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dc.contributor.authorYang, Shun-Chieh
dc.contributor.authorChang, Su-Sen
dc.contributor.authorChen, Hsin-Yi
dc.contributor.authorChen, Yu-Chian
dc.date.accessioned2012-04-26T18:51:25Z
dc.date.available2012-04-26T18:51:25Z
dc.date.issued2011-10
dc.date.submitted2011-06
dc.identifier.issn1553-734X
dc.identifier.issn1553-7358
dc.identifier.urihttp://hdl.handle.net/1721.1/70415
dc.description.abstractOverexpression 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.en_US
dc.description.sponsorshipNational Science Council of Taiwan (NSC 99-2221-E-039-013-)en_US
dc.description.sponsorshipCommittee on Chinese Medicine and Pharmacy (CCMP100-RD-030)en_US
dc.description.sponsorshipChina Medical University (CMU98-TCM)en_US
dc.description.sponsorshipChina Medical University (CMU99-TCM)en_US
dc.description.sponsorshipChina Medical University (CMU99-S-02)en_US
dc.description.sponsorshipChina Medical University (CMU99-ASIA-25)en_US
dc.description.sponsorshipChina Medical University (CMU99-ASIA-26)en_US
dc.description.sponsorshipChina Medical University (CMU99-ASIA-27)en_US
dc.description.sponsorshipChina Medical University (CMU99-ASIA-28)en_US
dc.description.sponsorshipAsia Universityen_US
dc.description.sponsorshipTaiwan Department of Health. Clinical Trial and Research Center of Excellence (DOH100-TD-B-111-004)en_US
dc.description.sponsorshipTaiwan Department of Health. Cancer Research Center of Excellence (DOH100-TD-C-111-005)en_US
dc.language.isoen_US
dc.publisherPublic Library of Scienceen_US
dc.relation.isversionofhttp://dx.doi.org/10.1371/journal.pcbi.1002189en_US
dc.rightsCreative Commons Attributionen_US
dc.rights.urihttp://creativecommons.org/licenses/by/2.5/en_US
dc.sourcePLoSen_US
dc.titleIdentification of Potent EGFR Inhibitors from TCM Database@Taiwanen_US
dc.typeArticleen_US
dc.identifier.citationYang, 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
dc.contributor.departmentMassachusetts Institute of Technology. Computational and Systems Biology Programen_US
dc.contributor.approverChen, Yu-Chian
dc.contributor.mitauthorChen, Yu-Chian
dc.relation.journalPLoS Computational Biologyen_US
dc.eprint.versionFinal published versionen_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dspace.orderedauthorsYang, Shun-Chieh; Chang, Su-Sen; Chen, Hsin-Yi; Chen, Calvin Yu-Chianen
mit.licensePUBLISHER_CCen_US
mit.metadata.statusComplete


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