ArticleJournal of chemical information and modeling2014
Identification of novel serotonin transporter compounds by virtual screening.
Article in Journal of chemical information and modeling, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 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
19 citing papers in PubMed, 32 citations in OpenAlex.
- Exploring Simple Drug Scaffolds from the Generated Database Chemical Space Reveals a Chiral Bicyclic Azepane with Potent Neuropharmacology.Journal of medicinal chemistry · 2025Article
- Unlocking the Potential of High-Quality Dopamine Transporter Pharmacological Data: Advancing Robust Machine Learning-Based QSAR Modeling.Advances in neurobiology · 2025Review
- Artificial intelligence and machine-learning approaches in structure and ligand-based discovery of drugs affecting central nervous system.Molecular diversity · 2023Review
- A MEDT computational study of the mechanism, reactivity and selectivity of non-polar [3+2] cycloaddition between quinazoline-3-oxide and methyl 3-methoxyacrylate.Journal of molecular modeling · 2020Article
- Focus on Human Monoamine Transporter Selectivity. New Human DAT and NET Models, Experimental Validation, and SERT Affinity Exploration.ACS chemical neuroscience · 2020Article
- In Silico Methods for the Discovery of Orthosteric GABAMolecules (Basel, Switzerland) · 2019Article
- Synthesis and anticonvulsant activity of phenoxyacetyl derivatives of amines, including aminoalkanols and amino acids.MedChemComm · 2018Article
- Substructural Connectivity Fingerprint and Extreme Entropy Machines-A New Method of Compound Representation and Analysis.Molecules (Basel, Switzerland) · 2018Article
- Practical application of the Average Information Content Maximization (AIC-MAX) algorithm: selection of the most important structural features for serotonin receptor ligands.Molecular diversity · 2017Article
- From Homology Models to a Set of Predictive Binding Pockets-a 5-HTJournal of chemical information and modeling · 2017Article
- Exploring the Inhibitory Mechanism of Approved Selective Norepinephrine Reuptake Inhibitors and Reboxetine Enantiomers by Molecular Dynamics Study.Scientific reports · 2016Article
- Average Information Content Maximization--A New Approach for Fingerprint Hybridization and Reduction.PloS one · 2016Article
- Discriminating agonist and antagonist ligands of the nuclear receptors using 3D-pharmacophores.Journal of cheminformatics · 2016Article
- Drug Design for CNS Diseases: Polypharmacological Profiling of Compounds Using Cheminformatic, 3D-QSAR and Virtual Screening Methodologies.Frontiers in neuroscience · 2016Review
- Hierarchical virtual screening approaches in small molecule drug discovery.Methods (San Diego, Calif.) · 2015Review
- Designing modulators of monoamine transporters using virtual screening techniques.Frontiers in pharmacology · 2015Review
- Computational studies to predict or explain G protein coupled receptor polypharmacology.Trends in pharmacological sciences · 2014Article
- LBVS: an online platform for ligand-based virtual screening using publicly accessible databases.Molecular diversity · 2014Article
- Discovery of novel-scaffold monoamine transporter ligands via in silico screening with the S1 pocket of the serotonin transporter.ACS chemical neuroscience · 2014Review
Corrections and comments
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Authors and funding
12 authors at 6 institutions in 3 countries.
Funding
Abstract
The serotonin (5-hydroxytryptamine, 5-HT) transporter (SERT) plays an essential role in the termination of serotonergic neurotransmission by removing 5-HT from the synaptic cleft into the presynaptic neuron. It is also of pharmacological importance being targeted by antidepressants and psychostimulant drugs. Here, five commercial databases containing approximately 3.24 million drug-like compounds have been screened using a combination of two-dimensional (2D) fingerprint-based and three-dimensional (3D) pharmacophore-based screening and flexible docking into multiple conformations of the binding pocket detected in an outward-open SERT homology model. Following virtual screening (VS), selected compounds were evaluated using in vitro screening and full binding assays and an in silico hit-to-lead (H2L) screening was performed to obtain analogues of the identified compounds. Using this multistep VS/H2L approach, 74 active compounds, 46 of which had K(i) values of ≤1000 nM, belonging to 16 structural classes, have been identified, and multiple compounds share no structural resemblance with known SERT binders.
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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.