Exploring the Underlying Mechanism of Shenyankangfu Tablet in the Treatment of Glomerulonephritis Through Network Pharmacology, Machine Learning, Molecular Docking, and Experimental Validation
Meiling Jin,1,2,* Wenwen Ren,3,* Weiguang Zhang,2 Linchang Liu,2,4 Zhiwei Yin,2,5 Diangeng Li6 1Department of Nephrology, Beijing-Chaoyang Hospital, Capital Medical University, Beijing, 100020, People’s Republic of China; 2Department of Nephrology, Chinese People’s Liberation Army Ge...
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Dove Medical Press
2021
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shenyankangfu tablet glomerulonephritis network pharmacology machine learning molecular docking Therapeutics. Pharmacology RM1-950 |
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shenyankangfu tablet glomerulonephritis network pharmacology machine learning molecular docking Therapeutics. Pharmacology RM1-950 Jin M Ren W Zhang W Liu L Yin Z Li D Exploring the Underlying Mechanism of Shenyankangfu Tablet in the Treatment of Glomerulonephritis Through Network Pharmacology, Machine Learning, Molecular Docking, and Experimental Validation |
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Meiling Jin,1,2,* Wenwen Ren,3,* Weiguang Zhang,2 Linchang Liu,2,4 Zhiwei Yin,2,5 Diangeng Li6 1Department of Nephrology, Beijing-Chaoyang Hospital, Capital Medical University, Beijing, 100020, People’s Republic of China; 2Department of Nephrology, Chinese People’s Liberation Army General Hospital, Chinese People’s Liberation Army Institute of Nephrology, State Key Laboratory of Kidney Diseases (2011DAV00088), National Clinical Research Center for Kidney Diseases, Beijing, 100853, People’s Republic of China; 3Department of Nephrology, Beijing Ditan Hospital,Capital Medical University, Beijing, 100015, People’s Republic of China; 4Department of Nephrology, Beijing Hospital of Integrated Traditional Chinese and Western Medicine, Beijing, 100039, People’s Republic of China; 5College of Chinese Integrative Medicine, Hebei Medical University, Shijiazhuang, 050017, People’s Republic of China; 6Department of Academic Research, Beijing-Chaoyang Hospital, Capital Medical University, Beijing, 100020, People’s Republic of China*These authors contributed equally to this workCorrespondence: Diangeng LiDepartment of Academic Research, Beijing-Chaoyang Hospital, Capital Medical University, Beijing, 100020, People’s Republic of ChinaTel/Fax +86 10-85231049Email lidiangeng@126.comZhiwei YinCollege of Chinese Integrative Medicine, Hebei Medical University, Shijiazhuang, 050017, People’s Republic of China; Department of Nephrology, Chinese People’s Liberation Army General Hospital, Chinese People’s Liberation Army Institute of Nephrology, State Key Laboratory of Kidney Diseases (2011DAV00088), National Clinical Research Center for Kidney Diseases, Beijing, 100853, People’s Republic of ChinaTel/Fax +86 10-66937010Email zhiwei_yin@126.comPurpose: This study aimed to explore the underlying mechanisms of Shenyankangfu tablet (SYKFT) in the treatment of glomerulonephritis (GN) based on network pharmacology, machine learning, molecular docking, and experimental validation.Methods: The active ingredients and potential targets of SYKFT were obtained through the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform, the targets of GN were obtained through GeneCards, etc. Perl and Cytoscape were used to construct an herb-active ingredient–target network. Then, the clusterProfiler package of R was used for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. We also used the STRING platform and Cytoscape to construct a protein–protein interaction (PPI) network, as well as the SwissTargetPrediction server to predict the target protein of the core active ingredient based on machine-learning model. Molecular-docking analysis was further performed using AutoDock Vina and Pymol. Finally, we verified the effect of SYKFT on GN in vivo.Results: A total of 154 active ingredients and 255 targets in SYKFT were screened, and 135 targets were identified to be related to GN. GO enrichment analysis indicated that biological processes were primarily associated with oxidative stress and cell proliferation. KEGG pathway analysis showed that these targets were involved mostly in infection-related and GN-related pathways. PPI network analysis identified 13 core targets of SYKFT. Results of machine-learning model suggested that STAT3 and AKT1 may be the key target. Results of molecular docking suggested that the main active components of SYKFT can be combined with various target proteins. In vivo experiments confirmed that SYKFT may alleviate renal pathological injury by regulating core genes, thereby reducing urinary protein.Conclusion: This study demonstrated for the first time the multicomponent, multitarget, and multipathway characteristics of SYKFT for GN treatment.Keywords: shenyankangfu tablet, glomerulonephritis, network pharmacology, machine learning, molecular docking |
| format |
article |
| author |
Jin M Ren W Zhang W Liu L Yin Z Li D |
| author_facet |
Jin M Ren W Zhang W Liu L Yin Z Li D |
| author_sort |
Jin M |
| title |
Exploring the Underlying Mechanism of Shenyankangfu Tablet in the Treatment of Glomerulonephritis Through Network Pharmacology, Machine Learning, Molecular Docking, and Experimental Validation |
| title_short |
Exploring the Underlying Mechanism of Shenyankangfu Tablet in the Treatment of Glomerulonephritis Through Network Pharmacology, Machine Learning, Molecular Docking, and Experimental Validation |
| title_full |
Exploring the Underlying Mechanism of Shenyankangfu Tablet in the Treatment of Glomerulonephritis Through Network Pharmacology, Machine Learning, Molecular Docking, and Experimental Validation |
| title_fullStr |
Exploring the Underlying Mechanism of Shenyankangfu Tablet in the Treatment of Glomerulonephritis Through Network Pharmacology, Machine Learning, Molecular Docking, and Experimental Validation |
| title_full_unstemmed |
Exploring the Underlying Mechanism of Shenyankangfu Tablet in the Treatment of Glomerulonephritis Through Network Pharmacology, Machine Learning, Molecular Docking, and Experimental Validation |
| title_sort |
exploring the underlying mechanism of shenyankangfu tablet in the treatment of glomerulonephritis through network pharmacology, machine learning, molecular docking, and experimental validation |
| publisher |
Dove Medical Press |
| publishDate |
2021 |
| url |
https://doaj.org/article/3f024dec572f47e7acabbe52e6101116 |
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oai:doaj.org-article:3f024dec572f47e7acabbe52e61011162021-11-09T18:40:35ZExploring the Underlying Mechanism of Shenyankangfu Tablet in the Treatment of Glomerulonephritis Through Network Pharmacology, Machine Learning, Molecular Docking, and Experimental Validation1177-8881https://doaj.org/article/3f024dec572f47e7acabbe52e61011162021-11-01T00:00:00Zhttps://www.dovepress.com/exploring-the-underlying-mechanism-of-shenyankangfu-tablet-in-the-trea-peer-reviewed-fulltext-article-DDDThttps://doaj.org/toc/1177-8881Meiling Jin,1,2,* Wenwen Ren,3,* Weiguang Zhang,2 Linchang Liu,2,4 Zhiwei Yin,2,5 Diangeng Li6 1Department of Nephrology, Beijing-Chaoyang Hospital, Capital Medical University, Beijing, 100020, People’s Republic of China; 2Department of Nephrology, Chinese People’s Liberation Army General Hospital, Chinese People’s Liberation Army Institute of Nephrology, State Key Laboratory of Kidney Diseases (2011DAV00088), National Clinical Research Center for Kidney Diseases, Beijing, 100853, People’s Republic of China; 3Department of Nephrology, Beijing Ditan Hospital,Capital Medical University, Beijing, 100015, People’s Republic of China; 4Department of Nephrology, Beijing Hospital of Integrated Traditional Chinese and Western Medicine, Beijing, 100039, People’s Republic of China; 5College of Chinese Integrative Medicine, Hebei Medical University, Shijiazhuang, 050017, People’s Republic of China; 6Department of Academic Research, Beijing-Chaoyang Hospital, Capital Medical University, Beijing, 100020, People’s Republic of China*These authors contributed equally to this workCorrespondence: Diangeng LiDepartment of Academic Research, Beijing-Chaoyang Hospital, Capital Medical University, Beijing, 100020, People’s Republic of ChinaTel/Fax +86 10-85231049Email lidiangeng@126.comZhiwei YinCollege of Chinese Integrative Medicine, Hebei Medical University, Shijiazhuang, 050017, People’s Republic of China; Department of Nephrology, Chinese People’s Liberation Army General Hospital, Chinese People’s Liberation Army Institute of Nephrology, State Key Laboratory of Kidney Diseases (2011DAV00088), National Clinical Research Center for Kidney Diseases, Beijing, 100853, People’s Republic of ChinaTel/Fax +86 10-66937010Email zhiwei_yin@126.comPurpose: This study aimed to explore the underlying mechanisms of Shenyankangfu tablet (SYKFT) in the treatment of glomerulonephritis (GN) based on network pharmacology, machine learning, molecular docking, and experimental validation.Methods: The active ingredients and potential targets of SYKFT were obtained through the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform, the targets of GN were obtained through GeneCards, etc. Perl and Cytoscape were used to construct an herb-active ingredient–target network. Then, the clusterProfiler package of R was used for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. We also used the STRING platform and Cytoscape to construct a protein–protein interaction (PPI) network, as well as the SwissTargetPrediction server to predict the target protein of the core active ingredient based on machine-learning model. Molecular-docking analysis was further performed using AutoDock Vina and Pymol. Finally, we verified the effect of SYKFT on GN in vivo.Results: A total of 154 active ingredients and 255 targets in SYKFT were screened, and 135 targets were identified to be related to GN. GO enrichment analysis indicated that biological processes were primarily associated with oxidative stress and cell proliferation. KEGG pathway analysis showed that these targets were involved mostly in infection-related and GN-related pathways. PPI network analysis identified 13 core targets of SYKFT. Results of machine-learning model suggested that STAT3 and AKT1 may be the key target. Results of molecular docking suggested that the main active components of SYKFT can be combined with various target proteins. In vivo experiments confirmed that SYKFT may alleviate renal pathological injury by regulating core genes, thereby reducing urinary protein.Conclusion: This study demonstrated for the first time the multicomponent, multitarget, and multipathway characteristics of SYKFT for GN treatment.Keywords: shenyankangfu tablet, glomerulonephritis, network pharmacology, machine learning, molecular dockingJin MRen WZhang WLiu LYin ZLi DDove Medical Pressarticleshenyankangfu tabletglomerulonephritisnetwork pharmacologymachine learningmolecular dockingTherapeutics. PharmacologyRM1-950ENDrug Design, Development and Therapy, Vol Volume 15, Pp 4585-4601 (2021) |