1. Gains from no real PAINS: Where ‘Fair Trial Strategy’ stands in the development of multi-target ligands
- Author
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Jianbo Sun, Hui Zhong, Li Chen, Na Li, and Kun Wang
- Subjects
CoA, coenzyme A ,Future studies ,LC−MS, liquid chromatography−mass spectrometry ,Computer science ,MTDLs, multitarget-directed ligands ,RM1-950 ,Review ,Positive data ,HTS, high-throughput screening ,Machine learning ,computer.software_genre ,03 medical and health sciences ,0302 clinical medicine ,Multi target ,QSAR, quantitative structure–activity relationship ,GSH, glutathione ,ROS, radicals and oxygen reactive species ,Multitarget-directed ligands ,HER2, human epidermal growth factor receptor 2 ,General Pharmacology, Toxicology and Pharmaceutics ,ALARM NMR, a La assay to detect reactive molecules by nuclear magnetic resonance ,030304 developmental biology ,0303 health sciences ,AD, Alzheimer disease ,Fair trial ,business.industry ,Highly selective ,In silico filtering ,EGFR, epidermal growth factor receptor ,Fair trial strategy ,PAINS, pan-assay interference compounds ,030220 oncology & carcinogenesis ,Biochemical experiment ,CADD, computer-aided drug design technology ,PAINS suspects ,Therapeutics. Pharmacology ,Artificial intelligence ,business ,computer - Abstract
Compounds that selectively modulate multiple targets can provide clinical benefits and are an alternative to traditional highly selective agents for unique targets. High-throughput screening (HTS) for multitarget-directed ligands (MTDLs) using approved drugs, and fragment-based drug design has become a regular strategy to achieve an ideal multitarget combination. However, the unexpected presence of pan-assay interference compounds (PAINS) suspects in the development of MTDLs frequently results in nonspecific interactions or other undesirable effects leading to artefacts or false-positive data of biological assays. Publicly available filters can help to identify PAINS suspects; however, these filters cannot comprehensively conclude whether these suspects are “bad” or innocent. Additionally, these in silico approaches may inappropriately label a ligand as PAINS. More than 80% of the initial hits can be identified as PAINS by the filters if appropriate biochemical tests are not used resulting in false positive data that are unacceptable for medicinal chemists in manuscript peer review and future studies. Therefore, extensive offline experiments should be used after online filtering to discriminate “bad” PAINS and avoid incorrect evaluation of good scaffolds. We suggest that the use of “Fair Trial Strategy” to identify interesting molecules in PAINS suspects to provide certain structure‒function insight in MTDL development., Graphical abstract PAINS result in nonspecific interactions or other undesirable effects. The use of “Fair Trial Strategy” to identify interesting molecules in PAINS to provide certain structure‒function insight in multitarget-directed ligand (MTDL) development.Image 1
- Published
- 2021
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