Abstract:
:QSAR analysis for modeling the antileishmanial activity screening of a series of 49 nitro derivatives of Hydrazides were carried out using different Chemometrics methods. First, a large number of descriptors were calculated using Hyperchem, Mopac and Dragon softwares. Then, a suitable number of these descriptors were selected using multiple linear regression (MLR) technique. Then selected descriptors were used as inputs for artificial neural networks with three different weight update functions including Levenberg-Marquardt back propagation network (LM-ANN), resilient back propagation network (RP-ANN) and variable learning rate algorithm (GDX-ANN). The best artificial neural network model was an LM-ANN with a 5-5-1 architecture. Comparison of the results indicates that the LM-ANN method has better predictive power than the other methods.
journal_name
Eur J Med Chemjournal_title
European journal of medicinal chemistryauthors
Garkani-Nejad Z,Ahmadi-Roudi Bdoi
10.1016/j.ejmech.2009.11.019subject
Has Abstractpub_date
2010-02-01 00:00:00pages
719-26issue
2eissn
0223-5234issn
1768-3254pii
S0223-5234(09)00589-3journal_volume
45pub_type
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