Virtual screening with a synthetic oracle Next, we examined how NGT performed in hit discovery. In contrast to molecular properties calculated only from the ligand in the previous section, biomolecular activity is determined by the receptor-ligand complex. AtomNet ® is a target-agnostic ("foundation") system of models to predict bioactivity and potency from docked receptor-ligand complexes . The AtomNet ® bioactivity module is a classification model and was trained on active and inactive compounds. The potency module is a regression model trained on active compounds only. Docking and scoring concomitant with NGT is computationally costly. Therefore, we designed a computationally tractable surrogate model that predicts "oracle" AtomNet ® bioactivity and potency scores from ligands alone (Supporting Information). The screens for both the NGT and HE methods start from a pre-scored Minimum Enumeration Library (MEL) . We performed a virtual high throughput screen against two established drug targets, Cyclin-dependent kinase 5 (CDK5), a cyclin-dependent serine/threonine kinase, and N-acylsphingosine amidohydrolase 1 (ASAH1), an acid ceramidase (Supporting Information).