Network Pharmacology and Molecular Docking Analysis on Pharmacological Mechanisms of Astragalus membranaceus in the Treatment of Gastric Ulcer

Abstract

Background. Astragalus membranaceus (AM, family: Leguminosae) exerts significant therapeutic effect on gastric ulcer (GU); however, there are scarce studies on its molecular mechanism against GU. This study aims to explore the key ingredients, key targets, and potential mechanisms of AM in the treatment of GU by utilizing network pharmacology and molecular docking. Methods. Several public databases were used to predict the targets of AM and GU, respectively, and the drug and disease targets were intersected to obtain the common targets. Next, the key ingredients and key targets were identified by constructing ingredient-target network and protein-protein-interaction (PPI) network. Gene Ontology biological processes (GOBP) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were carried out on the common targets in order to ascertain the biological processes and signaling pathways involved. Finally, molecular docking was conducted to verify the binding affinity between the key ingredients and key targets. Results. A total of 552 predicted targets were obtained from 23 screened active ingredients, of which 203 targets were the common targets with GU. Quercetin, kaempferol, and isorhamnetin were identified as the key ingredients by constructing ingredient-target network, and TP53, AKT1, VEGFA, IL6, TNF, CASP3, and EGFR were selected as the key targets by constructing PPI network. GOBP and KEGG pathway enrichment analysis suggested that the therapeutic effect of AM on GU involved multiple biological processes and signaling pathways related to inflammation, oxidative stress, apoptosis, cell proliferation, and angiogenesis. Molecular docking validation demonstrated that all key ingredients had good binding affinity with the key targets. Conclusion. This study revealed the key ingredients, key targets, and potential mechanisms of AM against GU, and these data may provide some crucial references for subsequent research and development of drugs for treating GU.

Analysis of the Mechanism of GuizhiFuling Wan in Treating Adenomyosis Based on Network Pharmacology Combined with Molecular Docking and Experimental Verification

“…The smaller the binding energy, the more stable the binding of ligands and receptors. When the binding energy is less than −5.0 kcal/mol, the ligands and receptors are considered to have a better binding capacity [ 30 ].…”

Molecular Mechanisms of Network Pharmacology-Based Immunomodulation of Huangqi (Astragali Radix)

“…diperoleh dari basis data TCMSP dengan menggunakan kata kunci "Huangqi". Komponen yang memiliki oral bioavailability (OB) ≥30% dan drug-likeness (DL) ≥0,18 dipilih sebagai komponen bioaktif (16)(17)(18) .…”

“…Pengumpulan protein target terbatas pada Homo sapiens (manusia) dan Tanimoto Coefficient (TC) ≥0,5 (20) . Protein target yang dikumpulkan dari kedua basis data digabungkan dan dihapus apabila ada duplikat (16,17) . Kemudian nama protein target distandarisasi sesuai basis data Uniprot.…”

“…Pengumpulan dan Penapisan Protein Target Terkait Imunomodulasi. Protein target yang terkait dengan aktivitas imunomodulasi diperoleh dengan memasukkan kata kunci "immunomodulation", "immunostimulation", dan "immune system" pada basis data OMIM, GeneCards, dan NCBI Gene (16,21) . Hasil yang diperoleh dari GeneCards dibatasi pada target yang memiliki nilai relevansi ≥10,00 (17) .…”

“…Organisme Homo sapiens (manusia) dan medium confidence 0,4 ditetapkan sebagai limitasi (18) . PPI network dari basis data STRING diunduh dalam format tab-separated value (TSV) dan divisualisasikan ke dalam Cytoscape v3.9.1 (16,17) . Kedua PPI network digabungkan (merge) dalam Cytoscape untuk diperoleh irisannya (intersection).…”