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Molecular docking studies of Traditional Chinese Medicinal compounds against known protein targets to treat non-small cell lung carcinomas

In silico drug design using virtual screening, absorption, distribution, metabolism and excretion (ADME)/Tox data analysis, automated docking and molecular dynamics simulations for the determination of lead compounds for further in vitro analysis is a cost effective strategy. The present study used...

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Detalles Bibliográficos
Autores principales: Zhao, Guo-Fang, Huang, Zuo-An, Du, Xue-Kui, Yang, Ming-Lei, Huang, Dan-Dan, Zhang, Shun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: D.A. Spandidos 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4940108/
https://www.ncbi.nlm.nih.gov/pubmed/27279494
http://dx.doi.org/10.3892/mmr.2016.5350
Descripción
Sumario:In silico drug design using virtual screening, absorption, distribution, metabolism and excretion (ADME)/Tox data analysis, automated docking and molecular dynamics simulations for the determination of lead compounds for further in vitro analysis is a cost effective strategy. The present study used this strategy to discover novel lead compounds from an in-house database of Traditional Chinese Medicinal (TCM) compounds against epithelial growth factor receptor (EGFR) protein for targeting non-small cell lung cancer (NSCLC). After virtual screening of an initial dataset of 2,242 TCM compounds, leads were identified based on binding energy and ADME/Tox data and subjected to automated docking followed by molecular dynamics simulation. Triptolide, a top compound identified by this vigorous in silico screening, was then tested in vitro on the H2347 cell line carrying wild-type EGFR, revealing an anti-proliferative potency similar to that of known drugs against NSCLC.