ArticleMedChemComm2016
From linked open data to molecular interaction: studying selectivity trends for ligands of the human serotonin and dopamine transporter.
Article in MedChemComm, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 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
9 citing papers in PubMed.
- Experimental and computational approaches for evaluating molecule interactions with equilibrative nucleoside transporters 1 and 2.The Journal of pharmacology and experimental therapeutics · 2025Article
- Computational Approaches for Predicting Drug Interactions with Human Organic Anion Transporter 4 (OAT4).Molecular pharmaceutics · 2025Article
- Ligand- and Structure-based Approaches for Transmembrane Transporter Modeling.Current drug research reviews · 2024Review
- Machine Learning Models Identify New Inhibitors for Human OATP1B1.Molecular pharmaceutics · 2022Article
- Multiple Computational Approaches for Predicting Drug Interactions with Human Equilibrative Nucleoside Transporter 1.Drug metabolism and disposition: the biological fate of chemicals · 2021Article
- Integrative Data Mining, Scaffold Analysis, and Sequential Binary Classification Models for Exploring Ligand Profiles of Hepatic Organic Anion Transporting Polypeptides.Journal of chemical information and modeling · 2019Article
- How Open Data Shapes In Silico Transporter Modeling.Molecules (Basel, Switzerland) · 2017Review
- Empowering pharmacoinformatics by linked life science data.Journal of computer-aided molecular design · 2017Article
- Neuropharmacology of Synthetic Cathinones.Handbook of experimental pharmacologyArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Retrieval of congeneric and consistent SAR data sets for protein targets of interest is still a laborious task to do if no appropriate in-house data set is available. However, combining integrated open data sources (such as the Open PHACTS Discovery Platform) with workflow tools now offers the possibility of querying across multiple domains and tailoring the search to the given research question. Starting from two phylogenetically related protein targets of interest (the human serotonin and dopamine transporters), the whole chemical compound space was explored by implementing a scaffold-based clustering of compounds possessing biological measurements for both targets. In addition, potential hERG blocking liabilities were included. The workflow allowed studying the selectivity trends of scaffold series, identifying potentially harmful compound series, and performing SAR, docking studies and molecular dynamics (MD) simulations for a consistent data set of 56 cathinones. This delivered useful insights into driving determinants for hDAT selectivity over hSERT. With respect to the scaffold-based analyses it should be noted that the cathinone data set could be retrieved only when Murcko scaffold analyses were combined with similarity searches such as a common substructure search.
Identifiers
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.