Identifying HER2 Inhibitors from Natural Products Database
Name
Yang-2011-Identifying HER2 inh.pdf
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1.25 MB
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Author(s)
Yang, Shun-Chieh
Chang, Su-Sen
Chen, Yu-Chian
Date Issued
December 2011
Journal
PLoS ONE
Publisher
Public Library of Science
Citation
Yang, Shun-Chieh, Su-Sen Chang, and Calvin Yu-Chian Chen. “Identifying HER2 Inhibitors from Natural Products Database.” Ed. Franca Fraternali. PLoS ONE 6.12 (2011): e28793. Web. 23 Feb. 2012.
Version
Final published version
Abstract
The relationship between abnormal HER2 expression and cancer is important in cancer therapeutics. Formation and spread of cancer cells may be restricted by inhibiting HER2. We conducted ligand-based and structure-based studies to assess the potency of natural compounds as potential HER2 inhibitors. Multiple linear regression (MLR) and support vector machine (SVM) models were constructed to predict biological activities of natural compounds, and molecular dynamics (MD) was used to assess their stability with HER2 under a dynamic environment. Predicted bioactivities of the natural compounds ranged from 6.014–9.077 using MLR (r[superscript 2] = 0.7954) and 5.122–6.950 using SVM (r[superscript 2] = 0.8620). Both models were in agreement and suggest bioactivity based on candidate structure. Conformation changes caused by MD favored the formation of stabilizing H-bonds. All candidates had higher stability than Lapinatib, which may be due to the number and spatial distribution of additional H-bonds and hydrophobic interactions. Amino acids Lys724 and Lys736 are critical for binding in HER2, and Thr798, Cys805, and Asp808 are also important for increased stability. Candidates may block the entrance to the ATP binding site located within the inner regions and prevent downstream activation of HER2. Our multidirectional approach indicates that the natural compounds have good ligand efficacy in addition to stable binding affinities to HER2, and should be potent candidates of HER2 inhibitors. With regard to drug design, designing HER2 inhibitors with carboxyl or carbonyl groups available for H-bond formation with Lys724 and Lys736, and benzene groups for hydrophobic contact with Cys805 may improve protein-ligand stability.
MIT Department
Massachusetts Institute of Technology. Computational and Systems Biology Program
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DOI of Published Version
https://doi.org/10.1371/journal.pone.0028793
