Computer aided drug design (CADD) uses computational methods to simulate drug-receptor interactions. CADD is heavily dependent on bioinformatics tools like homology modeling, similarity searches, and physicochemical modeling. These "gears" can be aided by greasing them through easier collaboration between researchers using tools of Web 2.0 like Google Docs, mind maps, and slide sharing to integrate CADD gears. Gaming consoles like the PS3 are also being explored as affordable clusters for CADD applications.
1. 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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3. 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
4. CADD methods are heavily dependent on bioinformatics tools, applications and databases. CADD methods are heavily dependent on bioinformatics tools, applications and databases.
5. 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
8. 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
9. Greasing using Web 2.0 would enable easier collaboration between researchers and research groups. Greasing using Web 2.0
17. Yugma – a web conferencing tool - http://www.yugma.com/
18. Freemind – a web based collaborative mind mapping tool - http://freemind.sourceforge.net/wiki/index.php/Main_Page
19. Slideshare – to share slides for reseach presentations - http://www.slideshare.net/
20. Research computing is currently very fragmented Existing approaches do not scale up to the amount of data now common Many 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 generated Almost all available systems are passive, and follow the (web) browsing model There 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 interface accessibility Integrating CADD gears
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22. Amazon web services for easier biological data retrieval Easier data retrieval