Structural analysis of structurally diverse α-glucosidase inhibitors for active site feature analysis

Figures & data

Table 1.  Summary of the validation results.

Model no	Statistical parameters	Training set	Test set
Model 1	R^2	0.8630	0.7452
	Q^2(LOO)	0.8397	0.7258
	Q^2(LMO)	0.8318
	Q^2(BS)	0.8286
	Q^2(LSO)	0.792
	PRESS	7.5528	7.7864
	SPRESS	0.4143
	SDEP	0.3967	0.5182
	R^20	0.4595	0.7442
	R^2pred		0.7315
	(R^2 − R^20)/R^2		0.0013
	Rm		0.7216
	k	1.0000	0.9037
	k′	0.8646	0.8243
	D^2 (avg)	2.9375
	Cooks (avg)	0.0204
Model 2	R^2	0.8548	0.7657
	Q^2(LOO)	0.8233	0.7318
	Q^2(LMO)	0.8293
	Q^2(BS)	0.8133
	Q^2(LSO)	0.7669
	PRESS	6.5830	9.6864
	SPRESS	0.4337
	SDEP	0.4108	0.5049
	R^20	0.4653	0.7449
	R^2pred		0.7641
	(R^2 − R^20)/R^2		0.0272
	Rm		0.6553
	k	1.0000	0.8654
	k′	0.8625	0.8599
	D^2 (avg)	2.9231
	Cooks (avg)	0.0259

Figure 1.  Scatterplot between observed activity and predicted activites (LSO, LOO, LMO, bootstraping and normal) of model 1.

Figure 2.  Scatterplot between observed activity and predicted activites (LSO, LMO, LOO, bootstraping, normal) of model 2.

Figure 3.  Scatterplot between observed and predicted activites of test compounds (model 1 and 2).

Figure 4.  Y-randomization test.

Table 2.  VIF and Durban–Watson values for the models.

Models no	Descriptors	Tolerance	R^2	VIF	Durbin–Watson
					Calc.	Tab
Model 1	E_str	0.4536	0.5462	2.2046	2.0440	1.2450–1.4910
	SMR_VSA0	0.4610	0.5390	2.1692
	vsurf_Wp4	0.4411	0.5589	2.2671
Model 2	E_str	0.4038	0.5962	2.4765	1.7361	1.1370–1.4520
	SMR_VSA0	0.3399	0.6601	2.9420
	vsurf_Wp4	0.4101	0.5899	2.4384