Back to Journals » Advances and Applications in Bioinformatics and Chemistry » Volume 3

Modeling of thermodynamic and physico-chemical properties of coumarins bioactivity against Candida albicans using a Levenberg–Marquardt neural network

Authors Mousavi S, Bokharaie H, Rahimi S, Soror SA, Hamidi M

Published 13 August 2010 Volume 2010:3 Pages 59—66

DOI https://doi.org/10.2147/AABC.S11812

Review by Single anonymous peer review

Peer reviewer comments 1



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–­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.

Keywords: Levenberg–Marquardt algorithm, coumarin, neural network

Creative Commons License © 2010 The Author(s). This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution - Non Commercial (unported, v3.0) License. By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms.