title: Neural networks studies: quantitative structure-activity relationships of antifungal 1.
abstract: Models of relationships between structure and antifungal activity of 1-[2-(substituted phenyl)allyl]imidazoles and related compounds were constructed by means of a multilayer neural network using the back-propagation (BP) algorithm. Each molecule was described by three structural and one physicochemical parameters. The leave-one-out procedure was used to assess the predictive ability of a neural network model. The results obtained were compared to those given in the literature by the multiple linear regression (MLR), and were found to be better. The contribution of each descriptor to the structure-activity relationships was evaluated. Hydrophobicity of the molecule was confirmed to take the most relevant part in the molecular description.
authors: Département de Chimie, Faculté des Sciences Semlalia, Université Cadi Ayyad, Morocco.
authors: S
authors: S
authors: Mghazli
authors: A
authors: A
authors: Jaouad
authors: M
authors: M
authors: Mansour
authors: D
authors: D
authors: Villemin
authors: D
authors: D
authors: Cherqaoui
mesh_terms: D000935:Antifungal Agents / Q000737:chemistry* / Q000494:pharmacology*; D005544:Forecasting / Q000379:methods; D007093:Imidazoles / Q000737:chemistry* / Q000494:pharmacology; D008956:Models, Chemical; D015233:Models, Statistical; D016571:Neural Networks, Computer; D021281:Quantitative Structure-Activity Relationship; D012044:Regression Analysis
chemical_list: D000935:Antifungal Agents; D007093:Imidazoles