scholarly journals Exploring the Potential Molecular Mechanism of Scutellaria baicalensis Georgi in the Treatment of Gastric Cancer Based on Network Pharmacological Analysis and Molecular Docking Technology

2021 ◽  
Vol 12 ◽  
Author(s):  
Yi Tu ◽  
Quanli Wu ◽  
Jiarui He ◽  
Jiasheng Xu ◽  
Shasha Yu ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Free Energy ◽  
Molecular Docking ◽  
Molecular Mechanism ◽  
Therapeutic Effect ◽  
Drug Targets ◽  
Target Genes ◽  
Binding Free Energy ◽  
Scutellaria Baicalensis ◽  
Pharmacological Analysis

Objective: To explore the molecular mechanism of Scutellaria baicalensis Georgi in treating gastric cancer by network pharmacological analysis and molecular docking.Methods: Taking Scutellaria baicalensis Georgi as the object, the active components and corresponding potential drug targets in Scutellaria baicalensis Georgi were obtained from the database of TCM Pharmacological System Analysis Platform (TCMSP). GeneCards/OMIM/DrugBank and other databases were used to collect gastric cancer-related genes, and the obtained genes were intersected with drug targets to obtain the target genes of Scutellaria baicalensis Georgi on gastric cancer. Furthermore, the interaction network of Scutellaria baicalensis Georgi-active ingredients-target-gastric cancer-related genes was constructed. Protein–protein interaction analysis and gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were performed on target genes. The PubChem website was used to screen the compounds corresponding to the target genes, and the target protein and 3D structure pdb format files were obtained from the PDB database. Finally, the molecular docking calculation was performed by the AutoDock Vina program. The in vivo cell experiments on the effect of Scutellaria baicalensis on proliferation and migration of gastric cancer cells were used to determine the therapeutic effect of Scutellaria baicalensis on gastric cancer, and the two genes ESR1 and FOS are the key targets of Scutellaria baicalensis on gastric cancer.Results: A total of 10 gastric cancer-related target genes were screened out, and Scutellaria baicalensis Georgi contained 10 active compounds targeting 10 gene sites. There are 30 effective compounds in Scutellaria baicalensis Georgi targeted to treat gastric cancer, and there are 91 corresponding targeting gene sites, involving a total of 10 pathways. The results of molecular docking show that ESR1, FOS, and Scutellaria baicalensis Georgi have good binding free energy and docking fraction. The docking fraction of FOS is −4.200 and the binding free energy is −27.893 kcal/mol. The docking fraction of ESR1 is −5.833 and the binding free energy is −30.001 kcal/mol. The effect of Scutellaria baicalensis Georgi on gastric cancer was verified by in vitro cell experiments and Western blotting.Conclusion:Scutellaria baicalensis Georgi can target and regulate multiple signal pathways by acting on ESR1 and FOS gene loci, thus having a potential therapeutic effect on gastric cancer.

scholarly journals Computational Determination of Potential Inhibitors of SARS-CoV-2 Main Protease

2020 ◽  
Author(s):  
Son Tung Ngo ◽  
Ngoc Quynh Anh Pham ◽  
Ly Le ◽  
Duc-Hung Pham ◽  
Van Vu
Keyword(s):  
Free Energy ◽  
Molecular Docking ◽  
Drug Targets ◽  
Binding Free Energy ◽  
Natural Compounds ◽  
Main Protease ◽  
Energy Perturbation ◽  
Novel Coronavirus ◽  
Potential Inhibitors ◽  
Hiv 1

<p>The novel coronavirus (SARS-CoV-2) has infected over 850,000 people and caused more than 42000 deaths worldwide as of April 1<sup>st</sup>, 2020. As the disease is spreading rapidly all over the world, it is urgent to find effective drugs to treat the virus. The main protease (Mpro) of SARS-CoV-2 is one of the potential drug targets. In this work, we used rigorous computational methods, including molecular docking, fast pulling of ligand (FPL), and free energy perturbation (FEP), to investigate potential inhibitors of SARS-CoV-2 Mpro. We first tested our approach with three reported inhibitors of SARS-CoV-2 Mpro; and our computational results are in good agreement with the respective experimental data. Subsequently, we applied our approach on a databases of ~4600 natural compounds found in Vietnamese plants, as well as 8 available HIV-1 protease (PR) inhibitors and an aza-peptide epoxide. Molecular docking resulted in a short list of 35 natural compounds, which was subsequently refined using the FPL scheme. FPL simulations resulted in five potential inhibitors, including 3 natural compounds and two available HIV-1 PR inhibitors. Finally, FEP, the most accurate and precise method, was used to determine the absolute binding free energy of these five compounds. FEP results indicate that two natural compounds, <i>cannabisin </i>A and <i>isoacteoside</i>, and an HIV-1 PR inhibitor, <i>darunavir</i>, exhibit large binding free energy to SARS-CoV-2 Mpro, which is larger than that of <b>13b</b>, the most reliable SARS-CoV-2 Mpro inhibitor recently reported. The binding free energy largely arises from van der Waals (vdW) interaction. We also found that Glu166 form H-bonds to all the inhibitors. Replacing Glu166 by an alanine residue leads to ~ 2.0 kcal/mol decreases in the affinity of <i>darunavir </i>to SARS-CoV-2 Mpro. Our results could contribute to the development of potentials drugs inhibiting SARS-CoV-2. </p>

scholarly journals Computational Determination of Potential Inhibitors of SARS-CoV-2 Main Protease

2020 ◽  
Author(s):  
Son Tung Ngo ◽  
Ngoc Quynh Anh Pham ◽  
Ly Le ◽  
Duc-Hung Pham ◽  
Van Vu
Keyword(s):  
Free Energy ◽  
Molecular Docking ◽  
Drug Targets ◽  
Binding Free Energy ◽  
Natural Compounds ◽  
Main Protease ◽  
Energy Perturbation ◽  
Novel Coronavirus ◽  
Potential Inhibitors ◽  
Hiv 1

<p>The novel coronavirus (SARS-CoV-2) has infected over 850,000 people and caused more than 42000 deaths worldwide as of April 1<sup>st</sup>, 2020. As the disease is spreading rapidly all over the world, it is urgent to find effective drugs to treat the virus. The main protease (Mpro) of SARS-CoV-2 is one of the potential drug targets. In this work, we used rigorous computational methods, including molecular docking, fast pulling of ligand (FPL), and free energy perturbation (FEP), to investigate potential inhibitors of SARS-CoV-2 Mpro. We first tested our approach with three reported inhibitors of SARS-CoV-2 Mpro; and our computational results are in good agreement with the respective experimental data. Subsequently, we applied our approach on a databases of ~4600 natural compounds found in Vietnamese plants, as well as 8 available HIV-1 protease (PR) inhibitors and an aza-peptide epoxide. Molecular docking resulted in a short list of 35 natural compounds, which was subsequently refined using the FPL scheme. FPL simulations resulted in five potential inhibitors, including 3 natural compounds and two available HIV-1 PR inhibitors. Finally, FEP, the most accurate and precise method, was used to determine the absolute binding free energy of these five compounds. FEP results indicate that two natural compounds, <i>cannabisin </i>A and <i>isoacteoside</i>, and an HIV-1 PR inhibitor, <i>darunavir</i>, exhibit large binding free energy to SARS-CoV-2 Mpro, which is larger than that of <b>13b</b>, the most reliable SARS-CoV-2 Mpro inhibitor recently reported. The binding free energy largely arises from van der Waals (vdW) interaction. We also found that Glu166 form H-bonds to all the inhibitors. Replacing Glu166 by an alanine residue leads to ~ 2.0 kcal/mol decreases in the affinity of <i>darunavir </i>to SARS-CoV-2 Mpro. Our results could contribute to the development of potentials drugs inhibiting SARS-CoV-2. </p>

scholarly journals Computational Determination of Potential Inhibitors of SARS-CoV-2 Main Protease

2020 ◽  
Author(s):  
Son Tung Ngo ◽  
Ngoc Quynh Anh Pham ◽  
Ly Le ◽  
Duc-Hung Pham ◽  
Van Vu
Keyword(s):  
Free Energy ◽  
Molecular Docking ◽  
Drug Targets ◽  
Binding Free Energy ◽  
Natural Compounds ◽  
Main Protease ◽  
Energy Perturbation ◽  
Novel Coronavirus ◽  
Potential Inhibitors ◽  
Hiv 1

<p>The novel coronavirus (SARS-CoV-2) has infected over 850,000 people and caused more than 42000 deaths worldwide as of April 1<sup>st</sup>, 2020. As the disease is spreading rapidly all over the world, it is urgent to find effective drugs to treat the virus. The main protease (Mpro) of SARS-CoV-2 is one of the potential drug targets. In this work, we used rigorous computational methods, including molecular docking, fast pulling of ligand (FPL), and free energy perturbation (FEP), to investigate potential inhibitors of SARS-CoV-2 Mpro. We first tested our approach with three reported inhibitors of SARS-CoV-2 Mpro; and our computational results are in good agreement with the respective experimental data. Subsequently, we applied our approach on a databases of ~4600 natural compounds found in Vietnamese plants, as well as 8 available HIV-1 protease (PR) inhibitors and an aza-peptide epoxide. Molecular docking resulted in a short list of 35 natural compounds, which was subsequently refined using the FPL scheme. FPL simulations resulted in five potential inhibitors, including 3 natural compounds and two available HIV-1 PR inhibitors. Finally, FEP, the most accurate and precise method, was used to determine the absolute binding free energy of these five compounds. FEP results indicate that two natural compounds, <i>cannabisin </i>A and <i>isoacteoside</i>, and an HIV-1 PR inhibitor, <i>darunavir</i>, exhibit large binding free energy to SARS-CoV-2 Mpro, which is larger than that of <b>13b</b>, the most reliable SARS-CoV-2 Mpro inhibitor recently reported. The binding free energy largely arises from van der Waals (vdW) interaction. We also found that Glu166 form H-bonds to all the inhibitors. Replacing Glu166 by an alanine residue leads to ~ 2.0 kcal/mol decreases in the affinity of <i>darunavir </i>to SARS-CoV-2 Mpro. Our results could contribute to the development of potentials drugs inhibiting SARS-CoV-2. </p>

Molecular Mechanism of The Effect of Huanglian Jiedu Decoction On Ulcerative Colitis Based On Network Pharmacology And Molecular Docking

2021 ◽  
Author(s):  
Jing Yang ◽  
Chao-Tao Tang ◽  
Ruiri Jin ◽  
Bixia Liu ◽  
Peng Wang ◽  
...  
Keyword(s):  
Ulcerative Colitis ◽  
Molecular Docking ◽  
Molecular Mechanism ◽  
Target Genes ◽  
Signal Pathway ◽  
Intestinal Barrier Function ◽  
Network Pharmacology ◽  
Bioactive Components ◽  
Ppi Network ◽  
Active Components

Abstract Huanglian jiedu decoction (HLJDD) is a heat-clearing and detoxifying agent composed of four kinds of Chinese herbal medicine. Previous studies have shown that HLJDD can improve the inflammatory response of ulcerative colitis (UC) and maintain intestinal barrier function. However, its molecular mechanism is not completely clear. In this study, we verified the bioactive components (BCI) and potential targets of HLJDD in the treatment of UC by means of network pharmacology and molecular docking, and constructed the pharmacological network and PPI network. Then the core genes were enriched by GO and KEGG. Finally, the bioactive components were docked with the key targets to verify the binding ability between them. A total of 54 active components related to UC were identified. Ten genes are considered to be very important to PPI network. Functional analysis showed that these target genes were mainly involved in the regulation of cell response to different stimuli, IL-17 signal pathway and TNF signal pathway. The results of molecular docking showed that the active components of HLJDD had good affinity with Hub gene. This study systematically elucidates the "multi-component, multi-target, multi-pathway" mechanism of anti-UC with HLJDD for the first time, suggesting that HLJDD or its active components may be candidate drugs for the treatment of ulcerative colitis.

Current Trends in Docking Methodologies

Oncology ◽  
2017 ◽  
pp. 829-847
Author(s):  
Shubhandra Tripathi ◽  
Akhil Kumar ◽  
Amandeep Kaur Kahlon ◽  
Ashok Sharma
Keyword(s):  
Free Energy ◽  
Molecular Docking ◽  
Binding Affinity ◽  
Binding Free Energy ◽  
Energy Calculation ◽  
Molecular Binding ◽  
New Horizons ◽  
Current Trends ◽  
Complex Scheme ◽  
Dynamics Simulations

Molecular docking was earlier considered to predict the binding affinity of the receptor and ligand molecules. With the progress in computational power and developing approaches, new horizons are now opening for accurate prediction of molecular binding affinity. In the current book chapter, recent strategies for Computer-Aided Drug Designing (CADD) including virtual screening and molecular docking, encompassing molecular dynamics simulations, and binding free energy calculation methods are discussed. Brief overview of different binding free energy methods MMPBSA, MMGBSA, LIE and TI have also been given along with the recent Relaxed Complex Scheme protocol.

scholarly journals Molecular mechanism and binding free energy of doxorubicin intercalation in DNA

2019 ◽  
Vol 21 (7) ◽  
pp. 3877-3893 ◽  
Author(s):  
Bahaa Jawad ◽  
Lokendra Poudel ◽  
Rudolf Podgornik ◽  
Nicole F. Steinmetz ◽  
Wai-Yim Ching
Keyword(s):  
Free Energy ◽  
Molecular Mechanism ◽  
Binding Free Energy ◽  
Md Simulations ◽  
Intercalation Process

The intercalation process of binding doxorubicin (DOX) in DNA is studied by extensive MD simulations.

Molecular docking study and development of an empirical binding free energy model for phosphodiesterase 4 inhibitors

2006 ◽  
Vol 14 (17) ◽  
pp. 6001-6011 ◽  
Author(s):  
Fernanda G. Oliveira ◽  
Carlos M.R. Sant’Anna ◽  
Ernesto R. Caffarena ◽  
Laurent E. Dardenne ◽  
Eliezer J. Barreiro
Keyword(s):  
Free Energy ◽  
Molecular Docking ◽  
Binding Free Energy ◽  
Docking Study ◽  
Energy Model ◽  
Molecular Docking Study ◽  
Phosphodiesterase 4 ◽  
Phosphodiesterase 4 Inhibitors ◽  
Free Energy Model
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