Seven Year Itch: Pan-Assay Interference Compounds (PAINS) in 2017-Utility and Limitations

Abstract

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.

Figure 1

Epoxide 1, aziridine 2, and nitroalkene 3 unrecognized by PAINS electronic filters because such compounds were not included in the inaugural WEHI HTS library. The dicyanoalkene 4, however, is a recognized PAINS chemotype, but the corresponding electronic filter ene_cyano_A would not recognize consequently plausible PAIN 5 simply because 5 was a substructure not represented by any compound in the initial HTS library from which PAINS were defined. Other reactive compounds such as β-aminoketone 6, isothiazolones 7, and toxoflavins like 8 are not recognized by PAINS filters because their PAINS behavior was only subsequently identified after filter definition.

Figure 2

Simplified ontology of hits and false-positives. Red boxes indicate potential approaches to identify different types of hits in a cascade of assays. The type and order of assays used in the cascade needs to be considered based on the expected hit rates and achievable throughputs of the relevant assays. The term “frequent hitter” in a sense lies outside this system as it presumes a body of associated historical screening data.

Figure 3

Interference by alkylanilines such as 9 with AlphaScreen signaling, probably through reaction with singlet oxygen, routinely returning an apparent IC₅₀ value of around 3 μM.

Figure 4

SMARTS implementations of the original SLN PAINS filter may inappropriately identify non-PAINS, shown here for 10 and 11 inappropriately identified as belonging to hzone_phenol_B and dyes5a PAINS classes, respectively.

Figure 5

An example of successful scaffold hop during optimization of a PAIN to a non-PAIN chemotype.