Biophysics Department, Faculty of Science, Cairo University, Giza, Egypt.
Centre of Scientific Excellence for Influenza Viruses (CSEIV), National Research Centre, Cairo, Egypt.
J Biomol Struct Dyn. 2024 Oct;42(17):9145-9158. doi: 10.1080/07391102.2023.2250479. Epub 2023 Aug 24.
Researchers worldwide are looking for molecules that might disrupt the COVID-19 life cycle. Endoribonuclease, which is responsible for processing viral RNA to avoid detection by the host defense system, and helicase, which is responsible for unwinding the RNA helices for replication, are two key non-structural proteins. This study performs a hierarchical structure-based virtual screening approach for NSP15 and helicase to reach compounds with high binding probabilities. In this investigation, we incorporated a variety of filtering strategies for predicting compound interactions. First, we evaluated 756,275 chemicals from four databases using a deep learning method (NCI, Drug Bank, Maybridge, and COCONUT). Following that, two docking techniques (extra precision and induced fit) were utilized to evaluate the compounds' binding affinity, followed by molecular dynamic simulation supported by the MM-GBSA free binding energy calculation. Remarkably, two compounds (90616 and CNP0111740) exhibited high binding affinity values of -66.03 and -12.34 kcal/mol for helicase and NSP15, respectively. The VERO-E6 cell line was employed to test their therapeutic impact. The CC for CNP0111740 and 90616 were determined to be 102.767 μg/ml and 379.526 μg/ml, while the IC values were 140.176 μg/ml and 5.147 μg/ml, respectively. As a result, the selectivity index for CNP0111740 and 90616 is 0.73 and 73.73, respectively. Finally, these compounds were found to be novel, effective inhibitors for the virus; however, further validation is needed.Communicated by Ramaswamy H. Sarma.
研究人员正在全球范围内寻找可能破坏 COVID-19 生命周期的分子。内切核糖核酸酶负责将病毒 RNA 加工成宿主防御系统无法检测到的形式，解旋酶负责解开 RNA 螺旋以进行复制，这两种都是关键的非结构蛋白。本研究采用基于层次结构的虚拟筛选方法对 NSP15 和 helicase 进行研究，以找到具有高结合概率的化合物。在这项研究中，我们采用了多种过滤策略来预测化合物的相互作用。首先，我们使用深度学习方法（NCI、Drug Bank、Maybridge 和 COCONUT）对来自四个数据库的 756,275 种化学物质进行了评估。之后，我们使用两种对接技术（extra precision 和 induced fit）来评估化合物的结合亲和力，然后使用 MM-GBSA 自由结合能计算来支持分子动力学模拟。值得注意的是，两种化合物（90616 和 CNP0111740）对 helicase 和 NSP15 的结合亲和力值分别高达-66.03 和-12.34 kcal/mol。我们使用 VERO-E6 细胞系来测试它们的治疗效果。确定 CNP0111740 和 90616 的 CC 分别为 102.767 μg/ml 和 379.526 μg/ml，IC 值分别为 140.176 μg/ml 和 5.147 μg/ml。因此，CNP0111740 和 90616 的选择性指数分别为 0.73 和 73.73。最后，这些化合物被发现是针对该病毒的新型有效抑制剂，但还需要进一步验证。由 Ramaswamy H. Sarma 传递。
