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  • Title: Quantitative structure-activity relationship models for predicting biological properties, developed by combining structure- and ligand-based approaches: an application to the human ether-a-go-go-related gene potassium channel inhibition.
    Author: Coi A, Massarelli I, Saraceno M, Carli N, Testai L, Calderone V, Bianucci AM.
    Journal: Chem Biol Drug Des; 2009 Oct; 74(4):416-33. PubMed ID: 19751420.
    Abstract:
    A strategy for developing accurate quantitative structure-activity relationship models enabling predictions of biological properties, when suitable knowledge concerning both ligands and biological target is available, was tested on a data set where molecules are characterized by high structural diversity. Such a strategy was applied to human ether-a-go-go-related gene K(+) channel inhibition and consists of a combination of ligand- and structure-based approaches, which can be carried out whenever the three-dimensional structure of the target macromolecule is known or may be modeled with good accuracy. Molecular conformations of ligands were obtained by means of molecular docking, performed in a previously built theoretical model of the channel pore, so that descriptors depending upon the three-dimensional molecular structure were properly computed. A modification of the directed sphere-exclusion algorithm was developed and exploited to properly splitting the whole dataset into Training/Test set pairs. Molecular descriptors, computed by means of the codessa program, were used for the search of reliable quantitative structure-activity relationship models that were subsequently identified through a rigorous validation analysis. Finally, pIC(50) values of a prediction set, external to the initial dataset, were predicted and the results confirmed the high predictive power of the model within a quite wide chemical space.
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