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J Comput Aided Mol Des (2008) 22:873883 DOI 10.1007/s10822-008-9219-2
QSID Tool: a new three-dimensional QSAR environmental tool
Dong Sun Park Jae Min Kim Young Bok Lee Chang Ho Ahn
Received: 4 December 2007 / Accepted: 24 April 2008 / Published online: 30 May 2008 Springer Science+Business Media B.V. 2008
Abstract QSID Tool (Quantitative structureactivity relationship tool for Innovative Discovery) was developed to provide an easy-to-use, robust and high quality environmental tool for 3D QSAR. Predictive models developed with QSID Tool can accelerate the discovery of lead compounds by enabling researchers to formulate and test hypotheses for optimizing efcacy and increasing drug safety and bioavailability early in the process of drug discovery. QSID Tool was evaluated by comparison with SYBYL using two different datasets derived from the inhibitors of Trypsin (Bhm et al., J Med Chem 42:458, 1999) and p38-MAPK (Liverton et al., J Med Chem 42:2180, 1999; Romeiro et al., J Comput Aided Mol Des 19:385, 2005; Romeiro et al., J Mol Model 12:855, 2006). The results suggest that QSID Tool is a useful model for the prediction of new analogue activities.
Keywords 3D QSAR Binding afnity PLS
Cross-validation Molecular alignment Neural network
Introduction
Quantitative structureactivity relationship (QSAR) [1] is an area of computational chemistry that builds statistical models to predict quantities such as binding afnity, acute toxicity or pharmacokinetic parameters of existing or
hypothetical molecules. In more detail, QSAR is a mathematical relationship between the biological activity of a molecule and its geometric and physicochemical characteristics and this relationship can be used to evaluate the activity of new molecules. QSAR also represents an attempt to correlate structural or property descriptors of molecules with activities. These physicochemical descriptors, which include accounts for hydrophobicity, topology, hydrogen bonding, electrostatic eld force and steric effects, are determined empirically. Activities used in QSAR calculations include chemical measurements and biological or biochemical data. QSAR is currently being applied in many disciplines, with many applications pertaining to drug design and prediction of drug toxicity. Drug design includes not only ligand design, but also pharmacokinetics and toxicity that are mostly beyond the possibilities of structure/computer-aided design. Researchers have used QSAR for many years to develop a drug that contains better efcacy or better solubility or less toxicity, for example. The use...