Advanced bioinformatics rapidly identifies existing therapeutics for patients with coronavirus disease-2019 (COVID-19).

BACKGROUND: The recent global pandemic has placed a high priority on identifying drugs to prevent or lessen clinical infection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), caused by Coronavirus disease-2019 (COVID-19). METHODS: We applied two computational approaches to identify potential therapeutics. First, we sought to identify existing FDA approved drugs that could block coronaviruses from entering cells by binding to ACE2 or TMPRSS2 using a high-throughput AI-based binding affinity prediction platform. Second, we sought to identify FDA approved drugs that could attenuate the gene expression patterns induced by coronaviruses, using our Disease Cancelling Technology (DCT) platform. RESULTS: Top results for ACE2 binding iincluded several ACE inhibitors, a beta-lactam antibiotic, two antiviral agents (Fosamprenavir and Emricasan) and glutathione. The platform also assessed specificity for ACE2 over ACE1, important for avoiding counterregulatory effects. Further studies are needed to weigh the benefit of blocking virus entry against potential counterregulatory effects and possible protective effects of ACE2. However, the data herein suggest readily available drugs that warrant experimental evaluation to assess potential benefit. DCT was run on an animal model of SARS-CoV, and ranked compounds by their ability to induce gene expression signals that counteract disease-associated signals. Top hits included Vitamin E, ruxolitinib, and glutamine. Glutathione and its precursor glutamine were highly ranked by two independent methods, suggesting both warrant further investigation for potential benefit against SARS-CoV-2. CONCLUSIONS: While these findings are not yet ready for clinical translation, this report highlights the potential use of two bioinformatics technologies to rapidly discover existing therapeutic agents that warrant further investigation for established and emerging disease processes.

Compositional differences between Copaxone and Glatopa are reflected in altered immunomodulation ex vivo in a mouse model.

Copaxone (glatiramer acetate, GA), a structurally and compositionally complex polypeptide nonbiological drug, is an effective treatment for multiple sclerosis, with a well-established favorable safety profile. The short antigenic polypeptide sequences comprising therapeutically active epitopes in GA cannot be deciphered with state-of-the-art methods; and GA has no measurable pharmacokinetic profile and no validated pharmacodynamic markers. The study reported herein describes the use of orthogonal standard and high-resolution physicochemical and biological tests to characterize GA and a U.S. Food and Drug Administration-approved generic version of GA, Glatopa (USA-FoGA). While similarities were observed with low-resolution or destructive tests, differences between GA and USA-FoGA were measured with high-resolution methods applied to an intact mixture, including variations in surface charge and a unique, high-molecular-weight, hydrophobic polypeptide population observed only in some USA-FoGA lots. Consistent with published reports that modifications in physicochemical attributes alter immune-related processes, genome-wide expression profiles of ex vivo activated splenocytes from mice immunized with either GA or USA-FoGA showed that 7-11% of modulated genes were differentially expressed and enriched for immune-related pathways. Thus, differences between USA-FoGA and GA may include variations in antigenic epitopes that differentially activate immune responses. We propose that the assays reported herein should be considered during the regulatory assessment process for nonbiological complex drugs such as GA.

Pharmacogenomics strategies to optimize treatments for multiple sclerosis: Insights from clinical research.

Multiple sclerosis (MS) is a chronic, progressive, disabling disorder characterized by immune-mediated demyelination, inflammation, and neurodegenerative tissue damage in the central nervous system (CNS), associated with frequent exacerbations and remissions of neurologic symptoms and eventual permanent neurologic disability. While there are several MS therapies that are successful in reducing MS relapses, none have been effective in treating all patients. The specific response of an individual patient to any one of the MS therapies remains largely unpredictable, and physicians and patients are forced to use a trial and error approach when deciding on treatment regimens. A priori markers to predict the optimal benefit-to-risk profile of an individual MS patient would greatly facilitate the decision-making process, thereby helping the patient receive the most optimal treatment early on in the disease process. Pharmacogenomic methods evaluate how a person's genetic and genomic makeup affects their response to therapeutics. This review focuses on how pharmacogenomics studies are being used to identify biologically relevant differences in MS treatments and provide characterization of the predictive clinical response patterns. As pharmacogenomics research is dependent on the availability of longitudinal clinical research, studies concerning glatiramer acetate and the interferon beta products which have the majority of published long term data to date are described in detail. These studies have provided considerable insight in the prognostic markers associated with MS disease and potential predictive markers of safety and beneficial response.

Pridopidine activates neuroprotective pathways impaired in Huntington Disease.

Pridopidine has demonstrated improvement in Huntington Disease (HD) motor symptoms as measured by secondary endpoints in clinical trials. Originally described as a dopamine stabilizer, this mechanism is insufficient to explain the clinical and preclinical effects of pridopidine. This study therefore explored pridopidine's potential mechanisms of action. The effect of pridopidine versus sham treatment on genome-wide expression profiling in the rat striatum was analysed and compared to the pathological expression profile in Q175 knock-in (Q175 KI) vs Q25 WT mouse models. A broad, unbiased pathway analysis was conducted, followed by testing the enrichment of relevant pathways. Pridopidine upregulated the BDNF pathway (P = 1.73E-10), and its effect on BDNF secretion was sigma 1 receptor (S1R) dependent. Many of the same genes were independently found to be downregulated in Q175 KI mice compared to WT (5.2e-7 < P < 0.04). In addition, pridopidine treatment upregulated the glucocorticoid receptor (GR) response, D1R-associated genes and the AKT/PI3K pathway (P = 1E-10, P = 0.001, P = 0.004, respectively). Pridopidine upregulates expression of BDNF, D1R, GR and AKT/PI3K pathways, known to promote neuronal plasticity and survival, as well as reported to demonstrate therapeutic benefit in HD animal models. Activation of S1R, necessary for its effect on the BDNF pathway, represents a core component of the mode of action of pridopidine. Since the newly identified pathways are downregulated in neurodegenerative diseases, including HD, these findings suggest that pridopidine may exert neuroprotective effects beyond its role in alleviating some symptoms of HD.

Functional effects of the antigen glatiramer acetate are complex and tightly associated with its composition.

Glatiramer acetate (Copaxone®; GA) is a non-biological complex drug for multiple sclerosis. GA modulated thousands of genes in genome-wide expression studies conducted in THP-1 cells and mouse splenocytes. Comparing GA with differently-manufactured glatiramoid Polimunol (Synthon) in mice yielded hundreds of differentially expressed probesets, including biologically-relevant genes (e.g. Il18, adj p<9e-6) and pathways. In human monocytes, 700+ probesets differed between Polimunol and GA, enriching for 130+ pathways including response to lipopolysaccharide (adj. p<0.006). Key differences were confirmed by qRT-PCR (splenocytes) or proteomics (THP-1). These studies demonstrate the complexity of GA's mechanisms of action, and may help inform therapeutic equivalence assessment.

Leveraging existing data sets to generate new insights into Alzheimer's disease biology in specific patient subsets.

To generate new insights into the biology of Alzheimer's Disease (AD), we developed methods to combine and reuse a wide variety of existing data sets in new ways. We first identified genes consistently associated with AD in each of four separate expression studies, and confirmed this result using a fifth study. We next developed algorithms to search hundreds of thousands of Gene Expression Omnibus (GEO) data sets, identifying a link between an AD-associated gene (NEUROD6) and gender. We therefore stratified patients by gender along with APOE4 status, and analyzed multiple SNP data sets to identify variants associated with AD. SNPs in either the region of NEUROD6 or SNAP25 were significantly associated with AD, in APOE4+ females and APOE4+ males, respectively. We developed algorithms to search Connectivity Map (CMAP) data for medicines that modulate AD-associated genes, identifying hypotheses that warrant further investigation for treating specific AD patient subsets. In contrast to other methods, this approach focused on integrating multiple gene expression datasets across platforms in order to achieve a robust intersection of disease-affected genes, and then leveraging these results in combination with genetic studies in order to prioritize potential genes for targeted therapy.

Gene expression studies of a human monocyte cell line identify dissimilarities between differently manufactured glatiramoids.

Glatiramer Acetate (GA) has provided safe and effective treatment for multiple sclerosis (MS) patients for two decades. It acts as an antigen, yet the precise mechanism of action remains to be fully elucidated, and no validated pharmacokinetic or pharmacodynamic biomarkers exist. In order to better characterize GA's biological impact, genome-wide expression studies were conducted with a human monocyte (THP-1) cell line. Consistent with previous literature, branded GA upregulated anti-inflammatory markers (e.g. IL10), and modulated multiple immune-related pathways. Despite some similarities, significant differences were observed between expression profiles induced by branded GA and Probioglat, a differently-manufactured glatiramoid purported to be a generic GA. Key results were verified using qRT-PCR. Genes (e.g. CCL5, adj. p < 4.1 × 10(-5)) critically involved in pro-inflammatory pathways (e.g. response to lipopolysaccharide, adj. p = 8.7 × 10(-4)) were significantly induced by Probioglat compared with branded GA. Key genes were also tested and confirmed at the protein level, and in primary human monocytes. These observations suggest differential biological impact by the two glatiramoids and warrant further investigation.

Detecting kinase activities from single cell lysate using concentration-enhanced mobility shift assay.

Electrokinetic preconcentration coupled with mobility shift assays can give rise to very high detection sensitivities. We describe a microfluidic device that utilizes this principle to detect cellular kinase activities by simultaneously concentrating and separating substrate peptides with different phosphorylation states. This platform is capable of reliably measuring kinase activities of single adherent cells cultured in nanoliter volume microwells. We also describe a novel method utilizing spacer peptides that significantly increase separation resolution while maintaining high concentration factors in this device. Thus, multiplexed kinase measurements can be implemented with single cell sensitivity. Multiple kinase activity profiling from single cell lysate could potentially allow us to study heterogeneous activation of signaling pathways that can lead to multiple cell fates.

Protein filter binding.

This protocol describes a method to monitor the binding of nucleic acid to protein, allowing the determination of the apparent affinity of a nucleic acid-protein interaction.

Microfluidic probe for single-cell analysis in adherent tissue culture.

Single-cell analysis provides information critical to understanding key disease processes that are characterized by significant cellular heterogeneity. Few current methods allow single-cell measurement without removing cells from the context of interest, which not only destroys contextual information but also may perturb the process under study. Here we present a microfluidic probe that lyses single adherent cells from standard tissue culture and captures the contents to perform single-cell biochemical assays. We use this probe to measure kinase and housekeeping protein activities, separately or simultaneously, from single human hepatocellular carcinoma cells in adherent culture. This tool has the valuable ability to perform measurements that clarify connections between extracellular context, signals and responses, especially in cases where only a few cells exhibit a characteristic of interest.

Conserved residues in yeast initiator tRNA calibrate initiation accuracy by regulating preinitiation complex stability at the start codon.

Eukaryotic initiator tRNA (tRNAi) contains several highly conserved unique sequence features, but their importance in accurate start codon selection was unknown. Here we show that conserved bases throughout tRNAi, from the anticodon stem to acceptor stem, play key roles in ensuring the fidelity of start codon recognition in yeast cells. Substituting the conserved G31:C39 base pair in the anticodon stem with different pairs reduces accuracy (the Sui(-) [suppressor of initiation codon] phenotype), whereas eliminating base pairing increases accuracy (the Ssu(-) [suppressor of Sui(-)] phenotype). The latter defect is fully suppressed by a Sui(-) substitution of T-loop residue A54. These genetic data are paralleled by opposing effects of Sui(-) and Ssu(-) substitutions on the stability of methionylated tRNAi (Met-tRNA(i)) binding (in the ternary complex [TC] with eIF2-GTP) to reconstituted preinitiation complexes (PICs). Disrupting the C3:G70 base pair in the acceptor stem produces a Sui(-) phenotype and also reduces the rate of TC binding to 40S subunits in vitro and in vivo. Both defects are suppressed by an Ssu(-) substitution in eIF1A that stabilizes the open/P(OUT) conformation of the PIC that exists prior to start codon recognition. Our data indicate that these signature sequences of tRNA(i) regulate accuracy by distinct mechanisms, promoting the open/P(OUT) conformation of the PIC (for C3:G70) or destabilizing the closed/P(IN) state (for G31:C39 and A54) that is critical for start codon recognition.

Explanatory chapter: nucleic acid concentration determination.

This protocol describes a method for determining the concentration of a nucleic acid sample.

Measurement and modeling of signaling at the single-cell level.

It has long been recognized that a deeper understanding of cell function, with respect to execution of phenotypic behaviors and their regulation by the extracellular environment, is likely to be achieved by analyzing the underlying molecular processes for individual cells selected from across a population, rather than averages of many cells comprising that population. In recent years, experimental and computational methods for undertaking these analyses have advanced rapidly. In this review, we provide a perspective on both measurement and modeling facets of biochemistry at a single-cell level. Our central focus is on receptor-mediated signaling networks that regulate cell phenotypic functions.

Eukaryotic initiator tRNA: finely tuned and ready for action.

The initiator tRNA must serve functions distinct from those of other tRNAs, evading binding to elongation factors and instead binding directly to the ribosomal P site with the aid of initiation factors. It plays a key role in decoding the start codon, setting the frame for translation of the mRNA. Sequence elements and modifications of the initiator tRNA distinguish it from the elongator methionyl tRNA and help it to perform its varied tasks. These identity elements appear to finely tune the structure of the initiator tRNA, and growing evidence suggests that the body of the tRNA is involved in transmitting the signal that the start codon has been found to the rest of the pre-initiation complex.

Kinetic and thermodynamic analysis of the role of start codon/anticodon base pairing during eukaryotic translation initiation.

Start codon recognition is a crucial event in the initiation of protein synthesis. To gain insight into the mechanism of start codon recognition in eukaryotes, we used a yeast reconstituted initiation system to isolate the step of Met-tRNA(i)*eIF2*GTP ternary complex (TC) binding to the 40S subunit. We examined the kinetics and thermodynamics of this step in the presence of base changes in the mRNA start codon and initiator methionyl tRNA anticodon, in order to investigate the effects of base pairing and sequence on the stability of the resulting 43S*mRNA complex. We observed that the formation of three base pairs, rather than their identities, was the key determinant of stability of TC binding, indicating that nothing is inherently special about the sequence AUG for this step. Surprisingly, the rate constant for TC binding to the 40S subunit was strongly codon dependent, whereas the rate constant for TC dissociation from the 43S*mRNA complex was not. The data suggest a model in which, after the initial diffusion-limited encounter of TC with the 40S subunit, the formation of three matching start codon/anticodon base pairs triggers a conformational change that locks the complex into a stable state. This induced-fit mechanism supports the proposal that initiation codon recognition by the 43S complex induces a conformational change from an open state to a closed one that arrests movement along the mRNA.

Reconstitution of yeast translation initiation.

To facilitate the mechanistic dissection of eukaryotic translation initiation we have reconstituted the steps of this process using purified Saccharomyces cerevisiae components. This system provides a bridge between biochemical studies in vitro and powerful yeast genetic techniques, and complements existing reconstituted mammalian translation systems (Benne and Hershey, 1978; Pestova and Hellen, 2000; Pestova et al., 1998; Trachsel et al., 1977). The following describes methods for synthesizing and purifying the components of the yeast initiation system and assays useful for its characterization.

Initiation of protein synthesis by hepatitis C virus is refractory to reduced eIF2.GTP.Met-tRNA(i)(Met) ternary complex availability.

A cornerstone of the antiviral interferon response is phosphorylation of eukaryotic initiation factor (eIF)2alpha. This limits the availability of eIF2.GTP.Met-tRNA(i)(Met) ternary complexes, reduces formation of 43S preinitiation complexes, and blocks viral (and most cellular) mRNA translation. However, many viruses have developed counterstrategies that circumvent this cellular response. Herein, we characterize a novel class of translation initiation inhibitors that block ternary complex formation and prevent the assembly of 43S preinitiation complexes. We find that translation driven by the HCV IRES is refractory to inhibition by these compounds at concentrations that effectively block cap-dependent translation in vitro and in vivo. Analysis of initiation complexes formed on the HCV IRES in the presence of inhibitor indicates that eIF2alpha and Met-tRNA(i)(Met) are present, defining a tactic used by HCV to evade part of the antiviral interferon response.

Yeast initiator tRNA identity elements cooperate to influence multiple steps of translation initiation.

All three kingdoms of life employ two methionine tRNAs, one for translation initiation and the other for insertion of methionines at internal positions within growing polypeptide chains. We have used a reconstituted yeast translation initiation system to explore the interactions of the initiator tRNA with the translation initiation machinery. Our data indicate that in addition to its previously characterized role in binding of the initiator tRNA to eukaryotic initiation factor 2 (eIF2), the initiator-specific A1:U72 base pair at the top of the acceptor stem is important for the binding of the eIF2.GTP.Met-tRNA(i) ternary complex to the 40S ribosomal subunit. We have also shown that the initiator-specific G:C base pairs in the anticodon stem of the initiator tRNA are required for the strong thermodynamic coupling between binding of the ternary complex and mRNA to the ribosome. This coupling reflects interactions that occur within the complex upon recognition of the start codon, suggesting that these initiator-specific G:C pairs influence this step. The effect of these anticodon stem identity elements is influenced by bases in the T loop of the tRNA, suggesting that conformational coupling between the D-loop-T-loop substructure and the anticodon stem of the initiator tRNA may occur during AUG codon selection in the ribosomal P-site, similar to the conformational coupling that occurs in A-site tRNAs engaged in mRNA decoding during the elongation phase of protein synthesis.