MCNS Laboratory, Faculty of Science, Moulay Ismail University, Meknes, Morocco.
AGC African Genome Centre, Mohammed VI Polytechnic University, Benguerir, Morocco.
J Biomol Struct Dyn. 2023 Nov;41(19):10070-10080. doi: 10.1080/07391102.2022.2152871. Epub 2022 Dec 5.
Plasmepsin II is a key enzyme in the life cycle of the parasite responsible for malaria, a disease that is causing deaths on a worldwide scale. Recently, plasmepsin II enzyme has gained much importance as an attractive drug target for the investigation of antimalarial drugs. In this sense, structure-based virtual screening have been utilized as tools in the process of discovering novel natural compounds based on quinoline as potential plasmepsin II inhibitors. Among the 58 quinoline derivatives isolated from different plants was screened by utilizing docking molecular, ADMET approaches, molecular dynamics simulation and MM-PBSA binding free energy. The first step in this work is building the 3 D structures of the plasmepsin II enzyme by using the SWISS-MODEL software. The optimized structures were subjected to virtual screening by Autodock Vina, an entity implicated in PyRx software. 21 were selected based on their binding affinity. The binding modes and interactions of the top-21 selected compounds were evaluated using AutoDock 4.2. Then, the pharmacokinetic proprieties and toxicity of these compounds were evaluated using ADMET analysis. Ten compounds were predicted to have ADMET characteristics with no side effects. Compounds M49 and M53 were found to be potential inhibitors. The stability of the selected two compounds was confirmed by MD simulation and MM/PBSA calculation during 200 ns. This study can be used to predict and to design new antimalarial drugs.Communicated by Ramaswamy H. Sarma.
疟原虫生活周期中的关键酶裂殖体蛋白 2 是引起疟疾的寄生虫，这种疾病正在全球范围内造成死亡。最近，裂殖体蛋白 2 酶作为抗疟药物研究的一个有吸引力的药物靶点而备受关注。在这方面，基于结构的虚拟筛选已被用作发现基于喹啉的新型天然化合物作为潜在裂殖体蛋白 2 抑制剂的工具。从不同植物中分离得到的 58 种喹啉衍生物中，利用对接分子、ADMET 方法、分子动力学模拟和 MM-PBSA 结合自由能对其中的一种进行了筛选。这项工作的第一步是使用 SWISS-MODEL 软件构建裂殖体蛋白 2 酶的 3D 结构。优化后的结构通过 Autodock Vina 进行虚拟筛选，Autodock Vina 是 PyRx 软件中的一个实体。根据结合亲和力选择了 21 个。使用 AutoDock 4.2 评估了前 21 个选定化合物的结合模式和相互作用。然后，使用 ADMET 分析评估这些化合物的药代动力学特性和毒性。预测这 10 种化合物具有 ADMET 特征且无副作用。发现化合物 M49 和 M53 可能是潜在的抑制剂。通过 MD 模拟和 MM/PBSA 计算在 200ns 内确认了所选两种化合物的稳定性。这项研究可用于预测和设计新的抗疟药物。由 Ramaswamy H. Sarma 交流。
