The mixing of information resources to transform data into information, and information into knowledge, for the intended purpose of making better decisions faster in the arena of drug lead identification and optimisation. [Brown 1998]
Chem(o)informatics is a generic term that encompasses the design, creation, organisation, management, retrieval, analysis, dissemination, visualisation and use of chemical information. [Paris 2000]
Many of the techniques used in chemoinformatics are in fact rather well established, being the result of years if not decades of research in academic, government and industrial laboratories. Indeed, it has been suggested that chemoinformatics is simply a new name for an old problem [Hann and Green 1999]. Whilst some of the current interest in chemoinformatics can be ascribed to the natural enthusiasm for things new, the main reason for its emergence can be traced to the need to deal with the vast quantities of data being generated by new approaches to drug discovery such as high-throughput screening and combinatorial chemistry [Russo 2002]. Concomitant increases in computer power, particularly for desktop machines, have provided the resources to deal with this deluge. Many other aspects of drug discovery also make use of chemoinformatics techniques, from the design of new synthetic routes by searching databases of known reactions through the construction of computational models such as Quantitative Structure–Activity Relationships that relate observed biological activity to chemical structure to the use of molecular docking programs to predict the three-dimensional structures of protein–ligand complexes in order to select a set of compounds for screening.
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