ArticlePharmaceutics2021
3D-ALMOND-QSAR Models to Predict the Antidepressant Effect of Some Natural Compounds.
Article in Pharmaceutics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.
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
9 citing papers in PubMed, 1 synthesis or guideline pooled it, 20 citations in OpenAlex.
- Progress, critical challenges, and translational prospects of intranasal administration of botanical essential oils for the treatment of depression.Frontiers in pharmacology · 2025Pooled it
- Linalyl acetate alleviates inflammatory pain via OLFR482 activation in the mouse anterior cingulate cortex.Frontiers in pharmacology · 2026Article
- Article
- Machine Learning Tool for New Selective Serotonin and Serotonin-Norepinephrine Reuptake Inhibitors.Molecules (Basel, Switzerland) · 2025Article
- Perturbation-theory machine learning for mood disorders: virtual design of dual inhibitors of NET and SERT proteins.BMC chemistry · 2025Article
- Differential effects of clary sage (Frontiers in medicine · 2025Article
- Bioinformatics Tools for the Analysis of Active Compounds Identified in Ranunculaceae Species.Pharmaceuticals (Basel, Switzerland) · 2023Article
- Effects of linalyl acetate on oxidative stress, inflammation and endothelial dysfunction: can linalyl acetate prevent mild cognitive impairment?Frontiers in pharmacology · 2023Review
- Advanced Bioinformatics Tools in the Pharmacokinetic Profiles of Natural and Synthetic Compounds with Anti-Diabetic Activity.Biomolecules · 2021Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 3 institutions in 1 country.
Funding
Abstract
The current treatment of depression involves antidepressant synthetic drugs that have a variety of side effects. In searching for alternatives, natural compounds could represent a solution, as many studies reported that such compounds modulate the nervous system and exhibit antidepressant effects. We used bioinformatics methods to predict the antidepressant effect of ten natural compounds with neuroleptic activity, reported in the literature. For all compounds we computed their drug-likeness, absorption, distribution, metabolism, excretion (ADME), and toxicity profiles. Their antidepressant and neuroleptic activities were predicted by 3D-ALMOND-QSAR models built by considering three important targets, namely serotonin transporter (SERT), 5-hydroxytryptamine receptor 1A (5-HT1A), and dopamine D2 receptor. For our QSAR models we have used the following molecular descriptors: hydrophobicity, electrostatic, and hydrogen bond donor/acceptor. Our results showed that all compounds present drug-likeness features as well as promising ADME features and no toxicity. Most compounds appear to modulate SERT, and fewer appear as ligands for 5-HT1A and D2 receptors. From our prediction, linalyl acetate appears as the only ligand for all three targets, neryl acetate appears as a ligand for SERT and D2 receptors, while 1,8-cineole appears as a ligand for 5-HT1A and D2 receptors.
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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.