摘要
目的通过生物信息学方法预测早幼粒细胞白血病蛋白与TAK1结合蛋白的相互作用,并通过免疫共沉淀方法进行实验验证。方法使用Rosetta软件,采用比较建模的方法,构建TAB1蛋白的三维模型;在PDB数据库中检索PML蛋白二级结构,并解析其晶体结构和三维结构。Zdock3.0.2软件进行PML与TAB1的蛋白-蛋白对接,并提取最佳构象进行对接模型的分子结构分析。α-MMC处理的M1炎性巨噬细胞,利用免疫共沉淀技术检测两种蛋白的相互作用。结果以PML的6IMQ为对接部位时,PML蛋白与TAB1蛋白能形成3个盐桥、6个氢键和6个疏水作用;以PML的5YUF为对接部位时,PML蛋白与TAB1蛋白能形成1个氢键、3个静电相互作用和9个疏水作用,两种对接模式皆能形成良好的分子对接和相互作用;在α-MMC处理4h后,其PML-IP组的细胞裂解沉淀液中分别能检测到显著的PML和TAB1阳性蛋白条带。结论PML蛋白与TAB1蛋白能发生较强的相互作用。
Objective To analyze the interaction between PML protein and TAB1 protein using bioinformatic approaches and experimentally verify the results.Methods Using Rosetta software,a 3D model of TAB1 protein was constructed through a comparative modeling approach;the secondary structure of PML protein was retrieved in the PDB database and its crystal structure and 3D structure were resolved.Zdock 3.0.2 software was used to perform protein-protein docking of PML and TAB1,and the best conformation was extracted for molecular structure analysis of the docking model.The interaction between the two proteins was detected using immunoprecipitation inα-MMC-treated M1 inflammatory macrophages.Results When 6IMQ of PML was used as the docking site,PML protein formed 3 salt bridges,6 hydrogen bonds and 6 hydrophobic interactions with TAB1 proteins;when 5YUF of PML was used as the docking site,PML protein formed 1 hydrogen bond,3 electrostatic interactions and 9 hydrophobic interactions with TAB1 proteins,and both of the docking modes formed good molecular docking and interactions.In the M1 inflammatory macrophages treated withα-MMC for 4 h,positive protein bands of PML and TAB1 were detected in the cell lysates in PML-IP group.Conclusion PML protein can interact strongly with TAB1 protein.
作者
成佳聪
李智慧
刘鳐
李成
黄鑫
田颖鑫
沈富兵
CHENG Jiacong;LI Zhihui;LIU Yao;LI Cheng;HUANG xin;TIAN Yinxin;SHEN Fubing(School of Laboratory Medicine,Chengdu Medical College,Chengdu 610500,China;School of Pharmacy,Chengdu Medical College,Chengdu 610500,China)
出处
《南方医科大学学报》
CAS
CSCD
北大核心
2024年第1期179-186,共8页
Journal of Southern Medical University
基金
四川省科技厅重点研发项目(2018SZ0016,2019YFS0307,2021YFS0053)
成都医学院自然科学基金(CYZYB22-04)
成都医学院检验医学院自然科学基金(JYZK202201)。
