1. Chemoinformatics, cheminformatics, chemical informatics: What is it?
Gary Wiggins and Wendie Shreve
Chemistry Library
Indiana University

2. Abstract
The terms “cheminformatics,” “chemiinformatics,” “cheminformatics,” and “chemical informatics” are all used to describe a broad array of computer techniques and applications to solve chemistry problems. We will look at the areas that comprise chemical informatics by examining the topics in existing textbooks and other secondary sources. The identified topics will be mapped to the graduate courses in the Chemical Informatics program at Indiana University

3. Dmitrii Ivanovich Mendeleev, 1834-1907
Discoverer of the Periodic Table—
An Early “Chemoinformatician”

4. Why Mendeleev?
Faced with a large amount of data, with many gaps, Mendeleev:
Sought patterns where none were obvious,
Made predictions about properties of unknown chemical substances, based on observed properties of known substances,
Created a great visualization tool!

5. The Periodic Table of the Elements by Mark Winter

6. Chemical Informatics: The New “Handmaid” of Chemistry
M.G. Mellon noted that Analytical Chemistry was at one time considered the handmaid of chemistry. (his Chemical Publications, 5th ed.)
Handmaid (def) – Something that is necessarily subservient or subordinate to another: Ceremony is but the handmaid of worship. (Also, Handmaiden)
--Random House Unabridged Dictionary, 2nd ed., 1993.
Handmaid, maybe, but definitely not handmade!

7. What is Chemical Informatics?
Chemical informatics helps chemists investigate new problems and organize and analyze scientific data to develop novel compounds, materials, and processes through the application of information technology.

8. Cheminformatics, etc. in the Lit, March 2000

9. Cheminformatics, etc. in the Lit, 31 July 2003

10. Indiana University MS in Chemical Informatics
Major aspects of chemical informatics
Information Acquisition: Methods for generating and collecting data empirically (experimentation) or from theory (molecular simulation)
Information Management: Storage and retrieval of information
Information Use: Data Analysis, correlation, and application to problems in the chemical and biochemical sciences

11. UMIST MSc in Cheminformatics
“This is a modular, one-year course which provides high-level training in the handling of chemical and biochemical information, molecular modelling and other aspects of cheminformatics.”

12. University of Sheffield MSc in Chemoinformatics Program
“Chemoinformatics involves the application of IT to chemical data and includes topics such as chemical databases, combinatorial library design, structure-activity relationships and structure-based drug design.”

13. Sheffield’s Short Course
Offered for the past three summers, in 4 days, emphasizes applications in modern drug discovery
Covers:
2D databases and database searching
Diversity and compound selection
Moving into 3D: experimental data sources
Computational methods for 3D

14. Sheffield Short Course
Coverage (continued):
3D databases
Combinatorial libraries
Analysis of high-throughput screening data

15. Graduate Courses in Chemical Informatics at Indiana University
C571 Chemical Information Technology
C572 Molecular Modeling & Computational Chemistry

16. JCICS – Major Research Areas
Chemical Information
Text Searching
Structure and Substructure Searching
Databases
Patents
George W.A. Milne
C571 Lecture
Fall 2002

17. JCICS – Major Research Areas
Chemical Computation
Quantum Mechanics
Statistics (regression, neural nets, etc.)
QSAR, QSPR
Graph Theory
DNA Computing
George W.A. Milne
C571 Lecture
Fall 2002

18. JCICS – Major Research Areas
Molecular Modeling
3D Structure Generation
3D Searching (pharmacophores)
Docking
George W.A. Milne
C571 Lecture
Fall 2002

19. JCICS – Major Research Areas
Biopharmaceutical Computation
Drug Design
Combinatorial Chemistry
Protein and Enzyme Structure
Membrane Structure
ADME-related Research
George W.A. Milne
C571 Lecture
Fall 2002

20. Desirable Skills for Chemistry Grads
George W.A. Milne
C571 Lecture, Fall 2002

21. Frank Brown’s Definition
…the mixing of information resources to transform data into information and information into knowledge, for the intended purpose of making decisions faster in the arena of drug lead identification and optimisation.
Brown, F.K. “Chemoinformatics, what it is and how does it impact drug discovery.” Annual Reports in Medicinal Chemistry, 1998, 33,

22. Application of Cheminformatics in the Drug Industry
The computer is used to analyze the interactions between the drug and the receptor site and design molecules with an optimal fit.
Once targets are developed, libraries of compounds are screened for activity with one or more relevant assays using High Throughput Screening.

23. Application of Cheminformatics in the Drug Industry
Hits are then evaluated for binding, potency, selectivity, and functional activity.
Seeking to improve:
Potency
Absorption
Distribution
Metabolism
Elimination

24. Some Methods and Tools Structure/Activity Relationships
Genetic Algorithms
Statistical Tools (e.g., recursive pairing)
Data Analysis Tools
Visualization
Hardware Developments
Chemically-Aware Web Language (CML)

25. CAS Indexing of a Relevant Article
“The impact of informatics and computational chemistry on synthesis and screening.” Manly, Charles J.; Louise-May, Shirley; Hammer, Jack D. Drug Discovery Today (2001), 6(21),
A review with 87 references

26. Controlled Vocabulary Indexing of the Manly Article
Chemistry
High throughput screening
Drug screening
Bioinformatics
Combinatorial chemistry
Drug design
Molecular modeling
Pharmacokinetics
Combinatorial library

27. Informatics Components (per Dow Chemical Visitors)
Architecture
LIMS
Components
of an
Informatics
System
Electronic Records Mgmt
Substance
Registry
Process Data Mgmt
Integration & User Interface

28. Chemical R&D vs. Pharmaceutical R&D
Much smaller number of substances tested in a week
Much larger number of tests to consider
Answers tend to come in shades of gray rather than yes or no
Targets change frequently in chemical R&D
Must integrate a large variety of sources that were not designed for integration
New approach to taxonomy is needed.
--L. David Rothman
The Dow Chemical Co.

29. Characteristics of a Chemical Informatics Faculty Member
Appreciates the value of algorithms
Is interested in data mining, data modeling, and relational database systems
Pays attention to searching issues and the literature
Has compatability and commonality with bioinformatics research
Is able to talk to computer scientists.

30. Major Journals
Journal of Chemical Information and Computer Sciences (ACS)
Journal of Molecular Graphics and Modelling (Elsevier)
Journal of Combinatorial Chemistry (ACS)
Journal of Proteome Research (ACS)
Proteomics (Wiley-VCH)
Molecular and Cellular Proteomics (ASBMB)
Acta Crystallographica (IUCr)

31. Textbooks
Leach, Andrew R.; Gillet, Valerie J. An Introduction to Chemoinformatics. Kluwer, ISBN
Gasteiger,Johann;Engel, Thomas. Chemoinformatics: A Textbook. Wiley-VCH, ISBN

32. Reference Works
Encyclopedia of Computational Chemistry, Schleyer, P. von R.; Allinger, N.L.; Clark, T.; Gasteiger, J.; Kollman, P.A.; Schaefer, H.F.; Shreiner, P.R. (Eds.). 5 v. Wiley, Chichester, 1998.
Gasteiger, Johann J., ed. Handbook of Chemoinformatics: From Data to Knowledge. 4 v. Wiley-VCH, ISBN
Reviews in Computational Chemistry. Wiley-VCH, 1990-
Paris, Greg. Bibliography: Chemical Information Retrieval and 3D Searching.
SIRCh: Chemical Informatics Home Page at Indiana University

33. Conclusion Chemical Informatics is an evolving field with many facets.
It will become increasingly important in areas of chemistry outside the drug industry.
It will play an increasing role in the developing area of proteomics.

34. Bibliography
Brown, F.K. “Chemoinformatics, what it is and how does it impact drug discovery.” Annual Reports in Medicinal Chemistry, 1998, 33,
Glen, Robert. “Developing tools and standards in molecular informatics.” Chemical Communications, 2002, (23),
Hann, Mike; Green, Richard. “Chemoinformatics—a new name for an old problem?” Current Opinion in Chemical Biology, 1979, 3,
Lipinski, C.A.; Lombardo, F.; Dominy, B.W.; Feeney, P.J. “Experimental and computational approaches to estimate the solubility and permeability in drug discovery and development settings. Advanced Drug Delivery Reviews, 1997, 23, 3-15.
Rosso, Eugene. “Chemistry plans a structural overhaul.” Nature (Naturejobs) 12 September 2002, 419(6903).
Rothman, L. David. “Information management for research in the chemical industry.” Abstracts of Papers, 223rd ACS National Meeting, Orlando, FL, United States, April 7-11, (2002), CINF-044.
Smith, Chris. “Cheminformatics: Redefining the crucible.” The Scientist, 2002, 16(8), 40.