- provides Internet Explorer with support for the HTML5 Canvas Tagflot -- a JavaScript-based graphing packageJinja - HTML templating engine used by WebFlowDDjQuery and jQuery UI -- JavaScript libraries that help make WebFlowDD pages interactivejQuery clickMenu plugin -- provides pulldown menus in the Data panejQuery Dimensions plugin -- manages the geometry of the web page elementsjQuery spin btn plugin -- turns text fields into numeric spin boxesOpenBabel -- providing underlying support for chemical fingerprinter and ChemTattooSimplejson -- used on the server side to convert Python data structures to and from JSON (JavaScript Object Notation) for exchange with web browsersSOAPy -- WebFlowDD uses SOAP to communicate with some other web servicesSQLAlchemy -- provides a database abstraction layerSQLite3 -- providing persistent store for WebFlowDDOther underlying FOSS packages: Beaker, fpconst, Imaging, numpy, python-datautil, pytz

Consultants Webservices: Indiana University: R. Guha, ChemSpider

David Moreland