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Herb-target virtual screening and network pharmacology for prediction of molecular mechanism of Danggui Beimu Kushen Wan for prostate cancer

Prostate cancer (PCa) is a cancer that occurs in the prostate with high morbidity and mortality. Danggui Beimu Kushen Wan (DBKW) is a classic formula for patients with difficult urination including PCa. This study aimed to investigate the molecular mechanisms of DBKW for PCa. We obtained DBKW compou...

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Detalles Bibliográficos
Autores principales: Li, Hong, Hung, Andrew, Yang, Angela Wei Hong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7988104/
https://www.ncbi.nlm.nih.gov/pubmed/33758314
http://dx.doi.org/10.1038/s41598-021-86141-1
Descripción
Sumario:Prostate cancer (PCa) is a cancer that occurs in the prostate with high morbidity and mortality. Danggui Beimu Kushen Wan (DBKW) is a classic formula for patients with difficult urination including PCa. This study aimed to investigate the molecular mechanisms of DBKW for PCa. We obtained DBKW compounds from our previous reviews. We identified potential targets for PCa from literature search, currently approved drugs and Open Targets database and filtered them by protein–protein interaction network analysis. We selected 26 targets to predict three cancer-related pathways. A total of 621 compounds were screened via molecular docking using PyRx and AutoDock Vina against 21 targets for PCa, producing 13041 docking results. The binding patterns and positions showed that a relatively small number of tight-binding compounds from DBKW were predicted to interact strongly and selectively with three targets. The top five high-binding-affinity compounds were selected to generate a network, indicating that compounds from all three herbs had high binding affinity against the 21 targets and may have potential biological activities with the targets. DBKW contains multi-targeting agents that could act on more than one pathway of PCa simultaneously. Further studies could focus on validating the computational results via experimental studies.