Residue-Specific Impact of EDTA and Methionine on Protein Oxidation in Biotherapeutics Formulations Using an Integrated Biotherapeutics Drug Product Development Workflow.

The rational design and selection of formulation composition to meet molecule-specific and product-specific needs are critical for biotherapeutics development to ensure physical and chemical stability. This work, based on three antibody-based (mAb) proteins (mAbA, mAbB, and mAbC), evaluates residue-specific impact of EDTA and methionine on protein oxidation, using an integrated biotherapeutics drug product development workflow. This workflow includes statistical experimental design, high-throughput experimental automation and execution, structure-based in silico modeling, inferential statistical analysis, and enhanced interactive data visualization of large datasets. This oxidation study evaluates the impact of formulation parameters including pH, protein concentration, and the presence of polysorbate 80 on the oxidation of specific conserved and variable residues of mAbs A, B, and C in the presence of stressors (iron, peroxide) and/or protectants (EDTA, L-methionine). Residue-specific analysis by automated high-throughput peptide mapping demonstrates differential residue-specific effects of EDTA and methionine in protecting against oxidation, highlighting the need for molecule-specific and product-specific selection of these excipients during formulation development. Computational modeling based on a homology model and the two-shell water coordination method (WCN) was employed to gain mechanistic understanding of residue-specific oxidation susceptibility of methionine residues. The computational determinants of local solvent exposure of methionine residues showed good correlation of WCN with experimentally determined oxidation for corresponding residues. The rapid generation of high-resolution data, statistical data analysis and interactive visualization of the high-throughput residue-level data containing ∼200 unique formulations facilitate residue-specific, molecule-specific and product-specific oxidation (global and local) assessment for oxidation protectants during early development for mAbs and related mAb-based modalities.

DNA-PK Is Targeted by Multiple Vaccinia Virus Proteins to Inhibit DNA Sensing.

Virus infection is sensed by pattern recognition receptors (PRRs) detecting virus nucleic acids and initiating an innate immune response. DNA-dependent protein kinase (DNA-PK) is a PRR that binds cytosolic DNA and is antagonized by vaccinia virus (VACV) protein C16. Here, VACV protein C4 is also shown to antagonize DNA-PK by binding to Ku and blocking Ku binding to DNA, leading to a reduced production of cytokines and chemokines in vivo and a diminished recruitment of inflammatory cells. C4 and C16 share redundancy in that a double deletion virus has reduced virulence not seen with single deletion viruses following intradermal infection. However, non-redundant functions exist because both single deletion viruses display attenuated virulence compared to wild-type VACV after intranasal infection. It is notable that VACV expresses two proteins to antagonize DNA-PK, but it is not known to target other DNA sensors, emphasizing the importance of this PRR in the response to infection in vivo.

Identification of a Novel Class of BRD4 Inhibitors by Computational Screening and Binding Simulations.

Computational screening is a method to prioritize small-molecule compounds based on the structural and biochemical attributes built from ligand and target information. Previously, we have developed a scalable virtual screening workflow to identify novel multitarget kinase/bromodomain inhibitors. In the current study, we identified several novel N-[3-(2-oxo-pyrrolidinyl)phenyl]-benzenesulfonamide derivatives that scored highly in our ensemble docking protocol. We quantified the binding affinity of these compounds for BRD4(BD1) biochemically and generated cocrystal structures, which were deposited in the Protein Data Bank. As the docking poses obtained in the virtual screening pipeline did not align with the experimental cocrystal structures, we evaluated the predictions of their precise binding modes by performing molecular dynamics (MD) simulations. The MD simulations closely reproduced the experimentally observed protein-ligand cocrystal binding conformations and interactions for all compounds. These results suggest a computational workflow to generate experimental-quality protein-ligand binding models, overcoming limitations of docking results due to receptor flexibility and incomplete sampling, as a useful starting point for the structure-based lead optimization of novel BRD4(BD1) inhibitors.

Potent Dual BET Bromodomain-Kinase Inhibitors as Value-Added Multitargeted Chemical Probes and Cancer Therapeutics.

Synergistic action of kinase and BET bromodomain inhibitors in cell killing has been reported for a variety of cancers. Using the chemical scaffold of the JAK2 inhibitor TG101348, we developed and characterized single agents which potently and simultaneously inhibit BRD4 and a specific set of oncogenic tyrosine kinases including JAK2, FLT3, RET, and ROS1. Lead compounds showed on-target inhibition in several blood cancer cell lines and were highly efficacious at inhibiting the growth of hematopoietic progenitor cells from patients with myeloproliferative neoplasm. Screening across 931 cancer cell lines revealed differential growth inhibitory potential with highest activity against bone and blood cancers and greatly enhanced activity over the single BET inhibitor JQ1. Gene drug sensitivity analyses and drug combination studies indicate synergism of BRD4 and kinase inhibition as a plausible reason for the superior potency in cell killing. Combined, our findings indicate promising potential of these agents as novel chemical probes and cancer therapeutics. Mol Cancer Ther; 16(6); 1054-67. ©2017 AACR.

Assessment of Bromodomain Target Engagement by a Series of BI2536 Analogues with Miniaturized BET-BRET.

Evaluating the engagement of a small molecule ligand with a protein target in cells provides useful information for chemical probe optimization and pharmaceutical development. While several techniques exist that can be performed in a low-throughput manner, systematic evaluation of large compound libraries remains a challenge. In-cell engagement measurements are especially useful when evaluating compound classes suspected to target multiple cellular factors. In this study we used a bioluminescent resonant energy transfer assay to assess bromodomain engagement by a compound series containing bromodomain- and kinase-biasing polypharmacophores based on the known dual BRD4 bromodomain/PLK1 kinase inhibitor BI2536. With this assay, we discovered several novel agents with bromodomain-selective specificity profiles and cellular activity. Thus, this platform aids in distinguishing molecules whose cellular activity is difficult to assess due to polypharmacologic effects.

Fluorinated aromatic amino acids are sensitive 19F NMR probes for bromodomain-ligand interactions.

We describe a (19)F NMR method for detecting bromodomain-ligand interactions using fluorine-labeled aromatic amino acids due to the conservation of aromatic residues in the bromodomain binding site. We test the sensitivity, accuracy, and speed of this method with small molecule ligands (+)-JQ1, BI2536, Dinaciclib, TG101348, and acetaminophen using three bromodomains Brd4, BrdT, and BPTF. Simplified (19)F NMR spectra allowed for simultaneous testing of multiple bromodomains to assess selectivity and identification of a new BPTF ligand. Fluorine labeling only modestly affected the Brd4 structure and function assessed by isothermal titration calorimetry, circular dichroism, and X-ray crystallography. The speed, ease of interpretation, and low concentration of protein needed for binding experiments affords a new method to discover and characterize both native and new ligands.

Acetyl-lysine binding site of bromodomain-containing protein 4 (BRD4) interacts with diverse kinase inhibitors.

Members of the bromodomain and extra terminal (BET) family of proteins are essential for the recognition of acetylated lysine (KAc) residues in histones and have emerged as promising drug targets in cancer, inflammation, and contraception research. In co-crystallization screening campaigns using the first bromodomain of BRD4 (BRD4-1) against kinase inhibitor libraries, we identified and characterized 14 kinase inhibitors (10 distinct chemical scaffolds) as ligands of the KAc binding site. Among these, the PLK1 inhibitor BI2536 and the JAK2 inhibitor TG101209 displayed strongest inhibitory potential against BRD4 (IC50=25 nM and 130 nM, respectively) and high selectivity for BET bromodomains. Comparative structural analysis revealed markedly different binding modes of kinase hinge-binding scaffolds in the KAc binding site, suggesting that BET proteins are potential off-targets of diverse kinase inhibitors. Combined, these findings provide a new structural framework for the rational design of next-generation BET-selective and dual-activity BET-kinase inhibitors.

Vaccinia virus immune evasion: mechanisms, virulence and immunogenicity.

Virus infection of mammalian cells is sensed by pattern recognition receptors and leads to an innate immune response that restricts virus replication and induces adaptive immunity. In response, viruses have evolved many countermeasures that enable them to replicate and be transmitted to new hosts, despite the host innate immune response. Poxviruses, such as vaccinia virus (VACV), have large DNA genomes and encode many proteins that are dedicated to host immune evasion. Some of these proteins are secreted from the infected cell, where they bind and neutralize complement factors, interferons, cytokines and chemokines. Other VACV proteins function inside cells to inhibit apoptosis or signalling pathways that lead to the production of interferons and pro-inflammatory cytokines and chemokines. In this review, these VACV immunomodulatory proteins are described and the potential to create more immunogenic VACV strains by manipulation of the gene encoding these proteins is discussed.

A mechanism for induction of a hypoxic response by vaccinia virus.

Viruses have evolved sophisticated strategies to exploit host cell function for their benefit. Here we show that under physiologically normal oxygen levels (normoxia) vaccinia virus (VACV) infection leads to a rapid stabilization of hypoxia-inducible factor (HIF)-1α, its translocation into the nucleus and the activation of HIF-responsive genes, such as vascular endothelial growth factor (VEGF), glucose transporter-1, and pyruvate dehydrogenase kinase-1. HIF-1α stabilization is mediated by VACV protein C16 that binds the human oxygen sensing enzyme prolyl-hydroxylase domain containing protein (PHD)2 and thereby inhibits PHD2-dependent hydroxylation of HIF-1α. The binding between C16 and PHD2 is direct and specific, and ectopic expression of C16 alone induces transcription of HIF-1α responsive genes. Conversely, a VACV strain lacking the gene for C16, C16L, is unable to induce HIF-1α stabilization. Interestingly, the N-terminal region of C16 is predicted to have a PHD2-like structural fold but lacks the catalytic active site residues of PHDs. The induction of a hypoxic response by VACV is reminiscent of the biochemical consequences of solid tumor formation, and illustrates a poxvirus strategy for manipulation of cellular gene expression and biochemistry.

Vaccinia virus protein C4 inhibits NF-κB activation and promotes virus virulence.

Vaccinia virus (VACV) strain Western Reserve protein C4 has been characterized and its function and contribution to virus virulence assessed. Bioinformatic analysis showed that C4 is conserved in six orthopoxvirus species and shares 43 % amino acid identity with VACV protein C16, a known virulence factor. A recombinant VACV expressing a C-terminally tagged version of C4 showed that, like C16, this 37 kDa protein is expressed early during infection and localizes to both the cytoplasm and the nucleus. Functional assays using a firefly luciferase reporter plasmid under the control of a nuclear factor kappa B (NF-κB)-dependent promoter demonstrated that C4 inhibits NF-κB activation at, or downstream of, the inhibitor of kappa kinase (IKK) complex. Consistent with this, C4 inhibited interleukin-1ß-induced translocation of p65 into the nucleus. A VACV lacking the C4L gene (vΔC4) showed no significant differences from wild-type virus in growth kinetics or spread in cell culture, but had reduced virulence in a murine intranasal model of infection. vΔC4-infected mice exhibited fewer symptoms, lost less weight and recovered 7 days earlier than animals infected with control viruses expressing C4. Furthermore, bronchoalveolar lavage fluid from vΔC4-infected mice had increased cell numbers at day 5 post-infection, which correlated with reduced lung virus titres from this time onward. C4 represents the ninth VACV protein to inhibit NF-κB activation and remarkably, in every case examined, loss of each protein individually caused an alteration in virus virulence, despite the presence of other NF-κB inhibitors.

Fast DNA and protein microarray tests for the diagnosis of hepatitis C virus infection on a single platform.

Hepatitis C virus (HCV) is a major cause of chronic liver disease and liver cancer, and remains a large health care burden to the world. In this study we developed a DNA microarray test to detect HCV RNA and a protein microarray to detect human anti-HCV antibodies on a single platform. A main focus of this study was to evaluate possibilities to reduce the assay time, as a short time-to-result (TTR) is a prerequisite for a point-of-care test. Significantly reducing hybridisation and washing times did not impair the assay performance. This was confirmed first using artificial targets and subsequently using clinical samples from an HCV seroconversion panel derived from a HCV-infected patient. We were able to reduce the time required for the detection of human anti-HCV antibodies to only 14 min, achieving nanomolar sensitivity. The protein microarray exhibited an analytical sensitivity comparable to that of commercial systems. Similar results were obtained with the DNA microarray using a universal probe which covered all different HCV genotypes. It was possible to reduce the assay time after PCR from 150 min to 16 min without any loss of sensitivity. Taken together, these results constitute a significant step forward in the design of rapid, microarray-based diagnostics for human infectious disease, and show that the protein microarray is currently the most favourable candidate to fill this role.

Peptide-tags for enhanced DNA microarray performance.

DNA microarrays are powerful tools for gene expression analysis and genotyping studies in research and diagnostic applications. A high sensitivity and short time-to-result are prerequisites for their practical application in the clinic. The hybridization efficiency of DNA microarrays depends on the probe density and the probe orientation and thus their accessibility for target molecules. In order to find an optimal probe immobilization procedure a set of different oligonucleotide modifications was tested on epoxy silane functionalized glass slides. It was found that histidine-tagged oligonucleotides resulted in the highest amount of bound probe and by far the best hybridization efficiencies. The detection limit obtained with histidine-tagged probes was up to two orders of magnitude lower compared to commonly used probe modifications. In order to further investigate the binding mechanism of histidine-tags towards functionalized glass substrates a set of different peptide-tags with and without free terminal amino-groups and with different amino acid compositions was tested. The results indicate an impact of the terminal amino group on the covalent surface binding and of aromatic amino acid residues on the enhanced hybridisation efficiency.

Multi-factorial analysis of class prediction error: estimating optimal number of biomarkers for various classification rules.

Machine learning and statistical model based classifiers have increasingly been used with more complex and high dimensional biological data obtained from high-throughput technologies. Understanding the impact of various factors associated with large and complex microarray datasets on the predictive performance of classifiers is computationally intensive, under investigated, yet vital in determining the optimal number of biomarkers for various classification purposes aimed towards improved detection, diagnosis, and therapeutic monitoring of diseases. We investigate the impact of microarray based data characteristics on the predictive performance for various classification rules using simulation studies. Our investigation using Random Forest, Support Vector Machines, Linear Discriminant Analysis and k-Nearest Neighbour shows that the predictive performance of classifiers is strongly influenced by training set size, biological and technical variability, replication, fold change and correlation between biomarkers. Optimal number of biomarkers for a classification problem should therefore be estimated taking account of the impact of all these factors. A database of average generalization errors is built for various combinations of these factors. The database of generalization errors can be used for estimating the optimal number of biomarkers for given levels of predictive accuracy as a function of these factors. Examples show that curves from actual biological data resemble that of simulated data with corresponding levels of data characteristics. An R package optBiomarker implementing the method is freely available for academic use from the Comprehensive R Archive Network (http://www.cran.r-project.org/web/packages/optBiomarker/).

Fluorescence lifetime imaging of quantum dot labeled DNA microarrays.

Quantum dot (QD) labeling combined with fluorescence lifetime imaging microscopy is proposed as a powerful transduction technique for the detection of DNA hybridization events. Fluorescence lifetime analysis of DNA microarray spots of hybridized QD labeled target indicated a characteristic lifetime value of 18.8 ns, compared to 13.3 ns obtained for spots of free QD solution, revealing that QD labels are sensitive to the spot microenvironment. Additionally, time gated detection was shown to improve the microarray image contrast ratio by 1.8, achieving femtomolar target sensitivity. Finally, lifetime multiplexing based on Qdot525 and Alexa430 was demonstrated using a single excitation-detection readout channel.