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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...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
D.A. Spandidos
2016
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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 |
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. |
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