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Development of machine learning models for the screening of potential HSP90 inhibitors
DC Field | Value | Language |
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dc.contributor.author | 동재준 | - |
dc.contributor.author | 이덕철 | - |
dc.date.accessioned | 2022-12-22T04:43:50Z | - |
dc.date.available | 2022-12-22T04:43:50Z | - |
dc.date.issued | 2022-10 | - |
dc.identifier.uri | https://ir.ymlib.yonsei.ac.kr/handle/22282913/192199 | - |
dc.description.abstract | Heat shock protein 90 (Hsp90) is a molecular chaperone playing a significant role in the folding of client proteins. This cellular protein is linked to the progression of several cancer types, including breast cancer, lung cancer, and gastrointestinal stromal tumors. Several oncogenic kinases are Hsp90 clients and their activity depends on this molecular chaperone. This makes HSP90 a prominent therapeutic target for cancer treatment. Studies have confirmed the inhibition of HSP90 as a striking therapeutic treatment for cancer management. In this study, we have utilized machine learning and different in silico approaches to screen the KCB database to identify the potential HSP90 inhibitors. Further evaluation of these inhibitors on various cancer cell lines showed favorable inhibitory activity. These inhibitors could serve as a basis for future development of effective HSP90 inhibitors. | - |
dc.description.statementOfResponsibility | open | - |
dc.language | English | - |
dc.publisher | Frontiers Media S.A. | - |
dc.relation.isPartOf | FRONTIERS IN MOLECULAR BIOSCIENCES | - |
dc.rights | CC BY-NC-ND 2.0 KR | - |
dc.title | Development of machine learning models for the screening of potential HSP90 inhibitors | - |
dc.type | Article | - |
dc.contributor.college | College of Medicine (의과대학) | - |
dc.contributor.department | Dept. of Family Medicine (가정의학교실) | - |
dc.contributor.googleauthor | Mohd Imran Khan | - |
dc.contributor.googleauthor | Taehwan Park | - |
dc.contributor.googleauthor | Mohammad Azhar Imran | - |
dc.contributor.googleauthor | Venu Venkatarame Gowda Saralamma | - |
dc.contributor.googleauthor | Duk Chul Lee | - |
dc.contributor.googleauthor | Jaehyuk Choi | - |
dc.contributor.googleauthor | Mohammad Hassan Baig | - |
dc.contributor.googleauthor | Jae-June Dong | - |
dc.identifier.doi | 10.3389/fmolb.2022.967510 | - |
dc.contributor.localId | A04927 | - |
dc.contributor.localId | A02716 | - |
dc.relation.journalcode | J04134 | - |
dc.identifier.eissn | 2296-889X | - |
dc.identifier.pmid | 36339714 | - |
dc.subject.keyword | Hsp90 | - |
dc.subject.keyword | cancer | - |
dc.subject.keyword | machine learing | - |
dc.subject.keyword | pharmacophore | - |
dc.subject.keyword | virtual screeening | - |
dc.contributor.alternativeName | Dong, Jae June | - |
dc.contributor.affiliatedAuthor | 동재준 | - |
dc.contributor.affiliatedAuthor | 이덕철 | - |
dc.citation.volume | 9 | - |
dc.citation.startPage | 967510 | - |
dc.identifier.bibliographicCitation | FRONTIERS IN MOLECULAR BIOSCIENCES, Vol.9 : 967510, 2022-10 | - |
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