Proven Drug Targets Research Articles

A computational biology approach for the identification of potential SARS-CoV-2 main protease inhibitors from natural essential oil compounds.

Background: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has fomented a climate of fear worldwide due to its rapidly spreading nature, and high mortality rate. The World Health Organization (WHO) declared it as a global pandemic on 11th March, 2020. Many endeavors have been made to find appropriate medications to restrain the SARS CoV-2 infection from spreading but there is no specific antiviral therapy to date. However, a computer-aided drug design approach can be an alternative to identify probable drug candidates within a short time. SARS-CoV-2 main protease is a proven drug target, and it plays a pivotal role in viral replication and transcription. Methods: In this study, we identified a total of 114 essential oil compounds as a feasible anti-SARS-CoV-2 agent from several online reservoirs. These compounds were screened by incorporating ADMET profiling, molecular docking, and 50 ns of molecular dynamics simulation to identify potential drug candidates against the SARS-CoV-2 main protease. The crystallized SARS-CoV-2 main protease structure was collected from the RCSB PDB database (PDB ID 6LU7). Results: According to the results of the ADMET study, none of the compounds have any side effects that could reduce their druglikeness or pharmacokinetic properties. Out of 114 compounds, we selected bisabololoxide B, eremanthin, and leptospermone as our top drug candidates based on their higher binding affinity scores, and strong interaction with the Cys 145-His 41 catalytic dyad. Finally, the molecular dynamics simulation was implemented to evaluate the structural stability of the ligand-receptor complex. MD simulations disclosed that all the hits showed conformational stability compared to the positive control α-ketoamide. Conclusions: Our study showed that the top three hits might work as potential anti-SARS-CoV-2 agents, which can pave the way for discovering new drugs, but for experimental validation, they will require more in vivo trials.

Pin1-catalyzed conformational regulation after phosphorylation: A distinct checkpoint in cell signaling and drug discovery.

Protein phosphorylation is one of the most common mechanisms regulating cellular signaling pathways, and many kinases and phosphatases are proven drug targets. Upon phosphorylation, protein functions can be further regulated by the distinct isomerase Pin1 through cis-trans isomerization. Numerous protein targets and many important roles have now been elucidated for Pin1. However, no tools are available to detect or target cis and trans conformation events in cells. The development of Pin1 inhibitors and stereo- and phospho-specific antibodies has revealed that cis and trans conformations have distinct and often opposing cellular functions. Aberrant conformational changes due to the dysregulation of Pin1 can drive pathogenesis but can be effectively targeted in age-related diseases, including cancers and neurodegenerative disorders. Here, we review advances in understanding the roles of Pin1 signaling in health and disease and highlight conformational regulation as a distinct signal transduction checkpoint in disease development and treatment.

Full-length αIIbβ3 cryo-EM structure reveals intact integrin initiate-activation intrinsic architecture

Integrin αIIbβ3 is the key receptor regulating platelet retraction and accumulation and a proven drug-target for antithrombotic therapies. Here we resolve the cryo-EM structures of the full-length αIIbβ3, which covers three distinct states along the activation pathway. Firstly, we obtain the αIIbβ3 structure at 3Å resolution in the inactive state, revealing the overall topology of the heterodimer with the transmembrane (TM) helices and the ligand-binding domain tucked in a specific angle proximity to the TM region. After the addition of a Mn2+ agonist, we resolve two coexisting structures representing two new states between inactive and active state. Our structures show conformational changes of the αIIbβ3 activating trajectory and a unique twisting of the integrin legs, which is required for platelets accumulation. Our structure provides direct structural evidence for how the lower legs are involved in full-length integrin activation mechanisms and offers a new strategy to target the αIIbβ3 lower leg.

Relational Graph Convolution Network with Multi Features for AntiCOVID-19 Drugs Discovery using 3CLpro Potential Target

Background: The potential of graph neural networks (GNNs) to revolutionize the analysis of non-Euclidean data has gained attention recently, making them attractive models for deep machine learning. However, insufficient compound or moleculargraphs and feature representations might significantly impair and jeopardize their full potential. Despite the devastating impacts of ongoing COVID-19 across the globe, for which there is no drug with proven efficacy that has been shown tobe effective. As various stages of drug discovery and repositioning require the accurate prediction of drugtarget interactions(DTI), here, we propose a relational graph convolution network using multi-features based on the developed drug chemicalcompound-coronavirus target graph representation and combination of features. During the implementation of the model, we further introduced the use of not only the feature module to understand the topological structure of drugs but also the structure of the proven drug target (i.e., 3CLpro) for SARS-Cov-2 that shares a genome sequence similar to that of other members of the beta-coronavirus group such as SARS-Cov, MERS-CoV, bat coronavirus. Our feature comprises topologicalinformation in molecular SMILES and local chemical context in the SMILES sequence for the drug chemical compound and drug target. Our proposed method prevailed with high and compelling performance accuracy of 97.30% which could beprioritized as the potential and promising prediction route for the development of novel oral antiviral medicine for COVID-19 drugs. Objective: Forecasting DTI stands as a pivotal aspect of drug discovery. The focus on computational methods in DTI prediction has intensified due to the considerable expense and time investment associated with conducting extensive in vitro and in vivo experiments. Machine learning techniques, particularly deep learning, have found broad applications in DTI prediction. We are convinced that this study could be prioritized and utilized as the promising predictive route for the development of novel oral antiviral treatments for COVID-19 and other variants of coronaviruses. Methods: This study addressed the problem of COVID-19 drugs using proposed RGCN with multifeatures as an attractive and potential route. This study focused mainly on the prediction of novel antiviral drugs against coronaviruses using graph-based methodology, namely RGCN. This research further utilized the features of both drugs and common potential drug targets found in betacoronaviruses group to deepen understanding of their underlying relation. Results: Our suggested approach prevailed with a high and convincing performance accuracy of 97.30%, which may be utilizedas a top priority to support and advance this field in the prediction and development of novel antiviral treatments against coronaviruses and their variants. Conclusion: We recursively performed experiments using the proposed method on our constructed DCCCvT graph dataset from our collected dataset with various single and multiple combinations of features and found that our model had achieved comparable best-averaged accuracy performance on T7 features followed by a combination of T7, R6, and L8. The proposed model implemented in this investigation turns out to outperform the previous related works.

Plasma Membrane-Cell Wall Feedback in Bacteria.

Most bacteria have cell wall peptidoglycan surrounding their plasma membranes. The essential cell wall provides a scaffold for the envelope, protection against turgor pressure and is a proven drug target. Synthesis of the cell wall involves reactions that span cytoplasmic and periplasmic compartments. Bacteria carry out the last steps of cell wall synthesis along their plasma membrane. The plasma membrane in bacteria is heterogeneous and contains membrane compartments. Here, I outline findings that highlight the emerging notion that plasma membrane compartments and the cell wall peptidoglycan are functionally intertwined. I start by providing models of cell wall synthesis compartmentalization within the plasma membrane in mycobacteria, Escherichia coli, and Bacillus subtilis. Then, I revisit literature that supports a role for the plasma membrane and its lipids in modulating enzymatic reactions that synthesize cell wall precursors. I also elaborate on what is known about bacterial lateral organization of the plasma membrane and the mechanisms by which organization is established and maintained. Finally, I discuss the implications of cell wall partitioning in bacteria and highlight how targeting plasma membrane compartmentalization serves as a way to disrupt cell wall synthesis in diverse species.

Rock1 is a novel host dependency factor of human enterovirus A71: Implication as a drug target.

Human enterovirus A71 (EV-A71) is the major causative agent of hand-foot-and-mouth disease (HFMD) commonly associated with severe neurological diseases, particularly in children under 5 years of age. Several investigational therapeutic agents and vaccine candidates are being developed. However, no approved drug against EV-A71 infection is available, and no proven drug target has been identified. Since host kinases are key regulators of multiple signaling pathways in response to viral infections, here we screened a kinase inhibitor library and identified potent inhibitors against EV-A71 infection. Among the hits, GSK269962A, a Rho Associated Coiled-Coil Containing Protein Kinase (Rock) inhibitor with potent antiviral activity, was selected for further analysis. We found that this Rock inhibitor not only efficiently suppressed the replication of EV-A71 in RD cells, but also in human intestinal organoids, in a dose-dependent manner. Interestingly, small interfering RNA depletion of Rock1, but not Rock2, significantly restricted viral replication in RD cells, indicating that Rock1 is a novel host dependency factor for EV-A71 replication and can serve as a target for the development of anti-EV-A71 therapeutics.

A computational biology approach for the identification of potential SARS-CoV-2 main protease inhibitors from natural essential oil compounds.

Background: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has fomented a climate of fear worldwide due to its rapidly spreading nature, and high mortality rate. The World Health Organization declared it a global pandemic on 11 March 2020. Many endeavors have been made to find appropriate medications to restrain the SARS-CoV-2 infection from spreading but there is no specific antiviral therapy to date. However, a computer-aided drug design approach can be an alternative to identify probable drug candidates within a short time. SARS-CoV-2 main protease is a proven drug target, and it plays a pivotal role in viral replication and transcription. Methods: In this study, we identified a total of 114 essential oil compounds as a feasible anti-SARS-CoV-2 agent from several online reservoirs. These compounds were screened by incorporating absorption, distribution, metabolism, excretion, and toxicity (ADMET) profiling, molecular docking, and 50 ns of molecular dynamics simulation to identify potential drug candidates. The crystallized SARS-CoV-2 main protease structure was collected from the Research Collaboratory for Structural Bioinformatics Protein Data Bank database (Protein Data Bank ID 6LU7). Results: According to the results of the ADMET study, none of the compounds have any side effects that could reduce their druglikeness or pharmacokinetic properties. Among 114 compounds, we selected bisabololoxide B, eremanthin, and leptospermone as top drug candidates based on their higher binding affinity scores, and strong interaction with the Cys 145-His 41 catalytic dyad. Finally, the molecular dynamics simulation was implemented to evaluate the structural stability of the ligand-receptor complex. Molecular dynamics simulation disclosed that all the hits showed conformational stability compared to the positive control α-ketoamide. Conclusions: Our study showed that the top three hits might work as potential anti-SARS-CoV-2 agents, which can pave the way for discovering new drugs, but further in vivo trials will require for experimental validation.

Abstract 605: MoA-based potency bioassays for immunotherapy programs targeting the TIGIT/CD112R/CD226 axis

Abstract Immune checkpoint (IC) receptors play critical roles in maintaining immune homeostasis and have emerged as proven drug targets for the treatment of various cancers and autoimmune disorders. Monoclonal antibodies (mAb) designed to block immune inhibitory receptors PD-1 and CTLA-4 have been approved and show unprecedented efficacy in cancer treatment. This led to rapid expansion of drug development to many more IC receptors including members of the T cell immunoreceptor with Ig and ITIM domains (TIGIT) - CD112R (PVRIG) - CD226 Axis. TIGIT binds to its ligands CD155 (PVR) and CD112 (PVRL2) while CD112R binds to CD112. Binding of TIGIT or CD112R to CD155/CD112 inhibits the co-stimulatory activity of the paired receptor CD226. Thus, therapeutic targeting of this axis can modulate T cell and NK cell activation and unleash anti-cancer immunity. One of the bottlenecks of immunotherapy drug development is the lack of quantitative and reproducible functional assays for mAb potency determination. Existing methods rely heavily on primary immune cells which is labor intensive and highly variable. To address this need, we developed a panel of cell-based reporter bioassays that can quantitatively measure the potencies of mAbs targeting TIGIT/CD155, TIGIT/CD112, and CD112R/CD112. Owing to positive clinical trial results of TIGIT blockade in combination with PD-1/PD-L1 blockade, we further developed a potency bioassay for bispecific antibodies simultaneously targeting TIGIT and PD-1/PD-L1. These bioassays each consist of an engineered T effector cell line that expresses T cell receptors and IC receptors of interest, and an engineered artificial antigen presenting cells (aAPC) expressing the corresponding ligands for the IC receptors. The T effector cell lines also express a luciferase reporter driven by a promoter specifically responding to TCR activation which can be inhibited by signaling from the IC receptors. Additionally, we developed bioassays that can measure potencies of agonist or antagonist mAbs targeting CD226. These bioassays are designed to reflect the mechanisms of action for the drug candidates designed for each IC receptor and the assay signals are specific. Most are prequalified according to ICH guidelines and show the precision, accuracy and linearity required for relative potency determination and product stability study under cGMP environments. Therefore, these MoA-based bioassays can serve as valuable tools for early drug discovery, potency determination and stability studies throughout the development of mAbs targeting the TIGIT/CD112R/CD226 axis. Citation Format: Jamison Grailer, Denise Garvin, Jim Hartnett, Frank Fan, Mei Cong, Zhi-Jie Jey Cheng. MoA-based potency bioassays for immunotherapy programs targeting the TIGIT/CD112R/CD226 axis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 605.

In Silico Evaluation of Antifungal Compounds from Marine Sponges against COVID-19-Associated Mucormycosis.

The world is already facing the devastating effects of the SARS-CoV-2 pandemic. A disseminated mucormycosis epidemic emerged to worsen this situation, causing havoc, especially in India. This research aimed to perform a multitargeted docking study of marine-sponge-origin bioactive compounds against mucormycosis. Information on proven drug targets and marine sponge compounds was obtained via a literature search. A total of seven different targets were selected. Thirty-five compounds were chosen using the PASS online program. For homology modeling and molecular docking, FASTA sequences and 3D structures for protein targets were retrieved from NCBI and PDB databases. Autodock Vina in PyRx 0.8 was used for docking studies. Further, molecular dynamics simulations were performed using the IMODS server for top-ranked docked complexes. Moreover, the drug-like properties and toxicity analyses were performed using Lipinski parameters in Swiss-ADME, OSIRIS, ProTox-II, pkCSM, and StopTox servers. The results indicated that naamine D, latrunculin A and S, (+)-curcudiol, (+)-curcuphenol, aurantoside I, and hyrtimomine A had the highest binding affinity values of −8.8, −8.6, −9.8, −11.4, −8.0, −11.4, and −9.0 kcal/mol, respectively. In sum, all MNPs included in this study are good candidates against mucormycosis. (+)-curcudiol and (+)-curcuphenol are promising compounds due to their broad-spectrum target inhibition potential.

A computational biology approach for the identification of potential SARS-CoV-2 main protease inhibitors from natural essential oil compounds.

Background: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has fomented a climate of fear worldwide due to its rapidly spreading nature, and high mortality rate. The World Health Organization (WHO) declared it as a global pandemic on 11th March, 2020. Many endeavors have been made to find appropriate medications to restrain the SARS CoV-2 infection from spreading but there is no specific antiviral therapy to date. However, a computer-aided drug design approach can be an alternative to identify probable drug candidates within a short time. SARS-CoV-2 main protease is a proven drug target, and it plays a pivotal role in viral replication and transcription. Methods: In this study, we identified a total of 114 essential oil compounds as a feasible anti-SARS-CoV-2 agent from several online reservoirs. These compounds were screened by incorporating ADMET profiling, molecular docking, and 50 ns of molecular dynamics simulation to identify potential drug candidates against the SARS-CoV-2 main protease. The crystallized SARS-CoV-2 main protease structure was collected from the RCSB PDB database (PDB ID 6LU7). Results: According to the results of the ADMET study, none of the compounds have any side effects that could reduce their druglikeness or pharmacokinetic properties. Out of 114 compounds, we selected bisabololoxide B, eremanthin, and leptospermone as our top drug candidates based on their higher binding affinity scores, and strong interaction with the Cys 145-His 41 catalytic dyad. Finally, the molecular dynamics simulation was implemented to evaluate the structural stability of the ligand-receptor complex. MD simulations disclosed that all the hits showed conformational stability compared to the positive control α-ketoamide. Conclusions: Our study showed that the top three hits might work as potential anti-SARS-CoV-2 agents, which can pave the way for discovering new drugs, but for experimental validation, they will require more in vivo trials.

A novel Apigenin derivative suppresses renal cell carcinoma via directly inhibiting wild-type and mutant MET

MET, the receptor of hepatocyte growth factor (HGF), is a driving factor in renal cell carcinoma (RCC) and also a proven drug target for cancer treatment. To improve the activity and to investigate the mechanisms of action of Apigenin (APG), novel derivatives of APG with improved properties were synthesized and their activities against Caki-1 human renal cancer cell line were evaluated. It was found that compound 15e exhibited excellent potency against the growth of multiple RCC cell lines including Caki-1, Caki-2 and ACHN and is superior to APG and Crizotinib. Subsequent investigations demonstrated that compound 15e can inhibit Caki-1 cell proliferation, migration and invasion. Mechanistically, 15e directly targeted the MET kinase domain, decreased its auto-phosphorylation at Y1234/Y1235 and inhibited its kinase activity and downstream signaling. Importantly, 15e had inhibitory activity against mutant MET V1238I and Y1248H which were resistant to approved MET inhibitors Cabozantinib, Crizotinib or Capmatinib. In vivo tumor graft study confirmed that 15e repressed RCC growth through inhibition of MET activation. These results indicate that compound 15e has the potential to be developed as a treatment for RCC, and especially against drug-resistant MET mutations.

Rapid, direct detection of bacterial topoisomerase 1-DNA adducts by RADAR/ELISA

Topoisomerases are proven drug targets, but antibiotics that poison bacterial Topoisomerase 1 (Top1) have yet to be discovered. We have developed a rapid and direct assay for quantification of Top1-DNA adducts that is suitable for high throughput assays. Adducts are recovered by "RADAR fractionation", a quick, convenient approach in which cells are lysed in chaotropic salts and detergent and nucleic acids and covalently bound adducts then precipitated with alcohol. Here we show that RADAR fractionation followed by ELISA immunodetection can quantify adducts formed by wild-type and mutant Top1 derivatives encoded by two different bacterial pathogens, Y. pestis and M. tuberculosis, expressed in E. coli or M. smegmatis, respectively. For both enzymes, quantification of adducts by RADAR/ELISA produces results comparable to the more cumbersome classical approach of CsCl density gradient fractionation. The experiments reported here establish that RADAR/ELISA assay offers a simple way to characterize Top1 mutants and analyze kinetics of adduct formation and repair. They also provide a foundation for discovery and optimization of drugs that poison bacterial Top1 using standard high-throughput approaches.

Molecular basis of the multifaceted functions of human leucyl-tRNA synthetase in protein synthesis and beyond.

Human cytosolic leucyl-tRNA synthetase (hcLRS) is an essential and multifunctional enzyme. Its canonical function is to catalyze the covalent ligation of leucine to tRNALeu, and it may also hydrolyze mischarged tRNAs through an editing mechanism. Together with eight other aminoacyl-tRNA synthetases (AaRSs) and three auxiliary proteins, it forms a large multi-synthetase complex (MSC). Beyond its role in translation, hcLRS has an important moonlight function as a leucine sensor in the rapamycin complex 1 (mTORC1) pathway. Since this pathway is active in cancer development, hcLRS is a potential target for anti-tumor drug development. Moreover, LRS from pathogenic microbes are proven drug targets for developing antibiotics, which however should not inhibit hcLRS. Here we present the crystal structure of hcLRS at a 2.5 Å resolution, the first complete structure of a eukaryotic LRS, and analyze the binding of various compounds that target different sites of hcLRS. We also deduce the assembly mechanism of hcLRS into the MSC through reconstitution of the entire mega complex in vitro. Overall, our study provides the molecular basis for understanding both the multifaceted functions of hcLRS and for drug development targeting these functions.

Divergent Mitochondrial Ribosomes in Unicellular Parasitic Protozoans

The mitochondrion in parasitic protozoans is a clinically proven drug target. A specialized ribosome (mitoribosome) is required to translate genes encoded on the mitochondrial (mt) DNA. Despite the significance, little is known about mitoribosomes in many medically and economically important unicellular protozoans.

A complex suite of loci and elements in eukaryotic type II topoisomerases determine selective sensitivity to distinct poisoning agents.

Type II topoisomerases catalyze essential DNA transactions and are proven drug targets. Drug discrimination by prokaryotic and eukaryotic topoisomerases is vital to therapeutic utility, but is poorly understood. We developed a next-generation sequencing (NGS) approach to identify drug-resistance mutations in eukaryotic topoisomerases. We show that alterations conferring resistance to poisons of human and yeast topoisomerase II derive from a rich mutational ‘landscape’ of amino acid substitutions broadly distributed throughout the entire enzyme. Both general and discriminatory drug-resistant behaviors are found to arise from different point mutations found at the same amino acid position and to occur far outside known drug-binding sites. Studies of selected resistant enzymes confirm the NGS data and further show that the anti-cancer quinolone vosaroxin acts solely as an intercalating poison, and that the antibacterial ciprofloxacin can poison yeast topoisomerase II. The innate drug-sensitivity of the DNA binding and cleavage region of human and yeast topoisomerases (particularly hTOP2β) is additionally revealed to be significantly regulated by the enzymes’ adenosine triphosphatase regions. Collectively, these studies highlight the utility of using NGS-based methods to rapidly map drug resistance landscapes and reveal that the nucleotide turnover elements of type II topoisomerases impact drug specificity.

Exploiting the Diversity of Ion Channels: Modulation of Ion Channels for Therapeutic Indications.

Ion channels are macromolecular proteins that form water-filled pores in cell membranes and they are critical for a variety of physiological and pharmacological functions. Dysfunctional ion channels can cause diseases known as channelopathies. Ion channels are encoded by approximately 400 genes, representing the second largest class of proven drug targets for therapeutic areas including neuropsychiatric disorders, cardiovascular and metabolic diseases, immunological diseases, nephrological diseases, gastrointestinal diseases, pulmonary/respiratory diseases, and many cancers. With more ion channel structures are being solved and functional robust assays are being developed, there are tremendous opportunities for identifying specific modulators targeting ion channels for new therapy.

Constrained target controllability of complex networks

It is of great theoretical interest and practical significance to study how to control a system by applying perturbations to only a few driver nodes. Recently, a hot topic of modern network researches is how to determine driver nodes that allow the control of an entire network. However, in practice, to control a complex network, especially a biological network, one may know not only the set of nodes which need to be controlled (i.e. target nodes), but also the set of nodes to which only control signals can be applied (i.e. constrained control nodes). Compared to the general concept of controllability, we introduce the concept of constrained target controllability (CTC) of complex networks, which concerns the ability to drive any state of target nodes to their desirable state by applying control signals to the driver nodes from the set of constrained control nodes. To efficiently investigate the CTC of complex networks, we further design a novel graph-theoretic algorithm called CTCA to estimate the ability of a given network to control targets by choosing driver nodes from the set of constrained control nodes. We extensively evaluate the CTC of numerous real complex networks. The results indicate that biological networks with a higher average degree are easier to control than biological networks with a lower average degree, while electronic networks with a lower average degree are easier to control than web networks with a higher average degree. We also show that our CTCA can more efficiently produce driver nodes for target-controlling the networks than existing state-of-the-art methods. Moreover, we use our CTCA to analyze two expert-curated bio-molecular networks and compare to other state-of-the-art methods. The results illustrate that our CTCA can efficiently identify proven drug targets and new potentials, according to the constrained controllability of those biological networks.

Removing the needle from the haystack: Enrichment of Wolbachia endosymbiont transcripts from host nematode RNA by Cappable-seq™.

Efficient transcriptomic sequencing of microbial mRNA derived from host-microbe associations is often compromised by the much lower relative abundance of microbial RNA in the mixed total RNA sample. One solution to this problem is to perform extensive sequencing until an acceptable level of transcriptome coverage is obtained. More cost-effective methods include use of prokaryotic and/or eukaryotic rRNA depletion strategies, sometimes in conjunction with depletion of polyadenylated eukaryotic mRNA. Here, we report use of Cappable-seq™ to specifically enrich, in a single step, Wolbachia endobacterial mRNA transcripts from total RNA prepared from the parasitic filarial nematode, Brugia malayi. The obligate Wolbachia endosymbiont is a proven drug target for many human filarial infections, yet the precise nature of its symbiosis with the nematode host is poorly understood. Insightful analysis of the expression levels of Wolbachia genes predicted to underpin the mutualistic association and of known drug target genes at different life cycle stages or in response to drug treatments is typically challenged by low transcriptomic coverage. Cappable-seq resulted in up to ~ 5-fold increase in the number of reads mapping to Wolbachia. On average, coverage of Wolbachia transcripts from B. malayi microfilariae was enriched ~40-fold by Cappable-seq. Additionally, this method has an additional benefit of selectively removing abundant prokaryotic ribosomal RNAs.The deeper microbial transcriptome sequencing afforded by Cappable-seq facilitates more detailed characterization of gene expression levels of pathogens and symbionts present in animal tissues.

Clinically proven drug targets differentially expressed in the prefrontal cortex of schizophrenia patients

BackgroundDue to the heterogeneous nature of schizophrenia, understanding the genetic risk for the disease is a complex task. Gene expression studies have proven to be more reliable than association studies as they are consistently replicated in a tissue specific manner. MethodsUsing RNA-Seq we analysed gene expression in the frontal cortex of 24 individuals with schizophrenia and 25 unaffected controls. ResultsWe identified 1146 genes that were differentially expressed in schizophrenia, approximately 60% of which were up-regulated and 366 of 1146 (32%) also have aberrant DNA methylation (p=2.46×10−39). The differentially expressed genes were significantly overrepresented in several pathways including inflammatory (p=8.7×10−3) and nitric oxide pathways (p=9.2×10−4). Moreover, these genes were significantly enriched for those with a druggable genome (p=0.04). We identified a number of genes that are significantly up-regulated in schizophrenia as confirmed in other gene expression studies using different brain tissues. Of the 349 genes associated with schizophrenia from the Psychiatric Genomics Consortium we identified 16 genes that are significant from our list of differentially expressed genes. ConclusionsOur results identified biological functional genes that are differentially expressed in schizophrenia. A subset of these genes are clinically proven drug targets. We also found a strong pattern of differentially expressed immune response genes that may reflect an underlying defect in schizophrenia.

Silencing c-Myc Translation As a Therapeutic Strategy through Targeting PI3K Delta and CK1 Epsilon in Hematological Malignancies

Introduction: c-Myc is a master transcription factor and one of the most frequently altered genes across a vast array of human cancers including diffuse large B-cell lymphoma (DLBCL), and is thus an attractive therapeutic target . However, no direct inhibitor of c-Myc has been successfully developed for the treatment of any cancer. The c-Myc protein has a short half-life of less than 30 minutes , and the complex secondary structures in the 5' untranslated region (UTR) of MYC mRNA make its translation highly dependent on the eukaryotic translation initiation factor 4F (eIF4F) . eIF4F exists as a complex comprised of the eIF4E, eIF4A, and eIF4G subunits. eIF4E can be sequestered by 4E-BP1, which acts as a "brake" for initiation of mRNA translation . Hyper-phosphorylation of 4E-BP1, caused by upstream signals such as mTORC1, leads to release of eIF4E from 4E-BP1, assembly of the eIF4F complex, and robust mRNA translation. Surprisingly, neither FDA approved mTORC1 inhibitors nor the investigational mTORC1/mTORC2 inhibitor MLN0128 has demonstrated adequate activity in aggressive lymphoma. The therapeutic effects of mTOR inhibition in c-Myc driven aggressive lymphoma remain poorly understood.Recognizing phosphoinositide 3-kinase (PI3K) and the proteasome pathway are both involved in activating mTOR, we hypothesized that co-targeting the PI3K and proteasome pathways might synergistically inhibit translation of c-Myc. Since both PI3K and proteasome are proven drug targets in blood cancer, such co-targeting strategy may be expeditiously studied in clinical trials for c-Myc driven aggressive lymphoma.Methods: Cytotoxicity was studied in lymphoma cell lines and primary lymphoma cells using Cell TiterGlo (Promega®). The Bliss additivism model was used to determine the expected inhibition of cell growth and the excess over Bliss (EOB) values. EOB values above 0 indicate synergy, with higher values indicating higher levels of synergy. Expression of c-Myc was investigated at the translation and transcription levels, using a combination of Western blot, qPCR, and a bi-cistronic luciferase reporter we developed to study cap dependent translation. Gene expression profiling (GEP) studies were conducted using RNAseq, and analyzed by the Fisher t-test and running enrichment score (RES) between different treatment groups. Mechanisms of synergy were determined through interrogating the effects of small molecule inhibitors and shRNA targeting regulators of various regulators of 4E-BP1. Structural studies of TGR-1202 were performed by in silico docking, and validated by synthesis of novel analogs of TGR-1202. Activity of TGR-1202 on CK1 epsilon was studied by kinome profiling (Reaction Biology®), cell free kinase assay of CK1e (Promega®), and cell based assay of CK1e autophosphorylation.Results: We found that a novel PI3K delta isoform inhibitor TGR-1202, but not the approved PI3Kd inhibitor idelalisib, was highly synergistic with the proteasome inhibitor carfilzomib in lymphoma, leukemia, and myeloma cell lines and primary lymphoma and leukemia cells (Figure 1). TGR-1202 and carfilzomib (TC) synergistically inhibited phosphorylation of eIF4E-binding protein 1 (4E-BP1), leading to suppression of c-Myc translation and silencing of c-Myc dependent transcription (Figure 2). Furthermore, the synergistic cytotoxicity of TC was rescued by overexpression of eIF4E or c-Myc. TGR-1202, but not other PI3Kd inhibitors, was active against casein kinase-1 (CK1) epsilon (Figure 3). Targeting CK1e using a selective chemical inhibitor or shRNA complements the effects of idelalisib, as a single agent or in combination with carfilzomib, in repressing phosphorylation of 4E-BP1 and the protein level of c-Myc.Conclusion: These results suggest that TGR-1202 is a first-in-class dual PI3Kd/CK1e inhibitor, which may in part explain the preliminary clinical activity of TGR-1202 in aggressive lymphoma not found with idelalisib. Targeting CK1e should become an integral part of therapeutic strategies targeting translation of oncogenes such as c-Myc. [Display omitted] [Display omitted] [Display omitted] DisclosuresLentzsch:BMS: Consultancy; Foundation One: Consultancy; Celgene: Consultancy, Honoraria. O'Connor:Seattle Genetics: Research Funding; Mundipharma: Membership on an entity's Board of Directors or advisory committees; Seattle Genetics: Research Funding; Spectrum: Research Funding; Spectrum: Research Funding; Mundipharma: Membership on an entity's Board of Directors or advisory committees; TG Therapeutics: Research Funding; TG Therapeutics: Research Funding; Bristol Myers Squibb: Research Funding; Bristol Myers Squibb: Research Funding; Celgene: Research Funding; Celgene: Research Funding.