These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

161 related articles for article (PubMed ID: 33581116)

  • 1. Benchmarking the mechanisms of frequent hitters: limitation of PAINS alerts.
    Yang ZY; Yang ZJ; He JH; Lu AP; Liu S; Hou TJ; Cao DS
    Drug Discov Today; 2021 Jun; 26(6):1353-1358. PubMed ID: 33581116
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Modeling Small-Molecule Reactivity Identifies Promiscuous Bioactive Compounds.
    Matlock MK; Hughes TB; Dahlin JL; Swamidass SJ
    J Chem Inf Model; 2018 Aug; 58(8):1483-1500. PubMed ID: 29990427
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Frequent hitters: nuisance artifacts in high-throughput screening.
    Yang ZY; He JH; Lu AP; Hou TJ; Cao DS
    Drug Discov Today; 2020 Apr; 25(4):657-667. PubMed ID: 31987936
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Nuisance Compounds, PAINS Filters, and Dark Chemical Matter in the GSK HTS Collection.
    Chakravorty SJ; Chan J; Greenwood MN; Popa-Burke I; Remlinger KS; Pickett SD; Green DVS; Fillmore MC; Dean TW; Luengo JI; Macarrón R
    SLAS Discov; 2018 Jul; 23(6):532-545. PubMed ID: 29699447
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Hit Dexter: A Machine-Learning Model for the Prediction of Frequent Hitters.
    Stork C; Wagner J; Friedrich NO; de Bruyn Kops C; Šícho M; Kirchmair J
    ChemMedChem; 2018 Mar; 13(6):564-571. PubMed ID: 29285887
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Phantom PAINS: Problems with the Utility of Alerts for Pan-Assay INterference CompoundS.
    Capuzzi SJ; Muratov EN; Tropsha A
    J Chem Inf Model; 2017 Mar; 57(3):417-427. PubMed ID: 28165734
    [TBL] [Abstract][Full Text] [Related]  

  • 7. New substructure filters for removal of pan assay interference compounds (PAINS) from screening libraries and for their exclusion in bioassays.
    Baell JB; Holloway GA
    J Med Chem; 2010 Apr; 53(7):2719-40. PubMed ID: 20131845
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Hit Dexter 2.0: Machine-Learning Models for the Prediction of Frequent Hitters.
    Stork C; Chen Y; Šícho M; Kirchmair J
    J Chem Inf Model; 2019 Mar; 59(3):1030-1043. PubMed ID: 30624935
    [TBL] [Abstract][Full Text] [Related]  

  • 9. How to Triage PAINS-Full Research.
    Dahlin JL; Walters MA
    Assay Drug Dev Technol; 2016 Apr; 14(3):168-74. PubMed ID: 26496388
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Exploring Activity Profiles of PAINS and Their Structural Context in Target-Ligand Complexes.
    Siramshetty VB; Preissner R; Gohlke BO
    J Chem Inf Model; 2018 Sep; 58(9):1847-1857. PubMed ID: 30105913
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Dealing with frequent hitters in drug discovery: a multidisciplinary view on the issue of filtering compounds on biological screenings.
    Dantas RF; Evangelista TCS; Neves BJ; Senger MR; Andrade CH; Ferreira SB; Silva-Junior FP
    Expert Opin Drug Discov; 2019 Dec; 14(12):1269-1282. PubMed ID: 31416369
    [No Abstract]   [Full Text] [Related]  

  • 12. Non-stoichiometric inhibition in integrated lead finding - a literature review.
    Klumpp M
    Expert Opin Drug Discov; 2016; 11(2):149-62. PubMed ID: 26653534
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Highly Accurate Filters to Flag Frequent Hitters in AlphaScreen Assays by Suggesting their Mechanism.
    Ghosh D; Koch U; Hadian K; Sattler M; Tetko IV
    Mol Inform; 2022 Mar; 41(3):e2100151. PubMed ID: 34676998
    [TBL] [Abstract][Full Text] [Related]  

  • 14. [Pain of high-throughput screening--pan assay interference compounds].
    Xie T; Du GH
    Yao Xue Xue Bao; 2015 Aug; 50(8):925-30. PubMed ID: 26668990
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Identification of Small-Molecule Frequent Hitters from AlphaScreen High-Throughput Screens.
    Schorpp K; Rothenaigner I; Salmina E; Reinshagen J; Low T; Brenke JK; Gopalakrishnan J; Tetko IV; Gul S; Hadian K
    J Biomol Screen; 2014 Jun; 19(5):715-26. PubMed ID: 24371213
    [TBL] [Abstract][Full Text] [Related]  

  • 16. PAIN(S) relievers for medicinal chemists: how computational methods can assist in hit evaluation.
    Stork C; Kirchmair J
    Future Med Chem; 2018 Jul; 10(13):1533-1535. PubMed ID: 29956552
    [No Abstract]   [Full Text] [Related]  

  • 17. Promoting GAINs (Give Attention to Limitations in Assays) over PAINs Alerts: no PAINS, more GAINs.
    Choo MZY; Chai CLL
    ChemMedChem; 2022 Apr; 17(7):e202100710. PubMed ID: 35146933
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Quantification of frequent-hitter behavior based on historical high-throughput screening data.
    M Nissink JW; Blackburn S
    Future Med Chem; 2014 Jun; 6(10):1113-26. PubMed ID: 25078133
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Scopy: an integrated negative design python library for desirable HTS/VS database design.
    Yang ZY; Yang ZJ; Lu AP; Hou TJ; Cao DS
    Brief Bioinform; 2021 May; 22(3):. PubMed ID: 32892221
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Comment on The Ecstasy and Agony of Assay Interference Compounds.
    Kenny PW
    J Chem Inf Model; 2017 Nov; 57(11):2640-2645. PubMed ID: 29048168
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 9.