Work

Integrating Network Pharmacology and In Silico Analysis to Explore the Bioactive Compounds Against Gastric Cancer Treatment

Year: 2024

Type: article

Abstract: Gastric cancer (GC) has become a major challenge in oncology research, primarily due to its detection at advanced stages. In this study, we identified and validated the pharmacological mechanisms involved in treating gastric cancer using an integrated approach combining network pharmacology, molecular docking, and a dynamic approach. Gastric cancer-related genes were obtained from DisGeNET, Genecard, and Malacard databases, while potential targets of bioactive compounds were predicted using SwissTargetPrediction. Network pharmacology and gene ontology (GO) enrichment analyses were employed to understand the molecular mechanisms of action. This should further be investigated to isolate bioactive compounds that can be used to treat different ailments. Albumin (ALB), B-cell lymphoma 2 (BCL-2), nuclear factor kappa B subunit 1 (NFKB1), hypoxia-inducible factor 1 alpha (HIF1A), and interleukin 6 (IL-6) had a higher expression in gastric cancer than in normal conditions. Top genes were validated by using the GEPIA (Gene Expression Profiling Interactive Analysis) database. Furthermore, the lead compounds dehydroxy-isocalamendiol and spathulenol exhibited the highest binding affinity with NFKB1 and HIF1A (-6.3 and -6 kJ/mol) in the molecular docking study. Enrichment analysis indicated enrichment of these hub targets in the programmed cell death-ligand 1 (PD-L1) checkpoint, phosphatidylinositol 3-kinases/protein kinase B (PI3K-Akt), Ras, and hypoxia-inducible factor-1 (HIF-1) signalling pathways with significant cut-offs of FDR < 0.01 and p < 0.05. Therefore, network pharmacology and molecular docking analyses revealed that dehydroxy-isocalamendiol and spathulenol exert therapeutic efﬁcacy on gastric cancer by multiple targets, NFKB1 and HIF1A, and pathways (MAPK, PD-L1 checkpoint, PI3K-Akt, Ras, and HIF-1 pathways).

Source: Cureus

DOI: 10.7759/cureus.75779

Authors: Smruti P Pradhan, Ayushman Gadnayak, Sukanta Kumar Pradhan, Venkatarao Epari

Institutions: Odisha University of Agriculture and Technology, Siksha O Anusandhan University, Institute of Medical Sciences and Sum Hospital

Language: English

Topic: Computational Drug Discovery Methods

Subfield: Computational Theory and Mathematics

Field: Computer Science

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: diamond

OpenAlex ID: W4405418153