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Artificial intelligence-driven new drug discovery targeting serine/threonine kinase 33 for cancer treatment
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Tran, Na Ly | - |
dc.contributor.author | Kim, Hyerim | - |
dc.contributor.author | Shin, Cheol-Hee | - |
dc.contributor.author | Ko, Eun | - |
dc.contributor.author | Oh, Seung Ja | - |
dc.date.accessioned | 2023-12-18T01:18:26Z | - |
dc.date.available | 2023-12-18T10:19:52Z | - |
dc.date.issued | 2023-12-12 | - |
dc.identifier.citation | Cancer Cell International, Vol.23(1):321 | ko_KR |
dc.identifier.issn | 1475-2867 | - |
dc.identifier.uri | https://hdl.handle.net/10371/198717 | - |
dc.description.abstract | Background
Artificial intelligence (AI) is capable of integrating a large amount of related information to predict therapeutic relationships such as disease treatment with known drugs, gene expression, and drug-target binding. AI has gained increasing attention as a promising tool for next-generation drug development. Methods An AI method was used for drug repurposing and target identification for cancer. Among 8 survived candidates after background checking, N-(1-propyl-1H-1,3-benzodiazol-2-yl)-3-(pyrrolidine-1-sulfonyl) benzamide (Z29077885) was newly selected as an new anti-cancer drug, and the anti-cancer efficacy of Z29077885 was confirmed using cell viability, western blot, cell cycle, apoptosis assay in MDA-MB 231 and A549 in vitro. Then, anti-tumor efficacy of Z29077885 was validated in an in vivo A549 xenograft in BALB/c nude mice. Results First, we discovered an antiviral agent, Z29077885, as a new anticancer drug candidate using the AI deep learning method. Next, we demonstrated that Z29077885 inhibits Serine/threonine kinase 33 (STK33) enzymatic function in vitro and showed the anticancer efficacy in various cancer cells. Then, we found enhanced apoptosis via S-phase cell cycle arrest as the mechanism underlying the anticancer efficacy of Z29077885 in both lung and breast cancer cells. Finally, we confirmed the anti-tumor efficacy of Z29077885 in an in vivo A549 xenograft. Conclusions In this study, we used an AI-driven screening strategy to find a novel anticancer medication targeting STK33 that triggers cancer cell apoptosis and cell cycle arrest at the s phase. It will pave a way to efficiently discover new anticancer drugs. | ko_KR |
dc.description.sponsorship | This work was supported and funded by Standigm Inc. This work was also supported in part by National Research Foundation (NRF) funded by Korean government (MIST) (No. RS-2023-00208795 and No. RS-2023-00260529 to S.J.O) | ko_KR |
dc.language.iso | en | ko_KR |
dc.publisher | BMC | ko_KR |
dc.subject | Artificial intelligence | - |
dc.subject | Drug repurposing | - |
dc.subject | Serine/threonine kinase 33 | - |
dc.subject | Cancer treatment | - |
dc.subject | Virtual screening | - |
dc.title | Artificial intelligence-driven new drug discovery targeting serine/threonine kinase 33 for cancer treatment | ko_KR |
dc.type | Article | ko_KR |
dc.identifier.doi | 10.1186/s12935-023-03176-2 | ko_KR |
dc.citation.journaltitle | Cancer Cell International | ko_KR |
dc.language.rfc3066 | en | - |
dc.rights.holder | The Author(s) | - |
dc.date.updated | 2023-12-17T04:08:52Z | - |
dc.citation.endpage | 11 | ko_KR |
dc.citation.number | 1 | ko_KR |
dc.citation.startpage | 1 | ko_KR |
dc.citation.volume | 23 | ko_KR |
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