QSAR studies on BK channel activators.

Bioorg Med Chem

Dipartimento di Scienze Farmaceutiche, Università di Pisa, Via Bonanno 6, 56126 Pisa, Italy.

Published: January 2009

AI Article Synopsis

  • QSAR studies were conducted using a dataset of BK channel activators to create models that predict the affinity of New Chemical Entities (NCEs) for the channel.
  • Various molecular descriptors were calculated using CODESSA software to help split the dataset into training and test sets, serving as a foundation for developing the QSAR models.
  • The models underwent thorough validation to ensure accuracy, focusing on finding the simplest model that could effectively predict BK channel affinity.

Article 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.

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Source
http://dx.doi.org/10.1016/j.bmc.2008.10.068DOI Listing

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