A new descriptor,namely scores vector of zero dimension,one dimension,two dimension and three dimension(SZOTT),was derived from principle components analysis of a matrix of 1 369 structural variables including 0D,1D,2...A new descriptor,namely scores vector of zero dimension,one dimension,two dimension and three dimension(SZOTT),was derived from principle components analysis of a matrix of 1 369 structural variables including 0D,1D,2D and 3D information for 20 coded amino acids.SZOTT scales were then employed to express structures of 20 thromboplastin inhibitors and 34 bactericidal peptides.The correlation coefficients of both whole calibration(%R%2=%R%2cu)and of cross validation(%Q%2=%R%2cv)for the multiple-variable models by classical partial least squares(PLS)and orthogonal signal correction-partial least squares(OSC-PLS)of 20 thromboplastin inhibitors were 0.989 and 0.748,0.994 and 0.936,respectively.%R%2 and %Q%2 for the models by PLS and OSC-PLS of 34 bactericidal peptides were 0.619 and 0.406,0.910 and 0.503,respectively.Satisfactory results obtained showed that structural information related to biological activity in both data sets could be described by SZOTT which included plentiful information related to biological activity,and which was conveniently operated and easy interpreted.,also predictive capability of models were relative robust.There is a high prospect for SZOTT wide applications on quantitative sequence-activity modeling(QSAM)of peptides.展开更多
以20种天然氨基酸的721个3D结构信息描述子经主成分分析,得出一种新的氨基酸描述子——SVTD(Scores Vector of Three Dimension Descriptors),将其应用于血管紧张素转化酶抑制剂与促凝血酶原酶抑制剂的结构表征,并应用偏最小二乘建模方...以20种天然氨基酸的721个3D结构信息描述子经主成分分析,得出一种新的氨基酸描述子——SVTD(Scores Vector of Three Dimension Descriptors),将其应用于血管紧张素转化酶抑制剂与促凝血酶原酶抑制剂的结构表征,并应用偏最小二乘建模方法建立定量构效关系模型,建模复相关系数R2cum、交互检验复相关系数Q2cum分别为0.880、0.778和0.998、0.804。结果表明:SVTD描述子能够系统地表征与生物活性相关的结构信息,该描述子有望成为多肽定量构效关系研究中一种有效的结构表达方法。展开更多
从20种天然氨基酸197个GETAWAY指数经主成分分析得出一种新3D氨基酸描述子——VSGETAWAY[vector of principal component scores for GETAWAY(geometry,topology and atom-weights assembly)].将其应用于48个苦味活性二肽、31个血管舒...从20种天然氨基酸197个GETAWAY指数经主成分分析得出一种新3D氨基酸描述子——VSGETAWAY[vector of principal component scores for GETAWAY(geometry,topology and atom-weights assembly)].将其应用于48个苦味活性二肽、31个血管舒缓激肽促进剂和20个促凝血酶原激酶抑制剂结构表征并以偏最小二乘(PLS)对3个体系建立定量构效关系(QSAR)模型,得复相关系数(Rc2um)与交互检验复相关系数(Qc2um)分别为0.887和0.753;0.995和0.708;0.999和0.802.研究结果表明,VSGETAWAY描述子操作简便、结构表达能力强,有望成为多肽药物QSAR研究中一种有效的结构表征方法.展开更多
从20种天然氨基酸的41个分子轮廓指数（randic molecular profiles,R）、44个分子特征值指数（eigenvalue based indices,E）和47个分子运转路径数目（walk and path counts,W）分别进行主成分分析,得出1种新的氨基酸描述符（scores vec...从20种天然氨基酸的41个分子轮廓指数（randic molecular profiles,R）、44个分子特征值指数（eigenvalue based indices,E）和47个分子运转路径数目（walk and path counts,W）分别进行主成分分析,得出1种新的氨基酸描述符（scores vector of R,E,W-SVREW）。将其应用于血管紧张素转化酶（ACE）抑制二肽、三肽、四肽、九肽结构表征,应用多元线性回归建立定量构效关系模型,同时采用内部与外部双重验证的方法验证模型的稳定性。所建ACE抑制二肽、三肽、四肽、九肽的模型复相关系数（Rcum^2）、留一法（LOO）交互校验复相关系数（Rcv^2）和外部样本校验相关系数（Qext^2）分别为：0.907、0.791、0.633;0.831、0.603、0.723;0.834、0.668、0.718;0.964、0.853、0.948。经研究表明：SVREW描述符应用于ACE抑制肽结构表征所建模型稳定性与预测能力均较好。展开更多
从20种天然氨基酸的41个randic molecular profiles、44个eigenvalue based indices和47个walk and path counts非零描述符分别进行主成分分析,得出一种新的氨基酸描述符——SVREW.将其应用于血管紧张素转化酶抑制三肽结构表征,应用多...从20种天然氨基酸的41个randic molecular profiles、44个eigenvalue based indices和47个walk and path counts非零描述符分别进行主成分分析,得出一种新的氨基酸描述符——SVREW.将其应用于血管紧张素转化酶抑制三肽结构表征,应用多元线性回归(MLR)及偏最小二乘(PLS)建立定量构效关系模型,同时采用内部与外部双重验证的方法验证模型的稳定性.所建模型复相关系数(Rcum2)、留一法(LOO)交互校验相关系数(Rcv2)和外部样本校验相关系数(Qext2)分别为MLR(0.994,0.974,0.991),P LS(0.949,0.886,0.898).然后利用此多元线性回归方程设计出一系列血管紧张素转化酶抑制三肽化合物并预测了其活性,并且应用分子对接验证所设计药物的合理性.经研究表明SVREW描述符应用于ACE三肽结构表征所建模型的稳定性与预测能力均较好,有望成为多肽定量构效关系研究中一种有效的结构表征方法,并对新药物的发现和研究提供指导.展开更多
文摘A new descriptor,namely scores vector of zero dimension,one dimension,two dimension and three dimension(SZOTT),was derived from principle components analysis of a matrix of 1 369 structural variables including 0D,1D,2D and 3D information for 20 coded amino acids.SZOTT scales were then employed to express structures of 20 thromboplastin inhibitors and 34 bactericidal peptides.The correlation coefficients of both whole calibration(%R%2=%R%2cu)and of cross validation(%Q%2=%R%2cv)for the multiple-variable models by classical partial least squares(PLS)and orthogonal signal correction-partial least squares(OSC-PLS)of 20 thromboplastin inhibitors were 0.989 and 0.748,0.994 and 0.936,respectively.%R%2 and %Q%2 for the models by PLS and OSC-PLS of 34 bactericidal peptides were 0.619 and 0.406,0.910 and 0.503,respectively.Satisfactory results obtained showed that structural information related to biological activity in both data sets could be described by SZOTT which included plentiful information related to biological activity,and which was conveniently operated and easy interpreted.,also predictive capability of models were relative robust.There is a high prospect for SZOTT wide applications on quantitative sequence-activity modeling(QSAM)of peptides.
文摘以20种天然氨基酸的721个3D结构信息描述子经主成分分析,得出一种新的氨基酸描述子——SVTD(Scores Vector of Three Dimension Descriptors),将其应用于血管紧张素转化酶抑制剂与促凝血酶原酶抑制剂的结构表征,并应用偏最小二乘建模方法建立定量构效关系模型,建模复相关系数R2cum、交互检验复相关系数Q2cum分别为0.880、0.778和0.998、0.804。结果表明:SVTD描述子能够系统地表征与生物活性相关的结构信息,该描述子有望成为多肽定量构效关系研究中一种有效的结构表达方法。
文摘从20种天然氨基酸197个GETAWAY指数经主成分分析得出一种新3D氨基酸描述子——VSGETAWAY[vector of principal component scores for GETAWAY(geometry,topology and atom-weights assembly)].将其应用于48个苦味活性二肽、31个血管舒缓激肽促进剂和20个促凝血酶原激酶抑制剂结构表征并以偏最小二乘(PLS)对3个体系建立定量构效关系(QSAR)模型,得复相关系数(Rc2um)与交互检验复相关系数(Qc2um)分别为0.887和0.753;0.995和0.708;0.999和0.802.研究结果表明,VSGETAWAY描述子操作简便、结构表达能力强,有望成为多肽药物QSAR研究中一种有效的结构表征方法.
文摘从20种天然氨基酸的41个分子轮廓指数（randic molecular profiles,R）、44个分子特征值指数（eigenvalue based indices,E）和47个分子运转路径数目（walk and path counts,W）分别进行主成分分析,得出1种新的氨基酸描述符（scores vector of R,E,W-SVREW）。将其应用于血管紧张素转化酶（ACE）抑制二肽、三肽、四肽、九肽结构表征,应用多元线性回归建立定量构效关系模型,同时采用内部与外部双重验证的方法验证模型的稳定性。所建ACE抑制二肽、三肽、四肽、九肽的模型复相关系数（Rcum^2）、留一法（LOO）交互校验复相关系数（Rcv^2）和外部样本校验相关系数（Qext^2）分别为：0.907、0.791、0.633;0.831、0.603、0.723;0.834、0.668、0.718;0.964、0.853、0.948。经研究表明：SVREW描述符应用于ACE抑制肽结构表征所建模型稳定性与预测能力均较好。
文摘从20种天然氨基酸的41个randic molecular profiles、44个eigenvalue based indices和47个walk and path counts非零描述符分别进行主成分分析,得出一种新的氨基酸描述符——SVREW.将其应用于血管紧张素转化酶抑制三肽结构表征,应用多元线性回归(MLR)及偏最小二乘(PLS)建立定量构效关系模型,同时采用内部与外部双重验证的方法验证模型的稳定性.所建模型复相关系数(Rcum2)、留一法(LOO)交互校验相关系数(Rcv2)和外部样本校验相关系数(Qext2)分别为MLR(0.994,0.974,0.991),P LS(0.949,0.886,0.898).然后利用此多元线性回归方程设计出一系列血管紧张素转化酶抑制三肽化合物并预测了其活性,并且应用分子对接验证所设计药物的合理性.经研究表明SVREW描述符应用于ACE三肽结构表征所建模型的稳定性与预测能力均较好,有望成为多肽定量构效关系研究中一种有效的结构表征方法,并对新药物的发现和研究提供指导.
