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The development of bioactive small molecules as probes or drug candidates requires discovery platforms that enable access to chemical diversity and can quickly reveal new ligands for a target of interest. Within the past 15 years, DNA-encoded library (DEL) technology has matured into a widely used platform for small-molecule discovery, yielding a wide variety of bioactive ligands for many therapeutically relevant targets. DELs offer many advantages compared with traditional screening methods, including efficiency of screening, easily multiplexed targets and library selections, minimized resources needed to evaluate an entire DEL and large library sizes. This Review provides accounts of recently described small molecules discovered from DELs, including their initial identification, optimization and validation of biological properties including suitability for clinical applications.DNA-encoded library (DEL) technology is a powerful small-molecule discovery platform, offering many advantages over traditional screening methods. Here, Peterson and Liu provide an in-depth review of recent small molecules discovered through DELs, illustrating the versatility, efficiency and broad impact of this technology.

Drug repurposing, the application of an existing therapeutic to a new disease indication, holds promise of rapid clinical impact at a lower cost than de novo drug development. So far, there has not been a systematic effort to identify such opportunities, limited in part by the lack of a comprehensive library of clinical compounds suitable for testing. To address this challenge, we hand-curated a collection of 4,707 compounds, experimentally confirmed their identities, and annotated them with literature-reported targets. The collection includes 3,422 drugs that are marketed around the world or that have been tested in human clinical trials. Compounds were obtained from more than 50 chemical vendors, and the purity of each sample was established. We have thus established a blueprint for others to easily assemble such a repurposing library, and we have created an online Drug Repurposing Hub (http://www.broadinstitute.org/repurposing

Recently, ‘tangible’ virtual libraries have made billions of molecules readily available. Prioritizing these molecules for synthesis and testing demands computational approaches, such as docking. Their success may depend on library diversity, their similarity to bio-like molecules and how receptor fit and artifacts change with library size. We compared a library of 3 million ‘in-stock’ molecules with billion-plus tangible libraries. The bias toward bio-like molecules in the tangible library decreases 19,000-fold versus those ‘in-stock’. Similarly, thousands of high-ranking molecules, including experimental actives, from five ultra-large-library docking campaigns are also dissimilar to bio-like molecules. Meanwhile, better-fitting molecules are found as the library grows, with the score improving log-linearly with library size. Finally, as library size increases, so too do rare molecules that rank artifactually well. Although the nature of these artifacts changes from target to target, the expectation of their occurrence does not, and simple strategies can minimize their impact. Docking virtual libraries against protein structures has identified potent ligands for multiple targets. A comprehensive analysis reveals that the increased size of virtual libraries improves receptor fit but diverges from bio-like molecules.

In December 2019, the first cases of infection with a novel coronavirus, SARS-CoV-2, were diagnosed. Currently, there is no effective antiviral treatment for COVID-19. To address this emerging problem, we focused on the SARS-CoV-2 main protease that constitutes one of the most attractive antiviral drug targets. We have synthesized a combinatorial library of fluorogenic substrates with glutamine in the P1 position. We used it to determine the substrate preferences of the SARS-CoV and SARS-CoV-2 main proteases. On the basis of these findings, we designed and synthesized a potent SARS-CoV-2 inhibitor (Ac-Abu- d Tyr-Leu-Gln-VS, half-maximal effective concentration of 3.7 µM) and two activity-based probes, for one of which we determined the crystal structure of its complex with the SARS-CoV-2 M pro . We visualized active SARS-CoV-2 M pro in nasopharyngeal epithelial cells of patients suffering from COVID-19 infection. The results of our work provide a structural framework for the design of inhibitors as antiviral agents and/or diagnostic tests. Screening for substrate preference of the SARS-CoV and SARS-CoV-2 main protease M pro leads to the development of activity-based probes useful for structural analysis and for visualization of active M pro in infected patient epithelial cells.

Natural products (NPs) are a significant source of inspiration towards the discovery of new bioactive compounds based on novel molecular scaffolds. However, there are currently only a small number of guiding synthetic strategies available to generate novel NP-inspired scaffolds, limiting both the number and types of compounds accessible. In this Perspective, we discuss a design approach for the preparation of biologically relevant small-molecule libraries, harnessing the unprecedented combination of NP-derived fragments as an overarching strategy for the synthesis of new bioactive compounds. These novel ‘pseudo-natural product’ classes retain the biological relevance of NPs, yet exhibit structures and bioactivities not accessible to nature or through the use of existing design strategies. We also analyse selected pseudo-NP libraries using chemoinformatic tools, to assess their molecular shape diversity and properties. To facilitate the exploration of biologically relevant chemical space, we identify design principles and connectivity patterns that would provide access to unprecedented pseudo-NP classes, offering new opportunities for bioactive small-molecule discovery.The structures of biologically active natural products have long served as inspiration in drug discovery. This Perspective outlines design principles and connectivity patterns for the de novo combination of natural product-derived fragments. The resulting ‘pseudo-natural products’ retain biological relevance yet exhibit structures and bioactivities not found in the natural products and their derivatives.

The neuromodulator melatonin synchronizes circadian rhythms and related physiological functions through the actions of two G-protein-coupled receptors: MT 1 and MT 2 . Circadian release of melatonin at night from the pineal gland activates melatonin receptors in the suprachiasmatic nucleus of the hypothalamus, synchronizing the physiology and behaviour of animals to the light–dark cycle 1 – 4 . The two receptors are established drug targets for aligning circadian phase to this cycle in disorders of sleep 5 , 6 and depression 1 – 4 , 7 – 9 . Despite their importance, few in vivo active MT 1 -selective ligands have been reported 2 , 8 , 10 – 12 , hampering both the understanding of circadian biology and the development of targeted therapeutics. Here we docked more than 150 million virtual molecules to an MT 1 crystal structure, prioritizing structural fit and chemical novelty. Of these compounds, 38 high-ranking molecules were synthesized and tested, revealing ligands with potencies ranging from 470 picomolar to 6 micromolar. Structure-based optimization led to two selective MT 1 inverse agonists—which were topologically unrelated to previously explored chemotypes—that acted as inverse agonists in a mouse model of circadian re-entrainment. Notably, we found that these MT 1 -selective inverse agonists advanced the phase of the mouse circadian clock by 1.3–1.5 h when given at subjective dusk, an agonist-like effect that was eliminated in MT 1 - but not in MT 2 -knockout mice. This study illustrates the opportunities for modulating melatonin receptor biology through MT 1 -selective ligands and for the discovery of previously undescribed, in vivo active chemotypes from structure-based screens of diverse, ultralarge libraries. A computational screen of an ultra-large virtual library against the structure of the melatonin receptor found nanomolar ligands, and ultimately two selective MT 1 inverse agonists that induced phase advancement of the mouse circadian clock when given at subjective dusk.

DNA-encoded libraries have emerged as a widely used resource for the discovery of bioactive small molecules, and offer substantial advantages compared with conventional small-molecule libraries. Here, we have developed and streamlined multiple fundamental aspects of DNA-encoded and DNA-templated library synthesis methodology, including computational identification and experimental validation of a 20 × 20 × 20 × 80 set of orthogonal codons, chemical and computational tools for enhancing the structural diversity and drug-likeness of library members, a highly efficient polymerase-mediated template library assembly strategy, and library isolation and purification methods. We have integrated these improved methods to produce a second-generation DNA-templated library of 256,000 small-molecule macrocycles with improved drug-like physical properties. In vitro selection of this library for insulin-degrading enzyme affinity resulted in novel insulin-degrading enzyme inhibitors, including one of unusual potency and novel macrocycle stereochemistry (IC50 = 40 nM). Collectively, these developments enable DNA-templated small-molecule libraries to serve as more powerful, accessible, streamlined and cost-effective tools for bioactive small-molecule discovery.

The peptidyl-prolyl isomerase, Pin1, is exploited in cancer to activate oncogenes and inactivate tumor suppressors. However, despite considerable efforts, Pin1 has remained an elusive drug target. Here, we screened an electrophilic fragment library to identify covalent inhibitors targeting Pin1’s active site Cys113, leading to the development of Sulfopin, a nanomolar Pin1 inhibitor. Sulfopin is highly selective, as validated by two independent chemoproteomics methods, achieves potent cellular and in vivo target engagement and phenocopies Pin1 genetic knockout. Pin1 inhibition had only a modest effect on cancer cell line viability. Nevertheless, Sulfopin induced downregulation of c-Myc target genes, reduced tumor progression and conferred survival benefit in murine and zebrafish models of MYCN-driven neuroblastoma, and in a murine model of pancreatic cancer. Our results demonstrate that Sulfopin is a chemical probe suitable for assessment of Pin1-dependent pharmacology in cells and in vivo, and that Pin1 warrants further investigation as a potential cancer drug target. The development of Sulfopin, a highly selective and potent, covalent Pin1 inhibitor that phenocopies Pin1 knockout and regresses tumors in murine and zebrafish models of neuroblastoma as well as in a pancreatic cancer mouse model.

Small molecules are usually compared by their chemical structure, but there is no unified analytic framework for representing and comparing their biological activity. We present the Chemical Checker (CC), which provides processed, harmonized and integrated bioactivity data on ~800,000 small molecules. The CC divides data into five levels of increasing complexity, from the chemical properties of compounds to their clinical outcomes. In between, it includes targets, off-targets, networks and cell-level information, such as omics data, growth inhibition and morphology. Bioactivity data are expressed in a vector format, extending the concept of chemical similarity to similarity between bioactivity signatures. We show how CC signatures can aid drug discovery tasks, including target identification and library characterization. We also demonstrate the discovery of compounds that reverse and mimic biological signatures of disease models and genetic perturbations in cases that could not be addressed using chemical information alone. Overall, the CC signatures facilitate the conversion of bioactivity data to a format that is readily amenable to machine learning methods. The biological activities of >800,000 small molecules are represented within a uniform framework.

Chordoma is a primary bone cancer with no approved therapy1. The identification of therapeutic targets in this disease has been challenging due to the infrequent occurrence of clinically actionable somatic mutations in chordoma tumors2,3. Here we describe the discovery of therapeutically targetable chordoma dependencies via genome-scale CRISPR-Cas9 screening and focused small-molecule sensitivity profiling. These systematic approaches reveal that the developmental transcription factor T (brachyury; TBXT) is the top selectively essential gene in chordoma, and that transcriptional cyclin-dependent kinase (CDK) inhibitors targeting CDK7/12/13 and CDK9 potently suppress chordoma cell proliferation. In other cancer types, transcriptional CDK inhibitors have been observed to downregulate highly expressed, enhancer-associated oncogenic transcription factors4,5. In chordoma, we find that T is associated with a 1.5-Mb region containing ‘super-enhancers’ and is the most highly expressed super-enhancer-associated transcription factor. Notably, transcriptional CDK inhibition leads to preferential and concentration-dependent downregulation of cellular brachyury protein levels in all models tested. In vivo, CDK7/12/13-inhibitor treatment substantially reduces tumor growth. Together, these data demonstrate small-molecule targeting of brachyury transcription factor addiction in chordoma, identify a mechanism of T gene regulation that underlies this therapeutic strategy, and provide a blueprint for applying systematic genetic and chemical screening approaches to discover vulnerabilities in genomically quiet cancers.A combination of genome-scale CRISPR-Cas9 screening and focused small-molecule sensitivity profiling enables the discovery of therapeutically targetable tumor dependencies in rare tumors.