ArticlePloS one2013
Promising Aedes aegypti repellent chemotypes identified through integrated QSAR, virtual screening, synthesis, and bioassay.
Article in PloS one, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 18 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
18 citing papers in PubMed.
- Accelerating Ligand Discovery for Insect Odorant Receptors.International journal of biological sciences · 2025Article
- Combining Machine Learning and Electrophysiology for Insect Odorant Receptor Studies.Methods in molecular biology (Clifton, N.J.) · 2025Article
- Repellent Screening of Selected Plant Essential Oils Against Dengue Fever Mosquitoes Using Behavior Bioassays.Neotropical entomology · 2023Article
- Article
- Liposomal Formulations Loaded with a Eugenol Derivative for Application as Insecticides: Encapsulation Studies and In Silico Identification of Protein Targets.Nanomaterials (Basel, Switzerland) · 2022Article
- Hierarchical Virtual Screening and Binding Free Energy Prediction of Potential Modulators of Aedes Aegypti Odorant-Binding Protein 1.Molecules (Basel, Switzerland) · 2022Article
- New Halogenated Compounds fromMolecules (Basel, Switzerland) · 2022Article
- Reverse chemical ecology in a moth: machine learning on odorant receptors identifies new behaviorally active agonists.Cellular and molecular life sciences : CMLS · 2021Article
- Design of a Repellent Against Aedes aegypti (Diptera: Culicidae) Using in silico Simulations With AaegOBP1 Protein.Journal of medical entomology · 2020Article
- Machine learning decodes chemical features to identify novel agonists of a moth odorant receptor.Scientific reports · 2020Article
- Review
- Odorant Receptors and Odorant-Binding Proteins as Insect Pest Control Targets: A Comparative Analysis.Frontiers in physiology · 2018Review
- New insights on repellent recognition by Anopheles gambiae odorant-binding protein 1.PloS one · 2018Article
- The crystal structure of the AgamOBP1•Icaridin complex reveals alternative binding modes and stereo-selective repellent recognition.Cellular and molecular life sciences : CMLS · 2017Article
- Olfactory Mechanisms for Discovery of Odorants to Reduce Insect-Host Contact.Journal of chemical ecology · 2016Review
- Article
- Reception of odors and repellents in mosquitoes.Current opinion in neurobiology · 2015Review
- In silico models for predicting vector control chemicals targeting Aedes aegypti.SAR and QSAR in environmental research · 2014Review
Corrections and comments
- Erratum issued
Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Molecular field topology analysis, scaffold hopping, and molecular docking were used as complementary computational tools for the design of repellents for Aedes aegypti, the insect vector for yellow fever, chikungunya, and dengue fever. A large number of analogues were evaluated by virtual screening with Glide molecular docking software. This produced several dozen hits that were either synthesized or procured from commercial sources. Analysis of these compounds by a repellent bioassay resulted in a few highly active chemicals (in terms of minimum effective dosage) as viable candidates for further hit-to-lead and lead optimization effort.
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What OpenQuestion holds
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.