Crowdsourced identification of multi-target kinase inhibitors for RET- and TAU- based disease: The Multi-Targeting Drug DREAM Challenge.
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 rea...
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Public Library of Science (PLoS)
2021
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oai:doaj.org-article:760d14f1687d40cc99f25eb1a90cecb72021-12-02T19:57:48ZCrowdsourced identification of multi-target kinase inhibitors for RET- and TAU- based disease: The Multi-Targeting Drug DREAM Challenge.1553-734X1553-735810.1371/journal.pcbi.1009302https://doaj.org/article/760d14f1687d40cc99f25eb1a90cecb72021-09-01T00:00:00Zhttps://doi.org/10.1371/journal.pcbi.1009302https://doaj.org/toc/1553-734Xhttps://doaj.org/toc/1553-7358A 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.Zhaoping XiongMinji JeonRobert J AllawayJaewoo KangDonghyeon ParkJinhyuk LeeHwisang JeonMiyoung KoHualiang JiangMingyue ZhengAik Choon TanXindi GuoMulti-Targeting Drug DREAM Challenge CommunityKristen K DangAlex TropshaChana HechtTirtha K DasHeather A CarlsonRuben AbagyanJustin GuinneyAvner SchlessingerRoss CaganPublic Library of Science (PLoS)articleBiology (General)QH301-705.5ENPLoS Computational Biology, Vol 17, Iss 9, p e1009302 (2021) |
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| topic |
Biology (General) QH301-705.5 |
| spellingShingle |
Biology (General) QH301-705.5 Zhaoping Xiong Minji Jeon Robert J Allaway Jaewoo Kang Donghyeon Park Jinhyuk Lee Hwisang Jeon Miyoung Ko Hualiang Jiang Mingyue Zheng Aik Choon Tan Xindi Guo Multi-Targeting Drug DREAM Challenge Community Kristen K Dang Alex Tropsha Chana Hecht Tirtha K Das Heather A Carlson Ruben Abagyan Justin Guinney Avner Schlessinger Ross Cagan Crowdsourced identification of multi-target kinase inhibitors for RET- and TAU- based disease: The Multi-Targeting Drug DREAM Challenge. |
| description |
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. |
| format |
article |
| author |
Zhaoping Xiong Minji Jeon Robert J Allaway Jaewoo Kang Donghyeon Park Jinhyuk Lee Hwisang Jeon Miyoung Ko Hualiang Jiang Mingyue Zheng Aik Choon Tan Xindi Guo Multi-Targeting Drug DREAM Challenge Community Kristen K Dang Alex Tropsha Chana Hecht Tirtha K Das Heather A Carlson Ruben Abagyan Justin Guinney Avner Schlessinger Ross Cagan |
| author_facet |
Zhaoping Xiong Minji Jeon Robert J Allaway Jaewoo Kang Donghyeon Park Jinhyuk Lee Hwisang Jeon Miyoung Ko Hualiang Jiang Mingyue Zheng Aik Choon Tan Xindi Guo Multi-Targeting Drug DREAM Challenge Community Kristen K Dang Alex Tropsha Chana Hecht Tirtha K Das Heather A Carlson Ruben Abagyan Justin Guinney Avner Schlessinger Ross Cagan |
| author_sort |
Zhaoping Xiong |
| title |
Crowdsourced identification of multi-target kinase inhibitors for RET- and TAU- based disease: The Multi-Targeting Drug DREAM Challenge. |
| title_short |
Crowdsourced identification of multi-target kinase inhibitors for RET- and TAU- based disease: The Multi-Targeting Drug DREAM Challenge. |
| title_full |
Crowdsourced identification of multi-target kinase inhibitors for RET- and TAU- based disease: The Multi-Targeting Drug DREAM Challenge. |
| title_fullStr |
Crowdsourced identification of multi-target kinase inhibitors for RET- and TAU- based disease: The Multi-Targeting Drug DREAM Challenge. |
| title_full_unstemmed |
Crowdsourced identification of multi-target kinase inhibitors for RET- and TAU- based disease: The Multi-Targeting Drug DREAM Challenge. |
| title_sort |
crowdsourced identification of multi-target kinase inhibitors for ret- and tau- based disease: the multi-targeting drug dream challenge. |
| publisher |
Public Library of Science (PLoS) |
| publishDate |
2021 |
| url |
https://doaj.org/article/760d14f1687d40cc99f25eb1a90cecb7 |
| work_keys_str_mv |
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| _version_ |
1718375784866906112 |