Multimodal small-molecule screening for human prion protein binders.

Prion disease is a rapidly progressive neurodegenerative disorder caused by misfolding and aggregation of the prion protein (PrP), and there are currently no therapeutic options. PrP ligands could theoretically antagonize prion formation by protecting the native protein from misfolding or by targeting it for degradation, but no validated small-molecule binders have been discovered to date. We deployed a variety of screening methods in an effort to discover binders of PrP, including 19F-observed and saturation transfer difference (STD) NMR spectroscopy, differential scanning fluorimetry (DSF), DNA-encoded library selection, and in silico screening. A single benzimidazole compound was confirmed in concentration-response, but affinity was very weak (Kd > 1 mm), and it could not be advanced further. The exceptionally low hit rate observed here suggests that PrP is a difficult target for small-molecule binders. Whereas orthogonal binder discovery methods could yield high-affinity compounds, non-small-molecule modalities may offer independent paths forward against prion disease.

Calibrating from Within: Multipoint Internal Calibration of a Quantitative Mass Spectrometric Assay of Serum Methotrexate.

BACKGROUND: Clinical LC-MS/MS assays traditionally require that samples be run in batches with calibration curves in each batch. This approach is inefficient and presents a barrier to random access analysis. We developed an alternative approach called multipoint internal calibration (MPIC) that eliminated the need for batch-mode analysis. METHODS: The new approach used 4 variants of 13C-labeled methotrexate (0.026-10.3 µM) as an internal calibration curve within each sample. One site carried out a comprehensive validation, which included an evaluation of interferences and matrix effects, lower limit of quantification (LLOQ), and 20-day precision. Three sites evaluated assay precision and linearity. MPIC was also compared with traditional LC-MS/MS and an immunoassay. RESULTS: Recovery of spiked analyte was 93%-102%. The LLOQ was validated to be 0.017 µM. Total variability, determined in a 20-day experiment, was 11.5%CV. In a 5-day variability study performed at each site, total imprecision was 3.4 to 16.8%CV. Linearity was validated throughout the calibrator range (r2 > 0.995, slopes = 0.996-1.01). In comparing 40 samples run in each laboratory, the median interlaboratory imprecision was 6.55%CV. MPIC quantification was comparable to both traditional LC-MS/MS and immunoassay (r2 = 0.96-0.98, slopes = 1.04-1.06). Bland-Altman analysis of all comparisons showed biases rarely exceeding 20% when MTX concentrations were >0.4 µM. CONCLUSION: The MPIC method for serum methotrexate quantification was validated in a multisite proof-of-concept study and represents a big step toward random-access LC-MS/MS analysis, which could change the paradigm of mass spectrometry in the clinical laboratory.

Modeling Small-Molecule Reactivity Identifies Promiscuous Bioactive Compounds.

Scientists rely on high-throughput screening tools to identify promising small-molecule compounds for the development of biochemical probes and drugs. This study focuses on the identification of promiscuous bioactive compounds, which are compounds that appear active in many high-throughput screening experiments against diverse targets but are often false-positives which may not be easily developed into successful probes. These compounds can exhibit bioactivity due to nonspecific, intractable mechanisms of action and/or by interference with specific assay technology readouts. Such "frequent hitters" are now commonly identified using substructure filters, including pan assay interference compounds (PAINS). Herein, we show that mechanistic modeling of small-molecule reactivity using deep learning can improve upon PAINS filters when modeling promiscuous bioactivity in PubChem assays. Without training on high-throughput screening data, a deep learning model of small-molecule reactivity achieves a sensitivity and specificity of 18.5% and 95.5%, respectively, in identifying promiscuous bioactive compounds. This performance is similar to PAINS filters, which achieve a sensitivity of 20.3% at the same specificity. Importantly, such reactivity modeling is complementary to PAINS filters. When PAINS filters and reactivity models are combined, the resulting model outperforms either method alone, achieving a sensitivity of 24% at the same specificity. However, as a probabilistic model, the sensitivity and specificity of the deep learning model can be tuned by adjusting the threshold. Moreover, for a subset of PAINS filters, this reactivity model can help discriminate between promiscuous and nonpromiscuous bioactive compounds even among compounds matching those filters. Critically, the reactivity model provides mechanistic hypotheses for assay interference by predicting the precise atoms involved in compound reactivity. Overall, our analysis suggests that deep learning approaches to modeling promiscuous compound bioactivity may provide a complementary approach to current methods for identifying promiscuous compounds.

Histone-modifying enzymes, histone modifications and histone chaperones in nucleosome assembly: Lessons learned from Rtt109 histone acetyltransferases.

During DNA replication, nucleosomes ahead of replication forks are disassembled to accommodate replication machinery. Following DNA replication, nucleosomes are then reassembled onto replicated DNA using both parental and newly synthesized histones. This process, termed DNA replication-coupled nucleosome assembly (RCNA), is critical for maintaining genome integrity and for the propagation of epigenetic information, dysfunctions of which have been implicated in cancers and aging. In recent years, it has been shown that RCNA is carefully orchestrated by a series of histone modifications, histone chaperones and histone-modifying enzymes. Interestingly, many features of RCNA are also found in processes involving DNA replication-independent nucleosome assembly like histone exchange and gene transcription. In yeast, histone H3 lysine K56 acetylation (H3K56ac) is found in newly synthesized histone H3 and is critical for proper nucleosome assembly and for maintaining genomic stability. The histone acetyltransferase (HAT) regulator of Ty1 transposition 109 (Rtt109) is the sole enzyme responsible for H3K56ac in yeast. Much research has centered on this particular histone modification and histone-modifying enzyme. This Critical Review summarizes much of our current understanding of nucleosome assembly and highlights many important insights learned from studying Rtt109 HATs in fungi. We highlight some seminal features in nucleosome assembly conserved in mammalian systems and describe some of the lingering questions in the field. Further studying fungal and mammalian chromatin assembly may have important public health implications, including deeper understandings of human cancers and aging as well as the pursuit of novel anti-fungal therapies.

Post-HTS case report and structural alert: Promiscuous 4-aroyl-1,5-disubstituted-3-hydroxy-2H-pyrrol-2-one actives verified by ALARM NMR.

Despite its wide use, not every high-throughput screen (HTS) yields chemical matter suitable for drug development campaigns, and seldom are 'go/no-go' decisions in drug discovery described in detail. This case report describes the follow-up of a 4-aroyl-1,5-disubstituted-3-hydroxy-2H-pyrrol-2-one active from a cell-free HTS to identify small-molecule inhibitors of Rtt109-catalyzed histone acetylation. While this compound and structural analogs inhibited Rtt109-catalyzed histone acetylation in vitro, further work on this series was halted after several risk mitigation strategies were performed. Compounds with this chemotype had a poor structure-activity relationship, exhibited poor selectivity among other histone acetyltransferases, and tested positive in a ß-lactamase counter-screen for chemical aggregates. Furthermore, ALARM NMR demonstrated compounds with this chemotype grossly perturbed the conformation of the La protein. In retrospect, this chemotype was flagged as a 'frequent hitter' in an analysis of a large corporate screening deck, yet similar compounds have been published as screening actives or chemical probes versus unrelated biological targets. This report-including the decision-making process behind the 'no-go' decision-should be informative for groups engaged in post-HTS triage and highlight the importance of considering physicochemical properties in early drug discovery.

Pneumocystis jirovecii Rtt109, a novel drug target for Pneumocystis pneumonia in immunosuppressed humans.

Pneumocystis pneumonia (PcP) is a significant cause of morbidity and mortality in immunocompromised patients. In humans, PcP is caused by the opportunistic fungal species Pneumocystis jirovecii. Progress in Pneumocystis research has been hampered by a lack of viable in vitro culture methods, which limits laboratory access to human-derived organisms for drug testing. Consequently, most basic drug discovery research for P. jirovecii is performed using related surrogate organisms such as Pneumocystis carinii, which is derived from immunosuppressed rodents. While these studies provide useful insights, important questions arise about interspecies variations and the relative utility of identified anti-Pneumocystis agents against human P. jirovecii. Our recent work has identified the histone acetyltransferase (HAT) Rtt109 in P. carinii (i.e., PcRtt109) as a potential therapeutic target for PcP, since Rtt109 HATs are widely conserved in fungi but are absent in humans. To further address the potential utility of this target in human disease, we now demonstrate the presence of a functional Rtt109 orthologue in the clinically relevant fungal pathogen P. jirovecii (i.e., PjRtt109). In a fashion similar to that of Pcrtt109, Pjrtt109 restores H3K56 acetylation and genotoxic resistance in rtt109-null yeast. Recombinant PjRtt109 is an active HAT in vitro, with activity comparable to that of PcRtt109 and yeast Rtt109. PjRtt109 HAT activity is also enhanced by the histone chaperone Asf1 in vitro. PjRtt109 and PcRtt109 showed similar low micromolar sensitivities to two reported small-molecule HAT inhibitors in vitro. Together, these results demonstrate that PjRtt109 is a functional Rtt109 HAT, and they support the development of anti-Pneumocystis agents directed at Rtt109-catalyzed histone acetylation as a novel therapeutic target for human PcP.

Methotrexate-based PROTACs as DHFR-specific chemical probes.

Methotrexate (MTX) is a tight-binding dihydrofolate reductase (DHFR) inhibitor, used as both an antineoplastic and immunosuppressant therapeutic. MTX, like folate undergoes folylpolyglutamate synthetase-mediated γ-glutamylation, which affects cellular retention and target specificity. Mechanisms of MTX resistance in cancers include a decrease in MTX poly-γ-glutamylation and an upregulation of DHFR. Here, we report a series of potent MTX-based proteolysis targeting chimeras (PROTACs) to investigate DHFR degradation pharmacology and one-carbon biochemistry. These on-target, cell-active PROTACs show proteasome- and E3 ligase-dependent activity, and selective degradation of DHFR in multiple cancer cell lines. By comparison, treatment with MTX increases cellular DHFR protein expression. Importantly, these PROTACs produced distinct, less-lethal phenotypes compared to MTX. The chemical probe set described here should complement conventional DHFR inhibitors and serve as useful tools for studying one-carbon biochemistry and dissecting complex polypharmacology of MTX and related drugs. Such compounds may also serve as leads for potential autoimmune and antineoplastic therapeutics.

Privacy-preserving record linkage across disparate institutions and datasets to enable a learning health system: The national COVID cohort collaborative (N3C) experience.

Introduction: Research driven by real-world clinical data is increasingly vital to enabling learning health systems, but integrating such data from across disparate health systems is challenging. As part of the NCATS National COVID Cohort Collaborative (N3C), the N3C Data Enclave was established as a centralized repository of deidentified and harmonized COVID-19 patient data from institutions across the US. However, making this data most useful for research requires linking it with information such as mortality data, images, and viral variants. The objective of this project was to establish privacy-preserving record linkage (PPRL) methods to ensure that patient-level EHR data remains secure and private when governance-approved linkages with other datasets occur. Methods: Separate agreements and approval processes govern N3C data contribution and data access. The Linkage Honest Broker (LHB), an independent neutral party (the Regenstrief Institute), ensures data linkages are robust and secure by adding an extra layer of separation between protected health information and clinical data. The LHB's PPRL methods (including algorithms, processes, and governance) match patient records using "deidentified tokens," which are hashed combinations of identifier fields that define a match across data repositories without using patients' clear-text identifiers. Results: These methods enable three linkage functions: Deduplication, Linking Multiple Datasets, and Cohort Discovery. To date, two external repositories have been cross-linked. As of March 1, 2023, 43 sites have signed the LHB Agreement; 35 sites have sent tokens generated for 9 528 998 patients. In this initial cohort, the LHB identified 135 037 matches and 68 596 duplicates. Conclusion: This large-scale linkage study using deidentified datasets of varying characteristics established secure methods for protecting the privacy of N3C patient data when linked for research purposes. This technology has potential for use with registries for other diseases and conditions.

Nonspecific membrane bilayer perturbations by ivermectin underlie SARS-CoV-2 in vitro activity.

Since it was proposed as a potential host-directed antiviral agent for SARS-CoV-2, the antiparasitic drug ivermectin has been investigated thoroughly in clinical trials, which have provided insufficient support for its clinical efficacy. To examine the potential for ivermectin to be repurposed as an antiviral agent, we therefore undertook a series of preclinical studies. Consistent with early reports, ivermectin decreased SARS-CoV-2 viral burden in in vitro models at low micromolar concentrations, five- to ten-fold higher than the reported toxic clinical concentration. At similar concentrations, ivermectin also decreased cell viability and increased biomarkers of cytotoxicity and apoptosis. Further mechanistic and profiling studies revealed that ivermectin nonspecifically perturbs membrane bilayers at the same concentrations where it decreases the SARS-CoV-2 viral burden, resulting in nonspecific modulation of membrane-based targets such as G-protein coupled receptors and ion channels. These results suggest that a primary molecular mechanism for the in vitro antiviral activity of ivermectin may be nonspecific membrane perturbation, indicating that ivermectin is unlikely to be translatable into a safe and effective antiviral agent. These results and experimental workflow provide a useful paradigm for performing preclinical studies on (pandemic-related) drug repurposing candidates.

Reference compounds for characterizing cellular injury in high-content cellular morphology assays.

Robust, generalizable approaches to identify compounds efficiently with undesirable mechanisms of action in complex cellular assays remain elusive. Such a process would be useful for hit triage during high-throughput screening and, ultimately, predictive toxicology during drug development. Here we generate cell painting and cellular health profiles for 218 prototypical cytotoxic and nuisance compounds in U-2 OS cells in a concentration-response format. A diversity of compounds that cause cellular damage produces bioactive cell painting morphologies, including cytoskeletal poisons, genotoxins, nonspecific electrophiles, and redox-active compounds. Further, we show that lower quality lysine acetyltransferase inhibitors and nonspecific electrophiles can be distinguished from more selective counterparts. We propose that the purposeful inclusion of cytotoxic and nuisance reference compounds such as those profiled in this resource will help with assay optimization and compound prioritization in complex cellular assays like cell painting.

Corrigendum to "Instability of 7-aminoclonazepam in frozen storage conditions" [Clin. Mass Spectrom. 9 (2018) 23-24].

[This corrects the article DOI: 10.1016/j.clinms.2018.07.002.].

Addressing Compound Reactivity and Aggregation Assay Interferences: Case Studies of Biochemical High-Throughput Screening Campaigns Benefiting from the National Institutes of Health Assay Guidance Manual Guidelines.

Compound-dependent assay interferences represent a continued burden in drug and chemical probe discovery. The open-source National Institutes of Health/National Center for Advancing Translational Sciences (NIH/NCATS) Assay Guidance Manual (AGM) established an "Assay Artifacts and Interferences" section to address different sources of artifacts and interferences in biological assays. In addition to the frequent introduction of new chapters in this important topic area, older chapters are periodically updated by experts from academia, industry, and government to include new technologies and practices. Section chapters describe many best practices for mitigating and identifying compound-dependent assay interferences. Using two previously reported biochemical high-throughput screening campaigns for small-molecule inhibitors of the epigenetic targets Rtt109 and NSD2, the authors review best practices and direct readers to high-yield resources in the AGM and elsewhere for the mitigation and identification of compound-dependent reactivity and aggregation assay interferences.

The Impact of Assay Design on Medicinal Chemistry: Case Studies.

A diverse range of biochemical and cellular assays are used by medicinal chemists to guide compound optimization. The data collected from these assays influence decisions taken on structure-activity relationship (SAR) campaigns. Therefore, it is paramount that medicinal chemists have a solid understanding of the strengths and limitations of each assay being used to characterize synthesized analogs. For the successful execution of a medicinal chemistry campaign, it is our contention that an early partnership among assay biologists, informaticians, and medicinal chemists must exist. Their combined skill sets are necessary to not only design and develop robust assays but also implement an effective screening cascade in which multiple orthogonal and counter assays are selected to validate the activity and target(s) of the synthesized compounds. We review multiple cases of drug and chemical probe discovery from collaborative National Center for Advancing Translational Sciences/National Institutes of Health projects and published scientific literature in which the evaluation of compounds in secondary or orthogonal assays led to the discovery of unexpected activities, forcing a reconsideration of the original assay design that was used to discover the biological activity of the compound. Using these retrospective case studies, the goal of this Perspective is to hedge toward the development of physiologically relevant assays that are able to capture the true bioactivity of compounds being developed in a medicinal chemistry campaign.

Cross-Platform Bayesian Optimization System for Autonomous Biological Assay Development.

Current high-throughput screening assay optimization is often a manual and time-consuming process, even when utilizing design-of-experiment approaches. A cross-platform, Cloud-based Bayesian optimization-based algorithm was developed as part of the National Center for Advancing Translational Sciences (NCATS) ASPIRE (A Specialized Platform for Innovative Research Exploration) Initiative to accelerate preclinical drug discovery. A cell-free assay for papain enzymatic activity was used as proof of concept for biological assay development and system operationalization. Compared with a brute-force approach that sequentially tested all 294 assay conditions to find the global optimum, the Bayesian optimization algorithm could find suitable conditions for optimal assay performance by testing 21 assay conditions on average, with up to 20 conditions being tested simultaneously, as confirmed by repeated simulation. The algorithm could achieve a sevenfold reduction in costs for lab supplies and high-throughput experimentation runtime, all while being controlled from a remote site through a secure connection. Based on this proof of concept, this technology is expected to be applied to more complex biological assays and automated chemistry reaction screening at NCATS, and should be transferable to other institutions.

Nuisance compounds in cellular assays.

Compounds that exhibit assay interference or undesirable mechanisms of bioactivity ("nuisance compounds") are routinely encountered in cellular assays, including phenotypic and high-content screening assays. Much is known regarding compound-dependent assay interferences in cell-free assays. However, despite the essential role of cellular assays in chemical biology and drug discovery, there is considerably less known about nuisance compounds in more complex cell-based assays. In our view, a major obstacle to realizing the full potential of chemical biology will not just be difficult-to-drug targets or even the sheer number of targets, but rather nuisance compounds, due to their ability to waste significant resources and erode scientific trust. In this review, we summarize our collective academic, government, and industry experiences regarding cellular nuisance compounds. We describe assay design strategies to mitigate the impact of nuisance compounds and suggest best practices to efficiently address these compounds in complex biological settings.

Remodelin Is a Cryptic Assay Interference Chemotype That Does Not Inhibit NAT10-Dependent Cytidine Acetylation.

Remodelin is a putative small molecule inhibitor of the RNA acetyltransferase NAT10 which has shown preclinical efficacy in models of the premature aging disease Hutchinson-Gilford Progeria Syndrome (HGPS). Here we evaluate remodelin's assay interference characteristics and effects on NAT10-catalyzed RNA cytidine acetylation. We find the remodelin chemotype constitutes a cryptic assay interference compound, which does not react with small molecule thiols but demonstrates protein reactivity in ALARM NMR and proteome-wide affinity profiling assays. Biophysical analyses find no direct evidence for interaction of remodelin with the NAT10 acetyltransferase active site. Cellular studies verify that N4-acetylcytidine (ac4C) is a nonredundant target of NAT10 activity in human cell lines and find that this RNA modification is not affected by remodelin treatment in several orthogonal assays. These studies display the potential for remodelin's chemotype to interact with multiple protein targets in cells and indicate remodelin should not be applied as a specific chemical inhibitor of NAT10-catalyzed RNA acetylation.

The Essential Medicinal Chemistry of Cannabidiol (CBD).

This Perspective of the published essential medicinal chemistry of cannabidiol (CBD) provides evidence that the popularization of CBD-fortified or CBD-labeled health products and CBD-associated health claims lacks a rigorous scientific foundation. CBD's reputation as a cure-all puts it in the same class as other "natural" panaceas, where valid ethnobotanicals are reduced to single, purportedly active ingredients. Such reductionist approaches oversimplify useful, chemically complex mixtures in an attempt to rationalize the commercial utility of natural compounds and exploit the "natural" label. Literature evidence associates CBD with certain semiubiquitous, broadly screened, primarily plant-based substances of undocumented purity that interfere with bioassays and have a low likelihood of becoming therapeutic agents. Widespread health challenges and pandemic crises such as SARS-CoV-2 create circumstances under which scientists must be particularly vigilant about healing claims that lack solid foundational data. Herein, we offer a critical review of the published medicinal chemistry properties of CBD, as well as precise definitions of CBD-containing substances and products, distilled to reveal the essential factors that impact its development as a therapeutic agent.

Development of Benzenesulfonamide Derivatives as Potent Glutathione Transferase Omega-1 Inhibitors.

Glutathione transferase omega-1 (GSTO1-1) is an enzyme whose function supports the activation of interleukin (IL)-1ß and IL-18 that are implicated in a variety of inflammatory disease states for which small-molecule inhibitors are sought. The potent reactivity of the active-site cysteine has resulted in reported inhibitors that act by covalent labeling. In this study, structure-activity relationship (SAR) elaboration of the reported GSTO1-1 inhibitor C1-27 was undertaken. Compounds were evaluated for inhibitory activity toward purified recombinant GSTO1-1 and for indicators of target engagement in cell-based assays. As covalent inhibitors, the kinact/KI values of selected compounds were determined, as well as in vivo pharmacokinetics analysis. Cocrystal structures of key novel compounds in complex with GSTO1-1 were also solved. This study represents the first application of a biochemical assay for GSTO1-1 to determine kinact/KI values for tested inhibitors and the most extensive set of cell-based data for a GSTO1-1 inhibitor SAR series reported to date. Our research culminated in the discovery of 25, which we propose as the preferred biochemical tool to interrogate cellular responses to GSTO1-1 inhibition.