Mining of the chemical information in GRID environment

Authors:
Uko Maran;Sulev Sild;Iiris Kahn;Kalev Takkis
Affiliations:
Department of Chemistry, University of Tartu, Tartu, Estonia;Department of Chemistry, University of Tartu, Tartu, Estonia;Department of Chemistry, University of Tartu, Tartu, Estonia;Department of Chemistry, University of Tartu, Tartu, Estonia
Venue:
Future Generation Computer Systems - Special section: Data mining in grid computing environments
Year:
2007

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Abstract

Data mining and knowledge exploration of chemical information is the key step in life science fields, such as drug discovery, property/activity prediction and many others, where the meaningful linking of experimental knowledge and information about chemical structure is necessary. In these fields the applications are often based on quantitative structure activity/property relationship (QSAR/QSPR) models, where relevant information for models is extracted from the large data sets of molecular descriptors. This requires multiple software packages to be used and linked via usually complicated workflow. It also requires extensive computational resources to be accessed via Grid middleware when applied to the complex datasets and/or when the time factor in decision support is critical. The OpenMolGRID system provides a grid-enabled infrastructure for molecular design and engineering, including tools for QSAR/QSPR modelling and building automated scientific workflows on top of the UNICORE Grid middleware. In the present article, the OpenMolGRID system is used for the modelling of the inhibition of aspartyl protease enzyme. Efficient inhibition of this enzyme can combat HIV-1.