Kajian In-Silico: Aktivitas Antiinflamasi Daun Ungu (Graptophyllum pictum L. Griff) dengan Metode Networking Pharmacology dan Molecular Docking Menggunakan Data dari Instrumen LC-HRMS

Abstract

Background: Inflammation is a vascular tissue response to harmful stimuli, such as the presence of pathogens, cellular damage, or irritants. Common symptoms of inflammation include redness, swelling, pain, increased temperature, and impaired tissue function. Inflammation is generally classified into two types: acute and chronic. The medications used to treat inflammation are known as anti-inflammatory drugs, which are divided into two main categories: steroidal and non-steroidal. Although these drugs are effective, they can also cause side effects such as dyspepsia, hypertension, myocardial infarction, nephrotic syndrome, and others. Objective: The aim of this study is to explore the potential anti-inflammatory effects of phenolic compounds from purple leaf (Graptophyllum pictum (L.) Griff.) using in silico methods through network pharmacology and molecular docking. Methods: The method used in this study is a descriptive in silico approach to investigate the anti-inflammatory effects of Graptophyllum pictum (L.) Griff. using network pharmacology and molecular docking. The procedures conducted include Lipinski’s Rule of Five screening, Pre-ADMET testing, identification of protein targets from phenolic bioactive compounds, identification of inflammation-related protein targets, protein network construction, identification and analysis of key targets, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, molecular docking including receptor preparation, ligand preparation, docking method validation, ligand-receptor docking, as well as interaction analysis and visualization between receptors and ligands. Results: This study identified five key target proteins, namely FCGR3B (Fc Gamma Receptor IIIb), IL10 (Interleukin 10), IL1B (Interleukin-1 beta), CD8A (Cluster of Differentiation 8a), and CXCR4 (C-X-C chemokine receptor type 4). Docking results revealed that among the four major compounds, ferulic acid exhibited the strongest binding affinity to the CXCR4 target protein with a Gibbs free energy of -6.0 kcal/mol, followed by p-coumaric acid binding to FCGR3B and CXCR4 (-4.9 kcal/mol), cinnamic acid to CXCR4 (-5.2 kcal/mol), while anacardic acid showed the weakest affinity across all targets, ranging from -3.1 to -4.3 kcal/mol. The affinity ranking from highest to lowest was: ferulic acid > cinnamic acid > p-coumaric acid > anacardic acid. GO enrichment analysis revealed 30 GO entries consisting of 10 biological processes, 10 cellular components, and 10 molecular functions. Additionally, 10 KEGG signaling pathways were identified, including key pathways involved in inflammatory responses. These results suggest that Graptophyllum pictum has potential as an herbal therapeutic agent for inflammation treatment by modulating multiple molecular signaling pathways. Conclusion: Based on the results of the study, the ethanol extract of Graptophyllum pictum (purple leaf) demonstrates potential as a natural anti-inflammatory agent. This is supported by molecular docking results showing that its phytochemical compounds can interact effectively through hydrogen bonding and hydrophobic interactions with key proteins involved in inflammatory and immune pathways, such as IL10 and IL1B. These interactions suggest that the compounds may act as biological inhibitors of inflammatory processes. Therefore, Graptophyllum pictum holds promising potential for further development as an anti-inflammatory therapeutic agent, although additional in vitro and in vivo studies, as well as pharmacodynamic and toxicity analyses, are necessary to confirm its efficacy and safety.

Keywords: Purple Leaf, Graptophyllum pictum (L.) Griff, Inflammation, Network pharmacology, Molecular docking.