ArticleFrontiers in pharmacology2025
Design and screening of novel 1,2,4-Triazole-3-thione derivatives as DCN1 inhibitors for anticardiac fibrosis based on 3D-QSAR modeling and molecular dynamics.
Article in Frontiers in pharmacology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
- Structure-adsorption relationships of phenyl- and benzylphosphonic acids and their esters on kaolinite:3D-QSAR study.Journal of molecular modeling · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: Defective in cullin neddylation 1 (DCN1) plays a pivotal role in anticardiac fibrosis by interacting with UBC12 and catalyzing cullin neddylation, which activates cullin-RING E3 ligases (CRLs). As a key modulator of anticardiac fibrosis, DCN1 has emerged as an attractive target for therapeutic intervention. The aim of this study is to design and evaluate novel DCN1 inhibitors using a combination of three-dimensional quantitative structure-activity relationship (3D-QSAR) modeling, molecular docking, and molecular dynamics simulations. Methods: A dataset of 47 derivatives was employed to construct Comparative Molecular Field Analysis (COMSIA) model, incorporating steric, electrostatic, hydrophobic, hydrogen bond donor, and acceptor fields to accurately predict compound activity. In silico molecular docking studies, selected compounds were docked with the target protein to evaluate their binding affinity. Additionally, molecular dynamics simulations were performed to assess the stability of the compounds, followed by energy decomposition analysis was used to identify key residues contributing to binding. Results: The comparative molecular similarity index analysis (COMSIA) model achieved a cross-validated q Conclusion: This study successfully designed and evaluated novel DCN1 inhibitors using an integrated approach that combines 3D-QSAR modeling, molecular docking, and molecular dynamics simulations. The findings provide an effective computational platform for the design of DCN1 inhibitors and lay a solid foundation for the development of drugs targeting anticardiac fibrosis.
Indexed as
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.