2D-QSAR,对接,分子动力学模拟与MM/GBSA方法对抗Graves病和PTPN22

Emmanuel Israel Edache, Adamu Uzairu, Paul Andrew Mamza, Gideon Adamu Shallangwa
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摘要

格雷夫斯病(GD)是一种自身免疫性疾病,经常引起甲状腺功能亢进和甲状腺毒症。蛋白酪氨酸磷酸酶,非受体22型(淋巴样)异构体1 (PTPN22),是治疗GD,类风湿性关节炎,1型糖尿病和其他自身免疫性疾病的有希望的治疗候选者。在MOPAC v22.0.4平台上,采用半经验PM7理论方法对31个分子化合物和2个标准药物进行优化,揭示影响其抑癌活性和选择性的关键因素。利用QSARIN软件,利用获得的属性/描述符创建定量结构活性关系(QSAR)模型,并检验观测值与预测值之间的相似性。分子对接模拟研究也揭示了所研究的化合物与受体之间的非共价相互作用。观察到的配体蛋白与GD蛋白(PDB ID 2XPG和4QT5)和PTPN22 (PDB ID 3BRH)的相互作用。并研究了其药代动力学(ADMET)特性。最后,通过分子动力学(MD)模拟和MM/GBSA研究,验证了PTPN22配合物的稳定性。结果表明,PTPN22具有稳定的相互作用轨迹和分子特性。
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2D-QSAR, Docking, Molecular Dynamics Simulations with the MM/GBSA Approaches against Graves' Disease and PTPN22
Graves' disease (GD) is an autoimmune condition that frequently causes hyperthyroidism and thyrotoxicosis. Protein tyrosine phosphatase, non-receptor type 22 (lymphoid) isoform 1 (PTPN22), is a promising therapeutic candidate for treating GD, rheumatoid arthritis, type 1 diabetes, and other autoimmune disorders. In this dataset, 31 molecular compounds and two standard drugs were optimized using the semi-empirical PM7 theory method via MOPAC v22.0.4 to reveal the key influencing factors contributing to their grave's disease inhibition activity and selectivity. Using QSARIN software, the acquired properties/descriptors were used to create a quantitative structural activities relationship (QSAR) model, and the similarities between the observed and predicted pIC50 values were examined. A molecular docking simulation study also uncovers non-covalent interactions between the investigated compounds and the receptors. The observed ligand-protein interactions with GD proteins (PDB ID 2XPG and 4QT5) and PTPN22 (PDB ID 3BRH) were investigated. The pharmacokinetics (ADMET) properties were also investigated. Finally, molecular dynamics (MD) simulation and MM/GBSA studies that demonstrated stable trajectory and molecular properties with a consistent interaction profile were used to validate the stability of the compounds in the complex with PTPN22.
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