FragAdd , a virtual screening model of target-binding small molecules and properties prediction, with a strategy of adding random fragments to entered molecules; improving the model's ability of learning high-quality features. Moreover, FragAdd works in a way that the original molecule is preserved unchanged, allowing for the augmentation with other learning protocols, such as masking. FragAdd demonstrated higher performance and accuracy than the average of other benchmarks.