Cheminformatics is the use of computer and informational techniques, applied to a range of problems in the field of chemistry. Also known as chemoinformatics and chemical informatics. These in silico techniques are used in pharmaceutical companies in the process of drug discovery.

History

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The term (chemical) graph was introduced by Cullen in 1758.D. Bonchev, D.H. Rouvray: Chemical Graph Theory: Introduction and Fundamentals. Gordon and Breach Science Publishers, 1990, ISBN 0-85626-454-7. He used those graphs for affinity diagrams showing a relationship between chemical substances. Those results have never been published officially.

The term Chemoinformatics was defined by F.K. BrownF.K. Brown Chapter 35. Chemoinformatics: What is it and How does it Impact Drug Discovery. Annual Reports in Med. Chem., Ed. James A. Bristol, 1998, Vol. 33, pp. 375.Brown, Frank. Editorial Opinion: Chemoinformatics – a ten year update Current Opinion in Drug Discovery & Development (2005), 8(3), 296-302. in 1998:

Chemoinformatics is the mixing of those information resources to transform data into information and information into knowledge for the intended purpose of making better decisions faster in the area of drug lead identification and optimization. (Brown, 1998).

Since this, the term has evolved to be established as Cheminformatics ^*.

Basics

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Cheminformatics combines the scientific working fields of Chemistry and Computer science for example in the area of chemical Graph theory and mining the chemical space.Gasteiger J.(Editor), Engel T.(Editor): Chemoinformatics : A Textbook. John Wiley & Sons, 2004, ISBN 3-52730-681-1A.R. Leach, V.J. Gillet: An Introduction to Chemoinformatics. Springer, 2003, ISBN 1-4020-1347-7 It is to be expected that the chemical space contains at least $10^\{62\}$ molecules.R. Lahana: How many leads from HTS?. Drug Discovery Today, 1999, 4, 447-448.

Applications

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Virtual screening

Creation of large in silico virtual libraries of compounds, which are then submitted to a docking program. In some cases, combinatorial chemistry are used in the development of the library to increase the efficiency in mining the chemical space. More commonly, a diverse library of small molecules or natural products is screened.

Quantitative Structure Activity Relationship (QSAR)

Calculation of Quantitative Structure Activity Relationship and Quantitative Structure Property Relationship values, used to predict the activity of compounds from their structures. In this context there is also a strong relationship to Chemometrics. In this context chemical expert systems are also highly important, since they represent parts of chemical knowledge as an in silico representation.

Typical computer science terms for data mining and machine learning topics are:

• Unstructured data
• Structured Data Mining, means mining Structured data
  • Database mining
  • Graph mining
  • Molecule mining
  • Sequence mining
  • Tree mining

File formats

In silico representation of chemical structures, using formats such as the XML based Chemical Markup Language, or SMILES. These representations are often used for storage in large chemical databases. See also Chemical file formats

Miscellaneous

• Statistics
• Data analysis
• Scientific Visualization

References

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See also

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• Bioinformatics
• Chemical file format
• Chemogenomics
• Computational chemistry
• Combinatorial chemistry
• Molecular modelling
• List of chemistry topics
• Journal of Chemical Information and Modeling

External links

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• Comprehensive cheminformatics link list and data set repository: http://www.cheminformatics.org
• A cheminformatics glossary: http://www.genomicglossaries.com/content/chemoinformatics_gloss.asp
• XML- CML.ORG - The Site for Chemical Markup Language: http://www.xml-cml.org/
• VCCLAB Virtual Computational Chemistry Laboratory: http://www.vcclab.org
• Famous Cheminformatics quotations

Computational chemistry | Cheminformatics

Cheminformatik | Chemo-informatique | ケモインフォマティクス