Abstract：
BACKGROUND: Inhibiting receptor-tyrosine-kinase (RTK) signalling pathways has emerged as a key focus of novel cancer therapy development. Vascular endothelial growth factor receptor (VEGFR) is a member of the RTK family and is required for vasculogenesis and angiogenesis. Because VEGFR 2 is the subtype responsible for cellular angiogenesis and vasculogenesis, blocking it will impair tumour cell blood supply, reducing their development, proliferation, and metastasis.
OBJECTIVE: The aim of this study is to obtain an optimised pharmacophore as a VEGFR2 inhibitor using QSAR investigations. This aids in determining the link between structure and activity in new chemical entities (NCEs).
METHODS: The multi-linear regression approach (MLR) method was utilised to generate the QSAR Model using the programme QSARINS v.2.2.4.
CONCLUSIONS: For 2D QSAR, the best models produced has correlation coefficients of R2= 0.9396. The 3D-QSAR model obtained with R2= 0.9121 and Q2 = 0.8377. Taking docking observations, pharmacological behaviour, and toxicity analyses into account, most of the derivatives demonstrated VEGFR2 inhibitory competence.
CONCLUSIONS: According to QSAR studies, more electron-donating groups on the benzene ring linked to the isoxazole were shown to be necessary for activity. In molecular docking studies, most compounds have shown stronger affinity for the crucial amino acids Cys:919, Asp:1046, and Glu:885, which are found in typical drugs. All NCEs passed the Lipinski screening.
OBJECTIVE: The aim of this study is to obtain an optimised pharmacophore as a VEGFR2 inhibitor using QSAR investigations. This aids in determining the link between structure and activity in new chemical entities (NCEs).
METHODS: The multi-linear regression approach (MLR) method was utilised to generate the QSAR Model using the programme QSARINS v.2.2.4.
CONCLUSIONS: For 2D QSAR, the best models produced has correlation coefficients of R2= 0.9396. The 3D-QSAR model obtained with R2= 0.9121 and Q2 = 0.8377. Taking docking observations, pharmacological behaviour, and toxicity analyses into account, most of the derivatives demonstrated VEGFR2 inhibitory competence.
CONCLUSIONS: According to QSAR studies, more electron-donating groups on the benzene ring linked to the isoxazole were shown to be necessary for activity. In molecular docking studies, most compounds have shown stronger affinity for the crucial amino acids Cys:919, Asp:1046, and Glu:885, which are found in typical drugs. All NCEs passed the Lipinski screening.
摘要：
背景：抑制受体-酪氨酸激酶（RTK）信号通路已成为新型癌症治疗开发的重点。血管内皮生长因子受体（VEGFR）是RTK家族的成员，是血管发生和血管生成所必需的。因为VEGFR2是负责细胞血管生成和血管生成的亚型，阻断它会损害肿瘤细胞的血液供应，减少他们的发展，扩散,和转移。
目的：本研究的目的是使用QSAR研究获得作为VEGFR2抑制剂的优化药效团。这有助于确定新化学实体（NCE）中结构与活性之间的联系。
方法：使用程序QSARINSv.2.2.2.4，利用多元线性回归方法（MLR）方法生成QSAR模型。
结论：对于2DQSAR，产生的最佳模型的相关系数为R2=0.9396。获得的3D-QSAR模子R2=0.9121和Q2=0.8377。进行对接观察，药理学行为，和毒性分析，大多数衍生物表现出VEGFR2抑制能力。
结论：根据QSAR研究，与异恶唑连接的苯环上的更多给电子基团被证明是活性所必需的。在分子对接研究中，大多数化合物对典型药物中发现的关键氨基酸Cys：919，Asp：1046和Glu：885显示出更强的亲和力。所有NCE都通过了Lipinski筛选。
目的：本研究的目的是使用QSAR研究获得作为VEGFR2抑制剂的优化药效团。这有助于确定新化学实体（NCE）中结构与活性之间的联系。
方法：使用程序QSARINSv.2.2.2.4，利用多元线性回归方法（MLR）方法生成QSAR模型。
结论：对于2DQSAR，产生的最佳模型的相关系数为R2=0.9396。获得的3D-QSAR模子R2=0.9121和Q2=0.8377。进行对接观察，药理学行为，和毒性分析，大多数衍生物表现出VEGFR2抑制能力。
结论：根据QSAR研究，与异恶唑连接的苯环上的更多给电子基团被证明是活性所必需的。在分子对接研究中，大多数化合物对典型药物中发现的关键氨基酸Cys：919，Asp：1046和Glu：885显示出更强的亲和力。所有NCE都通过了Lipinski筛选。
