In this study. an automated conformer selection procedure using generic algorithm (GA) has been applied in comparative molecular field analysis (CoMFA) method. Using genetic algorithm. the 3D-QSAR model is optimized t...In this study. an automated conformer selection procedure using generic algorithm (GA) has been applied in comparative molecular field analysis (CoMFA) method. Using genetic algorithm. the 3D-QSAR model is optimized to an optimal one. From the calculation results, a group of QSAR models with high predictive ability can be obtained, which is superior than using conventional CoMFA: meanwhile. the active conformers for these compounds in data set can be determined fi om the best model.展开更多
Canceling grids accommodating probes in comparative molecular field analysis (CoMFA), the idea of flexibleness is introduced into the CoMFA, and in combination with swarm intelligent algorithm which attempts to optimi...Canceling grids accommodating probes in comparative molecular field analysis (CoMFA), the idea of flexibleness is introduced into the CoMFA, and in combination with swarm intelligent algorithm which attempts to optimize distributions of diverse probes around drug molecules, a new 3D-QSAR method is proposed in this context as flexible comparative molecular field analysis (FCoMFA). In preliminary at-tempts to performing QSAR studies on 47 glycogen phosphorylase inhibitors, FCoMFA is employed and confirmed to be potent to exploring ligand-receptor interaction manners at active positions and thus to generating stable and predictable models. Simultaneously by an intuitive graphics regarding probe distribution patterns, impacts of different substituted groups on activities is also given an insight into.展开更多
应用比较分子力场分析(Comparative molecular force field analysis,CoMFA)方法研究了18种氟喹诺酮C-3噻唑酮衍生物对胰腺Capan-1细胞的体外抗增殖活性(p A).训练集中14个化合物用于建立预测模型,测试集6个化合物(含模板分子和新设计的...应用比较分子力场分析(Comparative molecular force field analysis,CoMFA)方法研究了18种氟喹诺酮C-3噻唑酮衍生物对胰腺Capan-1细胞的体外抗增殖活性(p A).训练集中14个化合物用于建立预测模型,测试集6个化合物(含模板分子和新设计的1个分子)作为模型验证.通过基于配体的原子契合的叠合方式,获得了训练集的统计显著模型.CoMFA模型使用3个主成分给出交叉验证系数(R 2 cv)值为0.436,非交叉验证系数(R 2)值为0.956,估计F值为72.217.结果显示,模型具有良好的稳健性与预测能力.基于CoMFA等高线图,揭示了该系列化合物抗增殖活性的一些关键结构因素.这些结果为理解其作用机制、设计具有高抗肿瘤活性的新型氟喹诺酮C-3噻唑酮类化合物提供有益的理论参考.展开更多
文摘In this study. an automated conformer selection procedure using generic algorithm (GA) has been applied in comparative molecular field analysis (CoMFA) method. Using genetic algorithm. the 3D-QSAR model is optimized to an optimal one. From the calculation results, a group of QSAR models with high predictive ability can be obtained, which is superior than using conventional CoMFA: meanwhile. the active conformers for these compounds in data set can be determined fi om the best model.
基金Supported by National High Technology (863) Program (Grant No. 2006AA02Z312)the State Key Laboratory of Chemo/Biosensing and Chemometrics Foundation (Grant No. 0501201)Chongqing University Innovation Fund (Grant No. 030506)
文摘Canceling grids accommodating probes in comparative molecular field analysis (CoMFA), the idea of flexibleness is introduced into the CoMFA, and in combination with swarm intelligent algorithm which attempts to optimize distributions of diverse probes around drug molecules, a new 3D-QSAR method is proposed in this context as flexible comparative molecular field analysis (FCoMFA). In preliminary at-tempts to performing QSAR studies on 47 glycogen phosphorylase inhibitors, FCoMFA is employed and confirmed to be potent to exploring ligand-receptor interaction manners at active positions and thus to generating stable and predictable models. Simultaneously by an intuitive graphics regarding probe distribution patterns, impacts of different substituted groups on activities is also given an insight into.
文摘应用比较分子力场分析(Comparative molecular force field analysis,CoMFA)方法研究了18种氟喹诺酮C-3噻唑酮衍生物对胰腺Capan-1细胞的体外抗增殖活性(p A).训练集中14个化合物用于建立预测模型,测试集6个化合物(含模板分子和新设计的1个分子)作为模型验证.通过基于配体的原子契合的叠合方式,获得了训练集的统计显著模型.CoMFA模型使用3个主成分给出交叉验证系数(R 2 cv)值为0.436,非交叉验证系数(R 2)值为0.956,估计F值为72.217.结果显示,模型具有良好的稳健性与预测能力.基于CoMFA等高线图,揭示了该系列化合物抗增殖活性的一些关键结构因素.这些结果为理解其作用机制、设计具有高抗肿瘤活性的新型氟喹诺酮C-3噻唑酮类化合物提供有益的理论参考.
