Department of Chemistry, Gebze Technical University, Kocaeli, Turkey.
Department of Molecular Biology and Genetics, Gebze Technical University, Kocaeli, Turkey.
J Biomol Struct Dyn. 2024 Oct;42(17):8958-8968. doi: 10.1080/07391102.2023.2249111. Epub 2023 Aug 20.
Malaria is a disease caused mostly by falciparum, affects millions of people each year. The kinases are validated targets for malaria infection. In this study, we investigate for real and hypothetical compounds that can inhibit cyclic guanosine monophosphate (CGMP)-dependent protein kinase using molecular docking combined similarity analysis, molecular dynamics simulations, quantitative structure activity relationship (QSAR). Using Tanimoto similarity scores, ∼8.4 million compounds were screened. Compounds that have at least 70% similarity are used in further analysis. These compounds are assessed by means of docking, MMBPSA, MMGBSA and ANI_LIE. Based on consensus of different free energy methods and docking we revealed two potential inhibitors that can be useful for treatment of malaria. Apart from screening of real compounds, we have also selected the 10 most plausible hypothetical compounds by performing QSAR. By QSAR proposed pharmacophores, we generated over 247 hypothetical compounds and among them 19 molecules with lower QSAR predicted IC50 values and high docking scores were selected for further analysis. We selected the top 10 inhibitor candidates and performed MD simulations for free energy calculations like the protocol applied for real compounds. According to the free energy calculations, we suggest 2 real (CHFNOS and CHFNOS, PubChem IDs: 140564801 and 89035196, respectively) and 2 hypothetical (CHFNOS, MOL3 and CHFNOS, MOL4) compounds that can be effective inhibitors against the protein kinase of falciparum.Communicated by Ramaswamy H. Sarma.
疟疾主要由恶性疟原虫引起，每年影响数百万人。激酶是疟原虫感染的有效靶点。在这项研究中，我们使用分子对接结合相似性分析、分子动力学模拟、定量构效关系（QSAR），研究了真实和假设的化合物，这些化合物可以抑制环鸟苷单磷酸（cGMP）依赖性蛋白激酶。利用 Tanimoto 相似性评分，筛选了约 840 万种化合物。至少具有 70%相似性的化合物用于进一步分析。通过对接、MMBPSA、MMGBSA 和 ANI_LIE 评估这些化合物。基于不同自由能方法和对接的共识，我们揭示了两种可能的抑制剂，可用于治疗疟疾。除了筛选真实化合物外，我们还通过 QSAR 选择了 10 种最合理的假设化合物。通过 QSAR 提出的药效团，我们生成了超过 247 种假设化合物，其中选择了 19 种具有较低 QSAR 预测 IC50 值和高对接分数的分子进行进一步分析。我们选择了前 10 名抑制剂候选者，并对它们进行了 MD 模拟，以进行自由能计算，方法与应用于真实化合物的协议相同。根据自由能计算，我们建议使用 2 种真实（CHFNOS 和 CHFNOS，PubChem ID：140564801 和 89035196）和 2 种假设（CHFNOS、MOL3 和 CHFNOS、MOL4）化合物作为抗恶性疟原虫蛋白激酶的有效抑制剂。由 Ramaswamy H. Sarma 传达。
