Pan-assay interference compounds (PAINS) are chemical compounds that often give false positive results in high-throughput screens.[1] PAINS tend to react nonspecifically with numerous biological targets rather than specifically affecting one desired target.[2] A number of disruptive functional groups are shared by many PAINS.[2][3][4]
While a number of filters have been proposed and are used in virtual screening and computer-aided drug design,[5] the accuracy of filters with regard to compounds they flag and don't flag has been criticized.[6]
Common PAINS include toxoflavin, isothiazolones, hydroxyphenyl hydrazones, curcumin, phenol-sulfonamides, rhodanines, enones, quinones, and catechols.[7]
See also
editReferences
edit- ^ Baell JB, Holloway GA (April 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. 53 (7): 2719–40. CiteSeerX 10.1.1.394.9155. doi:10.1021/jm901137j. PMID 20131845.
- ^ a b Baell J, Walters MA (September 2014). "Chemistry: Chemical con artists foil drug discovery". Nature. 513 (7519): 481–3. Bibcode:2014Natur.513..481B. doi:10.1038/513481a. PMID 25254460.
- ^ Dahlin JL, Walters MA (July 2014). "The essential roles of chemistry in high-throughput screening triage". Future Medicinal Chemistry. 6 (11): 1265–90. doi:10.4155/fmc.14.60. PMC 4465542. PMID 25163000.
- ^ Baell, JB (25 March 2016). "Feeling Nature's PAINS: Natural Products, Natural Product Drugs, and Pan Assay Interference Compounds (PAINS)". Journal of Natural Products. 79 (3): 616–28. doi:10.1021/acs.jnatprod.5b00947. PMID 26900761.
- ^ Baell JB, Holloway GA (April 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. 53 (7): 2719–40. CiteSeerX 10.1.1.394.9155. doi:10.1021/jm901137j. PMID 20131845.
- ^ Capuzzi SJ, Muratov EN, Tropsha A (March 2017). "Phantom PAINS: Problems with the Utility of Alerts for Pan-Assay INterference CompoundS". Journal of Chemical Information and Modeling. 57 (3): 417–427. doi:10.1021/acs.jcim.6b00465. PMC 5411023. PMID 28165734.
- ^ Jonathan Baell and Michael A. Walters (September 24, 2014). "Chemistry: Chemical con artists foil drug discovery". Nature. 513 (7519): 481–483. Bibcode:2014Natur.513..481B. doi:10.1038/513481a. PMID 25254460.
Further reading
edit- Yang JJ, Ursu O, Lipinski CA, Sklar LA, Oprea TI, Bologa CG (2016). "Badapple: promiscuity patterns from noisy evidence". Journal of Cheminformatics. 8: 29. doi:10.1186/s13321-016-0137-3. PMC 4884375. PMID 27239230.
- BadApple database
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