In the next step, the CoMFA model was validated by the external test set of four compounds, ie, delphinidin, malvidin, pelargonidin-3,5-diglucoside, and peonidin-3-glucoside.
It can also be seen from Tables 2 and 3 that the CoMSIA model was validated by the external test set of the same four compounds with an r of 0.812, an F of 8.636, and a standard error of estimation of 0.263 (P<0.0989), suggesting that the CoMSIA model could accurately predict compound activity in 81% of cases.
The viscosity and specific gravity of foam contrast were measured using viscometer (HBDV-II + Pro, Brookfield Engineering Laboratories, Inc., MA, USA) and electronic densitometer (MD-300S, Alfa Mirage Co., Ltd., Osaka, Japan) at ambient temperature of 23°C by the external testing laboratory (Korea Polymer Testing & Research Institute, Seoul, Korea).
Furthermore, the developed model also possesses promising predictive ability as discerned by the testing on the external test set.
The performance of the stepwise and PLS models was tested by cross-validation and the external test set prediction.
The developed model also possesses promising predictive ability as discerned by the testing on the external test set, and should be useful to further understand the molecular nature of inhibitor enzyme interactions and to aid in the design of more potent sialyltransferase inhibitors.
The accuracy, equal to a fraction of correctly classified sequences, was measured by its mean value for the cross-validated experiments and, finally, by its measurement on the external test.
The 20 chemicals of the training set and the seven compounds of the external testing set were described by means of using descriptors.
The external test set (test set 2) compiled by Zaretzkiet et al. [16] was used for further method validation.
To validate the model by external test set, activities of 24 compounds were predicted and the residual values for external and internal data sets were evaluated (Table 2).
