scholarly journals Exploring the Antihyperglycemic Chemical Composition and Mechanisms of Tea Using Molecular Docking

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Yue Sun ◽  
Lufei Wang ◽  
Lily K. Shaughnessy ◽  
Yan Lin ◽  
Qingliang Xu ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Molecular Mechanisms ◽  
Binding Capacity ◽  
Close Correlation ◽  
Tea Plant ◽  
Protein Targets ◽  
Docking Approach ◽  
Bioactive Ingredients ◽  
Target Binding ◽  
Potential Interactions

Tea, a widely consumed beverage, has long been utilized for promoting human health with a close correlation to hyperglycemia. The Tea Metabolome Database (TMDB), the most complete and comprehensive curated collection of tea compounds data containing 1271 identified small molecule compounds from the tea plant (Camellia sinensis), was established previously by our research team. More recently, our studies have found that various tea types possess an antihyperglycemic effect in mice. However, the bioactive ingredients from tea have potential antihyperglycemic activity and their underlying molecular mechanisms remain unclear. In this study, we used a molecular docking approach to investigate the potential interactions between a selected 747 constituents contained in tea and 11 key protein targets of clinical antihyperglycemic drugs. According to our results, the main antihyperglycemic targets of tea composition were consistent with those of the drug rosiglitazone. The screening results showed that GCG, ECG3’Me, TMDB-01443, and CG had great target binding capacity. The results indicated that these chemicals of tea might affect hyperglycemia by acting on protein targets of rosiglitazone.

scholarly journals MOLECULAR DOCKING STUDY BETWEEN 3 THAI MEDICINAL PLANTS COMPOUNDS AND COVID-19 THERAPEUTIC PROTEIN TARGETS: SARS-COV-2 MAIN PROTEASE, ACE-2, AND PAK-1

2021 ◽  
pp. 41-48
Author(s):  
SAFIRA CANDRA ASIH ◽  
RAFIDHA IRDIANI ◽  
MUHAMAD SAHLAN ◽  
MOHAMMAD NASIKIN
Keyword(s):  
Molecular Docking ◽  
Medicinal Plants ◽  
Profile Analysis ◽  
Binding Free Energy ◽  
Docking Study ◽  
Molecular Docking Study ◽  
Protein Targets ◽  
Main Protease ◽  
Docking Approach ◽  
Thai Medicinal Plants

Objective: The present study aimed to evaluate those 3 compounds among 122 Thai natural products by using a molecular docking approach to inhibit Main Protease (Mpro) of SARS-CoV-2 (PDB code: 6Y2F), Angiotensin Converting Enzyme (ACE)-2 (PDB code: 1R4L), and PAK-1 kinase (PDB code: 5DEW). Methods: The evaluation was performed on the docking scores calculated using AutoDock Vina as a docking engine and interaction profile analysis through 2-dimensional visualization using LigPlot+. The determination of the docking score was done by selecting the conformation of the ligand that has the lowest binding free energy (best pose). Result: The results of this study indicate that overall, Panduratin A has the best affinity in inhibiting the main protease of SARS-CoV-2, ACE-2, and PAK-1 compared to other compounds. Conclusion: The three thai medicinal plants compound has the potential to be developed as specific therapeutic agents against COVID-19.

Network Pharmacology and Reverse Molecular Docking-Based Prediction of the Molecular Targets and Pathways for Avicularin Against Cancer

2019 ◽  
Vol 22 (1) ◽  
pp. 4-12 ◽  
Author(s):  
Chaohui Duan ◽  
Yang Li ◽  
Xiaorui Dong ◽  
Weibin Xu ◽  
Yingli Ma
Keyword(s):  
Molecular Docking ◽  
Molecular Mechanisms ◽  
Mapk Signaling ◽  
Network Pharmacology ◽  
Literature Mining ◽  
Protein Database ◽  
Topology Analysis ◽  
Powerful Means ◽  
Bioactive Ingredients

Aim and Objective: Avicularin has been found to inhibit the proliferation of HepG-2 cells in vitro in the screening of our laboratory. We intended to explain the molecular mechanism of this effect. Therefore, the combined methods of reverse molecular docking and network pharmacology were used in order to illuminate the molecular mechanisms for Avicularin against cancer. Materials and Methods: Potential targets associated with anti-tumor effects of Avicularin were screened by reverse molecular docking, then a protein database was established through constructing the drugprotein network from literature mining data, and the protein-protein network was built through an in-depth exploration of the relationships between the proteins, and then the network topology analysis was performed. Additionally, gene function and signaling pathways were analyzed by Go bio-enrichment and KEGG Pathway. Results: The result showed that Avicularin was closely related to 16 targets associated with cancer, and it may significantly influence the pro-survival signals in MAPK signaling pathway that can activate and regulate a series of cellular activities and participate in the regulation of cell proliferation, differentiation, transformation and apoptosis. Conclusion: The network pharmacology strategy used herein provided a powerful means for the mechanisms of action for bioactive ingredients.

scholarly journals Network Pharmacology Integrated Molecular Docking Reveals the Anti-COVID-19 Mechanism of Qing-Fei-Da-Yuan Granules

2020 ◽  
Vol 15 (6) ◽  
pp. 1934578X2093421 ◽  
Author(s):  
Zongchao Hong ◽  
Xueyun Duan ◽  
Songtao Wu ◽  
Yang Yanfang ◽  
Hezhen Wu
Keyword(s):  
Molecular Docking ◽  
Molecular Mechanisms ◽  
Interaction Analysis ◽  
Binding Capacity ◽  
Chemical Constituents ◽  
Network Pharmacology ◽  
Binding Ability ◽  
The Core ◽  
Strong Binding ◽  
Compound Target

Coronavirus disease (COVID-19), caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is a highly infectious viral disease. Clinical observations have shown that Qing-Fei-Da-Yuan (QFDY) granules have good anti-COVID-19 effects, but the underlying molecular mechanisms are unclear. In this study, we explored the potential mechanism of QFDY with regard to its anti-COVID-19 effect. We first screened the active chemical constituents of QFDY based on the pharmacodynamic activity parameters, followed by screening with the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform. The Uniprot database was used for querying the corresponding genes of the target, and Cyoscape 3.6.1 software was used to construct the network of herb-compound-target. Protein interaction analysis, target gene function enrichment analysis, and signal pathway analysis were performed via STRING database, Database for Annotation, Visualization, and Integrated Discovery, and KEGG Pathway database. Molecular docking was used to predict the binding capacity of the core compound with COVID-19 hydrolase 3CL and angiotensin converting enzyme 2 (ACE2). The results showed that a network of herb-compound-target was successfully constructed, with key targets involving PTGS2, HSP90AA1, CAMKK2, NCOA2, and ESR1. Major metabolic pathways affected were those in cancer, procancer, nonsmall cell lung cancer, and apoptosis. The core compounds, such as quercetin, luteolin, and naringenin, showed a strong binding ability with COVID-19 3CL hydrolase; compounds such as anemasaponin C and medicocarpin showed a strong binding ability with ACE2. Thus, it is predicted that QFDY has the characteristics for multicomponent, multitarget, and multichannel overall control. The mechanism of action of QFDY in the treatment of COVID-19 may be associated with the regulation of genes co-expressed with ACE2, the regulation of inflammation and immune-related signaling pathways, and the influence of COVID-19 3CL hydrolase and ACE2 binding ability.

scholarly journals DockScreen: A Database of In Silico Biomolecular Interactions to Support Computational Toxicology

2014 ◽  
Vol 2014 ◽  
pp. 1-5 ◽  
Author(s):  
Michael-Rock Goldsmith ◽  
Christopher M. Grulke ◽  
Daniel T. Chang ◽  
Thomas R. Transue ◽  
Stephen B. Little ◽  
...  
Keyword(s):  
Molecular Docking ◽  
In Silico ◽  
High Performance ◽  
Search Algorithm ◽  
Biomolecular Interactions ◽  
Computational Toxicology ◽  
Docking Approach ◽  
Minimum Score ◽  
Target Binding

We have developed DockScreen, a database of in silico biomolecular interactions designed to enable rational molecular toxicological insight within a computational toxicology framework. This database is composed of chemical/target (receptor and enzyme) binding scores calculated by molecular docking of more than 1000 chemicals into 150 protein targets and contains nearly 135 thousand unique ligand/target binding scores. Obtaining this dataset was achieved using eHiTS (Simbiosys Inc.), a fragment-based molecular docking approach with an exhaustive search algorithm, on a heterogeneous distributed high-performance computing framework. The chemical landscape covered in DockScreen comprises selected environmental and therapeutic chemicals. The target landscape covered in DockScreen was selected based on the availability of high-quality crystal structures that covered the assay space of phase I ToxCast in vitro assays. This in silico data provides continuous information that establishes a means for quantitatively comparing, on a structural biophysical basis, a chemical’s profile of biomolecular interactions. The combined minimum-score chemical/target matrix is provided.

scholarly journals Tea flavonoids blocking multiple SARS-CoV-2 protein targets judged from molecular docking

2020 ◽  
Author(s):  
Lufei Wang ◽  
Siyao Sang ◽  
Mingjie Su ◽  
Simin Wang ◽  
Hui Li
Keyword(s):  
Molecular Docking ◽  
Severe Acute Respiratory Syndrome ◽  
Molecular Mechanisms ◽  
Positive Control ◽  
Potential Candidate ◽  
Protein Targets ◽  
Angiotensin Converting Enzyme 2 ◽  
Patent Medicines ◽  
Main Protease ◽  
Chinese Patent

Abstract Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has caused Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) pandemic. Flavonoids derived Chinese patent medicines has outstanding curative effects for the improvement and treatment of COVID-19. There are numerous studies suggesting that flavonoids-rich tea have antiviral effects. However, bioactive compounds from tea flavonoids with anti-COVID-19 effect, and the potential molecular mechanisms are unclear. In this study, we performed a molecular docking of 468 tea flavonoids and its derivatives with main protease (Mpro), angiotensin-converting enzyme 2 (ACE2), RNA dependent RNA polymerase (RdRp), compared with the positive control drugs of each target. The results suggested that ACE2 and RdRp are the main targets inhibited by tea flavonoids.Q3G Isovitexin, and TF would be considered as the potential candidate compounds of RdRp and ACE2. Our study provides a theoretical basis for further drug design of anti-COVID-19.

Molecular Docking Approaches to Suggest the Anti-Mycobacterial Targets of Natural Products

2020 ◽  
Author(s):  
Rafael Baptista ◽  
Sumana Bhowmick ◽  
Shen Jianying ◽  
Luis Mur
Keyword(s):  
Natural Products ◽  
Molecular Docking ◽  
Free Energies ◽  
Antibiotic Resistant ◽  
Drug Lead ◽  
Bisbenzylisoquinoline Alkaloids ◽  
Docking Approach ◽  
Global Threat ◽  
Physicochemical And Structural Properties

Tuberculosis (TB) is a major global threat mostly due to the development of antibiotic resistant forms of Mycobacterium tuberculosis, the causal agent of the disease. Driven by the pressing need for new anti-mycobacterial agents, several natural products (NPs) have been shown to have in vitro activities against M. tuberculosis. The utility of any NP as a drug lead is augmented when the anti-mycobacterial target(s) is unknown. To suggest these, we used a molecular docking approach to predict the interactions of 53 selected anti-mycobacterial NPs against known ‘druggable’ mycobacterial targets ClpP1P2, DprE1, InhA, KasA, PanK, PknB and Pks13. The docking scores / binding free energies were predicted and calculated using AutoDock Vina along with physicochemical and structural properties of the NPs, using PaDEL descriptors. These were compared to the established inhibitor (control) drugs for each mycobacterial target. The specific interactions of the bisbenzylisoquinoline alkaloids 2-nortiliacorinine, tiliacorine and 13’-bromotiliacorinine against the targets PknB and DprE1 (-11.4, -10.9 and -9.8 kcal.mol-1 ; -12.7, -10.9 and -10.3 kcal.mol-1 , respectively) and the lignan αcubebin and Pks13 (-11.0 kcal.mol-1 ) had significantly superior docking scores compared to controls. Our approach can be used to suggest predicted targets for the NP to be validated experimentally but these in silico steps are likely to facilitate drug optimisation.

Molecular Docking, Synthesis and anti-HIV-1 Protease Activity of Novel Chalcones

2020 ◽  
Vol 26 (8) ◽  
pp. 802-814 ◽  
Author(s):  
Nemanja Turkovic ◽  
Branka Ivkovic ◽  
Jelena Kotur-Stevuljevic ◽  
Milica Tasic ◽  
Bojan Marković ◽  
...  
Keyword(s):  
Molecular Weight ◽  
Molecular Docking ◽  
Chemical Synthesis ◽  
Protease Activity ◽  
Molecular Mechanisms ◽  
Replication Cycle ◽  
Low Molecular Weight ◽  
Chalcone Derivatives ◽  
Anti Hiv ◽  
Hiv 1

Background: Since the beginning of the HIV/AIDS epidemic, 75 million people have been infected with the HIV and about 32 million people have died of AIDS. Investigation of the molecular mechanisms critical to the HIV replication cycle led to the identification of potential drug targets for AIDS therapy. One of the most important discoveries is HIV-1 protease, an enzyme that plays an essential role in the replication cycle of HIV. Objective: The aim of the present study is to synthesize and investigate anti-HIV-1 protease activity of some chalcone derivatives with the hope of discovering new lead structure devoid drug resistance. Methods: 20 structurally similar chalcone derivatives were synthesized and their physico-chemical characterization was performed. Binding of chalcones to HIV-1 protease was investigated by fluorimetric assay. Molecular docking studies were conducted to understand the interactions. Results: The obtained results revealed that all compounds showed anti-HIV-1 protease activity. Compound C1 showed the highest inhibitory activity with an IC50 value of 0.001 μM, which is comparable with commercial product Darunavir. Conclusion: It is difficult to provide general principles of inhibitor design. Structural properties of the compounds are not the only consideration; ease of chemical synthesis, low molecular weight, bioavailability, and stability are also of crucial importance. Compared to commercial products the main advantage of compound C1 is the ease of chemical synthesis and low molecular weight. Furthermore, compound C1 has a structure that is different to peptidomimetics, which could contribute to its stability and bioavailability.

Ligand based Drug Design of New Heterocyclic Imines of GABA Analogues: A Molecular Docking Approach for the Discovery of New GABA-AT Inhibitors

2017 ◽  
Vol 17 (1) ◽  
pp. 58-63 ◽  
Author(s):  
Bijo Mathew ◽  
Githa Mathew ◽  
Jerad Suresh ◽  
Dhasthakeer Usman ◽  
Puthucode Subramanyan ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Drug Design ◽  
Docking Approach ◽  
Gaba Analogues

scholarly journals Insights into the molecular mechanisms of Huangqi decoction on liver fibrosis via computational systems pharmacology approaches

2021 ◽  
Vol 16 (1) ◽  
Author(s):  
Biting Wang ◽  
Zengrui Wu ◽  
Weihua Li ◽  
Guixia Liu ◽  
Yun Tang
Keyword(s):  
Molecular Docking ◽  
Liver Fibrosis ◽  
Molecular Mechanisms ◽  
Docking Simulation ◽  
Chinese Herbs ◽  
Network Pharmacology ◽  
Bipartite Network ◽  
Metabolomics Data ◽  
Metabolic Products ◽  
Compound Target

Abstract Background The traditional Chinese medicine Huangqi decoction (HQD) consists of Radix Astragali and Radix Glycyrrhizae in a ratio of 6: 1, which has been used for the treatment of liver fibrosis. In this study, we tried to elucidate its action of mechanism (MoA) via a combination of metabolomics data, network pharmacology and molecular docking methods. Methods Firstly, we collected prototype components and metabolic products after administration of HQD from a publication. With known and predicted targets, compound-target interactions were obtained. Then, the global compound-liver fibrosis target bipartite network and the HQD-liver fibrosis protein–protein interaction network were constructed, separately. KEGG pathway analysis was applied to further understand the mechanisms related to the target proteins of HQD. Additionally, molecular docking simulation was performed to determine the binding efficiency of compounds with targets. Finally, considering the concentrations of prototype compounds and metabolites of HQD, the critical compound-liver fibrosis target bipartite network was constructed. Results 68 compounds including 17 prototype components and 51 metabolic products were collected. 540 compound-target interactions were obtained between the 68 compounds and 95 targets. Combining network analysis, molecular docking and concentration of compounds, our final results demonstrated that eight compounds (three prototype compounds and five metabolites) and eight targets (CDK1, MMP9, PPARD, PPARG, PTGS2, SERPINE1, TP53, and HIF1A) might contribute to the effects of HQD on liver fibrosis. These interactions would maintain the balance of ECM, reduce liver damage, inhibit hepatocyte apoptosis, and alleviate liver inflammation through five signaling pathways including p53, PPAR, HIF-1, IL-17, and TNF signaling pathway. Conclusions This study provides a new way to understand the MoA of HQD on liver fibrosis by considering the concentrations of components and metabolites, which might be a model for investigation of MoA of other Chinese herbs.

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