Markush claims are widely used in chemical patents to define large chemical spaces, however understanding these structures, their formalized representation, search and analysis is complex and poorly supported. The problem becomes more acute with the need for comparison of these potentially vast patent Markush structures with classic structure and combinatorial virtual libraries. At this time, all of the existing Markush representations are incomplete, search systems are proprietary and not available for in-house integration and with many key use cases there are no existing tools and often no algorithmic background to begin the solve. This presentation briefly summarizes the current state of Markush claims, the existing challenges from the perspective of both IP professionals and computational chemists and highlights some promising new developments directly relevant to today's discovery processes.

1. MARKUSH CLAIMS: REPRESENTATION,
SEARCH, ANALYSIS & CONSTRUCTION
Árpád Figyelmesi
27th ICICInternational Conferencefor the InformationCommunity
Nice2015
Where Are We and How to Go Forward?

2. OVERVIEW
History and current state of Markush claims

3. Origins
Dr. Eugene A. Markush
1888 Budapest, Hungary
1968 New York, USA
US1506316A
”The process for manufacture of
dyes…”
colorantshistory.org

4. Importance
• Between 1994 and 2013
• 3,704,996 US patent
• 468,262 with Markush claims
• Every eighth patent contains
Markush claims
Joseph J. Mallon, 2014

5. The real value in Patents not in Drugs…
You Need Good Markush Technology
or
Lot of manual work (with unavoidable mistakes)
Drug Discovery workflow
Find relevant
documents
Analyze prior art
and invent
something new
Create your
own Patents

6. Variation types
• Substituent variation
• Position variation
• Frequency variation
• Homology variation
• Variation inside variation (nested)
• Additional logical constraints

7. Patent Markush
• Nested R-groups
• Homologies
• Additional logical constraints
Combinatorial Library
• No nested R-groups
• No Homologies, Repeating
units and Position variation
Markush types

8. Markush chemical space size
Zhengwei Peng, 2014

9. Existing databases
Thomson Markush database (MMS)
2.4 million patents
1.6 million Markush structures
2 million specific compounds
CAS Markush database (MARPAT)
0.5 million patent
1 million Markush structures

10. REPRESENTATION
Markush representation techniques and challenges

11. ● R-groups
● Atom lists
● Bond list
● Position variations
● Repeating units
● Homology groups
Markush Representation

12. US5948793A
Claimed structure represented
with multiple structures
Workarounds

13. CONSTRUCTION
Sketching and automatic generation of Markush structures

14. General structure editors

15. Markush Editor
R-group definitions
Tree view Scaffold
Structure checker
Nesting view & Preview

16. Markush Composer
Automatic Markush generation from compound list

17. DOCUMENT CURATION
Extracting Markush structures from Patents

18. Representing Covered Chemical Space
● Document processing (XML,
PDF, HTML)
● Name to structure
● NLP technologies
● OSR (CLiDE & OSRA)

19. Automatic Markush extraction
ChemProspektor
InfoChem
Theseus research project founded
by the Federal Ministry of
Economics and Technology
Dr. Josef Eiblmaier, ACS National Meeting,
Philadelphia, August 19 - 22, 2012

20. ChemCurator Markush extraction view
Markush editor
Example structures
Annotated document
Selected structures
Structure checker

21. MARKUSH SEARCH & ANALYSIS
Understanding covered chemical space and comparison

22. Markush Search & Hit Visualization
● Substructure
● Full structure
● (Similarity)
● Hit visualization
● Non-Hit visualization

23. Markush Enumeration
• Full enumeration
• Random enumeration
• Partial enumeration
• Library size calculation
• Biased enumeration
• (Property distribution
characterization)

24. Markush Overlap
Overlapping chemical space
calculation
Results:
● Percentage of overlap
● Overlapping Markush
Benefits:
● No enumeration
● No size limitations

25. SUMMARY

26. Summary
• Important breakthroughs in Markush
technology
– Search & hit visualization
– Comparison
– Construction
– Curation
• Active development in challenging areas
– Similarity search
– Characterization

27. THANK YOU
Árpád Figyelmesi
afigyelmesi@chemaxon.com
27th ICIC International Conference for the Information Community
Nice 2015