| Cheminformatics |
Website Links For Cheminformatics |
Information AboutCheminformatics |
| CATEGORIES ABOUT CHEMINFORMATICS | |
| computational chemistry | |
| cheminformatics | |
| drug discovery | |
| chemistrycomputational chemistry | |
| cheminformatics | |
| drug discovery | |
| chemistry | |
| chemistry | |
| statistics | |
| computational science | |
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HISTORY The term (chemical) Graph was introduced by Cullen in 1758 (Bonchev,1990). 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. Brown 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 {Link without Title} . BASICS Cheminformatics combines the scientific working fields of Chemistry and Computer Science especially in the area of chemical Graph Theory (Bonchev/Rouvray, 1990) and mining the chemical space. It is to be expected that the chemical Space contains at least molecules (Lahana, 1999). APPLICATIONS Screening Creation of large In Silico ''virtual libraries'' of compounds using Combinatorial Chemistry techniques to increase the efficiency in mining the chemical space. The post-QSAR technologies enable researchers to create the focused (targeted) hit compound libraries, that are the libraries of small molecules, which are ranked according to their accurately calculated constant Affinity to a particular protein disease Biological Target and pre-defined Toxicology profile. So now this virtual screening procedure considerably reduces time and costs in Drug Discovery . 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 System s 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:
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 Database s. ''See also '' Chemical File Format s Miscellaneous FURTHER READING
SEE ALSO EXTERNAL LINKS
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