Crowdsourced identification of multi-target kinase inhibitors for RET- and TAU- based disease: The Multi-Targeting Drug DREAM Challenge

doi:10.1371/journal.pcbi.1009302

	Crowdsourced identification of multi-target kinase inhibitors for RET- and TAU- based disease: The Multi-Targeting Drug DREAM Challenge
	Xiong, Zhaoping1 ; Jeon, Minji 2; Allaway, Robert J.3; Kang, Jaewoo 2; Park, Donghyeon 2; Lee, Jinhyuk 2; Jeon, Hwisang 4,5; Ko, Miyoung 2; Jiang, Hualiang1,5 ; Zheng, Mingyue K.5; Tan, Aik Choon 6; Guo, Xindi 3; Dang, Kristen K. K.3; Tropsha, Alex A.7; Hecht, Chana 8; Das, Tirtha K.8; Carlson, Heather A.9; Abagyan, Ruben 10; Guinney, Justin 3; Schlessinger, Avner 11; Cagan, Ross 8,12
	2021
发表期刊	PLOS COMPUTATIONAL BIOLOGY
ISSN	1553-734X
EISSN	1553-7358
卷号	17 期号:9
DOI	10.1371/journal.pcbi.1009302
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.
URL	查看原文
收录类别	SCIE ; EI
语种	英语
WOS研究方向	Biochemistry & Molecular Biology ; Mathematical & Computational Biology
WOS类目	Biochemical Research Methods ; Mathematical & Computational Biology
WOS记录号	WOS:000696734100002
出版者	PUBLIC LIBRARY SCIENCE
原始文献类型	Article
引用统计
文献类型	期刊论文
条目标识符	https://kms.shanghaitech.edu.cn/handle/2MSLDSTB/128243
专题	生命科学与技术学院_博士生免疫化学研究所_特聘教授组_蒋华良组
通讯作者	Schlessinger, Avner; Cagan, Ross
作者单位	1.ShanghaiTech Univ, Shanghai Inst Adv Immunochem Studies, Shanghai, Peoples R China; 2.Korea Univ, Dept Comp Sci & Engn, Seoul, South Korea; 3.Sage Bionetworks, Seattle, WA USA; 4.Korea Univ, Interdisciplinary Grad Program Bioinformat, Seoul, South Korea; 5.Chinese Acad Sci, Shanghai Inst Mat Med, State Key Lab Drug Res, Drug Discovery & Design Ctr, Shanghai, Peoples R China; 6.H Lee Moffitt Canc Ctr & Res Inst, Dept Biostat & Bioinformat, Tampa, FL USA; 7.Univ N Carolina, UNC Eshelman Sch Pharm, Lab Mol Modeling, Div Chem Biol & Med Chem, Chapel Hill, NC 27515 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; 11.Icahn Sch Med Mt Sinai, Dept Pharmacol Sci, New York, NY 10029 USA; 12.Univ Glasgow, Inst Canc Sci, Glasgow, Lanark, Scotland
第一作者单位	免疫化学研究所
第一作者的第一单位	免疫化学研究所
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).
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).
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).