Department of Pharmacognosy, College of Pharmacy, King Khalid University, Asir, Saudi Arabia.
Chemistry of Natural Compounds Department, Pharmaceutical and Drug Industries Research Institute, National Research Centre, Dokki, Cairo, Egypt.
PLoS One. 2024 Mar 8;19(3):e0300035. doi: 10.1371/journal.pone.0300035. eCollection 2024.
The development of effective drugs targeting the K-Ras oncogene product is a significant focus in anticancer drug development. Despite the lack of successful Ras signaling inhibitors, recent research has identified PDEδ, a KRAS transporter, as a potential target for inhibiting the oncogenic KRAS signaling pathway. This study aims to investigate the interactions between eight K-Ras inhibitors (deltarazine, deltaflexin 1 and 2, and its analogues) and PDEδ to understand their binding modes. The research will utilize computational techniques such as density functional theory (DFT) and molecular electrostatic surface potential (MESP), molecular docking, binding site analyses, molecular dynamic (MD) simulations, electronic structure computations, and predictions of the binding free energy. Molecular dynamic simulations (MD) will be used to predict the binding conformations and pharmacophoric features in the active site of PDEδ for the examined structures. The binding free energies determined using the MMPB(GB)SA method will be compared with the observed potency values of the tested compounds. This computational approach aims to enhance understanding of the PDEδ selective mechanism, which could contribute to the development of novel selective inhibitors for K-Ras signaling.
针对 K-Ras 癌基因产物的有效药物的开发是抗癌药物开发的一个重要焦点。尽管缺乏成功的 Ras 信号抑制剂,但最近的研究已经确定 PDEδ(一种 KRAS 转运蛋白)是抑制致癌 KRAS 信号通路的潜在靶点。本研究旨在研究八种 K-Ras 抑制剂(deltarazine、deltaflexin 1 和 2 及其类似物)与 PDEδ 之间的相互作用,以了解它们的结合模式。该研究将利用计算技术,如密度泛函理论(DFT)和分子静电表面势能(MESP)、分子对接、结合位点分析、分子动力学(MD)模拟、电子结构计算和结合自由能的预测。分子动力学模拟(MD)将用于预测在 PDEδ 的活性位点中检查结构的结合构象和药效特征。使用 MMPB(GB)SA 方法确定的结合自由能将与测试化合物的观察到的效力值进行比较。这种计算方法旨在增强对 PDEδ 选择性机制的理解,这可能有助于开发针对 K-Ras 信号的新型选择性抑制剂。