Analisis In Silico Molecular Docking Senyawa Daun Sirih (Piper betle L.) Terhadap Enzim Lipase Cutibacterium Acnes Sebagai Kandidat Anti-Acne Vulgaris
A Acne (acne vulgaris) is an inflammatory skin disease influenced by the lipase activity of Cutibacterium acnes, which produces inflammation-triggering free fatty acids. This study aimed to analyze the potential of bioactive compounds from betel leaves (Piper betle L.), namely hydroxychavicol, chavicol, eugenol, and carvacrol, as candidate inhibitors of the Cutibacterium acnes lipase enzyme using an in silico molecular docking approach. The study was conducted through drug-likeness, skin permeation, and PAINS/BRENK alert analyses using SwissADME, toxicity prediction using ProTox 3.0, validation of the docking method against the target proteins with PDB IDs 6KHM and 6KHK, and molecular docking simulations using AutoDock Vina. The docking validation results showed that PDB ID 6KHM produced an RMSD value of 1.9255 , which met the validation criterion, while PDB ID 6KHK produced an RMSD value above 2 and therefore did not meet the validation criterion. Therefore, molecular docking of the test compounds was performed using the PDB ID 6KHM protein. The results showed that all compounds met the prediction criteria and were classified as toxicity class 4. Carvacrol exhibited the most negative binding affinity of −6.124 kcal/mol and a binding inhibition constant () of 32.4 µM. It also had a predicted skin permeation value of 4.74 cm/s, with no PAINS alerts and one Brenk alert. Based on these results, carvacrol has potential as a candidate inhibitor of the Cutibacterium acnes lipase enzyme and as a natural-based anti-acne vulgaris agent.
Authors
- Jesi Pebralia (ORCID: https://orcid.org/0000-0002-2777-8416)
- Yoza Fendriani (ORCID: https://orcid.org/0000-0002-4440-5355)
- Livia Nur Risky
- Feliska Ratmalia
- Alrizal
- Reyhan Zumiandri
- Ropina
Institutions
- Universitas Jambi (ID)
Publication Details
- Journal
- Newton-Maxwell Journal of Physics
- Published
- 2026-10-30
- DOI
- https://doi.org/10.33369/nmj.v7i2.51450
- Primary Topic
- Computational Drug Discovery Methods
- Type
- article
- Field-Weighted Citation Impact
- 0.00