ArticleChemical biology & drug design2007
In silico prediction of SARS protease inhibitors by virtual high throughput screening.
Article in Chemical biology & drug design, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
6 citing papers in PubMed.
- In silico screening of potent bioactive compounds from honeybee products against COVID-19 target enzymes.Environmental science and pollution research international · 2021Article
- Progress in Developing Inhibitors of SARS-CoV-2 3C-Like Protease.Microorganisms · 2020Review
- Potential COVID-19 papain-like protease PLPeerJ · 2020Article
- Cloud infrastructures for in silico drug discovery: economic and practical aspects.BioMed research international · 2013Article
- Virtual screening for potential inhibitors of homology modeled Leptospira interrogans MurD ligase.Journal of chemical biology · 2010Article
- The interactome: predicting the protein-protein interactions in cells.Cellular & molecular biology letters · 2009Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
A structure-based in silico virtual drug discovery procedure was assessed with severe acute respiratory syndrome coronavirus main protease serving as a case study. First, potential compounds were extracted from protein-ligand complexes selected from Protein Data Bank database based on structural similarity to the target protein. Later, the set of compounds was ranked by docking scores using a Electronic High-Throughput Screening flexible docking procedure to select the most promising molecules. The set of best performing compounds was then used for similarity search over the 1 million entries in the Ligand.Info Meta-Database. Selected molecules having close structural relationship to a 2-methyl-2,4-pentanediol may provide candidate lead compounds toward the development of novel allosteric severe acute respiratory syndrome protease inhibitors.
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Registered trials
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