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The need to control the activity and fidelity of CRISPR-associated nucleases has resulted in a demand for inhibitory anti-CRISPR molecules. The small-molecule inhibitor discovery platforms available at present are not generalizable to multiple nuclease classes, only target the initial step in the catalytic activity and require high concentrations of nuclease, resulting in inhibitors with suboptimal attributes, including poor potency. Here we report a high-throughput discovery pipeline consisting of a fluorescence resonance energy transfer-based assay that is generalizable to contemporary and emerging nucleases, operates at low nuclease concentrations and targets all catalytic steps. We applied this pipeline to identify BRD7586, a cell-permeable small-molecule inhibitor of SpCas9 that is twofold more potent than other inhibitors identified to date. Furthermore, unlike the reported inhibitors, BRD7586 enhanced SpCas9 specificity and its activity was independent of the genomic loci, DNA-repair pathway or mode of nuclease delivery. Overall, these studies describe a general pipeline to identify inhibitors of contemporary and emerging CRISPR-associated nucleases., (© 2022. The Author(s), under exclusive licence to Springer Nature Limited.)

Clinical, biomedical, and translational science has reached an inflection point in the breadth and diversity of available data and the potential impact of such data to improve human health and well-being. However, the data are often siloed, disorganized, and not broadly accessible due to discipline-specific differences in terminology and representation. To address these challenges, the Biomedical Data Translator Consortium has developed and tested a pilot knowledge graph-based "Translator" system capable of integrating existing biomedical data sets and "translating" those data into insights intended to augment human reasoning and accelerate translational science. Having demonstrated feasibility of the Translator system, the Translator program has since moved into development, and the Translator Consortium has made significant progress in the research, design, and implementation of an operational system. Herein, we describe the current system's architecture, performance, and quality of results. We apply Translator to several real-world use cases developed in collaboration with subject-matter experts. Finally, we discuss the scientific and technical features of Translator and compare those features to other state-of-the-art, biomedical graph-based question-answering systems., (© 2022 The Authors. Clinical and Translational Science published by Wiley Periodicals LLC on behalf of American Society for Clinical Pharmacology and Therapeutics.)

Small-molecule discovery typically involves large-scale screening campaigns, spanning multiple compound collections. However, such activities can be cost- or time-prohibitive, especially when using complex assay systems, limiting the number of compounds tested. Further, low hit rates can make the process inefficient. Sparse coverage of chemical structure or biological activity space can lead to limited success in a primary screen and represents a missed opportunity by virtue of selecting the "wrong" compounds to test. Thus, the choice of screening collections becomes of paramount importance. In this perspective, we discuss the utility of generating "informer sets" for small-molecule discovery, and how this strategy can be leveraged to prioritize probe candidates. While many researchers may assume that informer sets are focused on particular targets (e.g., kinases) or processes (e.g., autophagy), efforts to assemble informer sets based on historical bioactivity or successful human exposure (e.g., repurposing collections) have shown promise as well. Another method for generating informer sets is based on chemical structure, particularly when the compounds have unknown activities and targets. We describe our efforts to screen an informer set representing a collection of 100,000 small molecules synthesized through diversity-oriented synthesis (DOS). This process enables researchers to identify activity early and more extensively screen only a few chemical scaffolds, rather than the entire collection. This elegant and economic outcome is a goal of the informer set approach. Here, we aim not only to shed light on this process, but also to promote the use of informer sets more widely in small-molecule discovery projects.

Availability: The API and associated software is open source and currently available for access at https://github.com/NCATS-Tangerine/translator-knowledge-beacon., Competing Interests: The commercial role of RMB within STAR Informatics / Delphinai Corporation is one of Founder CEO and Principal Scientist of the firm. All other authors working for the firm conducted the work under regular full-time or temporary employment contract basis, under primary supervision by RMB. The Biomedical Data Translator project outputs for this paper, open sourced and access in nature, as delivered by the consultancy subcontract, do not represent any other marketable commercial benefit to the firm in terms of patents, products in development, or marketed products. This does not alter our adherence to PLOS ONE policies on sharing data and materials.

Ferroptosis-an iron-dependent, non-apoptotic cell death process-is involved in various degenerative diseases and represents a targetable susceptibility in certain cancers 1 . The ferroptosis-susceptible cell state can either pre-exist in cells that arise from certain lineages or be acquired during cell-state transitions 2-5 . However, precisely how susceptibility to ferroptosis is dynamically regulated remains poorly understood. Here we use genome-wide CRISPR-Cas9 suppressor screens to identify the oxidative organelles peroxisomes as critical contributors to ferroptosis sensitivity in human renal and ovarian carcinoma cells. Using lipidomic profiling we show that peroxisomes contribute to ferroptosis by synthesizing polyunsaturated ether phospholipids (PUFA-ePLs), which act as substrates for lipid peroxidation that, in turn, results in the induction of ferroptosis. Carcinoma cells that are initially sensitive to ferroptosis can switch to a ferroptosis-resistant state in vivo in mice, which is associated with extensive downregulation of PUFA-ePLs. We further find that the pro-ferroptotic role of PUFA-ePLs can be extended beyond neoplastic cells to other cell types, including neurons and cardiomyocytes. Together, our work reveals roles for the peroxisome-ether-phospholipid axis in driving susceptibility to and evasion from ferroptosis, highlights PUFA-ePL as a distinct functional lipid class that is dynamically regulated during cell-state transitions, and suggests multiple regulatory nodes for therapeutic interventions in diseases that involve ferroptosis.

The precise control of CRISPR-Cas9 activity is required for a number of genome engineering technologies. Here, we report a generalizable platform that provided the first synthetic small-molecule inhibitors of Streptococcus pyogenes Cas9 (SpCas9) that weigh <500 Da and are cell permeable, reversible, and stable under physiological conditions. We developed a suite of high-throughput assays for SpCas9 functions, including a primary screening assay for SpCas9 binding to the protospacer adjacent motif, and used these assays to screen a structurally diverse collection of natural-product-like small molecules to ultimately identify compounds that disrupt the SpCas9-DNA interaction. Using these synthetic anti-CRISPR small molecules, we demonstrated dose and temporal control of SpCas9 and catalytically impaired SpCas9 technologies, including transcription activation, and identified a pharmacophore for SpCas9 inhibition using structure-activity relationships. These studies establish a platform for rapidly identifying synthetic, miniature, cell-permeable, and reversible inhibitors against both SpCas9 and next-generation CRISPR-associated nucleases., (Published by Elsevier Inc.)

The development of site-specific recombinases (SSRs) as genome editing agents is limited by the difficulty of altering their native DNA specificities. Here we describe Rec-seq, a method for revealing the DNA specificity determinants and potential off-target substrates of SSRs in a comprehensive and unbiased manner. We applied Rec-seq to characterize the DNA specificity determinants of several natural and evolved SSRs including Cre, evolved variants of Cre, and other SSR family members. Rec-seq profiling of these enzymes and mutants thereof revealed previously uncharacterized SSR interactions, including specificity determinants not evident from SSR:DNA structures. Finally, we used Rec-seq specificity profiles to predict off-target substrates of Tre and Brec1 recombinases, including endogenous human genomic sequences, and confirmed their ability to recombine these off-target sequences in human cells. These findings establish Rec-seq as a high-resolution method for rapidly characterizing the DNA specificity of recombinases with single-nucleotide resolution, and for informing their further development.

Clear-cell carcinomas (CCCs) are a histological group of highly aggressive malignancies commonly originating in the kidney and ovary. CCCs are distinguished by aberrant lipid and glycogen accumulation and are refractory to a broad range of anti-cancer therapies. Here we identify an intrinsic vulnerability to ferroptosis associated with the unique metabolic state in CCCs. This vulnerability transcends lineage and genetic landscape, and can be exploited by inhibiting glutathione peroxidase 4 (GPX4) with small-molecules. Using CRISPR screening and lipidomic profiling, we identify the hypoxia-inducible factor (HIF) pathway as a driver of this vulnerability. In renal CCCs, HIF-2α selectively enriches polyunsaturated lipids, the rate-limiting substrates for lipid peroxidation, by activating the expression of hypoxia-inducible, lipid droplet-associated protein (HILPDA). Our study suggests targeting GPX4 as a therapeutic opportunity in CCCs, and highlights that therapeutic approaches can be identified on the basis of cell states manifested by morphological and metabolic features in hard-to-treat cancers.

Advances in human genetics have dramatically expanded our understanding of complex heritable diseases. Genome-wide association studies have identified an allelic series of CARD9 variants associated with increased risk of or protection from inflammatory bowel disease (IBD). The predisposing variant of CARD9 is associated with increased NF-κB-mediated cytokine production. Conversely, the protective variant lacks a functional C-terminal domain and is unable to recruit the E3 ubiquitin ligase TRIM62. Here, we used biochemical insights into CARD9 variant proteins to create a blueprint for IBD therapeutics and recapitulated the mechanism of the CARD9 protective variant using small molecules. We developed a multiplexed bead-based technology to screen compounds for disruption of the CARD9-TRIM62 interaction. We identified compounds that directly and selectively bind CARD9, disrupt TRIM62 recruitment, inhibit TRIM62-mediated ubiquitinylation of CARD9, and demonstrate cellular activity and selectivity in CARD9-dependent pathways. Taken together, small molecules targeting CARD9 illustrate a path toward improved IBD therapeutics., Competing Interests: Conflict of interest statement: S.L.S. and B.F.C. were coauthors on a 2015 review article. S.L.S. and K.M.S. were coauthors on a 2015 research paper. B.F.C. and K.M.S. independently supplied reagents to the same laboratory. There was no active collaboration., (Published under the PNAS license.)

Broadly neutralizing monoclonal antibodies (bNAbs) for viral infections, such as HIV, respiratory syncytial virus (RSV), and influenza, are increasingly entering clinical development. For influenza, most neutralizing antibodies target influenza virus hemagglutinin. These bNAbs represent an emerging, promising modality for treatment and prophylaxis of influenza due to their multiple mechanisms of antiviral action and generally safe profile. Preclinical work in other viral diseases, such as dengue, has demonstrated the potential for antibody-based therapies to enhance viral uptake, leading to enhanced viremia and worsening of disease. This phenomenon is referred to as antibody-dependent enhancement (ADE). In the context of influenza, ADE has been used to explain several preclinical and clinical phenomena. Using structural and viral kinetics modeling, we assess the role of ADE in the treatment of influenza with a bNAb., (Copyright © 2016. Published by Elsevier Ltd.)

Purpose: We used human stem and progenitor cells to develop a genetically accurate novel model of MYC-driven Group 3 medulloblastoma. We also developed a new informatics method, Disease-model Signature versus Compound-Variety Enriched Response ("DiSCoVER"), to identify novel therapeutics that target this specific disease subtype., Experimental Design: Human neural stem and progenitor cells derived from the cerebellar anlage were transduced with oncogenic elements associated with aggressive medulloblastoma. An in silico analysis method for screening drug sensitivity databases (DiSCoVER) was used in multiple drug sensitivity datasets. We validated the top hits from this analysis in vitro and in vivo, Results: Human neural stem and progenitor cells transformed with c-MYC, dominant-negative p53, constitutively active AKT and hTERT formed tumors in mice that recapitulated Group 3 medulloblastoma in terms of pathology and expression profile. DiSCoVER analysis predicted that aggressive MYC-driven Group 3 medulloblastoma would be sensitive to cyclin-dependent kinase (CDK) inhibitors. The CDK 4/6 inhibitor palbociclib decreased proliferation, increased apoptosis, and significantly extended the survival of mice with orthotopic medulloblastoma xenografts., Conclusions: We present a new method to generate genetically accurate models of rare tumors, and a companion computational methodology to find therapeutic interventions that target them. We validated our human neural stem cell model of MYC-driven Group 3 medulloblastoma and showed that CDK 4/6 inhibitors are active against this subgroup. Our results suggest that palbociclib is a potential effective treatment for poor prognosis MYC-driven Group 3 medulloblastoma tumors in carefully selected patients. Clin Cancer Res; 22(15); 3903-14. ©2016 AACR., Competing Interests: The authors report no conflict of interest, (©2016 American Association for Cancer Research.)

Restoring functional β-cell mass is an important therapeutic goal for both type 1 and type 2 diabetes (1). While proliferation of existing β-cells is the primary means of β-cell replacement in rodents (2), it is unclear whether a similar principle applies to humans, as human β-cells are remarkably resistant to stimulation of division (3,4). Here, we show that 5-iodotubercidin (5-IT), an annotated adenosine kinase inhibitor previously reported to increase proliferation in rodent and porcine islets (5), strongly and selectively increases human β-cell proliferation in vitro and in vivo. Remarkably, 5-IT also increased glucose-dependent insulin secretion after prolonged treatment. Kinome profiling revealed 5-IT to be a potent and selective inhibitor of the dual-specificity tyrosine phosphorylation-regulated kinase (DYRK) and cell division cycle-like kinase families. Induction of β-cell proliferation by either 5-IT or harmine, another natural product DYRK1A inhibitor, was suppressed by coincubation with the calcineurin inhibitor FK506, suggesting involvement of DYRK1A and nuclear factor of activated T cells signaling. Gene expression profiling in whole islets treated with 5-IT revealed induction of proliferation- and cell cycle-related genes, suggesting that true proliferation is induced by 5-IT. Furthermore, 5-IT promotes β-cell proliferation in human islets grafted under the kidney capsule of NOD-scid IL2Rg(null) mice. These results point to inhibition of DYRK1A as a therapeutic strategy to increase human β-cell proliferation., (© 2016 by the American Diabetes Association. Readers may use this article as long as the work is properly cited, the use is educational and not for profit, and the work is not altered.)

Changes in cellular gene expression in response to small-molecule or genetic perturbations have yielded signatures that can connect unknown mechanisms of action (MoA) to ones previously established. We hypothesized that differential basal gene expression could be correlated with patterns of small-molecule sensitivity across many cell lines to illuminate the actions of compounds whose MoA are unknown. To test this idea, we correlated the sensitivity patterns of 481 compounds with ∼19,000 basal transcript levels across 823 different human cancer cell lines and identified selective outlier transcripts. This process yielded many novel mechanistic insights, including the identification of activation mechanisms, cellular transporters and direct protein targets. We found that ML239, originally identified in a phenotypic screen for selective cytotoxicity in breast cancer stem-like cells, most likely acts through activation of fatty acid desaturase 2 (FADS2). These data and analytical tools are available to the research community through the Cancer Therapeutics Response Portal.

Unlabelled: Identifying genetic alterations that prime a cancer cell to respond to a particular therapeutic agent can facilitate the development of precision cancer medicines. Cancer cell-line (CCL) profiling of small-molecule sensitivity has emerged as an unbiased method to assess the relationships between genetic or cellular features of CCLs and small-molecule response. Here, we developed annotated cluster multidimensional enrichment analysis to explore the associations between groups of small molecules and groups of CCLs in a new, quantitative sensitivity dataset. This analysis reveals insights into small-molecule mechanisms of action, and genomic features that associate with CCL response to small-molecule treatment. We are able to recapitulate known relationships between FDA-approved therapies and cancer dependencies and to uncover new relationships, including for KRAS-mutant cancers and neuroblastoma. To enable the cancer community to explore these data, and to generate novel hypotheses, we created an updated version of the Cancer Therapeutic Response Portal (CTRP v2)., Significance: We present the largest CCL sensitivity dataset yet available, and an analysis method integrating information from multiple CCLs and multiple small molecules to identify CCL response predictors robustly. We updated the CTRP to enable the cancer research community to leverage these data and analyses., (©2015 American Association for Cancer Research.)

Studies of human genetics and pathophysiology have implicated the regulation of autophagy in inflammation, neurodegeneration, infection, and autoimmunity. These findings have motivated the use of small-molecule probes to study how modulation of autophagy affects disease-associated phenotypes. Here, we describe the discovery of the small-molecule probe BRD5631 that is derived from diversity-oriented synthesis and enhances autophagy through an mTOR-independent pathway. We demonstrate that BRD5631 affects several cellular disease phenotypes previously linked to autophagy, including protein aggregation, cell survival, bacterial replication, and inflammatory cytokine production. BRD5631 can serve as a valuable tool for studying the role of autophagy in the context of cellular homeostasis and disease.

Phenotypic cell-based screening is a powerful approach to small-molecule discovery, but a major challenge of this strategy lies in determining the intracellular target and mechanism of action (MoA) for validated hits. Here, we show that the small-molecule BRD0476, a novel suppressor of pancreatic β-cell apoptosis, inhibits interferon-gamma (IFN-γ)-induced Janus kinase 2 (JAK2) and signal transducer and activation of transcription 1 (STAT1) signaling to promote β-cell survival. However, unlike common JAK-STAT pathway inhibitors, BRD0476 inhibits JAK-STAT signaling without suppressing the kinase activity of any JAK. Rather, we identified the deubiquitinase ubiquitin-specific peptidase 9X (USP9X) as an intracellular target, using a quantitative proteomic analysis in rat β cells. RNAi-mediated and CRISPR/Cas9 knockdown mimicked the effects of BRD0476, and reverse chemical genetics using a known inhibitor of USP9X blocked JAK-STAT signaling without suppressing JAK activity. Site-directed mutagenesis of a putative ubiquitination site on JAK2 mitigated BRD0476 activity, suggesting a competition between phosphorylation and ubiquitination to explain small-molecule MoA. These results demonstrate that phenotypic screening, followed by comprehensive MoA efforts, can provide novel mechanistic insights into ostensibly well-understood cell signaling pathways. Furthermore, these results uncover USP9X as a potential target for regulating JAK2 activity in cellular inflammation., Competing Interests: Notes The authors declare no competing financial interest.

Novel therapeutic approaches are urgently required for multiple myeloma (MM). We used a phenotypic screening approach using co-cultures of MM cells with bone marrow stromal cells to identify compounds that overcome stromal resistance. One such compound, BRD9876, displayed selectivity over normal hematopoietic progenitors and was discovered to be an unusual ATP non-competitive kinesin-5 (Eg5) inhibitor. A novel mutation caused resistance, suggesting a binding site distinct from known Eg5 inhibitors, and BRD9876 inhibited only microtubule-bound Eg5. Eg5 phosphorylation, which increases microtubule binding, uniquely enhanced BRD9876 activity. MM cells have greater phosphorylated Eg5 than hematopoietic cells, consistent with increased vulnerability specifically to BRD9876's mode of action. Thus, differences in Eg5-microtubule binding between malignant and normal blood cells may be exploited to treat multiple myeloma. Additional steps are required for further therapeutic development, but our results indicate that unbiased chemical biology approaches can identify therapeutic strategies unanticipated by prior knowledge of protein targets., (Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.)

Defects in insulin secretion play a central role in the pathogenesis of type 2 diabetes, yet the mechanisms driving beta-cell dysfunction remain poorly understood, and therapies to preserve glucose-dependent insulin release are inadequate. We report a luminescent insulin secretion assay that enables large-scale investigations of beta-cell function, created by inserting Gaussia luciferase into the C-peptide portion of proinsulin. Beta-cell lines expressing this construct cosecrete luciferase and insulin in close correlation, under both standard conditions or when stressed by cytokines, fatty acids, or ER toxins. We adapted the reporter for high-throughput assays and performed a 1,600-compound pilot screen, which identified several classes of drugs inhibiting secretion, as well as glucose-potentiated secretagogues that were confirmed to have activity in primary human islets. Requiring 40-fold less time and expense than the traditional ELISA, this assay may accelerate the identification of pathways governing insulin secretion and compounds that safely augment beta-cell function in diabetes., (Copyright © 2015 Elsevier Inc. All rights reserved.)

Genetic alterations that reduce the function of the immunoregulatory cytokine IL-10 contribute to colitis in mouse and man. Myeloid cells such as macrophages (MΦs) and dendritic cells (DCs) play an essential role in determining the relative abundance of IL-10 versus inflammatory cytokines in the gut. As such, using small molecules to boost IL-10 production by DCs-MΦs represents a promising approach to increase levels of this cytokine specifically in gut tissues. Toward this end, we screened a library of well-annotated kinase inhibitors for compounds that enhance production of IL-10 by murine bone-marrow-derived DCs stimulated with the yeast cell wall preparation zymosan. This approach identified a number of kinase inhibitors that robustly up-regulate IL-10 production including the Food and Drug Administration (FDA)-approved drugs dasatinib, bosutinib, and saracatinib that target ABL, SRC-family, and numerous other kinases. Correlating the kinase selectivity profiles of the active compounds with their effect on IL-10 production suggests that inhibition of salt-inducible kinases (SIKs) mediates the observed IL-10 increase. This was confirmed using the SIK-targeting inhibitor HG-9-91-01 and a series of structural analogs. The stimulatory effect of SIK inhibition on IL-10 is also associated with decreased production of the proinflammatory cytokines IL-1β, IL-6, IL-12, and TNF-α, and these coordinated effects are observed in human DCs-MΦs and anti-inflammatory CD11c(+) CX3CR1(hi) cells isolated from murine gut tissue. Collectively, these studies demonstrate that SIK inhibition promotes an anti-inflammatory phenotype in activated myeloid cells marked by robust IL-10 production and establish these effects as a previously unidentified activity associated with several FDA-approved multikinase inhibitors.

High-throughput screening has become a mainstay of small-molecule probe and early drug discovery. The question of how to build and evolve efficient screening collections systematically for cell-based and biochemical screening is still unresolved. It is often assumed that chemical structure diversity leads to diverse biological performance of a library. Here, we confirm earlier results showing that this inference is not always valid and suggest instead using biological measurement diversity derived from multiplexed profiling in the construction of libraries with diverse assay performance patterns for cell-based screens. Rather than using results from tens or hundreds of completed assays, which is resource intensive and not easily extensible, we use high-dimensional image-based cell morphology and gene expression profiles. We piloted this approach using over 30,000 compounds. We show that small-molecule profiling can be used to select compound sets with high rates of activity and diverse biological performance.

Understanding the structure-activity relationships (SARs) of small molecules is important for developing probes and novel therapeutic agents in chemical biology and drug discovery. Increasingly, multiplexed small-molecule profiling assays allow simultaneous measurement of many biological response parameters for the same compound (e.g., expression levels for many genes or binding constants against many proteins). Although such methods promise to capture SARs with high granularity, few computational methods are available to support SAR analyses of high-dimensional compound activity profiles. Many of these methods are not generally applicable or reduce the activity space to scalar summary statistics before establishing SARs. In this article, we present a versatile computational method that automatically extracts interpretable SAR rules from high-dimensional profiling data. The rules connect chemical structural features of compounds to patterns in their biological activity profiles. We applied our method to data from novel cell-based gene-expression and imaging assays collected on more than 30,000 small molecules. Based on the rules identified for this data set, we prioritized groups of compounds for further study, including a novel set of putative histone deacetylase inhibitors., (© 2014 Society for Laboratory Automation and Screening.)

High-throughput screening allows rapid identification of new candidate compounds for biological probe or drug development. Here, we describe a principled method to generate "assay performance profiles" for individual compounds that can serve as a basis for similarity searches and cluster analyses. Our method overcomes three challenges associated with generating robust assay performance profiles: (1) we transform data, allowing us to build profiles from assays having diverse dynamic ranges and variability; (2) we apply appropriate mathematical principles to handle missing data; and (3) we mitigate the fact that loss-of-signal assay measurements may not distinguish between multiple mechanisms that can lead to certain phenotypes (e.g., cell death). Our method connected compounds with similar mechanisms of action, enabling prediction of new targets and mechanisms both for known bioactives and for compounds emerging from new screens. Furthermore, we used Bayesian modeling of promiscuous compounds to distinguish between broadly bioactive and narrowly bioactive compound communities. Several examples illustrate the utility of our method to support mechanism-of-action studies in probe development and target identification projects., (© 2014 Society for Laboratory Automation and Screening.)

Type-1 diabetes (T1D) is an autoimmune disease in which insulin-secreting pancreatic beta cells are destroyed by the immune system. An emerging strategy to regenerate beta-cell mass is through transdifferentiation of pancreatic alpha cells to beta cells. We previously reported two small molecules, BRD7389 and GW8510, that induce insulin expression in a mouse alpha cell line and provide a glimpse into potential intermediate cell states in beta-cell reprogramming from alpha cells. These small-molecule studies suggested that inhibition of kinases in particular may induce the expression of several beta-cell markers in alpha cells. To identify potential lineage reprogramming protein targets, we compared the transcriptome, proteome, and phosphoproteome of alpha cells, beta cells, and compound-treated alpha cells. Our phosphoproteomic analysis indicated that two kinases, BRSK1 and CAMKK2, exhibit decreased phosphorylation in beta cells compared to alpha cells, and in compound-treated alpha cells compared to DMSO-treated alpha cells. Knock-down of these kinases in alpha cells resulted in expression of key beta-cell markers. These results provide evidence that perturbation of the kinome may be important for lineage reprogramming of alpha cells to beta cells.

Target-identification and mechanism-of-action studies have important roles in small-molecule probe and drug discovery. Biological and technological advances have resulted in the increasing use of cell-based assays to discover new biologically active small molecules. Such studies allow small-molecule action to be tested in a more disease-relevant setting at the outset, but they require follow-up studies to determine the precise protein target or targets responsible for the observed phenotype. Target identification can be approached by direct biochemical methods, genetic interactions or computational inference. In many cases, however, combinations of approaches may be required to fully characterize on-target and off-target effects and to understand mechanisms of small-molecule action.

Using a diverse collection of small molecules we recently found that compound sets from different sources (commercial; academic; natural) have different protein-binding behaviors, and these behaviors correlate with trends in stereochemical complexity for these compound sets. These results lend insight into structural features that synthetic chemists might target when synthesizing screening collections for biological discovery. We report extensive characterization of structural properties and diversity of biological performance for these compounds and expand comparative analyses to include physicochemical properties and three-dimensional shapes of predicted conformers. The results highlight additional similarities and differences between the sets, but also the dependence of such comparisons on the choice of molecular descriptors. Using a protein-binding dataset, we introduce an information-theoretic measure to assess diversity of performance with a constraint on specificity. Rather than relying on finding individual active compounds, this measure allows rational judgment of compound subsets as groups. We also apply this measure to publicly available data from ChemBank for the same compound sets across a diverse group of functional assays. We find that performance diversity of compound sets is relatively stable across a range of property values as judged by this measure, both in protein-binding studies and functional assays. Because building screening collections with improved performance depends on efficient use of synthetic organic chemistry resources, these studies illustrate an important quantitative framework to help prioritize choices made in building such collections.