A general fragment-based approach to identify and optimize bioactive ligands targeting RNA Article Swipe
Blessy M. Suresh
,
Weichao Li
,
Peiyuan Zhang
,
Kye Won Wang
,
Ilyas Yildirim
,
Christopher G. Parker
,
Matthew D. Disney
·
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.1073/pnas.2012217117
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.1073/pnas.2012217117
Significance The development of selective bioactive compounds that target RNA structures is difficult. Here we report an approach to identify low molecular weight fragments that bind to a cancer-causing RNA. By determining where the fragments bind within an RNA target, they can be assembled to provide a high-affinity and potent inhibitor. This approach could be a general way to develop bioactive small molecules that target RNA, which previously was considered “undruggable.” It was applied to provide a precision lead medicine against an RNA that contributes to cancer metastasis.
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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1073/pnas.2012217117
- OA Status
- green
- Cited By
- 103
- References
- 58
- Related Works
- 10
- OpenAlex ID
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All OpenAlex metadata
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https://openalex.org/W3111745408Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1073/pnas.2012217117Digital Object Identifier
- Title
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A general fragment-based approach to identify and optimize bioactive ligands targeting RNAWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2020Year of publication
- Publication date
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2020-12-14Full publication date if available
- Authors
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Blessy M. Suresh, Weichao Li, Peiyuan Zhang, Kye Won Wang, Ilyas Yildirim, Christopher G. Parker, Matthew D. DisneyList of authors in order
- Landing page
-
https://doi.org/10.1073/pnas.2012217117Publisher landing page
- Open access
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YesWhether a free full text is available
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greenOpen access status per OpenAlex
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https://www.ncbi.nlm.nih.gov/pmc/articles/7777249Direct OA link when available
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RNA, Computational biology, Small molecule, Fragment (logic), Chemistry, Combinatorial chemistry, Biochemistry, Biology, Computer science, Gene, AlgorithmTop concepts (fields/topics) attached by OpenAlex
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103Total citation count in OpenAlex
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2025: 27, 2024: 24, 2023: 20, 2022: 18, 2021: 13Per-year citation counts (last 5 years)
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58Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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