Pharmaceutical companies are screening millions of molecules in silica. These processes require fast and accurate predictive QSAR models. Unfortunately, nowadays these models do not include information-rich quantum-chemical descriptors, because of their time-consuming calculation procedure. Collection of experimental data is also difficult, because the sources are usually located in disparate resources. These challenges make indispensable the usage of GRID systems. OpenMolGRID (Open Computing GRID for Molecular Science and Engineering) is one of the first realizations of the GRID technology in drug design. The system is designed to build QSAR models based on thousands of different type of descriptors, and apply these models to find novel structures with targeted properties. An implemented data warehouse technology makes possible to collect data from geographically distributed, heterogeneous resources. The system will be tested in real-life situations: Predictive models will be built on in vitro human toxicity values determined for 30,000 novel and diverse chemical structures. © Springer-Verlag 2004.
CITATION STYLE
Darvas, F., Papp, Á., Bágyi, I., Ambrus, G., & Ürge, L. (2004). OpenMolGRID, a GRID based system for solving large-scale drug design problems. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 3165, 69–76. https://doi.org/10.1007/978-3-540-28642-4_8
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