Despite intense interest in expanding chemical space, libraries of hundreds-of-millions to billions of diverse molecules have remained inaccessible. Here, we investigate structure-based docking of 170 million make-on-demand compounds from 130 well-characterized reactions. The resulting library is diverse, representing over 10.7 million scaffolds otherwise unavailable. The library was docked against AmpC β-lactamase and the D 4 dopamine receptor. From the top-ranking molecules, 44 and 549 were synthesized and tested, respectively. This revealed an unprecedented phenolate inhibitor of AmpC, which was optimized to 77 nM, the most potent non-covalent AmpC inhibitor known. Crystal structures of this and other new AmpC inhibitors confirmed the docking predictions. Against D 4 , hit rates fell monotonically with docking score, and a hit-rate vs. score curve predicted 453,000 D 4 ligands in the library. Of 81 new chemotypes discovered, 30 were sub-micromolar, including a 180 pM sub-type selective agonist.

Enzymes fold into unique three-dimensional structures, which underlie their remarkable catalytic properties. The requirement to adopt a stable, folded conformation is likely to contribute to their relatively large size (> 10,000 Dalton). However, much shorter peptides can achieve well-defined conformations through the formation of amyloid fibrils. To test whether short amyloid-forming peptides might in fact be capable of enzyme-like catalysis, we designed a series of 7-residue peptides that act as Zn2+-dependent esterases. Zn2+ helps stabilize the fibril formation, while also acting as a cofactor to catalyze acyl ester hydrolysis. These results indicate that prion-like fibrils are able to not only catalyze their own formation – they also can catalyze chemical reactions. Thus, they might have served as intermediates in the evolution of modern-day enzymes. These results also have implications for the design of self-assembling nanostructured catalysts including ones containing a variety of biological and nonbiological metal ions.

On average, an approved drug today costs $2–3 billion and takes over ten years to develop 1 . In part, this is due to expensive and time-consuming wet-lab experiments, poor initial hit compounds, and the high attrition rates in the (pre-)clinical phases. Structure-based virtual screening (SBVS) has the potential to mitigate these problems. With SBVS, the quality of the hits improves with the number of compounds screened 2 . However, despite the fact that large compound databases exist, the ability to carry out large-scale SBVSs on computer clusters in an accessible, efficient, and flexible manner has remained elusive. Here we designed VirtualFlow, a highly automated and versatile open-source platform with perfect scaling behaviour that is able to prepare and efficiently screen ultra-large ligand libraries of compounds. VirtualFlow is able to use a variety of the most powerful docking programs. Using VirtualFlow, we have prepared the largest and freely available ready-to-dock ligand library available, with over 1.4 billion commercially available molecules. To demonstrate the power of VirtualFlow, we screened over 1 billion compounds and discovered a small molecule inhibitor (iKeap1) that engages KEAP1 with nanomolar affinity ( K d = 114 nM) and disrupts the interaction between KEAP1 and the transcription factor NRF2. We also identified a set of structurally diverse molecules that bind to KEAP1 with submicromolar affinity. This illustrates the potential of VirtualFlow to access vast regions of the chemical space and identify binders with high affinity for target proteins.

Identifying and purchasing new small molecules to test in biological assays are enabling for ligand discovery, but as purchasable chemical space continues to grow into the tens of billions based on inexpensive make-on-demand compounds, simply searching this space becomes a major challenge. We have therefore developed ZINC20, a new version of ZINC with two major new features: billions of new molecules and new methods to search them. As a fully enumerated database, ZINC can be searched precisely using explicit atomic-level graph-based methods, such as SmallWorld for similarity and Arthor for pattern and substructure search, as well as 3D methods such as docking. Analysis of the new make-on-demand compound sets by these and related tools reveals startling features. For instance, over 97% of the core Bemis–Murcko scaffolds in make-on-demand libraries are unavailable from “in-stock” collections. Correspondingly, the number of new Bemis–Murcko scaffolds is rising almost as a linear fraction of the elaborated molecules. Thus, an 88-fold increase in the number of molecules in the make-on-demand versus the in-stock sets is built upon a 16-fold increase in the number of Bemis–Murcko scaffolds. The make-on-demand library is also more structurally diverse than physical libraries, with a massive increase in disc- and sphere-like shaped molecules. The new system is freely available at .

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