The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
New Substructure Filters for Removal of Pan Assay Interference Compounds (PAINS) from Screening Libraries and for Their Exclusion in Bioassays
Abstract
This report describes a number of substructural features which can help to identify compounds that appear as frequent hitters (promiscuous compounds) in many biochemical high throughput screens. The compounds identified by such substructural features are not recognized by filters commonly used to identify reactive compounds. Even though these substructural features were identified using only one assay detection technology, such compounds have been reported to be active from many different assays. In fact, these compounds are increasingly prevalent in the literature as potential starting points for further exploration, whereas they may not be.
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Cites
Zhang, J.-H., Chung, T. D. Y., & Oldenburg, K. R. (1999) · SLAS Discovery · doi:10.1177/108705719900400206 · Cited by 6,847
Necula, M., Kayed, R., Milton, S., & Glabe, C. G. (2007) · Journal of Biological Chemistry · doi:10.1074/jbc.m608207200 · Cited by 680
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The Essential Medicinal Chemistry of Curcumin
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Metadata
- Authors
- Baell, J. B., & Holloway, G. A.
- Venue
- Journal of Medicinal Chemistry
- Publisher
- American Chemical Society (ACS)
- Published
- 2010-04-08
- Volume
- 53
- Issue
- 7
- Pages
- 2719-2740
- ISSN
- 0022-2623 (ISSN-L)
- 1520-4804
- OpenAlex
- W2043509228
- Cited by
- 3,944
- References
- 2
- FWCI
- 72.86
- Type
- journal article
- Language
- en
- Open access
- closed
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- The paper
- Baell, J. B., & Holloway, G. A. (2010). New Substructure Filters for Removal of Pan Assay Interference Compounds (PAINS) from Screening Libraries and for Their Exclusion in Bioassays. Journal of Medicinal Chemistry. https://doi.org/10.1021/jm901137j
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
