 Quantitative Structure-Activity Relationship
"Quantitative Structure-Activity Relationship" is a descriptor in the National Library of Medicine's controlled vocabulary thesaurus,
MeSH (Medical Subject Headings). Descriptors are arranged in a hierarchical structure,
which enables searching at various levels of specificity.
A quantitative prediction of the biological, ecotoxicological or pharmaceutical activity of a molecule. It is based upon structure and activity information gathered from a series of similar compounds.
| Descriptor ID |
D021281
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| MeSH Number(s) |
G02.111.830.500 G07.690.773.997.500
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| Concept/Terms |
Quantitative Structure-Activity Relationship- Quantitative Structure-Activity Relationship
- Quantitative Structure Activity Relationship
- Quantitative Structure-Activity Relationships
- Relationship, Quantitative Structure-Activity
- Relationships, Quantitative Structure-Activity
- Structure-Activity Relationship, Quantitative
- Structure-Activity Relationships, Quantitative
- Structure Activity Relationship, Quantitative
- QSAR
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Below are MeSH descriptors whose meaning is more general than "Quantitative Structure-Activity Relationship".
Below are MeSH descriptors whose meaning is more specific than "Quantitative Structure-Activity Relationship".
This graph shows the total number of publications written about "Quantitative Structure-Activity Relationship" by people in this website by year, and whether "Quantitative Structure-Activity Relationship" was a major or minor topic of these publications.
To see the data from this visualization as text, click here.
| Year | Major Topic | Minor Topic | Total |
|---|
| 2002 | 0 | 1 | 1 | | 2004 | 1 | 0 | 1 | | 2005 | 2 | 0 | 2 | | 2008 | 1 | 0 | 1 | | 2011 | 0 | 2 | 2 | | 2012 | 0 | 1 | 1 | | 2014 | 0 | 2 | 2 | | 2015 | 2 | 1 | 3 | | 2017 | 1 | 0 | 1 | | 2024 | 1 | 0 | 1 |
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Below are the most recent publications written about "Quantitative Structure-Activity Relationship" by people in Profiles.
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Singh AV, Shelar A, Rai M, Laux P, Thakur M, Dosnkyi I, Santomauro G, Singh AK, Luch A, Patil R, Bill J. Harmonization Risks and Rewards: Nano-QSAR for Agricultural Nanomaterials. J Agric Food Chem. 2024 Feb 14; 72(6):2835-2852.
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Wu L, Liu Z, Auerbach S, Huang R, Chen M, McEuen K, Xu J, Fang H, Tong W. Integrating Drug's Mode of Action into Quantitative Structure-Activity Relationships for Improved Prediction of Drug-Induced Liver Injury. J Chem Inf Model. 2017 04 24; 57(4):1000-1006.
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Xiong W, Matheson CJ, Xu M, Backos DS, Mills TS, Salian-Mehta S, Kiseljak-Vassiliades K, Reigan P, Wierman ME. Structure-Based Screen Identification of a Mammalian Ste20-like Kinase 4 (MST4) Inhibitor with Therapeutic Potential for Pituitary Tumors. Mol Cancer Ther. 2016 Mar; 15(3):412-20.
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Singarapu KK, Otte MM, Tonelli M, Westler WM, Escalante-Semerena JC, Markley JL. Solution Structural Studies of GTP:Adenosylcobinamide-Phosphateguanylyl Transferase (CobY) from Methanocaldococcus jannaschii. PLoS One. 2015; 10(10):e0141297.
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Liao Z, Gu L, Vergalli J, Mariani SA, De Dominici M, Lokareddy RK, Dagvadorj A, Purushottamachar P, McCue PA, Trabulsi E, Lallas CD, Gupta S, Ellsworth E, Blackmon S, Ertel A, Fortina P, Leiby B, Xia G, Rui H, Hoang DT, Gomella LG, Cingolani G, Njar V, Pattabiraman N, Calabretta B, Nevalainen MT. Structure-Based Screen Identifies a Potent Small Molecule Inhibitor of Stat5a/b with Therapeutic Potential for Prostate Cancer and Chronic Myeloid Leukemia. Mol Cancer Ther. 2015 Aug; 14(8):1777-93.
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Baugh L, Phan I, Begley DW, Clifton MC, Armour B, Dranow DM, Taylor BM, Muruthi MM, Abendroth J, Fairman JW, Fox D, Dieterich SH, Staker BL, Gardberg AS, Choi R, Hewitt SN, Napuli AJ, Myers J, Barrett LK, Zhang Y, Ferrell M, Mundt E, Thompkins K, Tran N, Lyons-Abbott S, Abramov A, Sekar A, Serbzhinskiy D, Lorimer D, Buchko GW, Stacy R, Stewart LJ, Edwards TE, Van Voorhis WC, Myler PJ. Increasing the structural coverage of tuberculosis drug targets. Tuberculosis (Edinb). 2015 Mar; 95(2):142-8.
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Gusenleitner D, Auerbach SS, Melia T, Gómez HF, Sherr DH, Monti S. Genomic models of short-term exposure accurately predict long-term chemical carcinogenicity and identify putative mechanisms of action. PLoS One. 2014; 9(7):e102579.
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McCoull W, Addie MS, Birch AM, Birtles S, Buckett LK, Butlin RJ, Bowker SS, Boyd S, Chapman S, Davies RD, Donald CS, Green CP, Jenner C, Kemmitt PD, Leach AG, Moody GC, Gutierrez PM, Newcombe NJ, Nowak T, Packer MJ, Plowright AT, Revill J, Schofield P, Sheldon C, Stokes S, Turnbull AV, Wang SJ, Whalley DP, Wood JM. Identification, optimisation and in vivo evaluation of oxadiazole DGAT-1 inhibitors for the treatment of obesity and diabetes. Bioorg Med Chem Lett. 2012 Jun 15; 22(12):3873-8.
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Valdameri G, Gauthier C, Terreux R, Kachadourian R, Day BJ, Winnischofer SM, Rocha ME, Frachet V, Ronot X, Di Pietro A, Boumendjel A. Investigation of chalcones as selective inhibitors of the breast cancer resistance protein: critical role of methoxylation in both inhibition potency and cytotoxicity. J Med Chem. 2012 Apr 12; 55(7):3193-200.
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Rasulev B, Turabekova M, Gorska M, Kulig K, Bielejewska A, Lipkowski J, Leszczynski J. Use of quantitative structure-enantioselective retention relationship for the liquid chromatography chiral separation prediction of the series of pyrrolidin-2-one compounds. Chirality. 2012 Jan; 24(1):72-7.
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