Evaluation of the Anticancer Potential of Lippia citriodora L. (Lemon Verbena) Using In Silico Methods

Öz

Objective: Lung cancer is among the most frequently diagnosed and most lethal malignancies worldwide. The cytotoxic effects of current therapies on healthy tissues have increased interest in plant-derived alternatives. This study evaluated the drug candidate potential of the major phytochemicals of Lippia citriodora L. (lemon verbena) in silico. Materials and Methods: The structures of the six compounds reported at the highest proportions in the essential oil (spathulenol, citral, geraniol, limonene, ar-curcumene, neral) were retrieved from PubChem; pharmacokinetic, drug-likeness and toxicity parameters were predicted with SwissADME, ADMETlab 3.0 and ProTox 3.0. Limonene and citral, selected from the ADMET profiles, were docked against TP53 (PDB ID: 8SWJ) and Caspase-3 (PDB ID: 6X8I) with AutoDock Vina via SwissDock; interactions were analysed with BIOVIA Discovery Studio Visualizer. Results: Spathulenol, citral, geraniol and neral fully complied with Lipinski's Rule of Five, whereas ar-curcumene violated it with a logP of 5.693. Limonene complied but displayed an excessively lipophilic profile owing to its lack of heteroatoms. The highest binding affinity was obtained for limonene–TP53 (−6.108 kcal/mol), followed by limonene–Caspase-3 (−5.026), citral–TP53 (−4.990) and citral–Caspase-3 (−4.010 kcal/mol). Limonene bound through Pi-sigma and Pi-alkyl interactions, whereas citral formed an additional hydrogen bond with TP53. Conclusion: Citral, geraniol and neral showed the most favourable ADMET profiles, while limonene bound most strongly to both targets. The findings are computational predictions and require validation by in vitro and in vivo studies.

Anahtar Kelimeler

• Lippia citriodora
• lung cancer
• molecular docking
• ADMET
• limonene
• TP53

Destekleyen Kurum

The authors did not receive any financial support for this study

Etik Beyan

This study was carried out entirely with in silico methods, using molecular and structural data obtained from public databases. It does not require ethics committee approval as it does not involve any experimental application on human or animal subjects.

Lippia citriodora L. (Limon Otu) Bitkisinin Antikanser Potansiyelinin In Silico Yöntemlerle Değerlendirilmesi

Öz

Amaç: Akciğer kanseri dünya genelinde en sık teşhis edilen ve mortalitesi en yüksek kanser türlerinden biridir. Mevcut tedavilerin sağlıklı dokular üzerindeki sitotoksik etkileri, bitkisel kökenli alternatif ajanlara ilgiyi artırmıştır. Bu çalışmada Lippia citriodora L. (limon otu) bitkisinin başlıca fitokimyasallarının ilaç adayı olma potansiyeli in silico olarak değerlendirilmiştir. Gereç ve Yöntem: Bitkinin uçucu yağında en yüksek oranda bildirilen altı bileşiğin (spatulenol, sitral, geraniol, limonen, ar-kurkumen, neral) yapıları PubChem'den alınmış; farmakokinetik, ilaç benzerliği ve toksisite parametreleri SwissADME, ADMETlab 3.0 ve ProTox 3.0 ile tahmin edilmiştir. ADMET profillerine göre seçilen limonen ve sitral, TP53 (PDB ID: 8SWJ) ve Kaspaz-3 (PDB ID: 6X8I) proteinlerine karşı SwissDock üzerinden AutoDock Vina ile kenetlenmiş; etkileşimler BIOVIA Discovery Studio Visualizer ile analiz edilmiştir. Bulgular: Spatulenol, sitral, geraniol ve neral Lipinski'nin beşli kuralına tam uyum göstermiş; ar-kurkumen logP değeriyle (5.693) kuralı ihlal etmiştir. Limonen kurala uymakla birlikte heteroatom içermemesi nedeniyle aşırı lipofilik bir profil sergilemiştir. En yüksek bağlanma afinitesi limonen–TP53 kompleksinde (−6.108 kcal/mol) elde edilmiş; bunu limonen–Kaspaz-3 (−5.026), sitral–TP53 (−4.990) ve sitral–Kaspaz-3 (−4.010 kcal/mol) izlemiştir. Limonenin bağlanması Pi-sigma ve Pi-alkil etkileşimleriyle sağlanırken sitral TP53 ile ilave bir hidrojen bağı kurmuştur. Sonuç: Sitral, geraniol ve neral en uygun ADMET profillerini sergilerken limonen her iki hedefe de en güçlü bağlanmayı göstermiştir. Bulgular hesaplamalı öngörüler olup in vitro ve in vivo çalışmalarla doğrulanmalıdır.

Anahtar Kelimeler

• : Lippia citriodora
• akciğer kanseri
• moleküler kenetlenme
• ADMET
• limonen
• TP53

Destekleyen Kurum

Yazarlar bu çalışma için herhangi bir finansal destek almamıştır.

Etik Beyan

Bu çalışma tümüyle in silico yöntemlerle, kamuya açık veri tabanlarından elde edilen moleküler ve yapısal veriler kullanılarak yürütülmüştür. İnsan veya hayvan denekleri üzerinde herhangi bir deneysel uygulama içermediğinden etik kurul onayı gerektirmemektedir.

Kaynakça

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