Elbaramawi Samar S, Eissa Ahmed G, Noureldin Nada A, Simons Claire
Department of Medicinal Chemistry, Faculty of Pharmacy, Zagazig University, Zagazig 44519, Egypt.
School of Pharmacy & Pharmaceutical Sciences, Cardiff University, King Edward VII Avenue, Cardiff CF10 3NB, UK.
Pharmaceuticals (Basel). 2023 Sep 6;16(9):1263. doi: 10.3390/ph16091263.
Currently, the treatment of infections is considered to be complicated as the organism has become resistant to numerous antibiotic classes. Therefore, new inhibitors should be developed, targeting bacterial molecular functions. Methionine tRNA synthetase (MetRS), a member of the aminoacyl-tRNA synthetase family, is essential for protein biosynthesis offering a promising target for novel antibiotics discovery. In the context of computer-aided drug design (CADD), the current research presents the construction and analysis of a comparative homology model for MetRS, enabling development of novel inhibitors with greater selectivity. Molecular Operating Environment (MOE) software was used to build a homology model for MetRS using MetRS as a template. The model was evaluated, and the active site of the target protein predicted from its sequence using conservation analysis. Molecular dynamic simulations were performed to evaluate the stability of the modeled protein structure. In order to evaluate the predicted active site interactions, methionine (the natural substrate of MetRS) and several inhibitors of bacterial MetRS were docked into the constructed model using MOE. After validation of the model, pharmacophore-based virtual screening for a systemically prepared dataset of compounds was performed to prove the feasibility of the proposed model, identifying possible parent compounds for further development of MetRS inhibitors against .
目前，由于该生物体已对多种抗生素类别产生耐药性，感染的治疗被认为很复杂。因此，应开发针对细菌分子功能的新型抑制剂。甲硫氨酸tRNA合成酶（MetRS）是氨酰-tRNA合成酶家族的成员，对蛋白质生物合成至关重要，为新型抗生素的发现提供了一个有前景的靶点。在计算机辅助药物设计（CADD）的背景下，当前的研究展示了MetRS比较同源模型的构建和分析，从而能够开发出具有更高选择性的新型抑制剂。使用分子操作环境（MOE）软件，以MetRS为模板构建了MetRS的同源模型。对该模型进行了评估，并通过保守性分析从其序列预测了靶蛋白的活性位点。进行分子动力学模拟以评估建模蛋白质结构的稳定性。为了评估预测的活性位点相互作用，使用MOE将甲硫氨酸（MetRS的天然底物）和几种细菌MetRS抑制剂对接至构建的模型中。在模型验证后，对系统制备的化合物数据集进行基于药效团的虚拟筛选，以证明所提出模型的可行性，识别出用于进一步开发抗MetRS抑制剂的可能母体化合物。
