Challenge #6

The available PDB crystal structures will be used as the targets of a high throughput docking protocol using an ensemble docking approach. To effectively screen ENAMINE in the given time frame, a “deep docking” approach will be used where a surrogate model of docking scores is iteratively trained to select compounds for docking. Docking will be performed using GNINA with its default parameters, which includes convolutional neural network scoring functions.  We explicitly target a distinct binding mode or simply filter by chemical similarity to avoid not novel compounds. The final hits will be filtered for solubility (predicted using a DL model). Compounds will be clustered by Tanimoto fingerprint similarity and the top 3 (according to GNINA’s CNN_VS score) of each cluster will be selected for evaluation.  If some selected compounds are significantly more expensive than others they may be skipped in favor of purchasing more potential hits. All curation and selection of the final hit list will be determined using docking scores, computational filters, and cost considerations with no human expert selection.