Data/hora: 04/06/2024 09:42:46

Provedor de dados: 	17	
País: 	United Kingdom	
Título: 	ANN Based Virtual Classification Model for Discriminating Active and Inactive Withanolide E Analogs against  Human Breast Cancer Cell Line MCF-7	
Autores: 	Om Prakash; Feroz Khan; R.S. Sangwan.	
Data: 	2011-11-17	
Ano: 	2011	
Palavras-chave: 	Bioinformatics.	
Resumo: 	Withanolides are a group of natural C-28 steroids built on an ergostane skeleton and classified into two major groups according to their structural skeleton: (a) compounds with a beta-oriented side chain and (b) compounds with an alpha-oriented side chain. Withanolide E represents one of the members of the latter group. Classification of active compounds on the basis of pharmacophore against specific cancer cell line poses a serious concern at the primary stage of virtual screening. To overcome this problem we have developed an artificial neural network based virtual screening model for discriminating active and non-active Withanolide-E-like derivatives or analogs against human breast cancer cell line MCF-7. In the present work, a 2D chemical descriptors ensemble pharmacophore has been modelled on the basis of withanolide E structural featured molecules. The ANN structure activity based classification model could be useful for identification of active withanolide analogs as anticancer leads against MCF-7. This model can be used for predicting possible growth inhibitory concentration (logGI50) against breast cancer cell line MCF-7. The virtual screening tool &amp;#x201c;CanWithaANN&amp;#x201d; can be accessed at local network of CIMAP.	
Tipo: 	Poster	
Identificador: 	http://precedings.nature.com/documents/6616/version/1

oai:nature.com:10.1038/npre.2011.6616.1

http://dx.doi.org/10.1038/npre.2011.6616.1	
Fonte: 	Nature Precedings	
Fonte: 	Creative Commons Attribution 3.0 License