Crowdsourced identification of multi-target kinase inhibitors for RET- and TAU- based disease: The Multi-Targeting Drug DREAM Challenge
文献类型：期刊论文
| 作者 | Xiong, Zhaoping2; Jeon, Minji3; Allaway, Robert J.4; Kang, Jaewoo3; Park, Donghyeon3; Lee, Jinhyuk3; Jeon, Hwisang5,6; Ko, Miyoung3; Jiang, Hualiang2,6 ; Zheng, Mingyue K.6
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| 刊名 | PLOS COMPUTATIONAL BIOLOGY
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| 出版日期 | 2021-09-01 |
| 卷号 | 17期号:9页码:19 |
| ISSN号 | 1553-734X |
| DOI | 10.1371/journal.pcbi.1009302 |
| 通讯作者 | Schlessinger, Avner(avner.schlessinger@mssm.edu) ; Cagan, Ross(ross.cagan@glasgow.ac.uk) |
| 英文摘要 | A continuing challenge in modern medicine is the identification of safer and more efficacious drugs. Precision therapeutics, which have one molecular target, have been long promised to be safer and more effective than traditional therapies. This approach has proven to be challenging for multiple reasons including lack of efficacy, rapidly acquired drug resistance, and narrow patient eligibility criteria. An alternative approach is the development of drugs that address the overall disease network by targeting multiple biological targets ('polypharmacology'). Rational development of these molecules will require improved methods for predicting single chemical structures that target multiple drug targets. To address this need, we developed the Multi-Targeting Drug DREAM Challenge, in which we challenged participants to predict single chemical entities that target pro-targets but avoid anti-targets for two unrelated diseases: RET-based tumors and a common form of inherited Tauopathy. Here, we report the results of this DREAM Challenge and the development of two neural network-based machine learning approaches that were applied to the challenge of rational polypharmacology. Together, these platforms provide a potentially useful first step towards developing lead therapeutic compounds that address disease complexity through rational polypharmacology. Author summary Many modern drugs are developed with the goal of modulating a single cellular pathway or target. However, many drugs are, in fact, 'dirty;' they target multiple cellular pathways or targets. This phenomenon is known as multi-targeting or polypharmacology. While some strive to develop 'cleaner' therapeutics that eliminate secondary targets, recent work has shown that multi-targeting therapeutics have key advantages for a variety of diseases. However, while multi-targeting drugs that affect a precisely-defined profile of targets may be more effective, it is difficult to computationally predict which molecules have desirable target profiles. Here, we report the results of a competitive crowdsourcing project (the Multi-Targeting Drug DREAM Challenge), where we challenged participants to predict chemicals that have desired target profiles for cancer and neurodegenerative disease. |
| WOS关键词 | DROSOPHILA MODEL ; PROLIFERATION ; DISCOVERY ; PLATFORM |
| 资助项目 | National Institutes of Health[U54OD020353] ; Office of Research Infrastructure Programs - National Institute of General Medical Sciences[R35GM131881] |
| WOS研究方向 | Biochemistry & Molecular Biology ; Mathematical & Computational Biology |
| 语种 | 英语 |
| 出版者 | PUBLIC LIBRARY SCIENCE |
| WOS记录号 | WOS:000696734100002 |
| 源URL | [http://119.78.100.183/handle/2S10ELR8/297872]  |
| 专题 | 新药研究国家重点实验室 |
| 通讯作者 | Schlessinger, Avner; Cagan, Ross |
| 作者单位 | 1.Univ N Carolina, UNC Eshelman Sch Pharm, Lab Mol Modeling, Div Chem Biol & Med Chem, Chapel Hill, NC 27515 USA 2.ShanghaiTech Univ, Shanghai Inst Adv Immunochem Studies, Shanghai, Peoples R China 3.Korea Univ, Dept Comp Sci & Engn, Seoul, South Korea 4.Sage Bionetworks, Seattle, WA USA 5.Korea Univ, Interdisciplinary Grad Program Bioinformat, Seoul, South Korea 6.Chinese Acad Sci, Shanghai Inst Mat Med, State Key Lab Drug Res, Drug Discovery & Design Ctr, Shanghai, Peoples R China 7.H Lee Moffitt Canc Ctr & Res Inst, Dept Biostat & Bioinformat, Tampa, FL USA 8.Icahn Sch Med Mt Sinai, Dept Cell Dev & Regenerat Biol, New York, NY 10029 USA 9.Univ Michigan, Dept Med Chem, Ann Arbor, MI 48109 USA 10.Univ Calif San Diego, Skaggs Sch Pharm & Pharmaceut Sci, San Diego, CA 92103 USA |
| 推荐引用方式 GB/T 7714 | Xiong, Zhaoping,Jeon, Minji,Allaway, Robert J.,et al. Crowdsourced identification of multi-target kinase inhibitors for RET- and TAU- based disease: The Multi-Targeting Drug DREAM Challenge[J]. PLOS COMPUTATIONAL BIOLOGY,2021,17(9):19. |
| APA | Xiong, Zhaoping.,Jeon, Minji.,Allaway, Robert J..,Kang, Jaewoo.,Park, Donghyeon.,...&Cagan, Ross.(2021).Crowdsourced identification of multi-target kinase inhibitors for RET- and TAU- based disease: The Multi-Targeting Drug DREAM Challenge.PLOS COMPUTATIONAL BIOLOGY,17(9),19. |
| MLA | Xiong, Zhaoping,et al."Crowdsourced identification of multi-target kinase inhibitors for RET- and TAU- based disease: The Multi-Targeting Drug DREAM Challenge".PLOS COMPUTATIONAL BIOLOGY 17.9(2021):19. |
入库方式： OAI收割
来源：上海药物研究所
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