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Aiding Computer Aided Drug Design

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Aiding Computer Aided Drug Design Mohd Shahir Shamsir (PhD) Bioinformatics Research Group (BIRG) Department of Biological Sciences, Faculty of Bioscience & Bioengineering Universiti Teknologi Malaysia
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Page 1: Aiding Computer Aided Drug Design

Aiding Computer Aided Drug Design

Mohd Shahir Shamsir (PhD)

Bioinformatics Research Group (BIRG)

Department of Biological Sciences,

Faculty of Bioscience & Bioengineering

Universiti Teknologi Malaysia

Page 2: Aiding Computer Aided Drug Design

Summary

• Aiding Computer Aided Drug Design

• Greasing the gears of CADD• Gaming gears• Video

Page 3: Aiding Computer Aided Drug Design

CADD is a specialised discipline that uses computational

methodsto simulate drug-receptor interactions – Richard

M casey

Computer aided drug design (CADD)

is a specialized discipline that uses computational methods to simulate drug-receptor interactions

Richard M. Casey

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CADD methods are heavily dependent on bioinformatics

tools, applications and databases.

CADD methods are heavily dependent on bioinformatics tools, applications and databases.

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CADD can metaphorically be an engine with many bioinformatics “gears” contributing towards the functioning of this “Engine”. Among these gears are homology modeling, similarity searchers, physicochemical modeling, virtual High

Throughput screening, drug lead optimization, drug bioavailability, drug bioactivity, sequence analysis. All of these is expected to translate into reduced time-to-market, cost savings and new insight into drug research.

Virtual High-Throughput Screening (vHTS)

Sequence Analysis

Homology Modeling Similarity Searches

Drug Lead Optimization

Physicochemical Modeling

Drug Bioavailability and Bioactivity

Cost Savings Time-to-Market

Insight

Computer Aided Drug Design

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Docking gears for example have varieties of tools that have

evolved

Page 7: Aiding Computer Aided Drug Design

We can aid/assist CADD by ‘greasing’

the ‘gears’ .Greasing CADD

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Interactions are key in ‘greasing’ the research gears. Science happens not just because of people doing experiments but because they are discussing those experiments

Christopher Surridge,Managing Editor PLoS ONE

Science happens not just because of people doing experiments but because they are discussing those experiments

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Greasing using Web 2.0 would enable easier collaboration between researchers and

research groups.Greasing using Web 2.0

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Multiple tools mostly user generated that has user generated content in mind

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Propels by a state of mind where users i.e. YOU generate content to be shared with other users

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Community and social collaboration

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Many examples of tools of web 2.0

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Tools created by the African Continent – unrestricted

creativity

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Landscape breakdown of how these tool are connected to

generate WEB 2.0

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Easier to Collaborate

• Collaborative tools examples

• Google Docs• Microsoft Office Live• Zoho• Thinkfree• Zimbra• springnote

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Yugma – a web conferencing tool - http://www.yugma.com/

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Freemind – a web based collaborative mind mapping tool

- http://freemind.sourceforge.net/

wiki/index.php/Main_Page

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Slideshare – to share slides for reseach presentations -

http://www.slideshare.net/

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Research computing is currently very fragmentedExisting approaches do not scale up to the amount of data now commonMany chemical informatics tools are obscure, difficult to use and access

Scientists’ questions are not that complex, but finding the answers is currently very time consuming and/or complex (for a human)“has anybody patented this chemical structure I just made?”

“can I get hold of a compound that might bind to the active site of this protein I just resolved?”“which compounds in this series are least likely to exhibit toxic effects?”

Answers are often “stale” after a short period of time – questions need to be re-answered as new information is generatedAlmost all available systems are passive, and follow the

(web) browsing modelThere tends to be one interface for every data source

(or encompassing just a few)

Scalability

passive

Scalability issue

Similarity Searches Research fragmentation

Complex questions

New pespective from new information

usability

Single interfaceaccessibility

Integrating CADD gears

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Automated Bioinformatics Workflows Tools

• Examples such as • Taverna - http://taverna.sourceforge.net/• Swami - http://www.ngbw.org/• Systems Biology Workbench - http://www.sys-bio.org/index.htm• SCSC Workbench - http://workbench.sdsc.edu/Integrating

CADD gears

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Amazon web services for easier biological data retrievalEasier data retrieval

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1. Annotated Human Genome Data provided by ENSEMBL (172GB).

2. GenBank provided by the National Center for Biotechnology Information (250GB)

3. UniGene provided by the National Center for Biotechnology Information (10 GB)

Easier data retrieval

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Digital Collaborations

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Initiated by O-Reilly meeting in 2004 called sci-foo

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Replicated in Second life (SL)

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Virtual meeting

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Virtual meeting

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Examples of material found on SL

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Gaming gears for CADD

Gaming Gears for CADD

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PS3?

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PS3!!

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First PS3 cluster for research by Dr Frank Mueller of North

Carolina University

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Warhawk Server Cluster

Costs lessReduced heatMinimum space

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CUDA support by n-VIDIA

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Statistics by Folding@Home

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Up and running eHITS application using PS3 by

SimBioSys Inc

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Video about Web 2.0VIDEO

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CADD still need hard working people.

CADD

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creditsImages from

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Questions


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