A key objective of drug discovery is to find new chemical compounds with the desired pharmacological characteristics. The promising drug candidates identified in the early phase of drug discovery face a high risk (around 95% ) of failure in later clinical trials, leading to a waste of resources . Therefore, diverse methods need to be developed to generate enough drug candidates. However, medicinal chemists must search for these candidates throughout a vast chemical space, which is costly and time-consuming. Recently, deep learning (DL) has demonstrated the potential to speed up the discovery of novel drug candidates .