Electronic Theses and Dissertation

ABSTRAK

Depresi merupakan gangguan kesehatan jiwa global yang pengobatannya masih menghadapi keterbatasan, ditandai sekitar 20-24% pasien tidak responsif terhadap antidepresan sintetik konvensional. Penelitian ini bertujuan mengidentifikasi senyawa bioaktif Bergamot Essential Oil (BEO, Citrus bergamia) yang berpotensi sebagai kandidat antidepressant-like melalui pendekatan in silico terintegrasi. Sebanyak 21 senyawa hasil identifikasi GC-MS disaring berdasarkan kriteria fisikokimia dan farmakokinetik CNS (ADMET), menghasilkan 14 senyawa kandidat yang selanjutnya dianalisis melalui network pharmacology terhadap 31 target umum (common targets) hasil irisan basis data senyawa aktif dan gen terkait depresi, memunculkan 10 senyawa aktif yang berinteraksi dengan empat target utama, yaitu DRD2, SLC6A3, MAO-A, dan MAO-B. Molecular docking menggunakan AutoDock menunjukkan BEOC09 (neryl acetate) memiliki afinitas pengikatan tertinggi di antara senyawa BEO yang diuji terhadap MAO-A (-6,63 kcal/mol) dan MAO-B (-6,09 kcal/mol), sedangkan BEOC13 (2-methyl-5-prop-1-en-2-ylcyclohexan-1-ol) merupakan satu-satunya senyawa yang memenuhi ambang batas afinitas terhadap DRD2 (-5,70 kcal/mol); interaksi terhadap SLC6A3 belum memenuhi ambang batas tersebut. Simulasi dinamika molekuler (MDS) selama 50 ns menggunakan YASARA mengindikasikan kestabilan kompleks BEOC09-MAOA dan BEOC09-MAOB pada energi ikatan MM-PBSA, profil RMSD dan RMSF yang sesuai dengan kriteria stabilitas pada literatur acuan. Temuan in silico ini mengindikasikan BEOC09 sebagai kandidat penghambat MAO-A/MAO-B yang prospektif dan menunjukkan sifat antidepressant-like lebih baik, sedangkan BEOC13 sebagai kandidat ligan DRD2 yang memiliki sifat antidepressant-like moderat, sehingga BEO berpeluang dikembangkan lebih lanjut sebagai sumber agen antidepressant-like berbasis bahan alam, dengan validasi eksperimental in vitro maupun in vivo yang diperlukan untuk mengonfirmasi temuan ini.
Kata kunci: Bergamot Essential Oil, network pharmacology, molecular docking, molecular dynamics simulation, antidepressant-like.

ABSTRACT Depression remains a global mental health burden whose treatment is still constrained by significant limitations, with approximately 20-24% of patients failing to respond to conventional synthetic antidepressants. This study aimed to identify bioactive compounds from Bergamot Essential Oil (Citrus bergamia) as potential antidepressant-like candidates through an integrated in silico approach. Twenty-one compounds identified via GC-MS were screened based on physicochemical and CNS pharmacokinetic (ADMET) criteria, yielding 14 candidate compounds that were subsequently analyzed through network pharmacology against 31 common targets obtained from the intersection of active-compound and depression-related gene databases, revealing 10 active compounds interacting with four key targets: DRD2, SLC6A3, MAO-A, and MAO-B. Molecular docking using AutoDock showed that BEOC09 (neryl acetate) exhibited the highest binding affinity among the tested BEO compounds toward MAO-A (-6.63 kcal/mol) and MAO-B (-6.09 kcal/mol), while BEOC13 (2-methyl-5-prop-1-en-2-ylcyclohexan-1-ol) was the only compound meeting the affinity threshold for DRD2 (-5.70 kcal/mol); interaction with SLC6A3 did not meet this threshold. A 50-ns molecular dynamics simulation (MDS) using YASARA indicated the stability of the BEOC09-MAOA and BEOC09-MAOB complexes, as reflected in their MM-PBSA binding energies and RMSD/RMSF profiles, which were consistent with the stability criteria established in reference literature. These in silico findings suggest BEOC09 as a promising MAO-A/MAO-B inhibitor candidate with stronger antidepressant-like properties, whereas BEOC13 emerges as a DRD2 ligand candidate with moderate antidepressant-like potential. Overall, BEO shows promise for further development as a natural-product-based source of antidepressant-like agents, although experimental validation through in vitro and in vivo studies is still required to confirm these findings. Keywords: Bergamot Essential Oil, network pharmacology, molecular docking, molecular dynamics simulation, antidepressant-like