Along with 44313 decoys generated and standardized by the DeepCoy model. The ratio of active to decoy in this set was maintained at 1:50. Finally, decoys generated by DeepCoy achieved a DOE score of 0.045, indicating a close to optimal embedding of actives and decoys in chemical space. Meanwhile, AUC-1NN value of 0.566 demonstrated the greater the similarity between the actives and decoys. Besides, the average doppelganger score, a measure of the structural similarity between actives and decoys, was 0.266 for the DeepCoy decoys, while the average maximum doppelganger was 0.469. These results strongly suggested that the decoys generated by DeepCoy should not carry an increased risk of artificial enrichment, analog bias, and false negative bias. , there is an opposite trend when observing the number of substances in the construction set and generated pharmacophore models. A possible explanation is that the greater structural diversity in the construction set led to the generation of a higher number of conformations. However, the less probability of aligning numerous conformations resulted in the lower models generated. Validation sets, including actives and decoys, were used to assess the performance of pharmacophore models generated by MOE from five train sets A, B, C, D, E. The standard performance metrics of pharmacophore-based virtual screening included AUC, EF, GH, and F1-score. The priority requirement was as many actives as possible (high TPR) and as few decoys as possible (low FPR), so the area under the ROC curve (AUC) is the priority value. Besides, EF is also a widely used validation metric for assessing the quality of virtual screening protocol to measure how many more actives are found within a defined "early recognition" fraction of the ordered list compared to a random distribution. Based on AUC and EF validation metric, the best pharmacophore model was RHHa_52 from the train set C. This model achieved a high AUC value (0.82) (Fig. ) and EF1% (19.466), however, GH (0.131) and F1-score (0.071) were very low.