Text

PENDEKATAN NETWORK PHARMACOLOGY DAN MOLECULAR DOCKING DALAM MEMPREDIKSI POTENSI ANTIINFLAMASI EKSTRAK DAUN KARI (Murraya koenigii.)

---

Penilaian

---

Inflammation is a complex biological response resulting from tissue injury, infection, or physical and chemical stimulation that triggers immune cell activation and the release of pro-inflammatory mediators. The use of synthetic anti-inflammatory drugs carries a risk of long-term side effects, so the exploration of natural ingredients with anti-inflammatory potential is an important alternative. Curry leaves (Murraya koenigii) are known to contain a variety of bioactive compounds that have the potential to be natural anti-inflammatory agents. This study aims to identify active compounds and predict the molecular mechanism of curry leaves in anti-inflammatory activity through network pharmacology and molecular docking approaches. The Swiss Target Prediction and GeneCards databases are used to predict targets related to curry leaves and anti-inflammatory. STRING, STITCH and cytoscape used to build a network of disease-target compounds and PPI tissues. Molecular docking is carried out using Autodock Vina to predict the binding of active components to the main action target. The results of Network pharmacology revealed 6 compounds and 17 target proteins with viridiflorol, caryophyllene, humulene, glutamic acid, naphthalene and palmitic acid as potential compounds in anti-inflammatory. The most important protein targets in the anti-inflammatory process include AKT1, PTGS2 and EGFR. The results of molecular docking of compounds and potential targets showed a strong interaction between palmitic acid and PTGS2, with a binding affinity value of -6.823 kcal/mol as well as carryophyllene and EGFR compounds that had the same amino acid residues and similar activities to the comparator compound, indomethacin

---

Availability

Inventory Code	Barcode	Call Number	Location	Status
2507003074	T173918	T1739182025	Central Library (Reference)	Available but not for loan - Not for Loan

Detail Information

Series Title

-

Call Number

T1739182025

Publisher

: Prodi Ilmu Farmasi, Fakultas Matematika dan Ilmu Pengetahuan Alam Universitas Sriwijaya., 2025

Collation

xii, 75 hlm.; ill.; tab.; 29 cm.

Language

Indonesia

ISBN/ISSN

-

Classification

615.407

Content Type

-

Media Type

-

Carrier Type

-

Edition

-

Subject(s)

Farmasi

Specific Detail Info

-

Statement of Responsibility

EM

Other version/related

File Attachment

Comments

---

You must be logged in to post a comment