NCATS Inxight Drugs: a comprehensive and curated portal for translational research.

The United States has a complex regulatory scheme for marketing drugs. Understanding drug regulatory status is a daunting task that requires integrating data from many sources from the United States Food and Drug Administration (FDA), US government publications, and other processes related to drug development. At NCATS, we created Inxight Drugs (https://drugs.ncats.io), a web resource that attempts to address this challenge in a systematic manner. NCATS Inxight Drugs incorporates and unifies a wealth of data, including those supplied by the FDA and from independent public sources. The database offers a substantial amount of manually curated literature data unavailable from other sources. Currently, the database contains 125 036 product ingredients, including 2566 US approved drugs, 6242 marketed drugs, and 9684 investigational drugs. All substances are rigorously defined according to the ISO 11238 standard to comply with existing regulatory standards for unique drug substance identification. A special emphasis was placed on capturing manually curated and referenced data on treatment modalities and semantic relationships between substances. A supplementary resource 'Novel FDA Drug Approvals' features regulatory details of newly approved FDA drugs. The database is regularly updated using NCATS Stitcher data integration tool that automates data aggregation and supports full data access through a RESTful API.

A patient safety knowledge graph supporting vaccine product development.

BACKGROUND: Knowledge graphs are well-suited for modeling complex, unstructured, and multi-source data and facilitating their analysis. During the COVID-19 pandemic, adverse event data were integrated into a knowledge graph to support vaccine safety surveillance and nimbly respond to urgent health authority questions. Here, we provide details of this post-marketing safety system using public data sources. In addition to challenges with varied data representations, adverse event reporting on the COVID-19 vaccines generated an unprecedented volume of data; an order of magnitude larger than adverse events for all previous vaccines. The Patient Safety Knowledge Graph (PSKG) is a robust data store to accommodate the volume of adverse event data and harmonize primary surveillance data sources. METHODS: We designed a semantic model to represent key safety concepts. We built an extract-transform-load (ETL) data pipeline to parse and import primary public data sources; align key elements such as vaccine names; integrated the Medical Dictionary for Regulatory Activities (MedDRA); and applied quality metrics. PSKG is deployed in a Neo4J graph database, and made available via a web interface and Application Programming Interfaces (APIs). RESULTS: We import and align adverse event data and vaccine exposure data from 250 countries on a weekly basis, producing a graph with 4,340,980 nodes and 30,544,475 edges as of July 1, 2022. PSKG is used for ad-hoc analyses and periodic reporting for several widely available COVID-19 vaccines. Analysis code using the knowledge graph is 80% shorter than an equivalent implementation written entirely in Python, and runs over 200 times faster. CONCLUSIONS: Organizing safety data into a concise model of nodes, properties, and edge relationships has greatly simplified analysis code by removing complex parsing and transformation algorithms from individual analyses and instead managing these centrally. The adoption of the knowledge graph transformed how the team answers key scientific and medical questions. Whereas previously an analysis would involve aggregating and transforming primary datasets from scratch to answer a specific question, the team can now iterate easily and respond as quickly as requests evolve (e.g., "Produce vaccine-X safety profile for adverse event-Y by country instead of age-range").

Global Substance Registration System: consistent scientific descriptions for substances related to health.

The US Food and Drug Administration (FDA) and the National Center for Advancing Translational Sciences (NCATS) have collaborated to publish rigorous scientific descriptions of substances relevant to regulated products. The FDA has adopted the global ISO 11238 data standard for the identification of substances in medicinal products and has populated a database to organize the agency's regulatory submissions and marketed products data. NCATS has worked with FDA to develop the Global Substance Registration System (GSRS) and produce a non-proprietary version of the database for public benefit. In 2019, more than half of all new drugs in clinical development were proteins, nucleic acid therapeutics, polymer products, structurally diverse natural products or cellular therapies. While multiple databases of small molecule chemical structures are available, this resource is unique in its application of regulatory standards for the identification of medicinal substances and its robust support for other substances in addition to small molecules. This public, manually curated dataset provides unique ingredient identifiers (UNIIs) and detailed descriptions for over 100 000 substances that are particularly relevant to medicine and translational research. The dataset can be accessed and queried at https://gsrs.ncats.nih.gov/app/substances.

TCRD and Pharos 2021: mining the human proteome for disease biology.

In 2014, the National Institutes of Health (NIH) initiated the Illuminating the Druggable Genome (IDG) program to identify and improve our understanding of poorly characterized proteins that can potentially be modulated using small molecules or biologics. Two resources produced from these efforts are: The Target Central Resource Database (TCRD) (http://juniper.health.unm.edu/tcrd/) and Pharos (https://pharos.nih.gov/), a web interface to browse the TCRD. The ultimate goal of these resources is to highlight and facilitate research into currently understudied proteins, by aggregating a multitude of data sources, and ranking targets based on the amount of data available, and presenting data in machine learning ready format. Since the 2017 release, both TCRD and Pharos have produced two major releases, which have incorporated or expanded an additional 25 data sources. Recently incorporated data types include human and viral-human protein-protein interactions, protein-disease and protein-phenotype associations, and drug-induced gene signatures, among others. These aggregated data have enabled us to generate new visualizations and content sections in Pharos, in order to empower users to find new areas of study in the druggable genome.

Sunitinib promotes myogenic regeneration and mitigates disease progression in the mdx mouse model of Duchenne muscular dystrophy.

Duchenne muscular dystrophy (DMD) is a lethal, muscle degenerative disease causing premature death of affected children. DMD is characterized by mutations in the dystrophin gene that result in a loss of the dystrophin protein. Loss of dystrophin causes an associated reduction in proteins of the dystrophin glycoprotein complex, leading to contraction-induced sarcolemmal weakening, muscle tearing, fibrotic infiltration and rounds of degeneration and failed regeneration affecting satellite cell populations. The α7ß1 integrin has been implicated in increasing myogenic capacity of satellite cells, therefore restoring muscle viability, increasing muscle force and preserving muscle function in dystrophic mouse models. In this study, we show that a Food and Drug Administration (FDA)-approved small molecule, Sunitinib, is a potent α7 integrin enhancer capable of promoting myogenic regeneration by stimulating satellite cell activation and increasing myofiber fusion. Sunitinib exerts its regenerative effects via transient inhibition of SHP-2 and subsequent activation of the STAT3 pathway. Treatment of mdx mice with Sunitinib demonstrated decreased membrane leakiness and damage owing to myofiber regeneration and enhanced support at the extracellular matrix. The decreased myofiber damage translated into a significant increase in muscle force production. This study identifies an already FDA-approved compound, Sunitinib, as a possible DMD therapeutic with the potential to treat other muscular dystrophies in which there is defective muscle repair.

Therapeutic effects of a small molecule agonist of the relaxin receptor ML290 in liver fibrosis.

Fibrosis is an underlying cause of cirrhosis and hepatic failure resulting in end stage liver disease with limited pharmacological options. The beneficial effects of relaxin peptide treatment were demonstrated in clinically relevant animal models of liver fibrosis. However, the use of relaxin is problematic because of a short half-life. The aim of this study was to test the therapeutic effects of recently identified small molecule agonists of the human relaxin receptor, relaxin family peptide receptor 1 (RXFP1). The lead compound of this series, ML290, was selected based on its effects on the expression of fibrosis-related genes in primary human stellate cells. RNA sequencing analysis of TGF-ß1-activated LX-2 cells showed that ML290 treatment primarily affected extracellular matrix remodeling and cytokine signaling, with expression profiles indicating an antifibrotic effect of ML290. ML290 treatment in human liver organoids with LPS-induced fibrotic phenotype resulted in a significant reduction of type I collagen. The pharmacokinetics of ML290 in mice demonstrated its high stability in vivo, as evidenced by the sustained concentrations of compound in the liver. In mice expressing human RXFP1 gene treated with carbon tetrachloride, ML290 significantly reduced collagen content, α-smooth muscle actin expression, and cell proliferation around portal ducts. In conclusion, ML290 demonstrated antifibrotic effects in liver fibrosis.-Kaftanovskaya, E. M., Ng, H. H., Soula, M., Rivas, B., Myhr, C., Ho, B. A., Cervantes, B. A., Shupe, T. D., Devarasetty, M., Hu, X., Xu, X., Patnaik, S., Wilson, K. J., Barnaeva, E., Ferrer, M., Southall, N. T., Marugan, J. J., Bishop, C. E., Agoulnik, I. U., Agoulnik, A. I. Therapeutic effects of a small molecule agonist of the relaxin receptor ML290 in liver fibrosis.

Critical Assessment of Artificial Intelligence Methods for Prediction of hERG Channel Inhibition in the "Big Data" Era.

The rise of novel artificial intelligence (AI) methods necessitates their benchmarking against classical machine learning for a typical drug-discovery project. Inhibition of the potassium ion channel, whose alpha subunit is encoded by the human ether-à-go-go-related gene (hERG), leads to a prolonged QT interval of the cardiac action potential and is a significant safety pharmacology target for the development of new medicines. Several computational approaches have been employed to develop prediction models for the assessment of hERG liabilities of small molecules including recent work using deep learning methods. Here, we perform a comprehensive comparison of hERG effect prediction models based on classical approaches (random forests and gradient boosting) and modern AI methods [deep neural networks (DNNs) and recurrent neural networks (RNNs)]. The training set (∼9000 compounds) was compiled by integrating the hERG bioactivity data from the ChEMBL database with experimental data generated from an in-house, high-throughput thallium flux assay. We utilized different molecular descriptors including the latent descriptors, which are real-value continuous vectors derived from chemical autoencoders trained on a large chemical space (>1.5 million compounds). The models were prospectively validated on ∼840 in-house compounds screened in the same thallium flux assay. The best results were obtained with the XGBoost method and RDKit descriptors. The comparison of models based only on latent descriptors revealed that the DNNs performed significantly better than the classical methods. The RNNs that operate on SMILES provided the highest model sensitivity. The best models were merged into a consensus model that offered superior performance compared to reference models from academic and commercial domains. Furthermore, we shed light on the potential of AI methods to exploit the big data in chemistry and generate novel chemical representations useful in predictive modeling and tailoring a new chemical space.

A large scale high-throughput screen identifies chemical inhibitors of phosphatidylinositol 4-kinase type II alpha.

The minor phospholipid, phosphatidylinositol 4-phosphate (PI4P), is emerging as a key regulator of lipid transfer in ER-membrane contact sites. Four different phosphatidylinositol 4-kinase (PI4K) enzymes generate PI4P in different membrane compartments supporting distinct cellular processes, many of which are crucial for the maintenance of cellular integrity but also hijacked by intracellular pathogens. While type III PI4Ks have been targeted by small molecular inhibitors, thus helping decipher their importance in cellular physiology, no inhibitors are available for the type II PI4Ks, which hinders investigations into their cellular functions. Here, we describe the identification of small molecular inhibitors of PI4K type II alpha (PI4K2A) by implementing a large scale small molecule high-throughput screening. A novel assay was developed that allows testing of selected inhibitors against PI4K2A in intact cells using a bioluminescence resonance energy transfer approach adapted to plate readers. The compounds disclosed here will pave the way to the optimization of PI4K2A inhibitors that can be used in cellular and animal studies to better understand the role of this enzyme in both normal and pathological states.

Identification, design and synthesis of novel pyrazolopyridine influenza virus nonstructural protein 1 antagonists.

Nonstructural protein 1 (NS1) plays a crucial function in the replication, spread, and pathogenesis of influenza virus by inhibiting the host innate immune response. Here we report the discovery and optimization of novel pyrazolopyridine NS1 antagonists that can potently inhibit influenza A/PR/8/34 replication in MDCK cells, rescue MDCK cells from cytopathic effects of seasonal influenza A strains, reverse NS1-dependent inhibition of IFN-ß gene expression, and suppress the slow growth phenotype in NS1-expressing yeast. These pyrazolopyridines will enable researchers to investigate NS1 function during infection and how antagonists can be utilized in the next generation of treatments for influenza infection.

Novel Consensus Architecture To Improve Performance of Large-Scale Multitask Deep Learning QSAR Models.

Advances in the development of high-throughput screening and automated chemistry have rapidly accelerated the production of chemical and biological data, much of them freely accessible through literature aggregator services such as ChEMBL and PubChem. Here, we explore how to use this comprehensive mapping of chemical biology space to support the development of large-scale quantitative structure-activity relationship (QSAR) models. We propose a new deep learning consensus architecture (DLCA) that combines consensus and multitask deep learning approaches together to generate large-scale QSAR models. This method improves knowledge transfer across different target/assays while also integrating contributions from models based on different descriptors. The proposed approach was validated and compared with proteochemometrics, multitask deep learning, and Random Forest methods paired with various descriptors types. DLCA models demonstrated improved prediction accuracy for both regression and classification tasks. The best models together with their modeling sets are provided through publicly available web services at https://predictor.ncats.io .

Pharos: Collating protein information to shed light on the druggable genome.

The 'druggable genome' encompasses several protein families, but only a subset of targets within them have attracted significant research attention and thus have information about them publicly available. The Illuminating the Druggable Genome (IDG) program was initiated in 2014, has the goal of developing experimental techniques and a Knowledge Management Center (KMC) that would collect and organize information about protein targets from four families, representing the most common druggable targets with an emphasis on understudied proteins. Here, we describe two resources developed by the KMC: the Target Central Resource Database (TCRD) which collates many heterogeneous gene/protein datasets and Pharos (https://pharos.nih.gov), a multimodal web interface that presents the data from TCRD. We briefly describe the types and sources of data considered by the KMC and then highlight features of the Pharos interface designed to enable intuitive access to the IDG knowledgebase. The aim of Pharos is to encourage 'serendipitous browsing', whereby related, relevant information is made easily discoverable. We conclude by describing two use cases that highlight the utility of Pharos and TCRD.

Identification of Positive Allosteric Modulators of the D1 Dopamine Receptor That Act at Diverse Binding Sites.

The D1 dopamine receptor is linked to a variety of neuropsychiatric disorders and represents an attractive drug target for the enhancement of cognition in schizophrenia, Alzheimer disease, and other disorders. Positive allosteric modulators (PAMs), with their potential for greater selectivity and larger therapeutic windows, may represent a viable drug development strategy, as orthosteric D1 receptor agonists possess known clinical liabilities. We discovered two structurally distinct D1 receptor PAMs, MLS6585 and MLS1082, via a high-throughput screen of the NIH Molecular Libraries program small-molecule library. Both compounds potentiate dopamine-stimulated G protein- and ß-arrestin-mediated signaling and increase the affinity of dopamine for the D1 receptor with low micromolar potencies. Neither compound displayed any intrinsic agonist activity. Both compounds were also found to potentiate the efficacy of partial agonists. We tested maximally effective concentrations of each PAM in combination to determine if the compounds might act at separate or similar sites. In combination, MLS1082 + MLS6585 produced an additive potentiation of dopamine potency beyond that caused by either PAM alone for both ß-arrestin recruitment and cAMP accumulation, suggesting diverse sites of action. In addition, MLS6585, but not MLS1082, had additive activity with the previously described D1 receptor PAM "Compound B," suggesting that MLS1082 and Compound B may share a common binding site. A point mutation (R130Q) in the D1 receptor was found to abrogate MLS1082 activity without affecting that of MLS6585, suggesting this residue may be involved in the binding/activity of MLS1082 but not that of MLS6585. Together, MLS1082 and MLS6585 may serve as important tool compounds for the characterization of diverse allosteric sites on the D1 receptor as well as the development of optimized lead compounds for therapeutic use.

Discovery of a Positive Allosteric Modulator of the Thyrotropin Receptor: Potentiation of Thyrotropin-Mediated Preosteoblast Differentiation In Vitro.

Recently, we showed that TSH-enhanced differentiation of a human preosteoblast-like cell model involved a ß-arrestin 1 (ß-Arr 1)-mediated pathway. To study this pathway in more detail, we sought to discover a small molecule ligand that was functionally selective toward human TSH receptor (TSHR) activation of ß-Arr 1. High-throughput screening using a cell line stably expressing mutated TSHRs and mutated ß-Arr 1 (DiscoverX1 cells) led to the discovery of agonists that stimulated translocation of ß-Arr 1 to the TSHR, but did not activate Gs-mediated signaling pathways, i.e., cAMP production. D3-ßArr (NCGC00379308) was selected. In DiscoverX1 cells, D3-ßArr stimulated ß-Arr 1 translocation with a 5.1-fold greater efficacy than TSH and therefore potentiated the effect of TSH in stimulating ß-Arr 1 translocation. In human U2OS-TSHR cells expressing wild-type TSHRs, which is a model of human preosteoblast-like cells, TSH upregulated the osteoblast-specific genes osteopontin (OPN) and alkaline phosphatase (ALPL). D3-ßArr alone had only a weak effect to upregulate these bone markers, but D3-ßArr potentiated TSH-induced upregulation of ALPL and OPN mRNA levels 1.6-fold and 5.5-fold, respectively, at the maximum dose of ligands. Furthermore, the positive allosteric modulator effect of D3-ßArr resulted in an increase of TSH-induced secretion of OPN protein. In summary, we have discovered the first small molecule positive allosteric modulator of TSHR. As D3-ßArr potentiates the effect of TSH to enhance differentiation of a human preosteoblast in an in vitro model, it will allow a novel experimental approach for probing the role of TSH-induced ß-Arr 1 signaling in osteoblast differentiation.

Efficacy and Mechanism of Action of Low Dose Emetine against Human Cytomegalovirus.

Infection with human cytomegalovirus (HCMV) is a threat for pregnant women and immunocompromised hosts. Although limited drugs are available, development of new agents against HCMV is desired. Through screening of the LOPAC library, we identified emetine as HCMV inhibitor. Additional studies confirmed its anti-HCMV activities in human foreskin fibroblasts: EC50-40±1.72 nM, CC50-8±0.56 µM, and selectivity index of 200. HCMV inhibition occurred after virus entry, but before DNA replication, and resulted in decreased expression of viral proteins. Synergistic virus inhibition was achieved when emetine was combined with ganciclovir. In a mouse CMV (MCMV) model, emetine was well-tolerated, displayed long half-life, preferential distribution to tissues over plasma, and effectively suppressed MCMV. Since the in vitro anti-HCMV activity of emetine decreased significantly in low-density cells, a mechanism involving cell cycle regulation was suspected. HCMV inhibition by emetine depended on ribosomal processing S14 (RPS14) binding to MDM2, leading to disruption of HCMV-induced MDM2-p53 and MDM2-IE2 interactions. Irrespective of cell density, emetine induced RPS14 translocation into the nucleus during infection. In infected high-density cells, MDM2 was available for interaction with RPS14, resulting in disruption of MDM2-p53 interaction. However, in low-density cells the pre-existing interaction of MDM2-p53 could not be disrupted, and RPS14 could not interact with MDM2. In high-density cells the interaction of MDM2-RPS14 resulted in ubiquitination and degradation of RPS14, which was not observed in low-density cells. In infected-only or in non-infected emetine-treated cells, RPS14 failed to translocate into the nucleus, hence could not interact with MDM2, and was not ubiquitinated. HCMV replicated similarly in RPS14 knockdown or control cells, but emetine did not inhibit virus replication in the former cell line. The interaction of MDM2-p53 was maintained in infected RPS14 knockdown cells despite emetine treatment, confirming a unique mechanism by which emetine exploits RPS14 to disrupt MDM2-p53 interaction. Summarized, emetine may represent a promising candidate for HCMV therapy alone or in combination with ganciclovir through a novel host-dependent mechanism.

SU9516 Increases α7ß1 Integrin and Ameliorates Disease Progression in the mdx Mouse Model of Duchenne Muscular Dystrophy.

Duchenne muscular dystrophy (DMD) is a fatal muscle disease caused by mutations in the dystrophin gene, resulting in a complete loss of the dystrophin protein. Dystrophin is a critical component of the dystrophin glycoprotein complex (DGC), which links laminin in the extracellular matrix to the actin cytoskeleton within myofibers and provides resistance to shear stresses during muscle activity. Loss of dystrophin in DMD patients results in a fragile sarcolemma prone to contraction-induced muscle damage. The α7ß1 integrin is a laminin receptor protein complex in skeletal and cardiac muscle and a major modifier of disease progression in DMD. In a muscle cell-based screen for α7 integrin transcriptional enhancers, we identified a small molecule, SU9516, that promoted increased α7ß1 integrin expression. Here we show that SU9516 leads to increased α7B integrin in murine C2C12 and human DMD patient myogenic cell lines. Oral administration of SU9516 in the mdx mouse model of DMD increased α7ß1 integrin in skeletal muscle, ameliorated pathology, and improved muscle function. We show that these improvements are mediated through SU9516 inhibitory actions on the p65-NF-κB pro-inflammatory and Ste20-related proline alanine rich kinase (SPAK)/OSR1 signaling pathways. This study identifies a first in-class α7 integrin-enhancing small-molecule compound with potential for the treatment of DMD.

Up-regulation of lysosomal TRPML1 channels is essential for lysosomal adaptation to nutrient starvation.

Upon nutrient starvation, autophagy digests unwanted cellular components to generate catabolites that are required for housekeeping biosynthesis processes. A complete execution of autophagy demands an enhancement in lysosome function and biogenesis to match the increase in autophagosome formation. Here, we report that mucolipin-1 (also known as TRPML1 or ML1), a Ca(2+) channel in the lysosome that regulates many aspects of lysosomal trafficking, plays a central role in this quality-control process. By using Ca(2+) imaging and whole-lysosome patch clamping, lysosomal Ca(2+) release and ML1 currents were detected within hours of nutrient starvation and were potently up-regulated. In contrast, lysosomal Na(+)-selective currents were not up-regulated. Inhibition of mammalian target of rapamycin (mTOR) or activation of transcription factor EB (TFEB) mimicked a starvation effect in fed cells. The starvation effect also included an increase in lysosomal proteostasis and enhanced clearance of lysosomal storage, including cholesterol accumulation in Niemann-Pick disease type C (NPC) cells. However, this effect was not observed when ML1 was pharmacologically inhibited or genetically deleted. Furthermore, overexpression of ML1 mimicked the starvation effect. Hence, lysosomal adaptation to environmental cues such as nutrient levels requires mTOR/TFEB-dependent, lysosome-to-nucleus regulation of lysosomal ML1 channels and Ca(2+) signaling.

Structural Insights into the Activation of Human Relaxin Family Peptide Receptor 1 by Small-Molecule Agonists.

The GPCR relaxin family peptide receptor 1 (RXFP1) mediates the action of relaxin peptide hormone, including its tissue remodeling and antifibrotic effects. The peptide has a short half-life in plasma, limiting its therapeutic utility. However, small-molecule agonists of human RXFP1 can overcome this limitation and may provide a useful therapeutic approach, especially for chronic diseases such as heart failure and fibrosis. The first small-molecule agonists of RXFP1 were recently identified from a high-throughput screening, using a homogeneous cell-based cAMP assay. Optimization of the hit compounds resulted in a series of highly potent and RXFP1 selective agonists with low cytotoxicity, and excellent in vitro ADME and pharmacokinetic properties. Here, we undertook extensive site-directed mutagenesis studies in combination with computational modeling analysis to probe the molecular basis of the small-molecule binding to RXFP1. The results showed that the agonists bind to an allosteric site of RXFP1 in a manner that closely interacts with the seventh transmembrane domain (TM7) and the third extracellular loop (ECL3). Several residues were determined to play an important role in the agonist binding and receptor activation, including a hydrophobic region at TM7 consisting of W664, F668, and L670. The G659/T660 motif within ECL3 is crucial to the observed species selectivity of the agonists for RXFP1. The receptor binding and activation effects by the small molecule ML290 were compared with the cognate ligand, relaxin, providing valuable insights on the structural basis and molecular mechanism of receptor activation and selectivity for RXFP1.

Kinetic, Mutational, and Structural Studies of the Venezuelan Equine Encephalitis Virus Nonstructural Protein 2 Cysteine Protease.

The Venezuelan equine encephalitis virus (VEEV) nonstructural protein 2 (nsP2) cysteine protease (EC 3.4.22.-) is essential for viral replication and is involved in the cytopathic effects (CPE) of the virus. The VEEV nsP2 protease is a member of MEROPS Clan CN and characteristically contains a papain-like protease linked to an S-adenosyl-l-methionine-dependent RNA methyltransferase (SAM MTase) domain. The protease contains an alternative active site motif, (475)NVCWAK(480), which differs from papain's (CGS(25)CWAFS), and the enzyme lacks a transition state-stabilizing residue homologous to Gln-19 in papain. To understand the roles of conserved residues in catalysis, we determined the structure of the free enzyme and the first structure of an inhibitor-bound alphaviral protease. The peptide-like E64d inhibitor was found to bind beneath a ß-hairpin at the interface of the SAM MTase and protease domains. His-546 adopted a conformation that differed from that found in the free enzyme; one or both of the conformers may assist in leaving group departure of either the amine or Cys thiolate during the catalytic cycle. Interestingly, E64c (200 µM), the carboxylic acid form of the E64d ester, did not inhibit the nsP2 protease. To identify key residues involved in substrate binding, a number of mutants were analyzed. Mutation of the motif residue, N475A, led to a 24-fold reduction in kcat/Km, and the conformation of this residue did not change after inhibition. N475 forms a hydrogen bond with R662 in the SAM MTase domain, and the R662A and R662K mutations both led to 16-fold decreases in kcat/Km. N475 forms the base of the P1 binding site and likely orients the substrate for nucleophilic attack or plays a role in product release. An Asn homologous to N475 is similarly found in coronaviral papain-like proteases (PLpro) of the Severe Acute Respiratory Syndrome (SARS) virus and Middle East Respiratory Syndrome (MERS) virus. Mutation of another motif residue, K480A, led to a 9-fold decrease in kcat and kcat/Km. K480 likely enhances the nucleophilicity of the Cys. Consistent with our substrate-bound models, the SAM MTase domain K706A mutation increased Km 4.5-fold to 500 µM. Within the ß-hairpin, the N545A mutation slightly but not significantly increased kcat and Km. The structures and identified active site residues may facilitate the discovery of protease inhibitors with antiviral activity.

High-content screening identifies small molecules that remove nuclear foci, affect MBNL distribution and CELF1 protein levels via a PKC-independent pathway in myotonic dystrophy cell lines.

Myotonic dystrophy (DM) is a multi-system neuromuscular disorder for which there is no treatment. We have developed a medium throughput phenotypic assay, based on the identification of nuclear foci in DM patient cell lines using in situ hybridization and high-content imaging to screen for potentially useful therapeutic compounds. A series of further assays based on molecular features of DM have also been employed. Two compounds that reduce and/or remove nuclear foci have been identified, Ro 31-8220 and chromomycin A3. Ro 31-8220 is a PKC inhibitor, previously shown to affect the hyperphosphorylation of CELF1 and ameliorate the cardiac phenotype in a DM1 mouse model. We show that the same compound eliminates nuclear foci, reduces MBNL1 protein in the nucleus, affects ATP2A1 alternative splicing and reduces steady-state levels of CELF1 protein. We demonstrate that this effect is independent of PKC activity and conclude that this compound may be acting on alternative kinase targets within DM pathophysiology. Understanding the activity profile for this compound is key for the development of targeted therapeutics in the treatment of DM.

Cell-based high-throughput screening identifies galactocerebrosidase enhancers as potential small-molecule therapies for Krabbe's disease.

Krabbe's disease, also known as globoid cell leukodystrophy (GLD), is a lysosomal storage disease caused by the deficiency of the lysosomal enzyme ß-galactocerebrosidase (GALC), resulting in severe neurological manifestations related to demyelination secondary to elevated galactosylsphingosine (psychosine) with its subsequent cytotoxicity. The only available treatment is hematopoietic stem cell transplantation, which delays disease onset but does not prevent long-term neurological manifestations. This article describes the identification of small molecules that enhance mutant GALC activity, identified by quantitative cell-based high-throughput screening (qHTS). Using a specific neurologically relevant murine cell line (145M-Twi) modified to express common human hGALC-G270D mutant, we were able to detect GALC activity in a 1,536-well microplate format. The qHTS of approximately 46,000 compounds identified three small molecules that showed significant enhancements of residual mutant GALC activity in primary cell lines from GLD patients. These compounds were shown to increase the levels of GALC-G270D mutant in the lysosomal compartment. In kinetic assessments, these small molecules failed to disturb the GALC kinetic profile under acidic conditions, which is highly desirable for folding-assisting molecules operating in the endoplasmic reticulum and not affecting GALC catalytic properties in the lysosomal compartment. In addition, these small molecules rescued the decreased GALC activity at neutral pH and partially stabilized GALC under heat-denaturating conditions. These drug-like compounds can be used as the starting point to develop novel small-molecule agents to treat the progressive neurodegenerative course of GLD. © 2016 Wiley Periodicals, Inc.