Identification of Potent EGFR Inhibitors from TCM Database@Taiwan
Overexpression of epidermal growth factor receptor (EGFR) has been associated with cancer. Targeted inhibition of the EGFR pathway has been shown to limit proliferation of cancerous cells. Hence, we employed Traditional Chinese Medicine Database (TCM Database@Taiwan) (http://tcm.cmu.edu.tw) to ident...
| Principais autores: | , , , |
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| Formato: | Artigo |
| Idioma: | en_US |
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Public Library of Science
2012
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| Acesso em linha: | http://hdl.handle.net/1721.1/70415 |
| _version_ | 1826201008416489472 |
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| author | Yang, Shun-Chieh Chang, Su-Sen Chen, Hsin-Yi Chen, Yu-Chian |
| author2 | Massachusetts Institute of Technology. Computational and Systems Biology Program |
| author_facet | Massachusetts Institute of Technology. Computational and Systems Biology Program Yang, Shun-Chieh Chang, Su-Sen Chen, Hsin-Yi Chen, Yu-Chian |
| author_sort | Yang, Shun-Chieh |
| collection | MIT |
| description | Overexpression of epidermal growth factor receptor (EGFR) has been associated with cancer. Targeted inhibition of the EGFR pathway has been shown to limit proliferation of cancerous cells. Hence, we employed Traditional Chinese Medicine Database (TCM Database@Taiwan) (http://tcm.cmu.edu.tw) to identify potential EGFR inhibitor. Multiple Linear Regression (MLR), Support Vector Machine (SVM), Comparative Molecular Field Analysis (CoMFA), and Comparative Molecular Similarities Indices Analysis (CoMSIA) models were generated using a training set of EGFR ligands of known inhibitory activities. The top four TCM candidates based on DockScore were 2-O-caffeoyl tartaric acid, Emitine, Rosmaricine, and 2-O-feruloyl tartaric acid, and all had higher binding affinities than the control Iressa®. The TCM candidates had interactions with Asp855, Lys716, and Lys728, all which are residues of the protein kinase binding site. Validated MLR (r² = 0.7858) and SVM (r² = 0.8754) models predicted good bioactivity for the TCM candidates. In addition, the TCM candidates contoured well to the 3D-Quantitative Structure-Activity Relationship (3D-QSAR) map derived from the CoMFA (q² = 0.721, r² = 0.986) and CoMSIA (q² = 0.662, r² = 0.988) models. The steric field, hydrophobic field, and H-bond of the 3D-QSAR map were well matched by each TCM candidate. Molecular docking indicated that all TCM candidates formed H-bonds within the EGFR protein kinase domain. Based on the different structures, H-bonds were formed at either Asp855 or Lys716/Lys728. The compounds remained stable throughout molecular dynamics (MD) simulation. Based on the results of this study, 2-O-caffeoyl tartaric acid, Emitine, Rosmaricine, and 2-O-feruloyl tartaric acid are suggested to be potential EGFR inhibitors. |
| first_indexed | 2024-09-23T11:45:13Z |
| format | Article |
| id | mit-1721.1/70415 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T11:45:13Z |
| publishDate | 2012 |
| publisher | Public Library of Science |
| record_format | dspace |
| spelling | mit-1721.1/704152022-10-01T05:43:30Z Identification of Potent EGFR Inhibitors from TCM Database@Taiwan Yang, Shun-Chieh Chang, Su-Sen Chen, Hsin-Yi Chen, Yu-Chian Massachusetts Institute of Technology. Computational and Systems Biology Program Chen, Yu-Chian Chen, Yu-Chian Overexpression of epidermal growth factor receptor (EGFR) has been associated with cancer. Targeted inhibition of the EGFR pathway has been shown to limit proliferation of cancerous cells. Hence, we employed Traditional Chinese Medicine Database (TCM Database@Taiwan) (http://tcm.cmu.edu.tw) to identify potential EGFR inhibitor. Multiple Linear Regression (MLR), Support Vector Machine (SVM), Comparative Molecular Field Analysis (CoMFA), and Comparative Molecular Similarities Indices Analysis (CoMSIA) models were generated using a training set of EGFR ligands of known inhibitory activities. The top four TCM candidates based on DockScore were 2-O-caffeoyl tartaric acid, Emitine, Rosmaricine, and 2-O-feruloyl tartaric acid, and all had higher binding affinities than the control Iressa®. The TCM candidates had interactions with Asp855, Lys716, and Lys728, all which are residues of the protein kinase binding site. Validated MLR (r² = 0.7858) and SVM (r² = 0.8754) models predicted good bioactivity for the TCM candidates. In addition, the TCM candidates contoured well to the 3D-Quantitative Structure-Activity Relationship (3D-QSAR) map derived from the CoMFA (q² = 0.721, r² = 0.986) and CoMSIA (q² = 0.662, r² = 0.988) models. The steric field, hydrophobic field, and H-bond of the 3D-QSAR map were well matched by each TCM candidate. Molecular docking indicated that all TCM candidates formed H-bonds within the EGFR protein kinase domain. Based on the different structures, H-bonds were formed at either Asp855 or Lys716/Lys728. The compounds remained stable throughout molecular dynamics (MD) simulation. Based on the results of this study, 2-O-caffeoyl tartaric acid, Emitine, Rosmaricine, and 2-O-feruloyl tartaric acid are suggested to be potential EGFR inhibitors. National Science Council of Taiwan (NSC 99-2221-E-039-013-) Committee on Chinese Medicine and Pharmacy (CCMP100-RD-030) China Medical University (CMU98-TCM) China Medical University (CMU99-TCM) China Medical University (CMU99-S-02) China Medical University (CMU99-ASIA-25) China Medical University (CMU99-ASIA-26) China Medical University (CMU99-ASIA-27) China Medical University (CMU99-ASIA-28) Asia University Taiwan Department of Health. Clinical Trial and Research Center of Excellence (DOH100-TD-B-111-004) Taiwan Department of Health. Cancer Research Center of Excellence (DOH100-TD-C-111-005) 2012-04-26T18:51:25Z 2012-04-26T18:51:25Z 2011-10 2011-06 Article http://purl.org/eprint/type/JournalArticle 1553-734X 1553-7358 http://hdl.handle.net/1721.1/70415 Yang, Shun-Chieh et al. “Identification of Potent EGFR Inhibitors from TCM Database@Taiwan.” Ed. James M. Briggs. PLoS Computational Biology 7.10 (2011): e1002189. Web. 26 Apr. 2012. en_US http://dx.doi.org/10.1371/journal.pcbi.1002189 PLoS Computational Biology Creative Commons Attribution http://creativecommons.org/licenses/by/2.5/ application/pdf Public Library of Science PLoS |
| spellingShingle | Yang, Shun-Chieh Chang, Su-Sen Chen, Hsin-Yi Chen, Yu-Chian Identification of Potent EGFR Inhibitors from TCM Database@Taiwan |
| title | Identification of Potent EGFR Inhibitors from TCM Database@Taiwan |
| title_full | Identification of Potent EGFR Inhibitors from TCM Database@Taiwan |
| title_fullStr | Identification of Potent EGFR Inhibitors from TCM Database@Taiwan |
| title_full_unstemmed | Identification of Potent EGFR Inhibitors from TCM Database@Taiwan |
| title_short | Identification of Potent EGFR Inhibitors from TCM Database@Taiwan |
| title_sort | identification of potent egfr inhibitors from tcm database taiwan |
| url | http://hdl.handle.net/1721.1/70415 |
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