 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 G07.690.830.500
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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 UAMS Profiles 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 |
|---|
| 2017 | 2 | 0 | 2 | | 2016 | 0 | 1 | 1 | | 2015 | 0 | 2 | 2 | | 2014 | 2 | 0 | 2 | | 2013 | 1 | 0 | 1 | | 2012 | 0 | 1 | 1 | | 2009 | 1 | 0 | 1 | | 2008 | 3 | 1 | 4 | | 2007 | 0 | 1 | 1 | | 2006 | 0 | 4 | 4 | | 2005 | 2 | 1 | 3 | | 2004 | 0 | 1 | 1 | | 2002 | 0 | 2 | 2 | | 2001 | 0 | 4 | 4 | | 2000 | 1 | 0 | 1 |
To return to the timeline, click here.
Below are the most recent publications written about "Quantitative Structure-Activity Relationship" by people in Profiles over the past ten years.
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Uchida T, Wakasugi M, Kitamura T, Yamamoto T, Asakura M, Fujiwara R, Itoh T, Fujii H, Hirono S. Exploration of DPP-IV inhibitors with a novel scaffold by multistep in silico screening. J Mol Graph Model. 2018 01; 79:254-263.
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Slavov S, Stoyanova-Slavova I, Li S, Zhao J, Huang R, Xia M, Beger R. Why are most phospholipidosis inducers also hERG blockers? Arch Toxicol. 2017 Dec; 91(12):3885-3895.
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Stoyanova-Slavova IB, Slavov SH, Buzatu DA, Beger RD, Wilkes JG. 3D-SDAR modeling of hERG potassium channel affinity: A case study in model design and toxicophore identification. J Mol Graph Model. 2017 03; 72:246-255.
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Mansouri K, Abdelaziz A, Rybacka A, Roncaglioni A, Tropsha A, Varnek A, Zakharov A, Worth A, Richard AM, Grulke CM, Trisciuzzi D, Fourches D, Horvath D, Benfenati E, Muratov E, Wedebye EB, Grisoni F, Mangiatordi GF, Incisivo GM, Hong H, Ng HW, Tetko IV, Balabin I, Kancherla J, Shen J, Burton J, Nicklaus M, Cassotti M, Nikolov NG, Nicolotti O, Andersson PL, Zang Q, Politi R, Beger RD, Todeschini R, Huang R, Farag S, Rosenberg SA, Slavov S, Hu X, Judson RS. CERAPP: Collaborative Estrogen Receptor Activity Prediction Project. Environ Health Perspect. 2016 07; 124(7):1023-33.
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Hidayat AN, Aki-Yalcin E, Beksac M, Tian E, Usmani SZ, Ertan-Bolelli T, Yalcin I. Insight into human protease activated receptor-1 as anticancer target by molecular modelling. SAR QSAR Environ Res. 2015; 26(10):795-807.
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Hughes TB, Miller GP, Swamidass SJ. Site of reactivity models predict molecular reactivity of diverse chemicals with glutathione. Chem Res Toxicol. 2015 Apr 20; 28(4):797-809.
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