目的·通过整合不孕症遗传因素大数据,挖掘突变规律及相关致病基因。方法·根据全球蛋白资源数据库(Universal Protein Resource,Uniprot)蛋白类别对搜集的人类不孕症致病基因进行分类,统计分析临床病例中每类基因的突变频数。...目的·通过整合不孕症遗传因素大数据,挖掘突变规律及相关致病基因。方法·根据全球蛋白资源数据库(Universal Protein Resource,Uniprot)蛋白类别对搜集的人类不孕症致病基因进行分类,统计分析临床病例中每类基因的突变频数。针对功能异常的氧化还原酶这一重要致病因素,进行功能和通路分析,观察通路的相关情况。于小鼠基因数据库(Mouse Genome Informatics,MGI)获取人类类固醇激素生成通路的小鼠同源基因及致病信息,寻找规律并结合基因互作分析评估其中的潜在基因。结果·不孕症致病基因里氧化还原酶类基因突变最常见,可能最易发生突变;其聚集于类固醇激素生成通路,发现潜在相关突变基因,并发现此通路醛酮还原酶家族1成员C3(aldo-keto reductase family 1 member C3,AKR1C3)是其中最可能的人类不孕症的潜在致病基因。结论·主要产生类固醇激素的氧化还原酶类致病基因在不孕症中突变最常见,可能包括AKR1C3。展开更多
As one of the three viral encoded enzymes of HIV-1 infection, HIV-1 integrase has become an attractive drug target for the treatment. Diketoacid compounds （DKAs） are one kind of potent and selective inhibitors of HI...As one of the three viral encoded enzymes of HIV-1 infection, HIV-1 integrase has become an attractive drug target for the treatment. Diketoacid compounds （DKAs） are one kind of potent and selective inhibitors of HIV-1 IN. In the present work, two three-dimensional QSAR techniques （CoMFA and CoMSIA） were employed to correlate the molecular structure with the activity of inhibiting the strand transfer for 147 DKAs. The all-oritation search （AOS） and all-placement search （APS） were used to optimize the CoMFA model. The diketo and keto-enol tautomers of DKAs were also used to establish the CoMFA models. The results indicated that the enol was the dominant conformation in the HIV-1 IN and DKAs complexes. It can provide a new method and reference to identify the bioactive conformation of drugs by using QSAR analysis. The best CoMSIA model, with five fields combined, implied that the hydrophobic field is very important as well as the steric and electrostatic fields. All models indicated favorable internal validation. A comparative analysis with the three models demonstrated that the CoMFA model seems to be more predictive. The contour maps could afford steric, electrostatic, hydrophobic and H-bond information about the interaction of ligand-receptor complex visually. The models would give some useful guidelines for designing novel and potent HIV-1 integrase inhibitors.展开更多
文摘目的·通过整合不孕症遗传因素大数据,挖掘突变规律及相关致病基因。方法·根据全球蛋白资源数据库(Universal Protein Resource,Uniprot)蛋白类别对搜集的人类不孕症致病基因进行分类,统计分析临床病例中每类基因的突变频数。针对功能异常的氧化还原酶这一重要致病因素,进行功能和通路分析,观察通路的相关情况。于小鼠基因数据库(Mouse Genome Informatics,MGI)获取人类类固醇激素生成通路的小鼠同源基因及致病信息,寻找规律并结合基因互作分析评估其中的潜在基因。结果·不孕症致病基因里氧化还原酶类基因突变最常见,可能最易发生突变;其聚集于类固醇激素生成通路,发现潜在相关突变基因,并发现此通路醛酮还原酶家族1成员C3(aldo-keto reductase family 1 member C3,AKR1C3)是其中最可能的人类不孕症的潜在致病基因。结论·主要产生类固醇激素的氧化还原酶类致病基因在不孕症中突变最常见,可能包括AKR1C3。
基金supported by the Natural Science Foundation of Zhejiang Province (Y. 4090578)
文摘As one of the three viral encoded enzymes of HIV-1 infection, HIV-1 integrase has become an attractive drug target for the treatment. Diketoacid compounds （DKAs） are one kind of potent and selective inhibitors of HIV-1 IN. In the present work, two three-dimensional QSAR techniques （CoMFA and CoMSIA） were employed to correlate the molecular structure with the activity of inhibiting the strand transfer for 147 DKAs. The all-oritation search （AOS） and all-placement search （APS） were used to optimize the CoMFA model. The diketo and keto-enol tautomers of DKAs were also used to establish the CoMFA models. The results indicated that the enol was the dominant conformation in the HIV-1 IN and DKAs complexes. It can provide a new method and reference to identify the bioactive conformation of drugs by using QSAR analysis. The best CoMSIA model, with five fields combined, implied that the hydrophobic field is very important as well as the steric and electrostatic fields. All models indicated favorable internal validation. A comparative analysis with the three models demonstrated that the CoMFA model seems to be more predictive. The contour maps could afford steric, electrostatic, hydrophobic and H-bond information about the interaction of ligand-receptor complex visually. The models would give some useful guidelines for designing novel and potent HIV-1 integrase inhibitors.
基金the National Natural Science Foundation of China(21708025,81925034,91753117,and 81773793)the Open Fund of State Key Laboratory of Oncogenes and Related Genes,Shanghai Jiao Tong University School of Medicine+3 种基金the Innovation Program of Shanghai Municipal Education Commission(2019-01-07-00-01-E00036)the Shanghai Science and Technology Innovation Foundation(19431901600)the China Postdoctoral Science Foundation(2016M601618 and 2017T100303)the National Science and Technology Major Project of China(2018ZX09711001-005-022)。
