ArticleJournal of advanced pharmaceutical technology & research
Computational approach in searching for dual action multitarget inhibitors for osteosarcoma.
Article in Journal of advanced pharmaceutical technology & research. 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, 2 citations in OpenAlex.
- Computational Exploration ofBioinformatics and biology insights · 2024Article
Corrections and comments
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Authors and funding
8 authors at 3 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Osteosarcoma is a common primary malignant bone tumor that typically manifests in the second decade of life. This study aimed to identify osteogenic compounds that potentially serve as multitarget inhibitors for osteosarcoma. The study was a molecular docking study of nine Food and Drug Administration-approved compounds with osteogenic properties to the key membrane proteins of osteosarcoma. The ligands used were raloxifene, simvastatin, dexamethasone, risedronate, ibandronate, zoledronic acid, ascorbic acid, alendronate, and β-glycerophosphate, whereas the target proteins used were RET, fibroblast growth factor receptor 1, KIT, PDGFRA, VEGFR1, and VEGFR2. Chem3D version 15.0.0.106 was used for ligand preparation, and AutoDockTools version 1.5.6 was used for protein preparation, whereas molecular docking was conducted using AutoDock Vina. Raloxifene, simvastatin, and dexamethasone had the lowest binding activity to the target proteins. The binding affinity of raloxifene was from -8.4 to -10.0 kcal mol
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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.