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
|
| MeSH Number(s) |
G02.111.830.500 G07.690.773.997.500
|
| 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
|
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 |
|---|
| 2000 | 0 | 1 | 1 |
| 2006 | 0 | 1 | 1 |
| 2008 | 0 | 1 | 1 |
| 2013 | 0 | 3 | 3 |
| 2017 | 9 | 4 | 13 |
| 2018 | 4 | 7 | 11 |
| 2019 | 1 | 3 | 4 |
| 2021 | 0 | 2 | 2 |
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Below are the most recent publications written about "Quantitative Structure-Activity Relationship" by people in Profiles.
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New Pyrazine Conjugates: Synthesis, Computational Studies, and Antiviral Properties against SARS-CoV-2. ChemMedChem. 2021 11 19; 16(22):3418-3427.
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The QSAR-search of effective agents towards coronaviruses applying the Monte Carlo method. SAR QSAR Environ Res. 2021 Sep; 32(9):689-698.
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Transcription factor NF-?B as target for SARS-CoV-2 drug discovery efforts using inflammation-based QSAR screening model. J Mol Graph Model. 2021 11; 108:107968.
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Robust classification-based molecular modelling of diverse chemical entities as potential SARS-CoV-2 3CLpro inhibitors: theoretical justification in light of experimental evidences. SAR QSAR Environ Res. 2021 Jun; 32(6):473-493.
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MolAICal: a soft tool for 3D drug design of protein targets by artificial intelligence and classical algorithm. Brief Bioinform. 2021 05 20; 22(3).
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Probing nano-QSAR to assess the interactions between carbon nanoparticles and a SARS-CoV-2 RNA fragment. Ecotoxicol Environ Saf. 2021 Aug; 219:112357.
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QSAR modeling and pharmacoinformatics of SARS coronavirus 3C-like protease inhibitors. Comput Biol Med. 2021 07; 134:104483.
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SARS-CoV-2 Papain-Like Protease Potential Inhibitors-In Silico Quantitative Assessment. Int J Mol Sci. 2021 Apr 12; 22(8).
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Macrolides May Prevent Severe Acute Respiratory Syndrome Coronavirus 2 Entry into Cells: A Quantitative Structure Activity Relationship Study and Experimental Validation. J Chem Inf Model. 2021 04 26; 61(4):2016-2025.
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Receptor-Based Pharmacophore Modeling in the Search for Natural Products for COVID-19 Mpro. Molecules. 2021 Mar 11; 26(6).