QSAR studies on BK channel activators.
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.
Coi
Alessio
A
Dipartimento di Scienze Farmaceutiche, Università di Pisa, Via Bonanno 6, 56126 Pisa, Italy.
Fiamingo
Francesca Lidia
FL
Livi
Oreste
O
Calderone
Vincenzo
V
Martelli
Alma
A
Massarelli
Ilaria
I
Bianucci
Anna Maria
AM
D001185:Artificial Intelligence; D006801:Humans; D051036:Large-Conductance Calcium-Activated Potassium Channels / Q000819:agonists*; D021281:Quantitative Structure-Activity Relationship; D012984:Software
D051036:Large-Conductance Calcium-Activated Potassium Channels