Skripsi

Penambatan Molekuler Potensi Senyawa Bioaktif Daun Afrika (Vernonia amygdalina) Sebagai Kandidat Agonis PPARγ Antidiabetes Secara In Silico = Molecular Docking Study of the Bioactive Compounds of Vernonia amygdalina Leaves as Potential PPARγ Agonists for Antidiabetic Activity Using an In Silico Approach.

Latar Belakang Diabetes melitus tipe 2 ditandai oleh resistensi insulin dan gangguan fungsi sel β. Aktivasi reseptor PPARγ berperan penting dalam meningkatkan sensitivitas insulin. Vernonia amygdalina mengandung senyawa bioaktif berpotensi antidiabetes, namun interaksi molekulernya dengan PPARγ belum banyak diteliti. Penelitian ini bertujuan mengevaluasi potensi penambatan senyawa bioaktif Vernonia amygdalina terhadap reseptor PPARγ secara in silico sebagai kandidat antidiabetes alami. Metode Penelitian ini dilakukan secara in silico menggunakan perangkat lunak Molegro Virtual Docker (MVD). Protein PPARγ dengan kode PDB 2PRG digunakan sebagai reseptor, sedangkan empat senyawa aktif dari Vernonia amygdalina diunduh dari basis data PubChem. Proses validasi dilakukan melalui metode redocking dengan nilai RMSD kurang dari 2 Å. Analisis mencakup penilaian Rerank Score serta evaluasi profil farmakokinetik dan toksisitas menggunakan pkCSM. Hasil Hasil docking menunjukkan bahwa hydroxyvernolide dan vernodalol memiliki afinitas pengikatan paling kuat terhadap PPARγ berdasarkan nilai ReRank Score, dengan dukungan ikatan hidrogen yang stabil. Luteolin dan vernonioside E menunjukkan afinitas lebih lemah. Analisis ADMEToks mengindikasikan bahwa hydroxyvernolide dan luteolin memiliki profil farmakokinetik yang baik serta risiko toksisitas yang rendah, sedangkan vernodalol berpotensi mutagenik dan vernonioside E terbatas oleh kelarutan rendah dan risiko interaksi metabolisme. Kesimpulan Secara keseluruhan, hydroxyvernolide dan luteolin merupakan kandidat paling potensial sebagai agonis alami PPARγ dari Vernonia amygdalina. Hasil ini mendukung potensi pengembangan senyawa bioaktif tanaman ini sebagai alternatif terapi antidiabetes, meskipun diperlukan validasi lebih lanjut melalui studi in vitro dan in vivo.
Kata Kunci: ADMEToks, Diabetes melitus tipe 2, In silico, Molecular docking, PPARγ, Vernonia amygdalina


Background Type 2 diabetes mellitus is characterized by insulin resistance and β-cell dysfunction. Activation of the PPARγ receptor plays a crucial role in improving insulin sensitivity. Vernonia amygdalina contains bioactive compounds with potential antidiabetic activity; however, their molecular interactions with PPARγ have not been extensively studied. This study aims to evaluate the molecular docking potential of Vernonia amygdalina bioactive compounds against the PPARγ receptor in silico as natural antidiabetic candidates. Methods This study was conducted in silico using the Molegro Virtual Docker (MVD) software. The PPARγ protein with PDB ID 2PRG was used as the receptor, while four active compounds from Vernonia amygdalina were retrieved from the PubChem database. Validation was performed through a redocking method with an RMSD value of less than 2 Å. The analysis included assessment of the Rerank Score and evaluation of pharmacokinetic and toxicity profiles using pkCSM. Results Docking results showed that hydroxyvernolide and vernodalol exhibited the strongest binding affinity to PPARγ based on ReRank Score, supported by stable hydrogen bonding. Luteolin and vernonioside E displayed weaker affinities. ADMETox analysis indicated that hydroxyvernolide and luteolin possessed favorable pharmacokinetic profiles and low toxicity risks, whereas vernodalol showed potential mutagenicity and vernonioside E was limited by poor solubility and metabolic interaction risks. Conclusion Overall, hydroxyvernolide and luteolin emerged as the most promising natural PPARγ agonist candidates from Vernonia amygdalina. These findings support the potential development of the plant’s bioactive compounds as alternative antidiabetic therapies, although further validation through in vitro and in vivo studies is required.
Keywords: ADMETox, Type 2 diabetes mellitus, In silico, Molecular docking, PPARγ, Vernonia amygdalina