Gondokesumo Marisca Evalina, Rasyak Muhammad Rezki, Ibrahim Mansur
Biology Pharmacy Department, Faculty of Pharmacy, University of Surabaya, Surabaya, Indonesia.
Eijkman Research Centre for Molecular Biology, National Research and Innovation Agency of Indonesia (BRIN), Jakarta, Indonesia.
J Adv Pharm Technol Res. 2025 Apr-Jun;16(2):53-60. doi: 10.4103/JAPTR.JAPTR_209_24. Epub 2025 May 19.
Traditional Indonesian medicine has long been recognized for its curative qualities, although concerns remain over the efficacy and safety of medicinal herbs. The application of computational methods in novel drug discovery is one of the promising new insights offered by recent technical advancements. This study attempts to find putative anticancer chemicals in two extensively used plants in Southeast Asia, and , using a computational technique. AKT1, a model protein implicated in the development of cancer cells, was used in this investigation. In these two plants, 28 different chemicals were found. We use strict selection standards, like Lipinski's rule of five, to ensure the identification of potential candidates. The findings demonstrated that 24 compounds had comparable binding affinities to the reference ligands, indicating encouraging therapeutic potential. Subsequent investigation showed that the compounds' chemical structures differed and that their similarities to the reference ligand were <10%. However, for both plant-derived drugs, the amino acid binding patterns revealed remarkable similarities that went above 50% similarity, suggesting that both may be useful.
传统的印度尼西亚医学长期以来因其治疗功效而得到认可，尽管人们对草药的疗效和安全性仍存在担忧。计算方法在新型药物发现中的应用是近期技术进步带来的有前景的新见解之一。本研究试图使用一种计算技术，在东南亚广泛使用的两种植物（[植物名称1]和[植物名称2]）中寻找推定的抗癌化学物质。本研究使用了与癌细胞发展相关的模型蛋白AKT1。在这两种植物中发现了28种不同的化学物质。我们使用严格的筛选标准，如Lipinski的五规则，以确保识别出潜在的候选物。研究结果表明，24种化合物与参考配体具有相当的结合亲和力，显示出令人鼓舞的治疗潜力。后续研究表明，这些化合物的化学结构不同，且它们与参考配体的相似度<10%。然而，对于这两种植物来源的药物，氨基酸结合模式显示出超过50%相似度的显著相似性，表明两者可能都有用。
