Hepatoselüler Karsinomda Temel Bir Hedef Olarak AURKA'nın Belirlenmesi: Bütünleşik Biyoinformatik Analiz ve Moleküler Kenetlenme ile Doğal Bileşiklerin Değerlendirilmesi

Abstract

Amaç: Bu çalışmada, biyoinformatik yöntemler kullanılarak hepatoselüler karsinom (HCC) ile ilişkili merkezi bir moleküler hedefin belirlenmesi ve bu hedefe karşı referans inhibitörler ile doğal bileşiklerin bağlanma potansiyellerinin moleküler kenetlenme yöntemiyle karşılaştırmalı olarak değerlendirilmesi amaçlanmıştır.

Gereç ve Yöntemler: GSE76427 mikrodizi veri setinde (Illumina HumanHT-12 V4.0), 115 HCC tümör dokusu ile 52 tümör dışı karaciğer dokusu karşılaştırılmış ve diferansiyel eksprese genler limma paketi kullanılarak belirlenmiştir (düzeltilmiş p < 0,05 ve |log2 kat değişimi| ≥ 1). Yukarı regüle genlerden STRING veritabanı kullanılarak bir protein-protein etkileşim (PPI) ağı oluşturulmuş, düğümler derece (degree) değerlerine göre sıralanmış ve ekspresyon tutarlılığı, biyolojik önemi, yapısal veri kalitesi ve ilaçlanabilirlik özellikleri dikkate alınarak moleküler kenetlenme hedefi olarak Aurora kinaz A (AURKA) seçilmiştir. İki referans inhibitör (Sorafenib ve Alisertib) ile altı doğal bileşik (Kurkumin, Kuersetin, Luteolin, Kaempferol, Apigenin ve Resveratrol), AURKA'nın 4JBQ kristal yapısına aynı grid kutusu ve aynı parametreler kullanılarak AutoDock Vina yazılımı ile kenetlenmiştir.

Bulgular: Toplam 362 prob diferansiyel olarak eksprese bulunmuştur (95 yukarı regüle, 267 aşağı regüle). Aşağı regüle genlerin karaciğere özgü metabolik ve detoksifikasyon fonksiyonlarıyla, yukarı regüle genlerin ise hücre döngüsü ve mitoz süreçleriyle ilişkili olduğu belirlenmiştir. STRING ağı 69 düğüm ve 422 kenardan oluşmuş olup (PPI zenginleşme p < 1,0 × 10⁻¹⁶), en merkezi düğümlerin büyük çoğunluğunu mitotik düzenleyiciler oluşturmuştur. Bu düğümler arasında AURKB (derece = 33) ve AURKA (derece = 32) sırasıyla birinci ve ikinci sırada yer almıştır. Moleküler kenetlenme analizinde en yüksek bağlanma afiniteleri Sorafenib (−9,537 kcal/mol) ve Alisertib (−9,066 kcal/mol) için elde edilirken, doğal bileşikler arasında Kurkumin (−8,414 kcal/mol) referans inhibitörlere en yakın bağlanma enerjisini göstermiştir. Etkileşim analizinde Sorafenib'in üre köprüsü aracılığıyla Ala273 ile hidrojen bağı, katalitik Lys162 ile π-katyon etkileşimi ve Glu181 ile halojen bağı oluşturduğu; ayrıca Asp274 içeren DFG bölgesine uzanan ATP-kompetitif bir bağlanma modeli sergilediği belirlenmiştir.

Sonuç: Transkriptomik analiz, ağ biyolojisi ve moleküler kenetlenmeyi birleştiren bu bütünleşik yaklaşım, AURKA'nın HCC ile ilişkili merkezi bir hedef gen olduğunu ortaya koymakta ve özellikle kurkumin başta olmak üzere doğal polifenollerin AURKA'ya karşı umut verici bağlanma adayları olabileceğini göstermektedir. Elde edilen bulgular, gelecekte gerçekleştirilecek deneysel doğrulama çalışmaları için test edilebilir hipotezler sunmaktadır.

Keywords

• Hepatoselüler karsinom
• diferansiyel eksprese genler
• protein-protein etkileşim ağı
• Aurora kinaz A (AURKA)
• moleküler kenetlenme.

Identification of AURKA as a Key Target in Hepatocellular Carcinoma: Integrated Bioinformatics Analysis and Evaluation of Natural Compounds via Molecular Docking

Abstract

Objective: This study aimed to identify a central molecular target associated with hepatocellular carcinoma (HCC) using bioinformatic methods and to comparatively evaluate the binding potential of reference inhibitors and natural compounds against this target by molecular docking.

Materials and Methods: In the GSE76427 microarray dataset (Illumina HumanHT-12 V4.0), 115 HCC tumor tissues were compared with 52 non-tumor liver tissues, and differentially expressed probes were determined with the limma package (adjusted p < 0.05 and |log2 fold change| ≥ 1). A STRING protein–protein interaction (PPI) network was constructed from the up-regulated genes, nodes were ranked by degree, and Aurora kinase A (AURKA) was selected as the docking target based on expression robustness, biological relevance, structural data quality, and druggability. Two reference inhibitors (Sorafenib and Alisertib) and six natural compounds (Curcumin, Quercetin, Luteolin, Kaempferol, Apigenin, Resveratrol) were docked into the 4JBQ crystal structure of AURKA using AutoDock Vina with a shared grid box and identical parameters.

Results: A total of 362 probes were differentially expressed (95 up-regulated, 267 down-regulated); down-regulated genes were associated with liver-specific metabolic and detoxification functions, whereas up-regulated genes were related to cell cycle and mitosis. The STRING network comprised 69 nodes and 422 edges (PPI enrichment p < 1.0 × 10⁻¹⁶), and nearly all of the most central nodes were mitotic regulators, with AURKB (degree = 33) and AURKA (degree = 32) ranking first and second. In docking, the highest affinities were obtained for Sorafenib (−9.537 kcal/mol) and Alisertib (−9.066 kcal/mol); among the natural compounds, Curcumin (−8.414 kcal/mol) yielded an energy close to that of the reference inhibitors. Interaction analysis showed that sorafenib formed a hydrogen bond with Ala273 through its urea bridge, a π-cation interaction with the catalytic Lys162, and a halogen bond with Glu181, exhibiting an ATP-competitive binding mode that extended toward the DFG region (Asp274).

Conclusion: This integrated approach combining transcriptomic analysis, network biology, and molecular docking highlights AURKA as a central HCC-associated hub gene and computationally prioritizes natural polyphenols, particularly curcumin, as potential AURKA-binding candidates. These docking-based predictions are hypothesis-generating and require experimental validation before any conclusions regarding biological or therapeutic efficacy can be drawn.

Keywords

• Hepatocellular carcinoma
• differentially expressed genes
• protein–protein interaction network
• Aurora kinase A (AURKA)
• molecular docking.

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