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.

Pocket Crafter: a 3D generative modeling based workflow for the rapid generation of hit molecules in drug discovery.

We present a user-friendly molecular generative pipeline called Pocket Crafter, specifically designed to facilitate hit finding activity in the drug discovery process. This workflow utilized a three-dimensional (3D) generative modeling method Pocket2Mol, for the de novo design of molecules in spatial perspective for the targeted protein structures, followed by filters for chemical-physical properties and drug-likeness, structure-activity relationship analysis, and clustering to generate top virtual hit scaffolds. In our WDR5 case study, we acquired a focused set of 2029 compounds after a targeted searching within Novartis archived library based on the virtual scaffolds. Subsequently, we experimentally profiled these compounds, resulting in a novel chemical scaffold series that demonstrated activity in biochemical and biophysical assays. Pocket Crafter successfully prototyped an effective end-to-end 3D generative chemistry-based workflow for the exploration of new chemical scaffolds, which represents a promising approach in early drug discovery for hit identification.

Compound Activity Prediction with Dose-Dependent Transcriptomic Profiles and Deep Learning.

Predicting compound activity in assays is a long-standing challenge in drug discovery. Computational models based on compound-induced gene expression signatures from a single profiling assay have shown promise toward predicting compound activity in other, seemingly unrelated, assays. Applications of such models include predicting mechanisms-of-action (MoA) for phenotypic hits, identifying off-target activities, and identifying polypharmacologies. Here, we introduce transcriptomics-to-activity transformer (TAT) models that leverage gene expression profiles observed over compound treatment at multiple concentrations to predict the compound activity in other biochemical or cellular assays. We built TAT models based on gene expression data from a RASL-seq assay to predict the activity of 2692 compounds in 262 dose-response assays. We obtained useful models for 51% of the assays, as determined through a realistic held-out set. Prospectively, we experimentally validated the activity predictions of a TAT model in a malaria inhibition assay. With a 63% hit rate, TAT successfully identified several submicromolar malaria inhibitors. Our results thus demonstrate the potential of transcriptomic responses over compound concentration and the TAT modeling framework as a cost-efficient way to identify the bioactivities of promising compounds across many assays.

Activation of human STING by a molecular glue-like compound.

Stimulator of interferon genes (STING) is a dimeric transmembrane adapter protein that plays a key role in the human innate immune response to infection and has been therapeutically exploited for its antitumor activity. The activation of STING requires its high-order oligomerization, which could be induced by binding of the endogenous ligand, cGAMP, to the cytosolic ligand-binding domain. Here we report the discovery through functional screens of a class of compounds, named NVS-STGs, that activate human STING. Our cryo-EM structures show that NVS-STG2 induces the high-order oligomerization of human STING by binding to a pocket between the transmembrane domains of the neighboring STING dimers, effectively acting as a molecular glue. Our functional assays showed that NVS-STG2 could elicit potent STING-mediated immune responses in cells and antitumor activities in animal models.

The feasibility and preliminary effects of a pilot randomized controlled trial: Videoconferencing acceptance and commitment therapy in distressed family caregivers of people with dementia.

This pilot randomized controlled trial (RCT) examined preliminary effects of an 8-week videoconferencing acceptance and commitment therapy (ACT) program supplemented with psychoeducation materials on distressed family caregivers of persons living with dementia (PLWD) compared to the control group provided with psychoeducation materials only. Nineteen family caregivers of PLWD in the USA were randomly assigned to the ACT group or the control group. Data was collected at pretest, posttest, and 1-month follow-up (F/U). Compared to the control group, the ACT group showed a significantly larger reduction in grief at posttest, with a medium effect size. Small effects of ACT were found in anxiety, psychological quality of life, and engagement in meaningful activities at posttest and grief, engagement in meaningful activities, and psychological flexibility at F/U compared to the control group. These promising findings warrant a full-scale RCT with adequate power to measure the efficacy of videoconferencing ACT for caregivers of PLWD.

Effects of a coach-guided videoconferencing acceptance and commitment therapy intervention combined with psychoeducation on distressed individuals living with spinal cord injury: a preliminary mixed-methods study.

PURPOSE: This study examined effects of coach-guided videoconferencing acceptance and commitment therapy (ACT) accompanied by psychoeducation on distressed individuals with spinal cord injury (SCI) and explored participants' experiences in the intervention. MATERIALS AND METHODS: Ten people with SCI participated in 8 individual videoconferencing sessions delivered by trained coaches. Data using self-reported questionnaires and individual interviews was collected at pretest and posttest and analyzing using Wilcoxon signed-rank tests and interpretative phenomenological analysis (ClinicalTrials.gov ID: NCT04670406). RESULTS: Statistically significant improvements were found in depression, anxiety, stress, grief, engagement in meaningful activities, and self-compassion with medium to large effect sizes. There was no significant change in quality of life, resilience, and ACT processes. Participants gained a new way of thinking by: being aware of thoughts and emotions; exploring perceptions of others; and focusing on the present. Also, the intervention equipped participants to deal with challenges by: improving coping with SCI-related conditions; practicing self-compassion, acceptance, and meditation; and acquiring skills of value-based decision making and committed action. CONCLUSIONS: Findings contribute to the limited evidence as the first study that measured effects of videoconferencing ACT on people with SCI. Future randomized controlled trials are needed to measure efficacy of internet-delivered ACT for people with SCI.IMPLICATIONS FOR REHABILITATIONGuided videoconferencing ACT may reduce depressive symptoms, anxiety, stress, and grief and increase engagement in meaningful activities and self-compassion in people with SCI.Professionals may consider ACT as a supportive or adjunct service for people with SCI who experience psychological distress.

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.

Acceptance and Commitment Therapy (ACT) Guided Online for Distressed Caregivers of Persons Living with Dementia.

OBJECTIVES: This study examined the effects of a guided online acceptance and commitment therapy (ACT) intervention on distressed family caregivers of persons living with dementia and explored the experiences of these caregivers in the ACT intervention. METHODS: Seven family caregivers experiencing psychological distress individually participated in 10 ACT videoconference sessions guided by a trained coach. Quantitative data, such as psychological distress, burden, and ACT processes, were collected at pretest and posttest and analyzed using the Wilcoxon signed-rank test. Individual interviews were conducted at posttest and analyzed using interpretative phenomenological analysis. RESULTS: Statistically significant reductions were found in depressive symptoms, anxiety, stress, and burden (p < .05) with medium effect sizes. ACT sessions helped caregivers gain renewed strength by: being equipped with resources to use under distress throughout the caregiving journey; being more self-compassionate and taking care of one's self; and being more patient with relatives with dementia. CONCLUSIONS: Findings contribute to the limited evidence in guided online ACT for caregivers of persons living with dementia. Further studies with a larger sample size are needed to evaluate the efficacy of guided online ACT. CLINICAL IMPLICATIONS: Guided online ACT may reduce depressive symptoms, anxiety, stress, and burden of family caregivers of persons living with dementia.

Learning epistatic gene interactions from perturbation screens.

The treatment of complex diseases often relies on combinatorial therapy, a strategy where drugs are used to target multiple genes simultaneously. Promising candidate genes for combinatorial perturbation often constitute epistatic genes, i.e., genes which contribute to a phenotype in a non-linear fashion. Experimental identification of the full landscape of genetic interactions by perturbing all gene combinations is prohibitive due to the exponential growth of testable hypotheses. Here we present a model for the inference of pairwise epistatic, including synthetic lethal, gene interactions from siRNA-based perturbation screens. The model exploits the combinatorial nature of siRNA-based screens resulting from the high numbers of sequence-dependent off-target effects, where each siRNA apart from its intended target knocks down hundreds of additional genes. We show that conditional and marginal epistasis can be estimated as interaction coefficients of regression models on perturbation data. We compare two methods, namely glinternet and xyz, for selecting non-zero effects in high dimensions as components of the model, and make recommendations for the appropriate use of each. For data simulated from real RNAi screening libraries, we show that glinternet successfully identifies epistatic gene pairs with high accuracy across a wide range of relevant parameters for the signal-to-noise ratio of observed phenotypes, the effect size of epistasis and the number of observations per double knockdown. xyz is also able to identify interactions from lower dimensional data sets (fewer genes), but is less accurate for many dimensions. Higher accuracy of glinternet, however, comes at the cost of longer running time compared to xyz. The general model is widely applicable and allows mining the wealth of publicly available RNAi screening data for the estimation of epistatic interactions between genes. As a proof of concept, we apply the model to search for interactions, and potential targets for treatment, among previously published sets of siRNA perturbation screens on various pathogens. The identified interactions include both known epistatic interactions as well as novel findings.

Cell size homeostasis is maintained by CDK4-dependent activation of p38 MAPK.

While molecules that promote the growth of animal cells have been identified, it remains unclear how such signals are orchestrated to determine a characteristic target size for different cell types. It is increasingly clear that cell size is determined by size checkpoints-mechanisms that restrict the cell cycle progression of cells that are smaller than their target size. Previously, we described a p38 MAPK-dependent cell size checkpoint mechanism whereby p38 is selectively activated and prevents cell cycle progression in cells that are smaller than a given target size. In this study, we show that the specific target size required for inactivation of p38 and transition through the cell cycle is determined by CDK4 activity. Our data suggest a model whereby p38 and CDK4 cooperate analogously to the function of a thermostat: while p38 senses irregularities in size, CDK4 corresponds to the thermostat dial that sets the target size.

CYP27A1-dependent anti-melanoma activity of limonoid natural products targets mitochondrial metabolism.

Three limonoid natural products with selective anti-proliferative activity against BRAF(V600E) and NRAS(Q61K)-mutation-dependent melanoma cell lines were identified. Differential transcriptome analysis revealed dependency of compound activity on expression of the mitochondrial cytochrome P450 oxidase CYP27A1, a transcriptional target of melanogenesis-associated transcription factor (MITF). We determined that CYP27A1 activity is necessary for the generation of a reactive metabolite that proceeds to inhibit cellular proliferation. A genome-wide small interfering RNA screen in combination with chemical proteomics experiments revealed gene-drug functional epistasis, suggesting that these compounds target mitochondrial biogenesis and inhibit tumor bioenergetics through a covalent mechanism. Our work suggests a strategy for melanoma-specific targeting by exploiting the expression of MITF target gene CYP27A1 and inhibiting mitochondrial oxidative phosphorylation in BRAF mutant melanomas.

Acceptance and commitment therapy for family caregivers: A systematic review and meta-analysis.

Acceptance and commitment therapy is an emerging evidenced-based practice, but no systematic review regarding the effects of ACT on family caregivers has been conducted. This article examined the effects of ACT on family caregivers by conducting meta-analysis with a random effects model. Twenty-four articles were identified from four electronic databases searched up to 30 March 2020. Meta-analyses found moderate effects of ACT on depressive symptoms and quality of life, small effects on anxiety, and small to moderate effects on stress. Further ACT studies should be conducted to measure effects on different outcomes for various family caregiver populations.

Phenotypic landscape of intestinal organoid regeneration.

The development of intestinal organoids from single adult intestinal stem cells in vitro recapitulates the regenerative capacity of the intestinal epithelium1,2. Here we unravel the mechanisms that orchestrate both organoid formation and the regeneration of intestinal tissue, using an image-based screen to assay an annotated library of compounds. We generate multivariate feature profiles for hundreds of thousands of organoids to quantitatively describe their phenotypic landscape. We then use these phenotypic fingerprints to infer regulatory genetic interactions, establishing a new approach to the mapping of genetic interactions in an emergent system. This allows us to identify genes that regulate cell-fate transitions and maintain the balance between regeneration and homeostasis, unravelling previously unknown roles for several pathways, among them retinoic acid signalling. We then characterize a crucial role for retinoic acid nuclear receptors in controlling exit from the regenerative state and driving enterocyte differentiation. By combining quantitative imaging with RNA sequencing, we show the role of endogenous retinoic acid metabolism in initiating transcriptional programs that guide the cell-fate transitions of intestinal epithelium, and we identify an inhibitor of the retinoid X receptor that improves intestinal regeneration in vivo.

Systematic Chemogenetic Library Assembly.

Chemogenetic libraries, collections of well-defined chemical probes, provide tremendous value to biomedical research but require substantial effort to ensure diversity as well as quality of the contents. We have assembled a chemogenetic library by data mining and crowdsourcing institutional expertise. We are sharing our approach, lessons learned, and disclosing our current collection of 4,185 compounds with their primary annotated gene targets (https://github.com/Novartis/MoaBox). This physical collection is regularly updated and used broadly both within Novartis and in collaboration with external partners.

Author Correction: CPSF3-dependent pre-mRNA processing as a druggable node in AML and Ewing's sarcoma.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

CPSF3-dependent pre-mRNA processing as a druggable node in AML and Ewing's sarcoma.

The post-genomic era has seen many advances in our understanding of cancer pathways, yet resistance and tumor heterogeneity necessitate multiple approaches to target even monogenic tumors. Here, we combine phenotypic screening with chemical genetics to identify pre-messenger RNA endonuclease cleavage and polyadenylation specificity factor 3 (CPSF3) as the target of JTE-607, a small molecule with previously unknown target. We show that CPSF3 represents a synthetic lethal node in a subset of acute myeloid leukemia (AML) and Ewing's sarcoma cancer cell lines. Inhibition of CPSF3 by JTE-607 alters expression of known downstream effectors in AML and Ewing's sarcoma lines, upregulates apoptosis and causes tumor-selective stasis in mouse xenografts. Mechanistically, it prevents the release of newly synthesized pre-mRNAs, resulting in read-through transcription and the formation of DNA-RNA hybrid R-loop structures. This study implicates pre-mRNA processing, and specifically CPSF3, as a druggable target providing an avenue to therapeutic intervention in cancer.

Benchmarking network algorithms for contextualizing genes of interest.

Computational approaches have shown promise in contextualizing genes of interest with known molecular interactions. In this work, we evaluate seventeen previously published algorithms based on characteristics of their output and their performance in three tasks: cross validation, prediction of drug targets, and behavior with random input. Our work highlights strengths and weaknesses of each algorithm and results in a recommendation of algorithms best suited for performing different tasks.

Cheminformatics Tools for Analyzing and Designing Optimized Small-Molecule Collections and Libraries.

Libraries of well-annotated small molecules have many uses in chemical genetics, drug discovery, and therapeutic repurposing. Multiple libraries are available, but few data-driven approaches exist to compare them and design new libraries. We describe an approach to scoring and creating libraries based on binding selectivity, target coverage, and induced cellular phenotypes as well as chemical structure, stage of clinical development, and user preference. The approach, available via the online tool http://www.smallmoleculesuite.org, assembles sets of compounds with the lowest possible off-target overlap. Analysis of six kinase inhibitor libraries using our approach reveals dramatic differences among them and led us to design a new LSP-OptimalKinase library that outperforms existing collections in target coverage and compact size. We also describe a mechanism of action library that optimally covers 1,852 targets in the liganded genome. Our tools facilitate creation, analysis, and updates of both private and public compound collections.

Discovery of a ZIP7 inhibitor from a Notch pathway screen.

The identification of activating mutations in NOTCH1 in 50% of T cell acute lymphoblastic leukemia has generated interest in elucidating how these mutations contribute to oncogenic transformation and in targeting the pathway. A phenotypic screen identified compounds that interfere with trafficking of Notch and induce apoptosis via an endoplasmic reticulum (ER) stress mechanism. Target identification approaches revealed a role for SLC39A7 (ZIP7), a zinc transport family member, in governing Notch trafficking and signaling. Generation and sequencing of a compound-resistant cell line identified a V430E mutation in ZIP7 that confers transferable resistance to the compound NVS-ZP7-4. NVS-ZP7-4 altered zinc in the ER, and an analog of the compound photoaffinity labeled ZIP7 in cells, suggesting a direct interaction between the compound and ZIP7. NVS-ZP7-4 is the first reported chemical tool to probe the impact of modulating ER zinc levels and investigate ZIP7 as a novel druggable node in the Notch pathway.