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摘要
deling of thermodynamic and physico-chemical properties of coumarins bioactivity against Candida albicans using a Levenberg每Marquardt neural network Original Research (4925) Total Article Views Authors: Seyyedeh Soghra Mousavi, Hanieh Bokharaie, Shadi Rahimi, et al Published Date August 2010 Volume 2010:3 Pages 59 - 66 DOI: http://dx.doi.org/10.2147/AABC.S11812 Seyyedeh Soghra Mousavi1, Hanieh Bokharaie2, Shadi Rahimi3, Sima Azadi Soror4, Mehrdad Hamidi5 1Department of Biotechnology, School of Pharmacy, Zanjan University of Medical Science, Zanjan, Iran; 2Genetic Group, Biology Department, Faculty of Basic Sciences, Science and Research Branch, Islamic Azad University, Tehran, Iran; 3Department of Biology, Faculty of Science, Tarbiat Moallem University, Tehran, Iran: 4Plant Protection Department, Faculty of Agriculture, Bu-Ali Sina University, Hamedan, Iran; 5Department of Pharmaceutics, School of Pharmacy, Zanjan University of Medical Science, Zanjan, Iran Abstract: In recent years, due to vital need for novel fungicidal agents, investigation on natural antifungal resources has been increased. The special features exhibited by neural -network classifiers make them suitable for handling complex problems like analyzing -different properties of candidate compounds in computer-aided drug design. In this study, by using a Levenberg每-Marquardt (LM) neural network (the fastest of the training algorithms), the -relation between some important thermodynamic and physico-chemical properties of coumarin compounds and their biological activities (tested against Candida albicans) has been evaluated. A set of already reported antifungal bioactive coumarin and some well-known physical descriptors have been selected and using LM training algorithm the best architecture of neural model has been designed for forecasting the new bioactive compounds.
