PENDEKATAN IN SILICO MELALUI QSAR DAN MOLECULAR DYNAMICS: TINJAUAN SISTEMATIS KANDIDAT OBAT ANTIBAKTERI RESISTEN
DOI:
https://doi.org/10.70248/jophs.v2i3.3134Abstract
Resistensi antibakteri merupakan ancaman serius bagi kesehatan global yang menuntut penemuan kandidat obat baru melalui pendekatan inovatif. Penelitian ini bertujuan untuk meninjau secara sistematis penerapan metode komputasi Quantitative Structure–Activity Relationship (QSAR) dan Molecular Dynamics (MD) dalam pengembangan obat antibakteri terhadap bakteri resisten. Kajian dilakukan menggunakan metode Systematic Literature Review (SLR) berdasarkan pedoman PRISMA dengan menelusuri publikasi ilmiah periode 2015–2025 yang relevan. Proses seleksi dan analisis literatur dilakukan untuk mengidentifikasi peran QSAR dan MD dalam prediksi, validasi, serta optimasi senyawa antibakteri potensial. Hasil kajian menunjukkan bahwa QSAR mampu memprediksi potensi aktivitas antibakteri berdasarkan hubungan kuantitatif antara struktur kimia dan aktivitas biologis, sedangkan MD berperan dalam mengevaluasi kestabilan kompleks ligan–protein serta mekanisme interaksi molekuler pada kondisi biologis simulatif. Target protein yang sering dikaji meliputi InhA, DNA gyrase, topoisomerase IV, IKK-β, sigmacidins, dan penicillin-binding protein (PBP), dengan fokus pada patogen prioritas seperti Staphylococcus aureus (MRSA), Pseudomonas aeruginosa, dan Streptococcus spp. Temuan ini menegaskan bahwa integrasi QSAR dan MD menghasilkan pendekatan komplementer yang efektif dalam mengidentifikasi serta memvalidasi kandidat molekul dengan aktivitas antibakteri tinggi, sehingga pendekatan in silico berbasis QSAR dan MD berpotensi menjadi strategi penting dalam percepatan penemuan obat untuk menghadapi krisis resistensi antibiotik di masa mendatang.
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