Exploring the mechanism of Jingshen Xiaoke decoction in treating T2DM mice based on network pharmacology and molecular docking

被引:0
作者
Maoa, Yongpo [1 ,2 ,3 ]
Pana, Shengwang [1 ]
Song, Yiming [1 ]
Wang, Wenxiang [2 ,4 ,5 ]
Li, Ning [2 ,4 ,5 ]
Feng, Binbin [2 ,4 ,5 ]
Zhang, Jianhai [2 ,4 ,5 ]
机构
[1] Chengdu Univ, Sch Food & Biol Engn, Chengdu, Sichuan, Peoples R China
[2] Chongqing Three Gorges Med Coll, Chongqing 404120, Peoples R China
[3] Chongqing Presch Educ Coll, Sch Early Childhood Dev, Chongqing, Peoples R China
[4] Chongqing Key Lab Dev & Utilizat Genuine Med Mat, Chongqing, Peoples R China
[5] Chinese Med Hlth Applicat Technol Promot Ctr Chon, Chongqing, Peoples R China
关键词
Jingshen Xiaoke decoction; network pharmacology; molecular docking; type two diabetes mellitus; western blot; mechanism of action; biological activity; TYPE-2; DIABETES-MELLITUS; INSULIN-RESISTANCE; PANAX-NOTOGINSENG; PATHWAYS; SAPONINS; KINASE; RISK;
D O I
10.3233/THC-220630
中图分类号
R19 [保健组织与事业(卫生事业管理)];
学科分类号
摘要
BACKGROUND: Jingshen Xiaoke decoction (JS) was prepared by studying the classic prescriptions of famous scholars in the past dynasties to prevent and treat diabetes. The related mechanism of JS against hyperlipidemia has yet to be revealed. OBJECTIVE: To investigate the mechanism of action of JS in treating diabetes mellitus by using bioinformatics methods. METHODS: A database was used to search the active ingredients and targets of the JS and targets for type 2 diabetes mellitus (T2DM). The protein interaction between the intersection targets, and the constructed the PPI network diagram was analyzed using the STRING database. Furthermore, the gene annotation tool DAVID was used to enrich the intersecting targets for the Gene ontology (GO) function and Kyoto encyclopedia of genes and genomes (KEGG) signaling pathway. Finally, Maestro software was used for molecular docking to verify the binding ability of the active ingredients to the core target genes. RESULTS: A total of 45 active ingredients in JS were screened out corresponding to 239 effective targets, of which 64 targets were potential targets for treating T2DM. The analysis of PPI network diagram analysis revealed that the ingredients' active components are quercetin, beta-sitosterol, stigmasterol, luteolin, and 7-Methoxy-2-methyl isoflavone. GO functional enrichment analysis indicated 186 biological processes (BP), 23 molecular functions (MF) and 13 cellular components (CC). KEGG pathway enrichment analysis revealed the enrichment of 59 signal pathways. The molecular docking results demonstrated that the active ingredients and core targets had a good docking affinity with a binding activity less than 7 kcal/mol. Finally, the western blotting illustrated that JS could up-regulate the liver PI3K/AKT-signaling pathway. CONCLUSION: JS can regulate glucolipid metabolism, reduce the inflammatory response, improve insulin resistance and modulate the immune response through PI3K/AKT signaling pathway treating of T2DM and its complications effects.
引用
收藏
页码:163 / 179
页数:17
相关论文
共 59 条
[1]   Systems Biological Approach of Molecular Descriptors Connectivity: Optimal Descriptors for Oral Bioavailability Prediction [J].
Ahmed, Shiek S. S. J. ;
Ramakrishnan, V. .
PLOS ONE, 2012, 7 (07)
[2]   Can luteolin be a therapeutic molecule for both colon cancer and diabetes? [J].
Ambasta, Rashmi K. ;
Gupta, Rohan ;
Kumar, Dhiraj ;
Bhattacharya, Saurabh ;
Sarkar, Aditi ;
Kumar, Pravir .
BRIEFINGS IN FUNCTIONAL GENOMICS, 2019, 18 (04) :230-239
[3]   Tumor Necrosis Factor (TNF)-α-induced Repression of GKAP42 Protein Levels through cGMP-dependent Kinase (cGK)-Iα Causes Insulin Resistance in 3T3-L1 Adipocytes [J].
Ando, Yasutoshi ;
Shinozawa, Yusuke ;
Iijima, Yumi ;
Yu, Bu-Chin ;
Sone, Meri ;
Ooi, Yuko ;
Watanaka, Yusuke ;
Chida, Kazuhiro ;
Hakuno, Fumihiko ;
Takahashi, Shin-Ichiro .
JOURNAL OF BIOLOGICAL CHEMISTRY, 2015, 290 (09) :5881-5892
[4]  
[Anonymous], 2021, Int J Endocrinol Metab, V41, P482, DOI [10.3760/cma.j.cn121383-20210825-08063, DOI 10.3760/CMA.J.CN121383-20210825-08063]
[5]   UniProt: the universal protein knowledgebase in 2021 [J].
Bateman, Alex ;
Martin, Maria-Jesus ;
Orchard, Sandra ;
Magrane, Michele ;
Agivetova, Rahat ;
Ahmad, Shadab ;
Alpi, Emanuele ;
Bowler-Barnett, Emily H. ;
Britto, Ramona ;
Bursteinas, Borisas ;
Bye-A-Jee, Hema ;
Coetzee, Ray ;
Cukura, Austra ;
Da Silva, Alan ;
Denny, Paul ;
Dogan, Tunca ;
Ebenezer, ThankGod ;
Fan, Jun ;
Castro, Leyla Garcia ;
Garmiri, Penelope ;
Georghiou, George ;
Gonzales, Leonardo ;
Hatton-Ellis, Emma ;
Hussein, Abdulrahman ;
Ignatchenko, Alexandr ;
Insana, Giuseppe ;
Ishtiaq, Rizwan ;
Jokinen, Petteri ;
Joshi, Vishal ;
Jyothi, Dushyanth ;
Lock, Antonia ;
Lopez, Rodrigo ;
Luciani, Aurelien ;
Luo, Jie ;
Lussi, Yvonne ;
Mac-Dougall, Alistair ;
Madeira, Fabio ;
Mahmoudy, Mahdi ;
Menchi, Manuela ;
Mishra, Alok ;
Moulang, Katie ;
Nightingale, Andrew ;
Oliveira, Carla Susana ;
Pundir, Sangya ;
Qi, Guoying ;
Raj, Shriya ;
Rice, Daniel ;
Lopez, Milagros Rodriguez ;
Saidi, Rabie ;
Sampson, Joseph .
NUCLEIC ACIDS RESEARCH, 2021, 49 (D1) :D480-D489
[6]   RCSB Protein Data Bank: powerful new tools for exploring 3D structures of biological macromolecules for basic and applied research and education in fundamental biology, biomedicine, biotechnology, bioengineering and energy sciences [J].
Burley, Stephen K. ;
Bhikadiya, Charmi ;
Bi, Chunxiao ;
Bittrich, Sebastian ;
Chen, Li ;
Crichlow, Gregg, V ;
Christie, Cole H. ;
Dalenberg, Kenneth ;
Di Costanzo, Luigi ;
Duarte, Jose M. ;
Dutta, Shuchismita ;
Feng, Zukang ;
Ganesan, Sai ;
Goodsell, David S. ;
Ghosh, Sutapa ;
Green, Rachel Kramer ;
Guranovic, Vladimir ;
Guzenko, Dmytro ;
Hudson, Brian P. ;
Lawson, Catherine L. ;
Liang, Yuhe ;
Lowe, Robert ;
Namkoong, Harry ;
Peisach, Ezra ;
Persikova, Irina ;
Randle, Chris ;
Rose, Alexander ;
Rose, Yana ;
Sali, Andrej ;
Segura, Joan ;
Sekharan, Monica ;
Shao, Chenghua ;
Tao, Yi-Ping ;
Voigt, Maria ;
Westbrook, John D. ;
Young, Jasmine Y. ;
Zardecki, Christine ;
Zhuravleva, Marina .
NUCLEIC ACIDS RESEARCH, 2021, 49 (D1) :D437-D451
[7]   AMPK signalling in health and disease [J].
Carling, David .
CURRENT OPINION IN CELL BIOLOGY, 2017, 45 :31-37
[8]   Comprehensive Medical Evaluation and Assessment of Comorbidities: Standards of Medical Care in Diabetes-2019 [J].
Cefalu, William T. ;
Berg, Erika Gebel ;
Saraco, Mindy ;
Petersen, Matthew P. ;
Uelmen, Sacha ;
Robinson, Shamera .
DIABETES CARE, 2019, 42 :S34-S45
[9]   Effects of Polygonatum sibiricum saponin on hyperglycemia, gut microbiota composition and metabolic profiles in type 2 diabetes mice [J].
Chai, Yangyang ;
Luo, Jiayuan ;
Bao, Yihong .
BIOMEDICINE & PHARMACOTHERAPY, 2021, 143
[10]   The inflammatory status score including IL-6, TNF-α, osteopontin, fractalkine, MCP-1 and adiponectin underlies whole-body insulin resistance and hyperglycemia in type 2 diabetes mellitus [J].
Daniele, G. ;
Guardado Mendoza, R. ;
Winnier, D. ;
Fiorentino, T. V. ;
Pengou, Z. ;
Cornell, J. ;
Andreozzi, F. ;
Jenkinson, C. ;
Cersosimo, E. ;
Federici, M. ;
Tripathy, D. ;
Folli, F. .
ACTA DIABETOLOGICA, 2014, 51 (01) :123-131