ArticleHeliyon2020
Chemoinformatic studies on some inhibitors of dopamine transporter and the receptor targeting schizophrenia for developing novel antipsychotic agents.
Article in Heliyon, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 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
5 citing papers in PubMed, 15 citations in OpenAlex.
- Perturbation-theory machine learning for mood disorders: virtual design of dual inhibitors of NET and SERT proteins.BMC chemistry · 2025Article
- Identification of novel amides and alkaloids as putative inhibitors of dopamine transporter for schizophrenia using computer-aided virtual screening.Frontiers in pharmacology · 2025Article
- Multivariate QSAR, similarity search and ADMET studies based in a set of methylamine derivatives described as dopamine transporter inhibitors.Molecular diversity · 2024Article
- Article
- Do AutoML-Based QSAR Models Fulfill OECD Principles for Regulatory Assessment? A 5-HTPharmaceutics · 2022Article
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 at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Chemoinformatic studies were carried on some inhibitors of dopamine transporter to develop a predictive and robust QSAR model and also to elucidate binding mode and molecular interactions between the ligands (inhibitors) and the receptor targeting schizophrenia as novel Antipsychotic agents. Density Functional Theory (DFT) approach was utilized to optimize the ligands at B3LYP/6-31G∗ at the ground state and Multi-linear regression of the genetic function approximation (MLR-GFA) method was employed in building Penta-parametric linear equation models. The best model with statistically significant parameters has squared correlation coefficient R
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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.