title: QSAR studies on BK channel activators.
abstract: QSAR studies were developed on the basis of a dataset comprising BK channel activators previously synthesized and biologically assayed in our laboratory, in order to obtain highly accurate models enabling prediction of affinity toward the channel for New Chemical Entities (NCEs). Many molecular descriptors were computed by the CODESSA software. They were initially exploited in order to rationally split the available dataset into training and test set pairs, which supplied the basis for the development of QSAR models. Models were subjected to rigorous validation analysis based on the estimate of several statistical parameters, for the seek of the most accurate and simplest model enabling prediction of BK channel affinity.
authors.affiliation: Dipartimento di Scienze Farmaceutiche, Università di Pisa, Via Bonanno 6, 56126 Pisa, Italy.
authors.forename: Alessio
authors.initials: A
authors.lastname: Coi
authors.forename: Francesca Lidia
authors.initials: FL
authors.lastname: Fiamingo
authors.forename: Oreste
authors.initials: O
authors.lastname: Livi
authors.forename: Vincenzo
authors.initials: V
authors.lastname: Calderone
authors.forename: Alma
authors.initials: A
authors.lastname: Martelli
authors.forename: Ilaria
authors.initials: I
authors.lastname: Massarelli
authors.forename: Anna Maria
authors.initials: AM
authors.lastname: Bianucci
mesh_terms: D001185:Artificial Intelligence; D006801:Humans; D051036:Large-Conductance Calcium-Activated Potassium Channels / Q000819:agonists*; D021281:Quantitative Structure-Activity Relationship; D012984:Software
chemical_list: D051036:Large-Conductance Calcium-Activated Potassium Channels