Investigation of Active Compounds of Brucea Javanica In Treating Hypertension Using A Network Pharmacology‐Based Analysis Combined with Homology Modeling, Molecular Docking and Molecular Dynamics Simulation

2022 ◽  
Vol 7 (1) ◽  
Author(s):  
Arwansyah Arwansyah ◽  
Abdur Rahman Arif ◽  
Irwan Ramli ◽  
Hasrianti Hasrianti ◽  
Isman Kurniawan ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Molecular Docking ◽  
Molecular Dynamics Simulation ◽  
Homology Modeling ◽  
Dynamics Simulation ◽  
Network Pharmacology ◽  
Active Compounds ◽  
Brucea Javanica

scholarly journals A network pharmacology-based investigation on the bioactive ingredients and molecular mechanisms of Gelsemium elegans Benth against colorectal cancer

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Wancai Que ◽  
Maohua Chen ◽  
Ling Yang ◽  
Bingqing Zhang ◽  
Zhichang Zhao ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Molecular Dynamics ◽  
Molecular Docking ◽  
Molecular Dynamics Simulation ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Molecular Mechanism ◽  
Enrichment Analysis ◽  
Dynamics Simulation ◽  
Network Pharmacology

Abstract Background Colorectal cancer (CRC) remains one of the leading causes of cancer-related death worldwide. Gelsemium elegans Benth (GEB) is a traditional Chinese medicine commonly used for treatment for gastrointestinal cancer, including CRC. However, the underlying active ingredients and mechanism remain unknown. This study aims to explore the active components and the functional mechanisms of GEB in treating CRC by network pharmacology-based approaches. Methods Candidate compounds of GEB were collected from the Traditional Chinese Medicine@Taiwan, Traditional Chinese Medicines Integrated Database, Bioinformatics Analysis Tool for Molecular mechanism of Traditional Chinese Medicine, and published literature. Potentially active targets of compounds in GEB were retrieved from SwissTargetPrediction databases. Keywords “colorectal cancer”, “rectal cancer” and “colon cancer” were used as keywords to search for related targets of CRC from the GeneCards database, then the overlapped targets of compounds and CRC were further intersected with CRC related genes from the TCGA database. The Cytoscape was applied to construct a graph of visualized compound-target and pathway networks. Protein-protein interaction networks were constructed by using STRING database. The DAVID tool was applied to carry out Gene Ontology and Kyoto Encyclopedia of Genes and Genome pathway enrichment analysis of final targets. Molecular docking was employed to validate the interaction between compounds and targets. AutoDockTools was used to construct docking grid box for each target. Docking and molecular dynamics simulation were performed by Autodock Vina and Gromacs software, respectively. Results Fifty-three bioactive compounds were successfully identified, corresponding to 136 targets that were screened out for the treatment of CRC. Functional enrichment analysis suggested that GEB exerted its pharmacological effects against CRC via modulating multiple pathways, such as pathways in cancer, cell cycle, and colorectal cancer. Molecular docking analysis showed that the representative compounds had good affinity with the key targets. Molecular dynamics simulation indicated that the best hit molecules formed a stable protein-ligand complex. Conclusion This network pharmacology study revealed the multiple ingredients, targets, and pathways synergistically involved in the anti-CRC effect of GEB, which will enhance our understanding of the potential molecular mechanism of GEB in treatment for CRC and lay a foundation for further experimental research.

scholarly journals Research on Saponin Active Ingredient of Stir-Fried Dolichos Lablab L. Kernel for Treatment of Type-2 Diabetes Based on UHPLC-Q-Exactive Orbitrap MS and Network Pharmacology

2020 ◽  
Author(s):  
Han Jun ◽  
Liangzi Fang ◽  
Qinfang Zheng
Keyword(s):  
Type 2 Diabetes ◽  
Molecular Dynamics ◽  
Molecular Docking ◽  
Molecular Dynamics Simulation ◽  
Dynamics Simulation ◽  
Network Pharmacology ◽  
Dolichos Lablab ◽  
Q Exactive ◽  
Orbitrap Ms

Abstract BackgroundAlthough the clinical effect of stir-fried Dolichos lablab L. kernel has been approved in modern traditional Chinese medicine, existing associated studies mainly focus on its clinical studies and chemical ingredients. However, there are few studies on pharmacodynamics material basis and molecular mechanism of stirfried Dolichos lablab L. kernel in treatment of type-2 diabetes(T2DM), thus restricting the further development and utilization of stir-fried Dolichos lablab L. kernel.MethodsA qualitative analysis on saponin chemical ingredients of stir-fried Dolichos lablab L. kernel was performed using UHPLC-Q-Exactive Orbitrap MS. A total of 10 saponin ingredients were selected. Moreover, target screening, biological process and metabolism pathway analysis were accomplished by network pharmacology. Four key proteins(EGFR, IGF1, MAPK1 and PIK3R1) of type-2 diabetes were selected for molecular docking verification with saponin ingredients. Specifically, molecular dynamics simulation of ingredients which have strong bindings with proteins was conducted. ResultsIn this study, 16 saponin ingredients were identified from stir-fried Dolichos lablab L. kernel. There were 91 intersection targets and the KEGG pathway enrichment involved 20 relevant pathways. According to the molecular docking verification, saponin ingredients of stir-fried Dolichos lablab L. kernel can form stable binding with key protein targets. The molecular dynamics simulation further verifies stability and reasonability of the docking results. ConclusionsThis study provides references to identification of efficient ingredients of stir-fried Dolichos lablab L. kernel, screening of quality markers and explanation of relevant action mechanism by combining UHPLC-Q-Exactive Orbitrap MS and network pharmacology.

Exploring the effect of inhibitor AKB‐9778 on VE‐PTP by molecular docking and molecular dynamics simulation

2019 ◽  
Vol 120 (10) ◽  
pp. 17015-17029 ◽  
Author(s):  
Wen‐Shan Liu ◽  
Rui‐Rui Wang ◽  
Ying‐Zhan Sun ◽  
Wei‐Ya Li ◽  
Hong‐Lian Li ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Molecular Docking ◽  
Molecular Dynamics Simulation ◽  
Dynamics Simulation
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