BET bromodomain inhibitors regulate keratinocyte plasticity.

Although most acute skin wounds heal rapidly, non-healing skin ulcers represent an increasing and substantial unmet medical need that urgently requires effective therapeutics. Keratinocytes resurface wounds to re-establish the epidermal barrier by transitioning to an activated, migratory state, but this ability is lost in dysfunctional chronic wounds. Small-molecule regulators of keratinocyte plasticity with the potential to reverse keratinocyte malfunction in situ could offer a novel therapeutic approach in skin wound healing. Utilizing high-throughput phenotypic screening of primary keratinocytes, we identify such small molecules, including bromodomain and extra-terminal domain (BET) protein family inhibitors (BETi). BETi induce a sustained activated, migratory state in keratinocytes in vitro, increase activation markers in human epidermis ex vivo and enhance skin wound healing in vivo. Our findings suggest potential clinical utility of BETi in promoting keratinocyte re-epithelialization of skin wounds. Importantly, this novel property of BETi is exclusively observed after transient low-dose exposure, revealing new potential for this compound class.

Enhancing the Small-Scale Screenable Biological Space beyond Known Chemogenomics Libraries with Gray Chemical Matter─Compounds with Novel Mechanisms from High-Throughput Screening Profiles.

Phenotypic assays have become an established approach to drug discovery. Greater disease relevance is often achieved through cellular models with increased complexity and more detailed readouts, such as gene expression or advanced imaging. However, the intricate nature and cost of these assays impose limitations on their screening capacity, often restricting screens to well-characterized small compound sets such as chemogenomics libraries. Here, we outline a cheminformatics approach to identify a small set of compounds with likely novel mechanisms of action (MoAs), expanding the MoA search space for throughput limited phenotypic assays. Our approach is based on mining existing large-scale, phenotypic high-throughput screening (HTS) data. It enables the identification of chemotypes that exhibit selectivity across multiple cell-based assays, which are characterized by persistent and broad structure activity relationships (SAR). We validate the effectiveness of our approach in broad cellular profiling assays (Cell Painting, DRUG-seq, and Promotor Signature Profiling) and chemical proteomics experiments. These experiments revealed that the compounds behave similarly to known chemogenetic libraries, but with a notable bias toward novel protein targets. To foster collaboration and advance research in this area, we have curated a public set of such compounds based on the PubChem BioAssay dataset and made it available for use by the scientific community.

Tyrosine kinase inhibitors can activate the NLRP3 inflammasome in myeloid cells through lysosomal damage and cell lysis.

Inflammasomes are intracellular protein complexes that promote an inflammatory host defense in response to pathogens and damaged or neoplastic tissues and are implicated in inflammatory disorders and therapeutic-induced toxicity. We investigated the mechanisms of activation for inflammasomes nucleated by NOD-like receptor (NLR) protiens. A screen of a small-molecule library revealed that several tyrosine kinase inhibitors (TKIs)-including those that are clinically approved (such as imatinib and crizotinib) or are in clinical trials (such as masitinib)-activated the NLRP3 inflammasome. Furthermore, imatinib and masitinib caused lysosomal swelling and damage independently of their kinase target, leading to cathepsin-mediated destabilization of myeloid cell membranes and, ultimately, cell lysis that was accompanied by potassium (K+) efflux, which activated NLRP3. This effect was specific to primary myeloid cells (such as peripheral blood mononuclear cells and mouse bone marrow-derived dendritic cells) and did not occur in other primary cell types or various cell lines. TKI-induced lytic cell death and NLRP3 activation, but not lysosomal damage, were prevented by stabilizing cell membranes. Our findings reveal a potential immunological off-target of some TKIs that may contribute to their clinical efficacy or to their adverse effects.

Screening in serum-derived medium reveals differential response to compounds targeting metabolism.

A challenge for screening new anticancer drugs is that efficacy in cell culture models is not always predictive of efficacy in patients. One limitation of standard cell culture is a reliance on non-physiological nutrient levels, which can influence cell metabolism and drug sensitivity. A general assessment of how physiological nutrients affect cancer cell response to small molecule therapies is lacking. To address this, we developed a serum-derived culture medium that supports the proliferation of diverse cancer cell lines and is amenable to high-throughput screening. We screened several small molecule libraries and found that compounds targeting metabolic enzymes were differentially effective in standard compared to serum-derived medium. We exploited the differences in nutrient levels between each medium to understand why medium conditions affected the response of cells to some compounds, illustrating how this approach can be used to screen potential therapeutics and understand how their efficacy is modified by available nutrients.

Screening in serum-derived medium reveals differential response to compounds targeting metabolism.

A challenge for screening new candidate drugs to treat cancer is that efficacy in cell culture models is not always predictive of efficacy in patients. One limitation of standard cell culture is a reliance on non-physiological nutrient levels to propagate cells. Which nutrients are available can influence how cancer cells use metabolism to proliferate and impact sensitivity to some drugs, but a general assessment of how physiological nutrients affect cancer cell response to small molecule therapies is lacking. To enable screening of compounds to determine how the nutrient environment impacts drug efficacy, we developed a serum-derived culture medium that supports the proliferation of diverse cancer cell lines and is amenable to high-throughput screening. We used this system to screen several small molecule libraries and found that compounds targeting metabolic enzymes were enriched as having differential efficacy in standard compared to serum-derived medium. We exploited the differences in nutrient levels between each medium to understand why medium conditions affected the response of cells to some compounds, illustrating how this approach can be used to screen potential therapeutics and understand how their efficacy is modified by available nutrients.

Small-molecule inhibition of APT1 affects Ras localization and signaling.

Cycles of depalmitoylation and repalmitoylation critically control the steady-state localization and function of various peripheral membrane proteins, such as Ras proto-oncogene products. Interference with acylation using small molecules is a strategy to modulate cellular localization--and thereby unregulated signaling--caused by palmitoylated Ras proteins. We present the knowledge-based development and characterization of a potent inhibitor of acyl protein thioesterase 1 (APT1), a bona fide depalmitoylating enzyme that is, so far, poorly characterized in cells. The inhibitor, palmostatin B, perturbs the cellular acylation cycle at the level of depalmitoylation and thereby causes a loss of the precise steady-state localization of palmitoylated Ras. As a consequence, palmostatin B induces partial phenotypic reversion in oncogenic HRasG12V-transformed fibroblasts. We identify APT1 as one of the thioesterases in the acylation cycle and show that this protein is a cellular target of the inhibitor.

Probing the bioactivity-relevant chemical space of robust reactions and common molecular building blocks.

In the search for new bioactive compounds, there is a trend toward increasingly complex compound libraries aiming to target the demanding targets of the future. In contrast, medicinal chemistry and traditional library design rely mainly on a small set of highly established and robust reactions. Here, we probe a set of 58 such reactions for their ability to sample the chemical space of known bioactive molecules, and the potential to create new scaffolds. Combined with ~26,000 common available building blocks, the reactions retrieve around 9% of a scaffold-diverse set of compounds active on human target proteins covering all major pharmaceutical target classes. Almost 80% of generated scaffolds from virtual one-step synthesis products are not present in a large set of known bioactive molecules for human targets, indicating potential for new discoveries. The results suggest that established synthesis resources are well suited to cover the known bioactivity-relevant chemical space and that there are plenty of unexplored regions accessible by these reactions, possibly providing valuable "low-hanging fruit" for hit discovery.

DRUG-seq Provides Unbiased Biological Activity Readouts for Neuroscience Drug Discovery.

Unbiased transcriptomic RNA-seq data has provided deep insights into biological processes. However, its impact in drug discovery has been narrow given high costs and low throughput. Proof-of-concept studies with Digital RNA with pertUrbation of Genes (DRUG)-seq demonstrated the potential to address this gap. We extended the DRUG-seq platform by subjecting it to rigorous testing and by adding an open-source analysis pipeline. The results demonstrate high reproducibility and ability to resolve the mechanism(s) of action for a diverse set of compounds. Furthermore, we demonstrate how this data can be incorporated into a drug discovery project aiming to develop therapeutics for schizophrenia using human stem cell-derived neurons. We identified both an on-target activation signature, induced by a set of chemically distinct positive allosteric modulators of the N-methyl-d-aspartate (NMDA) receptor, and independent off-target effects. Overall, the protocol and open-source analysis pipeline are a step toward industrializing RNA-seq for high-complexity transcriptomics studies performed at a saturating scale.

Interactive exploration of chemical space with Scaffold Hunter.

We describe Scaffold Hunter, a highly interactive computer-based tool for navigation in chemical space that fosters intuitive recognition of complex structural relationships associated with bioactivity. The program reads compound structures and bioactivity data, generates compound scaffolds, correlates them in a hierarchical tree-like arrangement, and annotates them with bioactivity. Brachiation along tree branches from structurally complex to simple scaffolds allows identification of new ligand types. We provide proof of concept for pyruvate kinase.

Bioactivity-guided mapping and navigation of chemical space.

The structure- and chemistry-based hierarchical organization of library scaffolds in tree-like arrangements provides a valid, intuitive means to map and navigate chemical space. We demonstrate that scaffold trees built using bioactivity as the key selection criterion for structural simplification during tree construction allow efficient and intuitive mapping, visualization and navigation of the chemical space defined by a given library, which in turn allows correlation of this chemical space with the investigated bioactivity and further compound design. Brachiation along the branches of such trees from structurally complex to simple scaffolds with retained yet varying bioactivity is feasible at high frequency for the five major pharmaceutically relevant target classes and allows for the identification of new inhibitor types for a given target. We provide proof of principle by identifying new active scaffolds for 5-lipoxygenase and the estrogen receptor ERalpha.

Mining for bioactive scaffolds with scaffold networks: improved compound set enrichment from primary screening data.

Identification of meaningful chemical patterns in the increasing amounts of high-throughput-generated bioactivity data available today is an increasingly important challenge for successful drug discovery. Herein, we present the scaffold network as a novel approach for mapping and navigation of chemical and biological space. A scaffold network represents the chemical space of a library of molecules consisting of all molecular scaffolds and smaller "parent" scaffolds generated therefrom by the pruning of rings, effectively leading to a network of common scaffold substructure relationships. This algorithm provides an extension of the scaffold tree algorithm that, instead of a network, generates a tree relationship between a heuristically rule-based selected subset of parent scaffolds. The approach was evaluated for the identification of statistically significantly active scaffolds from primary screening data for which the scaffold tree approach has already been shown to be successful. Because of the exhaustive enumeration of smaller scaffolds and the full enumeration of relationships between them, about twice as many statistically significantly active scaffolds were identified compared to the scaffold-tree-based approach. We suggest visualizing scaffold networks as islands of active scaffolds.

A collection of robust organic synthesis reactions for in silico molecule design.

A focused collection of organic synthesis reactions for computer-based molecule construction is presented. It is inspired by real-world chemistry and has been compiled in close collaboration with medicinal chemists to achieve high practical relevance. Virtual molecules assembled from existing starting material connected by these reactions are supposed to have an enhanced chance to be amenable to real chemical synthesis. About 50% of the reactions in the dataset are ring-forming reactions, which fosters the assembly of novel ring systems and innovative chemotypes. A comparison with a recent survey of the reactions used in early drug discovery revealed considerable overlaps with the collection presented here. The dataset is available encoded as computer-readable Reaction SMARTS expressions from the Supporting Information presented for this paper.

Development of highly potent inhibitors of the Ras-targeting human acyl protein thioesterases based on substrate similarity design.

A matter of common sense: a common recognition motif consisting of a negatively charged group five to six bonds away (red) from the (thio)ester functionality (green) and a positively charged tail group ten to twelve bonds away (blue) was identified in two native acyl protein thioesterase 1 (APT1) substrates. This similarity led to the design of potent inhibitors of the Ras-depalmitoylating enzyme APT1.

Gene-signature-derived IC50s/EC50s reflect the potency of causative upstream targets and downstream phenotypes.

Multiplexed gene-signature-based phenotypic assays are increasingly used for the identification and profiling of small molecule-tool compounds and drugs. Here we introduce a method (provided as R-package) for the quantification of the dose-response potency of a gene-signature as EC50 and IC50 values. Two signaling pathways were used as models to validate our methods: beta-adrenergic agonistic activity on cAMP generation (dedicated dataset generated for this study) and EGFR inhibitory effect on cancer cell viability. In both cases, potencies derived from multi-gene expression data were highly correlated with orthogonal potencies derived from cAMP and cell growth readouts, and superior to potencies derived from single individual genes. Based on our results we propose gene-signature potencies as a novel valid alternative for the quantitative prioritization, optimization and development of novel drugs.

Synthesis and structure-activity correlation of a brunsvicamide-inspired cyclopeptide collection.

Cyanobacterial cyclopeptides: A series of analogues of the cyanobacterial cyclopeptide brunsvicamide A was prepared by effective solid-support-based total synthesis. Variations in stereochemistry revealed the importance of the D-lysine and the L-isoleucine residues for the substrate-competitive inhibitory activity of brunsvicamide A against carboxypeptidase A. The brunsvicamides are modified cyclopeptides from cyanobacteria, cyclised through the epsilon-amino group of a D-lysine unit. They are functionalised with urea groups and show potent carboxypeptidase inhibitory activities. In order to unravel the structural parameters that determine their activities, a collection of brunsvicamide analogues with varied amino acid structures and stereochemistries was synthesised by a combined solution- and solid-phase approach. Biochemical investigation of the compound collection for carboxypeptidase A inhibition revealed that the presence of D-lysine and L-isoleucine in the urea section is important for inhibition. It was found that brunsvicamide A is a substrate-competitive inhibitor of carboxypeptidase A. These findings are in agreement with the substrate specificity of the enzyme and were rationalised by computational studies, which showed the high relevance of the lysine stereochemistry for inhibitory activity.

Synergism of virtual screening and medicinal chemistry: identification and optimization of allosteric antagonists of metabotropic glutamate receptor 1.

We report the identification of novel potent and selective metabotropic glutamate receptor 1 (mGluR1) antagonists by virtual screening and subsequent hit optimization. For ligand-based virtual screening, molecules were represented by a topological pharmacophore descriptor (CATS-2D) and clustered by a self-organizing map (SOM). The most promising compounds were tested in mGluR1 functional and binding assays. We identified a potent chemotype exhibiting selective antagonistic activity at mGluR1 (functional IC(50)=0.74+/-0.29 microM). Hit optimization yielded lead structure 16 with an affinity of K(i)=0.024+/-0.001 microM and greater than 1000-fold selectivity for mGluR1 versus mGluR5. Homology-based receptor modelling suggests a binding site compatible with previously reported mutation studies. Our study demonstrates the usefulness of ligand-based virtual screening for scaffold-hopping and rapid lead structure identification in early drug discovery projects.

Positive and negative modulation of group I metabotropic glutamate receptors.

A discriminating pharmacophore model for noncompetitive metabotropic glutamate receptor antagonists of subtype 1 (mGluR1) was developed that facilitated the discovery of moderately active mGluR1 antagonists. One scaffold was selected for the design of several focused libraries where different substitution patterns were introduced. This approach facilitated the discovery of potent mGluR1 antagonists, as well as positive and negative mGluR5 modulators, because both receptor subtypes share similar binding pockets. For mGluR1 antagonists, a homology model of the mGlu1 receptor was established, and a putative binding mode within the receptor's transmembrane domain was visualized.

DRUG-seq for miniaturized high-throughput transcriptome profiling in drug discovery.

Here we report Digital RNA with pertUrbation of Genes (DRUG-seq), a high-throughput platform for drug discovery. Pharmaceutical discovery relies on high-throughput screening, yet current platforms have limited readouts. RNA-seq is a powerful tool to investigate drug effects using transcriptome changes as a proxy, yet standard library construction is costly. DRUG-seq captures transcriptional changes detected in standard RNA-seq at 1/100th the cost. In proof-of-concept experiments profiling 433 compounds across 8 doses, transcription profiles generated from DRUG-seq successfully grouped compounds into functional clusters by mechanism of actions (MoAs) based on their intended targets. Perturbation differences reflected in transcriptome changes were detected for compounds engaging the same target, demonstrating the value of using DRUG-seq for understanding on and off-target activities. We demonstrate DRUG-seq captures common mechanisms, as well as differences between compound treatment and CRISPR on the same target. DRUG-seq provides a powerful tool for comprehensive transcriptome readout in a high-throughput screening environment.

A pseudo-ligand approach to virtual screening.

A virtual screening method is presented that is grounded on a receptor-derived pharmacophore model termed "virtual ligand" or "pseudo-ligand". The model represents an idealized constellation of potential ligand sites that interact with residues of the binding pocket. For rapid virtual screening of compound libraries the potential pharmacophore points of the virtual ligand are encoded as an alignment-free correlation vector, avoiding spatial alignment of pharmacophore features between the pharmacophore query (i.e., the virtual ligand) and the candidate molecule. The method was successfully applied to retrieving factor Xa inhibitors from a Ugi three-component combinatorial library, and yielded high enrichment of actives in a retrospective search for cyclooxygenase-2 (COX-2) inhibitors. The approach provides a concept for "de-orphanizing" potential drug targets and identifying ligands for hitherto unexplored or allosteric binding pockets.