ArticleJournal of chemical information and modeling2009
Search for novel aminoglycosides by combining fragment-based virtual screening and 3D-QSAR scoring.
Article in Journal of chemical information and modeling, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed, 28 citations in OpenAlex.
- Harnessing Computational Approaches for RNA-Targeted Drug Discovery.RNA nanomed · 2024Article
- Quantitative Structure-Activity Relationship (QSAR) Study Predicts Small-Molecule Binding to RNA Structure.Journal of medicinal chemistry · 2022Article
- Structural basis for the diversity of the mechanism of nucleotide hydrolysis by the aminoglycoside-2''-phosphotransferases.Acta crystallographica. Section D, Structural biology · 2019Article
- Driving factors in amiloride recognition of HIV RNA targets.Organic & biomolecular chemistry · 2019Article
- Molecular structures enumeration and virtual screening in the chemical space with RetroPath2.0.Journal of cheminformatics · 2017Article
- Methods to enable the design of bioactive small molecules targeting RNA.Organic & biomolecular chemistry · 2014Review
- Strategies to overcome the action of aminoglycoside-modifying enzymes for treating resistant bacterial infections.Future medicinal chemistry · 2013Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
Aminoglycosides are antibiotics targeting the 16S RNA A site of the bacterial ribosome. There have been many efforts directed toward design of their synthetic derivatives, however with only few successes. As RNA binders, aminoglycosides are also a difficult target for computational drug design, since most of the existing methods were developed for protein ligands. Here, we present an approach that allows for evading the problems related to still poorly developed RNA docking and scoring algorithms. It is aimed at identification of new molecular scaffolds potentially binding to the A site. The considered molecules are based on the neamine core, which is common for all aminoglycosides and provides specificity toward the binding site, linked with diverse molecular fragments via its O5 or O6 oxygen atom. Suitable fragments are selected with the use of 3D searches of molecular fragments library against two distinct pharmacophores designed on the basis of available structural data for aminoglycoside-RNA complexes. The compounds resulting from fragments assembly with neamine are then scored with a 3D-QSAR model developed using the biological data for known aminoglycoside derivatives. Twenty-one new potential ligands are obtained, four of which have predicted activities comparable to less potent aminoglycoside antibiotics.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.