KinomeMETA: a web platform for kinome-wide polypharmacology profiling with meta-learning
文献类型：期刊论文
| 作者 | Li, Zhaojun5,8; Qu, Ning6,7; Zhou, Jingyi3,4,7; Sun, Jingjing6,7; Ren, Qun2; Meng, Jingyi2; Wang, Guangchao8; Wang, Rongyan8; Liu, Jin1,7; Chen, Yijie |
| 刊名 | NUCLEIC ACIDS RESEARCH
 |
| 出版日期 | 2024-05-16 |
| 页码 | 9 |
| ISSN号 | 0305-1048 |
| DOI | 10.1093/nar/gkae380 |
| 通讯作者 | Zhang, Sulin(slzhang@simm.ac.cn) ; Zheng, Mingyue(myzheng@simm.ac.cn) ; Li, Xutong(lixutong@simm.ac.cn) |
| 英文摘要 | Kinase-targeted inhibitors hold promise for new therapeutic options, with multi-target inhibitors offering the potential for broader efficacy while minimizing polypharmacology risks. However, comprehensive experimental profiling of kinome-wide activity is expensive, and existing computational approaches often lack scalability or accuracy for understudied kinases. We introduce KinomeMETA, an artificial intelligence (AI)-powered web platform that significantly expands the predictive range with scalability for predicting the polypharmacological effects of small molecules across the kinome. By leveraging a novel meta-learning algorithm, KinomeMETA efficiently utilizes sparse activity data, enabling rapid generalization to new kinase tasks even with limited information. This significantly expands the repertoire of accurately predictable kinases to 661 wild-type and clinically-relevant mutant kinases, far exceeding existing methods. Additionally, KinomeMETA empowers users to customize models with their proprietary data for specific research needs. Case studies demonstrate its ability to discover new active compounds by quickly adapting to small dataset. Overall, KinomeMETA offers enhanced kinome virtual profiling capabilities and is positioned as a powerful tool for developing new kinase inhibitors and advancing kinase research. The KinomeMETA server is freely accessible without registration at https://kinomemeta.alphama.com.cn/. Graphical Abstract |
| WOS关键词 | KINASE INHIBITORS |
| 资助项目 | National Natural Science Foundation of China[82204278] ; National Natural Science Foundation of China[T2225002] ; National Natural Science Foundation of China[82273855] ; National Key Research and Development Program of China[2022YFC3400504] ; SIMM-SHUTCM Traditional Chinese Medicine Innovation Joint Research Program[E2G805H] ; China Postdoctoral Science Foundation[2022M720153] ; Youth Innovation Promotion Association CAS[2023296] ; Shanghai Municipal Science and Technology Major Project |
| WOS研究方向 | Biochemistry & Molecular Biology |
| 语种 | 英语 |
| WOS记录号 | WOS:001223716000001 |
| 出版者 | OXFORD UNIV PRESS |
| 源URL | [http://119.78.100.183/handle/2S10ELR8/311294]  |
| 专题 | 新药研究国家重点实验室 |
| 通讯作者 | Zhang, Sulin; Zheng, Mingyue; Li, Xutong |
| 作者单位 | 1.Zhejiang Univ, Coll Pharmaceut Sci, Hangzhou 310058, Peoples R China 2.Nanjing Univ Chinese Med, Sch Chinese Materia Med, 138 Xianlin Rd, Nanjing 210023, Peoples R China 3.Lingang Lab, Shanghai 200031, Peoples R China 4.Shanghaitech Univ, Sch Phys Sci & Technol, Shanghai 201210, Peoples R China 5.Suzhou Alphama Biotechnol Co Ltd, Dev Dept, Suzhou 215000, Peoples R China 6.Univ Chinese Acad Sci, 19A Yuquan Rd, Beijing 100049, Peoples R China 7.Chinese Acad Sci, Shanghai Inst Materia Med, State Key Lab Drug Res, Drug Discovery & Design Ctr, 555 Zuchongzhi Rd, Shanghai 201203, Peoples R China 8.Dezhou Univ, Coll Comp & Informat Engn, Dezhou 253023, Peoples R China |
| 推荐引用方式 GB/T 7714 | Li, Zhaojun,Qu, Ning,Zhou, Jingyi,et al. KinomeMETA: a web platform for kinome-wide polypharmacology profiling with meta-learning[J]. NUCLEIC ACIDS RESEARCH,2024:9. |
| APA | Li, Zhaojun.,Qu, Ning.,Zhou, Jingyi.,Sun, Jingjing.,Ren, Qun.,...&Li, Xutong.(2024).KinomeMETA: a web platform for kinome-wide polypharmacology profiling with meta-learning.NUCLEIC ACIDS RESEARCH,9. |
| MLA | Li, Zhaojun,et al."KinomeMETA: a web platform for kinome-wide polypharmacology profiling with meta-learning".NUCLEIC ACIDS RESEARCH (2024):9. |
入库方式： OAI收割
来源：上海药物研究所
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