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CHEMINFORMATICS
SCALING-UP FOR THE AGE
OF BIG DATA
Árpád Figyelmesi
29th ICIC Heidelberg 2017
Big data
Big data is a term for data sets that are so large or complex that traditional data
processing application software is inadequate to deal with them.
(Wikipedia)
Big data is high-volume, high-velocity and/or high-variety information assets that
demand cost-effective, innovative forms of information processing that enable
enhanced insight, decision making, and process automation.
(Gartner – IT Glossary)
TRADITIONAL SEARCH
Why searching?
• Find relevant chemical patterns (substructure search)
• Find similar compounds (similarity search)
• Find building blocks (superstructure search)
• Compare libraries (overlap analysis)
• Identify compound families (clustering)
Screening
Library
250k-1M
Real life chemical data
Corporate
Compound
Repository
3M
Chemical data in patent literature
Enumerated virtual compounds
Old „traditional” vs New „traditional”
SureChEMBL real-time search
SOMETHING LESS TRADITIONAL
MadFast Similarity Search
• Ultra fast chemical similarity
search
• In-memory data storage
• Optimized multi-threaded
implementation
Near real-time search of 1 billion
100k x 1M exhaustive search in a few mins
Chemical white-space analysis
• Find potential drug analogs/novel ring systems
• From synthetically feasible virtual chemical space
• As close as possible to known drugs
• As far as possible from patented compounds
Case study
• Filter drugs from ChEMBL
• Search analogs in GDB-13
• Analyze overlap with
SureChEMBL
https://www.chemaxon.com/app/uploads/2017/03
/mfss-study-poster-23-1-imre-gabor-1.pdf
Results
Results
Results
THE FUTURE IS NOW
Extreme fast search engines
• Search time is not a question anymore
• Hits as you draw
• Real-time clustering for search suggestions and
drill down
New ways of interactions fundamentally change
the chemical patent search
Beyond the search
• Real-time analysis of extreme large
compound libraries
• Proactive exploration of synthetically
feasible and patentable chemical space
THANK YOU
Árpád Figyelmesi

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ICIC 2017: Cheminformatics Scaling-up for the Age of Big Data