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


ABSTRACT: 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.

SUBMITTER: Zhao GF 

PROVIDER: S-EPMC4940108 | biostudies-literature | 2016 Aug

REPOSITORIES: biostudies-literature

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

Zhao Guo-Fang GF   Huang Zuo-An ZA   Du Xue-Kui XK   Yang Ming-Lei ML   Huang Dan-Dan DD   Zhang Shun S  

Molecular medicine reports 20160527 2


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-sma  ...[more]

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