Perspective │2 Artificial intelligence (AI) tools are increasingly being applied in drug discovery. Whilst some protagonists point to vast opportunities potentially offered by such tools, others remain skeptical, waiting for a clear impact to be shown in drug discovery projects. The truth is probably somewhere between these extremes, but it is clear that AI is providing new challenges not only for the scientists involved but also for the biopharma industry and its established processes for discovering and developing new medicines. This article presents the views of a diverse group of international experts on the 'grand challenges' for small-molecule drug discovery with AI and approaches to address them.

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The Drug Design Data Resource (D3R) aims to identify best practice methods for computer aided drug design through blinded ligand pose prediction and affinity challenges. Herein, we report on the results of Grand Challenge 4 (GC4). GC4 focused on proteins beta secretase 1 and Cathepsin S, and was run in an analogous manner to prior challenges. In Stage 1, participant ability to predict the pose and affinity of BACE1 ligands were assessed. Following the completion of Stage 1, all BACE1 co-crystal structures were released, and Stage 2 tested affinity rankings with co-crystal structures. We provide an analysis of the results and discuss insights into determined best practice methods.

KRAS is frequently mutated in several of the most lethal types of cancer; however, the KRAS protein has proven a challenging drug target. K-RAS4B must be localized to the plasma membrane by prenylation to activate oncogenic signaling, thus we endeavored to target the protein-membrane interface with small-molecule compounds. While all reported lead compounds have low affinity for KRAS in solution, the potency of Cmpd2 was strongly enhanced when prenylated K-RAS4B is associated with a lipid bilayer. We have elucidated a unique mechanism of action of Cmpd2, which simultaneously engages a shallow pocket on KRAS and associates with the lipid bilayer, thereby stabilizing KRAS in an orientation in which the membrane occludes its effector-binding site, reducing RAF binding and impairing activation of RAF. Furthermore, enrichment of Cmpd2 on the bilayer enhances potency by promoting interaction with KRAS. This insight reveals a novel approach to developing inhibitors of membrane-associated proteins.

[formula: see text] Paclitaxel and epothilone represent the two major classes of antimicrotubule agents that promote tubulin polymerization and, presumably, mitotic arrest during cell division. A common minireceptor binding site model at beta-tubulin has been constructed for these structurally divergent compounds. Utilizing 20 amino acids identified in photoaffinity labeling experiments, the 3-D model correlates measured and predicted Ki's with r = 0.99 and rms(delta Gcalc-delta Gexp) = 0.2 kcal/mol. In addition, the model predicts the affinity of compounds not used in the training set and explains much of the SAR for the paclitaxel and epothilone families.