Article citationsMore>>

F. Zheng, E. Bayram, S. P. Sumithran, J. T. Ayers, C. Zhan, J. D. Schmitt and L. P. Dwoskin, “QSAR Modeling of Monoand Bis-Quaternary Ammonium Salts That Act as Antagonists at Neuronal Nicotinic Acetylcholine Receptors Mediating Dopamine Release,” Bioorganic & Medicinal Chemistry, Vol. 14, No. 9, 2006, pp. 3017-3037. doi:10.1016/j.bmc.2005.12.036

has been cited by the following article:

• TITLE: Using Multiple Linear Regression and Artificial Neural Network Techniques for Predicting CCR5 Binding Affinity of Substituted 1-(3, 3-Diphenylpropyl)-Piperidinyl Amides and Ureas

  AUTHORS: Rokaya Mouhibi, Mohamed Zahouily, Khalid El Akri, Naîma Hanafi

  KEYWORDS: Artificial Neural Network, Descriptors; CCR5; Multiple Linear Regression; Structure-Activity Relationship

  JOURNAL NAME: Open Journal of Medicinal Chemistry, Vol.3 No.1, March 29, 2013

  ABSTRACT: Quantitative structure–activity relationship (QSAR) models were developed to predict for CCR5 binding affinity of substituted 1-(3, 3-diphenylpropyl)-piperidinyl amides and ureas using multiple linear regression (MLR) and artificial neural network (ANN) techniques. A model with four descriptors, including Hydrogen-bonding donors HBD(R7), the partition coefficient between n-octanol and water logP and logP(R1) and Molecular weight MW(R7), showed good statistics both in the regression and artificial neural network with a configuration of (4-3-1) by using Bayesian and Leven-berg-Marquardt Methods. Comparison of the descriptor’s contribution obtained in MLR and ANN analysis shows that the contribution of some of the descriptors to activity may be non-linear.