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

Mol Med Rep. 2016 Aug;14(2):1132-8. doi: 10.3892/mmr.2016.5350. Epub 2016 May 27.

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.

MeSH terms

  • Antineoplastic Agents / chemistry*
  • Antineoplastic Agents / pharmacology
  • Carcinoma, Non-Small-Cell Lung
  • Cell Line, Tumor
  • Computer Simulation
  • Drug Design*
  • Drugs, Chinese Herbal / chemistry*
  • Drugs, Chinese Herbal / pharmacology
  • ErbB Receptors / antagonists & inhibitors
  • ErbB Receptors / chemistry
  • Humans
  • Hydrogen Bonding
  • Lung Neoplasms
  • Models, Molecular
  • Molecular Conformation
  • Molecular Docking Simulation*
  • Molecular Dynamics Simulation*
  • Protein Binding

Substances

  • Antineoplastic Agents
  • Drugs, Chinese Herbal
  • ErbB Receptors