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Journal of Enzyme Inhibition and Medicinal Chemistry Volume 24, 2009 - Issue 5
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Research Article

QSAR studies on 4-anilino-3-quinolinecarbonitriles as Src kinase inhibitors using robust PCA and both linear and nonlinear models

Min SunPharmaceutical Engineering Institute, School of Chemistry and Chemical Engineering, Southeast University, 2 Sipailou, Nanjing 210096, China
,
Youguang ZhengPharmaceutical Engineering Institute, School of Chemistry and Chemical Engineering, Southeast University, 2 Sipailou, Nanjing 210096, China
,
Hongtao WeiPharmaceutical Engineering Institute, School of Chemistry and Chemical Engineering, Southeast University, 2 Sipailou, Nanjing 210096, China
,
Junqing ChenPharmaceutical Engineering Institute, School of Chemistry and Chemical Engineering, Southeast University, 2 Sipailou, Nanjing 210096, China
&
Min JiPharmaceutical Engineering Institute, School of Chemistry and Chemical Engineering, Southeast University, 2 Sipailou, Nanjing 210096, ChinaCorrespondence[email protected]
Pages 1109-1116 | Received 10 Sep 2008, Accepted 10 Nov 2008, Published online: 07 Apr 2009

Figures & data

Figure 1.  Orthogonal distance versus score distance for 37 samples using robust PCA.

Figure 1.  Orthogonal distance versus score distance for 37 samples using robust PCA.

Table 1.  Compound, experimental and calculated log(1/IC50) values, as well as corresponding residuals based on ERM model.

Figure 2.  Score plot of PCA for training and test samples.

Figure 2.  Score plot of PCA for training and test samples.

Figure 3.  Plot of predicted versus experimental log(1/IC50) values for ERM model.

Figure 3.  Plot of predicted versus experimental log(1/IC50) values for ERM model.

Figure 4.  Plot of residuals against the experimental log(1/IC50) values using ERM for samples in training and test sets, as well as outliers.

Figure 4.  Plot of residuals against the experimental log(1/IC50) values using ERM for samples in training and test sets, as well as outliers.

Table 2.  Molecular descriptors selected in models.

Table 3.  Statistical results of performance validation.

Table 4.  Y-randomization result of ERM model.

Table 5.  Predictive ability analysis result of ERM model.

Table 6.  Correlation matrix for descriptors selected in ERM model.

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