ArticleIn silico pharmacology2023
Network analysis and molecular docking studies of quercetin as a potential treatment for prostate cancer.
Article in In silico pharmacology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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
2 citing papers in PubMed, 15 citations in OpenAlex.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Globally, the prevalence of prostate cancer is only the second to lung cancer. In Africa however, the commonest cancer among men is cancer of the prostate. The use of natural compounds from plants such as quercetin is being explored as a potential cure. Quercetin is a plant-based flavonoid that has anti-inflammatory, antioxidant and anticancer properties. Although quercetin has been extensively studied, its chemo preventive mode of action is not well-understood. The molecular targets and potential mechanisms underlying the action of quercetin against prostate cancer were identified and validated using network pharmacology and molecular docking methods. The biological targets of quercetin and targets associated with prostate cancer were obtained through database mining. Overlapping targets associated with quercetin and prostate cancer were identified and used to construct a compound-disease target (C-D) network and the targets were subjected to Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and protein-protein interaction analysis (PPI). A disease target- pathway network was constructed and then merged with C-D network to form a compound-disease_target-pathway (C-D-P) network. Hub targets were obtained from the C-D-P and PPI networks. The binding affinities between quercetin and the retrieved hub targets were identified. Pathway enrichment analysis showed that prostate cancer associated quercetin targets were mainly linked with pathways such as the cancer signaling pathways (HIF-1 and ErbB) and hepatitis B. Basing on the PPI and C-D-P network analysis STAT3, TP53, MAPK1, MAPK3 and KRAS were identified as the main targets and were subjected to molecular docking. The results showed quercetin's ability to stably bind to the key targets. In conclusion, this study showed the potential molecular targets and mode of action of quercetin in prostate cancer treatment. This can potentially inform the future use of quercetin in the treatment of prostate cancer.
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.