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Integrating Computational Methods into Antibacterial Drug Discovery and Development from Natural Products Yuliandra, Yori; Syafni, Nova
JSFK (Jurnal Sains Farmasi & Klinis) Vol 11 No 1 (2024): J Sains Farm Klin 11(1), April 2024
Publisher : Fakultas Farmasi Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jsfk.11.1.80-85.2024

Abstract

Natural products have long been pivotal in sustaining civilizations due to their medicinal properties and have served as a rich source of bioactive compounds for drug discovery. With the rise of antibiotic-resistant bacteria, there is an urgent need for new antibacterial agents. Natural products, with their diverse chemical structures, provide a promising reservoir for identifying new lead compounds. Historically, the discovery of bioactive natural products often relied on serendipity, but modern advancements in computational approaches, particularly computer-aided drug design (CADD), have revolutionized this process. In the modern era, vast data from advanced technologies can provide valuable insights through computational methods. These approaches enable the structural analysis of molecules and the prediction of their biological activities, accelerating drug discovery. Advances in molecular sciences have identified more antibacterial targets, further facilitating this process. Integrating computational drug design with the study of natural products allows for the efficient identification and optimization of potential antibacterial agents. Moreover, many medicinal plants harbor mechanisms of action that remain unexplored by conventional methods. By employing computational techniques, researchers can uncover these mechanisms and develop novel antibacterial drugs. This combined approach not only enhances our understanding of natural products but also addresses the critical need for new treatments in the fight against bacterial infections.