The DOI matches its Crossref record; 28 of the 28 references it cites were found in a registry or an index.
Seven Year Itch: Pan-Assay Interference Compounds (PAINS) in 2017—Utility and Limitations
Open accessAbstract
Pan-Assay Interference Compounds (PAINS) are very familiar to medicinal chemists who have spent time fruitlessly trying to optimize these nonprogressible compounds. Electronic filters formulated to recognize PAINS can process hundreds and thousands of compounds in seconds and are in widespread current use to identify PAINS in order to exclude them from further analysis. However, this practice is fraught with danger because such black box treatment is simplistic. Here, we outline for the first time all necessary considerations for the appropriate use of PAINS filters.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Baell, J. B., & Holloway, G. A. (2010) · Journal of Medicinal Chemistry · doi:10.1021/jm901137j · Cited by 3,944
Self-citationChemistry: Chemical con artists foil drug discovery
Baell, J., & Walters, M. A. (2014) · Nature · doi:10.1038/513481a · Cited by 1,043
Self-citationThe promise and peril of chemical probes
Arrowsmith, C. H., Audia, J. E., Austin, C., Baell, J., Bennett, J., Blagg, J., Bountra, C., Brennan, P. E., Brown, P. J., Bunnage, M. E., et al. (2015) · Nature Chemical Biology · doi:10.1038/nchembio.1867 · Cited by 839
Self-citationWang, Y., Bryant, S. H., Cheng, T., Wang, J., Gindulyte, A., Shoemaker, B. A., Thiessen, P. A., He, S., & Zhang, J. (2017) · Nucleic Acids Research · doi:10.1093/nar/gkw1118 · Cited by 671
Baell, J. B. (2016) · Journal of Natural Products · doi:10.1021/acs.jnatprod.5b00947 · Cited by 539
Self-citationDahlin, J. L., Nissink, J. W. M., Strasser, J. M., Francis, S., Higgins, L., Zhou, H., Zhang, Z., & Walters, M. A. (2015) · Journal of Medicinal Chemistry · doi:10.1021/jm5019093 · Cited by 351
Self-citationRules for Identifying Potentially Reactive or Promiscuous Compounds
Bruns, R. F., & Watson, I. A. (2012) · Journal of Medicinal Chemistry · doi:10.1021/jm301008n · Cited by 338
FAF-Drugs3: a web server for compound property calculation and chemical library design
Lagorce, D., Sperandio, O., Baell, J. B., Miteva, M. A., & Villoutreix, B. O. (2015) · Nucleic Acids Research · doi:10.1093/nar/gkv353 · Cited by 272
Self-citationPhantom PAINS: Problems with the Utility of Alerts for P an-A ssay IN terference Compound S
Capuzzi, S. J., Muratov, E. N., & Tropsha, A. (2017) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.6b00465 · Cited by 260
Roche, O., Schneider, P., Zuegge, J., Guba, W., Kansy, M., Alanine, A., Bleicher, K., Danel, F., Gutknecht, E.-M., Rogers-Evans, M., et al. (2002) · Journal of Medicinal Chemistry · doi:10.1021/jm010934d · Cited by 248
Cited by
Bioisosteres of the Phenyl Ring: Recent Strategic Applications in Lead Optimization and Drug Design
Subbaiah, M. A. M., & Meanwell, N. A. (2021) · Journal of Medicinal Chemistry · doi:10.1021/acs.jmedchem.1c01215 · Cited by 710
An open-source drug discovery platform enables ultra-large virtual screens
Gorgulla, C., Boeszoermenyi, A., Wang, Z.-F., Fischer, P. D., Coote, P. W., Padmanabha Das, K. M., Malets, Y. S., Radchenko, D. S., Moroz, Y. S., Scott, D. A., et al. (2020) · Nature · doi:10.1038/s41586-020-2117-z · Cited by 641
Advances in Targeting ‘Undruggable’ transcription Factors With Small Molecules
Henley, M. J., & Koehler, A. N. (2021) · Nature Reviews Drug Discovery · doi:10.1038/s41573-021-00199-0 · Cited by 409
The Synthesizability of Molecules Proposed by Generative Models
Gao, W., & Coley, C. W. (2020) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.0c00174 · Cited by 394
Xie, C., Zhuang, X.-X., Niu, Z., Ai, R., Lautrup, S., Zheng, S., Jiang, Y., Han, R., Gupta, T. S., Cao, S., et al. (2022) · Nature Biomedical Engineering · doi:10.1038/s41551-021-00819-5 · Cited by 336
Metadata
- Authors
- Baell, J. B., & Nissink, J. W. M.
- Venue
- ACS Chemical Biology
- Publisher
- American Chemical Society (ACS)
- Published
- 2017-12-26
- Volume
- 13
- Issue
- 1
- Pages
- 36-44
- ISSN
- 1554-8929 (ISSN-L)
- 1554-8937
- OpenAlex
- W2774836366
- Cited by
- 648
- References
- 28
- FWCI
- 35.90
- Type
- journal article
- Language
- en
- Open access
- hybrid
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Seven Year Itch: Pan-Assay Interference Compounds (PAINS) in 2017—Utility and Limitations. https://app.cochat.ai/papers/10.1021/acschembio.7b00903
- The paper
- Baell, J. B., & Nissink, J. W. M. (2018). Seven Year Itch: Pan-Assay Interference Compounds (PAINS) in 2017—Utility and Limitations. ACS Chemical Biology. https://doi.org/10.1021/acschembio.7b00903
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
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.