Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/1162
Type: Artigo de periódico
Title: A neural networks study of quinone compounds with trypanocidal activity
Author: MOLFETTA, Fabio Alberto de
ANGELOTTI, Wagner Fernando Delfino
ROMERO, Roseli Aparecida Francelin
MONTANARI, Carlos Alberto
SILVA, Alberico Borges Ferreira da
Abstract: This work investigates neural network models for predicting the trypanocidal activity of 28 quinone compounds. Artificial neural networks (ANN), such as multilayer perceptrons (MLP) and Kohonen models, were employed with the aim of modeling the nonlinear relationship between quantum and molecular descriptors and trypanocidal activity. The calculated descriptors and the principal components were used as input to train neural network models to verify the behavior of the nets. The best model for both network models (MLP and Kohonen) was obtained with four descriptors as input. The descriptors were T(5) (torsion angle), QTS1 (sum of absolute values of the atomic charges), VOLS2 (volume of the substituent at region B) and HOMO-1 (energy of the molecular orbital below HOMO). These descriptors provide information on the kind of interaction that occurs between the compounds and the biological receptor. Both neural network models used here can predict the trypanocidal activity of the quinone compounds with good agreement, with low errors in the testing set and a high correctness rate. Thanks to the nonlinear model obtained from the neural network models, we can conclude that electronic and structural properties are important factors in the interaction between quinone compounds that exhibit trypanocidal activity and their biological receptors. The final ANN models should be useful in the design of novel trypanocidal quinones having improved potency.
Subject: quinone
trypanocidal activity
neural network
multilayer perceptrons
Kohonen models
Country: Estados Unidos
Editor: SPRINGER
Citation: JOURNAL OF MOLECULAR MODELING, v.14, n.10, p.975-985, 2008
Rights: fechado
Identifier DOI: 10.1007/s00894-008-0332-x
Address: http://dx.doi.org/10.1007/s00894-008-0332-x
http://apps.isiknowledge.com/InboundService.do?Func=Frame&product=WOS&action=retrieve&SrcApp=EndNote&UT=000258611500011&Init=Yes&SrcAuth=ResearchSoft&mode=FullRecord
Date Issue: 2008
Appears in Collections:IQ - Artigos e Outros Documentos

Files in This Item:
File Description SizeFormat 
art_MOLFETTA_A_neural_networks_study_of_quinone_compounds_2008.pdfpublished version405.67 kBAdobe PDFView/Open


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.