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.
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.
authors.affiliation: Dipartimento di Scienze Farmaceutiche, Università di Pisa, 56126 Pisa, Italy.
authors.forename: Alessio
authors.initials: A
authors.lastname: Coi
authors.forename: Ilaria
authors.initials: I
authors.lastname: Massarelli
authors.forename: Marilena
authors.initials: M
authors.lastname: Saraceno
authors.forename: Niccolò
authors.initials: N
authors.lastname: Carli
authors.forename: Lara
authors.initials: L
authors.lastname: Testai
authors.forename: Vincenzo
authors.initials: V
authors.lastname: Calderone
authors.forename: Anna Maria
authors.initials: AM
authors.lastname: Bianucci
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D051638:Ether-A-Go-Go Potassium Channels / Q000037:antagonists & inhibitors / Q000235:genetics / Q000378:metabolism*; D006801:Humans; D016018:Least-Squares Analysis; D008024:Ligands; D021281:Quantitative Structure-Activity Relationship; D012044:Regression Analysis
chemical_list: D051638:Ether-A-Go-Go Potassium Channels; D008024:Ligands