Identification of selective hepatitis delta virus ribozyme inhibitors by high-throughput screening of small molecule libraries.

Background & Aims: Chronic hepatitis delta is the most severe form of chronic viral hepatitis and is associated with faster progression towards cirrhosis, liver decompensation, and hepatocellular carcinoma. Hepatitis delta virus (HDV)'s tight dependency on hepatitis B virus and the host cell machinery for its life cycle limits the development of direct-acting antivirals. Thus, we aimed to identify compounds that could block HDV replication by targeting its antigenomic ribozyme. Methods: We generated stable Huh7 human hepatoma cells expressing a reporter gene (Gaussia luciferase) either downstream (Gluc-2xRz) or upstream (2xRz-Gluc) of two HDV antigenomic ribozyme sequences. We performed high-throughput screening of three small molecule libraries. The secreted luciferase was measured as a readout of ribozyme inhibition upon addition of the molecules. Each plate was considered valid when the Z factor was >0.4. Specificity and toxicity evaluations were performed for the hits with a Z-score >5 and half-maximal inhibitory concentration was calculated by performing a dose-response experiment. Results: A dose-dependent induction of luciferase expression was detected in Gluc-2xRz-transfected cells incubated with the antisense morpholino, suggesting that the catalytic activity of the ribozyme cloned downstream of the reporter gene was efficiently inhibited. Among the 6,644 compounds screened, we identified four compounds that showed a specific inhibitory effect on the HDV antigenomic ribozyme in Gluc-2xRz cells, i.e. three histone deacetylase inhibitors and the purine analogue 8-azaguanine. The latter also significantly decreased HDV replication (by 40%) in differentiated HepaRG cells six days post infection. Conclusion: Using a novel cell culture model, we identified four small molecules active against the antigenomic HDV ribozyme. These results may provide insights into the structural requirements of molecules designed for the potent and specific inhibition of HDV replication. Impact and implications: Chronic hepatitis delta is the most severe form of chronic viral hepatitis and is associated with faster progression towards cirrhosis, liver decompensation, and the development of hepatocellular carcinoma. Despite the current development of several new compounds, there is still a need for efficient antiviral treatments specifically targeting hepatitis delta virus (HDV). This work describes a novel cell culture model that allows for the high-throughput screening of compounds able to inhibit HDV ribozymes. We identified four small molecules active against the antigenomic HDV ribozyme (the ribozyme involved in the early step of HDV replication), with the strongest activity shown by 8-azaguanine, a purine analogue. Our data may provide insights into the structural requirements of molecules designed to inhibit HDV.

DenovoProfiling: A webserver for de novo generated molecule library profiling.

Various deep learning-based architectures for molecular generation have been proposed for de novo drug design. The flourish of the de novo molecular generation methods and applications has created a great demand for the visualization and functional profiling for the de novo generated molecules. An increasing number of publicly available chemogenomic databases sets good foundations and creates good opportunities for comprehensive profiling of the de novo library. In this paper, we present DenovoProfiling, a webserver dedicated to de novo library visualization and functional profiling. Currently, DenovoProfiling contains six modules: (1) identification & visualization module for chemical structure visualization and identify the reported structures, (2) chemical space module for chemical space exploration using similarity maps, principal components analysis (PCA), drug-like properties distribution, and scaffold-based clustering, (3) ADMET prediction module for predicting the ADMET properties of the de novo molecules, (4) molecular alignment module for three dimensional molecular shape analysis, (5) drugs mapping module for identifying structural similar drugs, and (6) target & pathway module for identifying the reported targets and corresponding functional pathways. DenovoProfiling could provide structural identification, chemical space exploration, drug mapping, and target & pathway information. The comprehensive annotated information could give users a clear picture of their de novo library and could guide the further selection of candidates for chemical synthesis and biological confirmation. DenovoProfiling is freely available at http://denovoprofiling.xielab.net.

Recent developments on UDP-N-acetylmuramoyl-L-alanine-D-gutamate ligase (Mur D) enzyme for antimicrobial drug development: An emphasis on in-silico approaches.

Introduction: The rapid emergence of antibiotic resistance among various bacterial pathogens has been one of the major concerns of health organizations across the world. In this context, for the development of novel inhibitors against antibiotic-resistant bacterial pathogens, UDP-N-Acetylmuramoyl-L-Alanine-D-Glutamate Ligase (MurD) enzyme represents one of the most apposite targets. Body: The present review focuses on updated advancements on MurD-targeted inhibitors in recent years along with genetic regulation, structural and functional characteristics of the MurD enzyme from various bacterial pathogens. A concise account of various crystal structures of MurD enzyme, submitted into Protein Data Bank is also discussed. Discussion: MurD, an ATP dependent cytoplasmic enzyme is an important target for drug discovery. The genetic organization of MurD enzyme is well elucidated and many crystal structures of MurD enzyme are submitted into Protein Data bank. Various inhibitors against MurD enzyme have been developed so far with an increase in the use of in-silico methods in the recent past. But cell permeability barriers and conformational changes of MurD enzyme during catalytic reaction need to be addressed for effective drug development. So, a combination of in-silico methods along with experimental work is proposed to counter the catalytic machinery of MurD enzyme.

Generation of an in vitro model for peripheral neuropathy in Fabry disease using CRISPR-Cas9 in the nociceptive dorsal root ganglion cell line 50B11.

Fabry disease is a glycosphingolipid storage disorder that is caused by a genetic deficiency of the lysosomal enzyme alpha-galactosidase A (AGA, EC 3.2.1.22). As a result, the glycolipid substrate, globotriaosylceramide (Gb3) accumulates in various cell types throughout the body producing a multisystem disease that affects the vascular, cardiac, renal, and nervous systems. A hallmark of this disorder is neuropathic pain that occurs in up to 80% of Fabry patients and has been characterized as a small fiber neuropathy. The molecular mechanism by which changes in AGA activity produce neuropathic pain is not clear, in part due to a lack of relevant model systems. Using 50B11 cells, an immortalized dorsal root ganglion neuron with nociceptive characteristics derived from rat, we used CRISPR-Cas9 gene editing of the galactosidase alpha (GLA) gene for AGA to create two stable knock-out clones that have the phenotypic characteristics of Fabry cells. The cell lines show severely reduced lysosomal AGA activity in homogenates as well as impaired degradation of Gb3 in cultured cells. This phenotype is stable over long-term culture. Similar to the unedited 50B11 cell line, the clones differentiate in response to forskolin and extend neurites. Flow cytometry experiments demonstrate that the gene-edited cells express TRPV1 pain receptor at increased levels compared to control, suggesting a possible mechanism for increased pain sensitization in Fabry patients. Our 50B11 cell lines show phenotypic characteristics of Fabry disease and grow well under standard cell culture conditions. These cell lines can provide a convenient model system to help elucidate the molecular mechanism of pain in Fabry patients.

Literature-based translation from synthetic lethality screening into therapeutics targets: CD82 is a novel target for KRAS mutation in colon cancer.

Synthetic lethality (SL) is an emerging therapeutic paradigm in cancer. We introduced a different approach to prioritize SL gene pairs through literature mining and RAS-mutant high-throughput screening (HTS) data. We matched essential genes from text-mining and mutant genes from the COSMIC and CCLE HTS datasets to build a prediction model of SL gene pairs. CCLE gene expression data were used to enrich the essential-mutant SL gene pairs using Spearman's correlation coefficient and literature mining. In total, 223 essential trigger terms were extracted and ranked. The threshold of the essential gene score ( S g ) was set to 10. We identified 586 genes essential for the SL prediction model of colon cancer. Seven essential RAS-mutant SL gene pairs were identified in our model, including CD82-KRAS/NRAS, PEBP1-NRAS, MT-CO2-HRAS, IFI27-NRAS/KRAS, and SUMO1-HRAS gene pairs. Using RAS-mutant HTS data validation, we identified two potential SL gene pairs, including the CD82 (essential gene)-KRAS (mutant gene) pair and CD82-NRAS pair in the DLD-1 colon cancer cell line (Spearman's correlation p-values = 0.004786 and 0.00249, respectively). Based on further annotations by PubChem, we observed that digitonin targeted the complex comprising CD82, especially in KRAS-mutated HCT116 cancer cells. Moreover, we experimentally demonstrated that CD82 exhibited selective vulnerability in KRAS-mutant colorectal cancer. We used literature mining and HTS data to identify candidates for SL targets for RAS-mutant colon cancer.

A DNA-based non-infectious replicon system to study SARS-CoV-2 RNA synthesis.

The coronavirus disease-2019 (COVID-19) pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has seriously affected public health around the world. In-depth studies on the pathogenic mechanisms of SARS-CoV-2 is urgently necessary for pandemic prevention. However, most laboratory studies on SARS-CoV-2 have to be carried out in bio-safety level 3 (BSL-3) laboratories, greatly restricting the progress of relevant experiments. In this study, we used a bacterial artificial chromosome (BAC) method to assemble a SARS-CoV-2 replication and transcription system in Vero E6 cells without virion envelope formation, thus avoiding the risk of coronavirus exposure. Furthermore, an improved real-time quantitative reverse transcription PCR (RT-qPCR) approach was used to distinguish the replication of full-length replicon RNAs and transcription of subgenomic RNAs (sgRNAs). Using the SARS-CoV-2 replicon, we demonstrated that the nucleocapsid (N) protein of SARS-CoV-2 facilitates the transcription of sgRNAs in the discontinuous synthesis process. Moreover, two high-frequency mutants of N protein, R203K and S194L, can obviously enhance the transcription level of the replicon, hinting that these mutations likely allow SARS-CoV-2 to spread and reproduce more quickly. In addition, remdesivir and chloroquine, two well-known drugs demonstrated to be effective against coronavirus in previous studies, also inhibited the transcription of our replicon, indicating the potential applications of this system in antiviral drug discovery. Overall, we developed a bio-safe and valuable replicon system of SARS-CoV-2 that is useful to study the mechanisms of viral RNA synthesis and has potential in novel antiviral drug screening.

Unraveling the mystery of efficacy in Chinese medicine formula: New approaches and technologies for research on pharmacodynamic substances.

Traditional Chinese medicine (TCM) is the key to unlock treasures of Chinese civilization. TCM and its compound play a beneficial role in medical activities to cure diseases, especially in major public health events such as novel coronavirus epidemics across the globe. The chemical composition in Chinese medicine formula is complex and diverse, but their effective substances resemble "mystery boxes". Revealing their active ingredients and their mechanisms of action has become focal point and difficulty of research for herbalists. Although the existing research methods are numerous and constantly updated iteratively, there is remain a lack of prospective reviews. Hence, this paper provides a comprehensive account of existing new approaches and technologies based on previous studies with an in vitro to in vivo perspective. In addition, the bottlenecks of studies on Chinese medicine formula effective substances are also revealed. Especially, we look ahead to new perspectives, technologies and applications for its future development. This work reviews based on new perspectives to open horizons for the future research. Consequently, herbal compounding pharmaceutical substances study should carry on the essence of TCM while pursuing innovations in the field.

Can constraint network analysis guide the identification phase of KnowVolution? A case study on improved thermostability of an endo-ß-glucanase.

Cellulases are industrially important enzymes, e.g., in the production of bioethanol, in pulp and paper industry, feedstock, and textile. Thermostability is often a prerequisite for high process stability and improving thermostability without affecting specific activities at lower temperatures is challenging and often time-consuming. Protein engineering strategies that combine experimental and computational are emerging in order to reduce experimental screening efforts and speed up enzyme engineering campaigns. Constraint Network Analysis (CNA) is a promising computational method that identifies beneficial positions in enzymes to improve thermostability. In this study, we compare CNA and directed evolution in the identification of beneficial positions in order to evaluate the potential of CNA in protein engineering campaigns (e.g., in the identification phase of KnowVolution). We engineered the industrially relevant endoglucanase EGLII from Penicillium verruculosum towards increased thermostability. From the CNA approach, six variants were obtained with an up to 2-fold improvement in thermostability. The overall experimental burden was reduced to 40% utilizing the CNA method in comparison to directed evolution. On a variant level, the success rate was similar for both strategies, with 0.27% and 0.18% improved variants in the epPCR and CNA-guided library, respectively. In essence, CNA is an effective method for identification of positions that improve thermostability.

Gains from no real PAINS: Where 'Fair Trial Strategy' stands in the development of multi-target ligands.

Compounds that selectively modulate multiple targets can provide clinical benefits and are an alternative to traditional highly selective agents for unique targets. High-throughput screening (HTS) for multitarget-directed ligands (MTDLs) using approved drugs, and fragment-based drug design has become a regular strategy to achieve an ideal multitarget combination. However, the unexpected presence of pan-assay interference compounds (PAINS) suspects in the development of MTDLs frequently results in nonspecific interactions or other undesirable effects leading to artefacts or false-positive data of biological assays. Publicly available filters can help to identify PAINS suspects; however, these filters cannot comprehensively conclude whether these suspects are "bad" or innocent. Additionally, these in silico approaches may inappropriately label a ligand as PAINS. More than 80% of the initial hits can be identified as PAINS by the filters if appropriate biochemical tests are not used resulting in false positive data that are unacceptable for medicinal chemists in manuscript peer review and future studies. Therefore, extensive offline experiments should be used after online filtering to discriminate "bad" PAINS and avoid incorrect evaluation of good scaffolds. We suggest that the use of "Fair Trial Strategy" to identify interesting molecules in PAINS suspects to provide certain structure‒function insight in MTDL development.

Binding mode analysis of ABCA7 for the prediction of novel Alzheimer's disease therapeutics.

The adenosine-triphosphate-(ATP)-binding cassette (ABC) transporter ABCA7 is a genetic risk factor for Alzheimer's disease (AD). Defective ABCA7 promotes AD development and/or progression. Unfortunately, ABCA7 belongs to the group of 'under-studied' ABC transporters that cannot be addressed by small-molecules. However, such small-molecules would allow for the exploration of ABCA7 as pharmacological target for the development of new AD diagnostics and therapeutics. Pan-ABC transporter modulators inherit the potential to explore under-studied ABC transporters as novel pharmacological targets by potentially binding to the proposed 'multitarget binding site'. Using the recently reported cryogenic-electron microscopy (cryo-EM) structures of ABCA1 and ABCA4, a homology model of ABCA7 has been generated. A set of novel, diverse, and potent pan-ABC transporter inhibitors has been docked to this ABCA7 homology model for the discovery of the multitarget binding site. Subsequently, application of pharmacophore modelling identified the essential pharmacophore features of these compounds that may support the rational drug design of innovative diagnostics and therapeutics against AD.

A new high-content screening assay of the entire hepatitis B virus life cycle identifies novel antivirals.

BACKGROUND & AIMS: Chronic hepatitis B is an incurable disease. Addressing the unmet medical need for therapies has been hampered by a lack of suitable cell culture models to investigate the HBV life cycle in a single experimental setup. We sought to develop a platform suitable to investigate all aspects of the entire HBV life cycle. METHODS: HepG2-NTCPsec+ cells were inoculated with HBV. Supernatants of infected cells were transferred to naïve cells. Inhibition of infection was determined in primary and secondary infected cells by high-content imaging of viral and cellular factors. Novel antivirals were triaged in cells infected with cell culture- or patient-derived HBV and in stably virus replicating cells. HBV internalisation and target-based receptor binding assays were conducted. RESULTS: We developed an HBV platform, screened 2,102 drugs and bioactives, and identified 3 early and 38 late novel HBV life cycle inhibitors using infectious HBV genotype D. Two early inhibitors, pranlukast (EC50 4.3 µM; 50% cytotoxic concentration [CC50] >50 µM) and cytochalasin D (EC50 0.07 µM; CC50 >50 µM), and 2 late inhibitors, fludarabine (EC50 0.1 µM; CC50 13.4 µM) and dexmedetomidine (EC50 6.2 µM; CC50 >50 µM), were further investigated. Pranlukast inhibited HBV preS1 binding, whereas cytochalasin D prevented the internalisation of HBV. Fludarabine inhibited the secretion of HBV progeny DNA, whereas dexmedetomidine interfered with the infectivity of HBV progeny. Patient-derived HBV genotype C was efficiently inhibited by fludarabine (EC50 0.08 µM) and dexmedetomidine (EC50 8.7 µM). CONCLUSIONS: The newly developed high-content assay is suitable to screen large-scale drug libraries, enables monitoring of the entire HBV life cycle, and discriminates between inhibition of early and late viral life cycle events. LAY SUMMARY: HBV infection is an incurable, chronic disease with few available treatments. Addressing this unmet medical need has been hampered by a lack of suitable cell culture models to study the entire viral life cycle in a single experimental setup. We developed an image-based approach suitable to screen large numbers of drugs, using a cell line that can be infected by HBV and produces large amounts of virus particles. By transferring viral supernatants from these infected cells to uninfected target cells, we could monitor the entire viral life cycle. We used this system to screen drug libraries and identified novel anti-HBV inhibitors that potently inhibit HBV in various phases of its life cycle. This assay will be an important new tool to study the HBV life cycle and accelerate the development of novel therapeutic strategies.

The Ca2+-activated chloride channel ANO1/TMEM16A: An emerging therapeutic target for epithelium-originated diseases?

Anoctamin 1 (ANO1) or TMEM16A gene encodes a member of Ca2+ activated Cl- channels (CaCCs) that are critical for physiological functions, such as epithelial secretion, smooth muscle contraction and sensory signal transduction. The attraction and interest in ANO1/TMEM16A arise from a decade long investigations that abnormal expression or dysfunction of ANO1 is involved in many pathological phenotypes and diseases, including asthma, neuropathic pain, hypertension and cancer. However, the lack of specific modulators of ANO1 has impeded the efforts to validate ANO1 as a therapeutic target. This review focuses on the recent progress made in understanding of the pathophysiological functions of CaCC ANO1 and the current modulators used as pharmacological tools, hopefully illustrating a broad spectrum of ANO1 channelopathy and a path forward for this target validation.

A multifunctional cross-validation high-throughput screening protocol enabling the discovery of new SHP2 inhibitors.

The protein tyrosine phosphatase Src homology phosphotyrosyl phosphatase 2 (SHP2) is implicated in various cancers, and targeting SHP2 has become a promising therapeutic approach. We herein described a robust cross-validation high-throughput screening protocol that combined the fluorescence-based enzyme assay and the conformation-dependent thermal shift assay for the discovery of SHP2 inhibitors. The established method can effectively exclude the false positive SHP2 inhibitors with fluorescence interference and was also successfully employed to identify new protein tyrosine phosphatase domain of SHP2 (SHP2-PTP) and allosteric inhibitors. Of note, this protocol showed potential for identifying SHP2 inhibitors against cancer-associated SHP2 mutation SHP2-E76A. After initial screening of our in-house compound library (∼2300 compounds), we identified 4 new SHP2-PTP inhibitors (0.17% hit rate) and 28 novel allosteric SHP2 inhibitors (1.22% hit rate), of which SYK-85 and WS-635 effectively inhibited SHP2-PTP (SYK-85: IC50 = 0.32 µmol/L; WS-635: IC50 = 4.13 µmol/L) and thus represent novel scaffolds for designing new SHP2-PTP inhibitors. TK-147, an allosteric inhibitor, inhibited SHP2 potently (IC50 = 0.25 µmol/L). In structure, TK-147 could be regarded as a bioisostere of the well characterized SHP2 inhibitor SHP-099, highlighting the essential structural elements for allosteric inhibition of SHP2. The principle underlying the cross-validation protocol is potentially feasible to identify allosteric inhibitors or those inactivating mutants of other proteins.

Development of small-molecule tropomyosin receptor kinase (TRK) inhibitors for NTRK fusion cancers.

Tropomyosin receptor kinase A, B and C (TRKA, TRKB and TRKC), which are well-known members of the cell surface receptor tyrosine kinase (RTK) family, are encoded by the neurotrophic receptor tyrosine kinase 1, 2 and 3 (NTRK1, NTRK2 and NTRK3) genes, respectively. TRKs can regulate cell proliferation, differentiation and even apoptosis through the RAS/MAPKs, PI3K/AKT and PLCγ pathways. Gene fusions involving NTRK act as oncogenic drivers of a broad diversity of adult and pediatric tumors, and TRKs have become promising antitumor targets. Therefore, achieving a comprehensive understanding of TRKs and relevant TRK inhibitors should be urgently pursued for the further development of novel TRK inhibitors for potential clinical applications. This review focuses on summarizing the biological functions of TRKs and NTRK fusion proteins, the development of small-molecule TRK inhibitors with different chemotypes and their activity and selectivity, and the potential therapeutic applications of these inhibitors for future cancer drug discovery efforts.

COSMOS next generation - A public knowledge base leveraging chemical and biological data to support the regulatory assessment of chemicals.

The COSMOS Database (DB) was originally established to provide reliable data for cosmetics-related chemicals within the COSMOS Project funded as part of the SEURAT-1 Research Initiative. The database has subsequently been maintained and developed further into COSMOS Next Generation (NG), a combination of database and in silico tools, essential components of a knowledge base. COSMOS DB provided a cosmetics inventory as well as other regulatory inventories, accompanied by assessment results and in vitro and in vivo toxicity data. In addition to data content curation, much effort was dedicated to data governance - data authorisation, characterisation of quality, documentation of meta information, and control of data use. Through this effort, COSMOS DB was able to merge and fuse data of various types from different sources. Building on the previous effort, the COSMOS Minimum Inclusion (MINIS) criteria for a toxicity database were further expanded to quantify the reliability of studies. COSMOS NG features multiple fingerprints for analysing structure similarity, and new tools to calculate molecular properties and screen chemicals with endpoint-related public profilers, such as DNA and protein binders, liver alerts and genotoxic alerts. The publicly available COSMOS NG enables users to compile information and execute analyses such as category formation and read-across. This paper provides a step-by-step guided workflow for a simple read-across case, starting from a target structure and culminating in an estimation of a NOAEL confidence interval. Given its strong technical foundation, inclusion of quality-reviewed data, and provision of tools designed to facilitate communication between users, COSMOS NG is a first step towards building a toxicological knowledge hub leveraging many public data systems for chemical safety evaluation. We continue to monitor the feedback from the user community at support@mn-am.com.

Discovery of the anti-angiogenesis effect of eltrombopag in breast cancer through targeting of HuR protein.

HuR (human antigen R), an mRNA-binding protein responsible for poor prognosis in nearly all kinds of malignancies, is a potential anti-tumor target for drug development. While screening HuR inhibitors with a fluorescence polarization (FP) based high-throughput screening (HTS) system, the clinically used drug eltrombopag was identified. Activity of eltrombopag on molecular level was verified with FP, electrophoretic mobility shift assay (EMSA), simulation docking and surface plasmon resonance (SPR). Further, we showed that eltrombopag inhibited in vitro cell proliferation of multiple cancer cell lines and macrophages, and the in vivo anti-tumor activity was also demonstrated in a 4T1 tumor-bearing mouse model. The in vivo data showed that eltrombopag was efficient in reducing microvessels in tumor tissues. We then confirmed the HuR-dependent anti-angiogenesis effect of eltrombopag in 4T1 cells and RAW264.7 macrophages with qRT-PCR, HuR-overexpression and HuR-silencing assays, RNA stability assays, RNA immunoprecipitation and luciferase assays. Finally, we analyzed the in vitro anti-angiogenesis effect of eltrombopag on human umbilical vein endothelial cells (HUVECs) mediated by macrophages with cell scratch assay and in vitro Matrigel angiogenesis assay. With these data, we revealed the HuR-dependent anti-angiogenesis effect of eltrombopag in breast tumor, suggesting that the existing drug eltrombopag may be used as an anti-cancer drug.

Neutralising effects of small molecule toxin inhibitors on nanofractionated coagulopathic Crotalinae snake venoms.

Repurposing small molecule drugs and drug candidates is considered as a promising approach to revolutionise the treatment of snakebite envenoming. In this study, we investigated the inhibiting effects of the small molecules varespladib (nonspecific phospholipase A2 inhibitor), marimastat (broad spectrum matrix metalloprotease inhibitor) and dimercaprol (metal ion chelator) against coagulopathic toxins found in Crotalinae (pit vipers) snake venoms. Venoms from Bothrops asper, Bothrops jararaca, Calloselasma rhodostoma and Deinagkistrodon acutus were separated by liquid chromatography, followed by nanofractionation and mass spectrometry identification undertaken in parallel. Nanofractions of the venom toxins were then subjected to a high-throughput coagulation assay in the presence of different concentrations of the small molecules under study. Anticoagulant venom toxins were mostly identified as phospholipases A2, while procoagulant venom activities were mainly associated with snake venom metalloproteinases and snake venom serine proteases. Varespladib was found to effectively inhibit most anticoagulant venom effects, and also showed some inhibition against procoagulant toxins. Contrastingly, marimastat and dimercaprol were both effective inhibitors of procoagulant venom activities but showed little inhibitory capability against anticoagulant toxins. The information obtained from this study aids our understanding of the mechanisms of action of toxin inhibitor drug candidates, and highlights their potential as future snakebite treatments.

Deep graph embedding for prioritizing synergistic anticancer drug combinations.

Drug combinations are frequently used for the treatment of cancer patients in order to increase efficacy, decrease adverse side effects, or overcome drug resistance. Given the enormous number of drug combinations, it is cost- and time-consuming to screen all possible drug pairs experimentally. Currently, it has not been fully explored to integrate multiple networks to predict synergistic drug combinations using recently developed deep learning technologies. In this study, we proposed a Graph Convolutional Network (GCN) model to predict synergistic drug combinations in particular cancer cell lines. Specifically, the GCN method used a convolutional neural network model to do heterogeneous graph embedding, and thus solved a link prediction task. The graph in this study was a multimodal graph, which was constructed by integrating the drug-drug combination, drug-protein interaction, and protein-protein interaction networks. We found that the GCN model was able to correctly predict cell line-specific synergistic drug combinations from a large heterogonous network. The majority (30) of the 39 cell line-specific models show an area under the receiver operational characteristic curve (AUC) larger than 0.80, resulting in a mean AUC of 0.84. Moreover, we conducted an in-depth literature survey to investigate the top predicted drug combinations in specific cancer cell lines and found that many of them have been found to show synergistic antitumor activity against the same or other cancers in vitro or in vivo. Taken together, the results indicate that our study provides a promising way to better predict and optimize synergistic drug pairs in silico.

Small molecules targeting the innate immune cGAS‒STING‒TBK1 signaling pathway.

Multiple cancer immunotherapies including chimeric antigen receptor T cell and immune checkpoint inhibitors (ICIs) have been successfully developed to treat various cancers by motivating the adaptive anti-tumor immunity. Particularly, the checkpoint blockade approach has achieved great clinic success as evidenced by several U.S. Food and Drug Administration (FDA)-approved anti-programmed death receptor 1/ligand 1 or anti-cytotoxic T lymphocyte associated protein 4 antibodies. However, the majority of cancers have low clinical response rates to these ICIs due to poor tumor immunogenicity. Indeed, the cyclic guanosine monophosphate-adenosine monophosphate synthase‒stimulator of interferon genes‒TANK-binding kinase 1 (cGAS‒STING‒TBK1) axis is now appreciated as the major signaling pathway in innate immune response across different species. Aberrant signaling of this pathway has been closely linked to multiple diseases, including auto-inflammation, virus infection and cancers. In this perspective, we provide an updated review on the latest progress on the development of small molecule modulators targeting the cGAS‒STING‒TBK1 signaling pathway and their preclinical and clinical use as a new immune stimulatory therapy. Meanwhile, highlights on the clinical candidates, limitations and challenges, as well as future directions in this field are also discussed. Further, small molecule inhibitors targeting this signaling axis and their potential therapeutic use for various indications are discussed as well.

Orthogonal assays for the identification of inhibitors of the single-stranded nucleic acid binding protein YB-1.

We have previously shown that high expression of the nucleic acid binding factor YB-1 is strongly associated with poor prognosis in a variety of cancer types. The 3-dimensional protein structure of YB-1 has yet to be determined and its role in transcriptional regulation remains elusive. Drug targeting of transcription factors is often thought to be difficult and there are very few published high-throughput screening approaches. YB-1 predominantly binds to single-stranded nucleic acids, adding further difficulty to drug discovery. Therefore, we have developed two novel screening assays to detect compounds that interfere with the transcriptional activation properties of YB-1, both of which may be generalizable to screen for inhibitors of other nucleic acid binding molecules. The first approach is a cell-based luciferase reporter gene assay that measures the level of activation of a fragment of the E2F1 promoter by YB-1. The second approach is a novel application of the AlphaScreen system, to detect interference of YB-1 interaction with a single-stranded DNA binding site. These complementary assays examine YB-1 binding to two discrete nucleic acid sequences using two different luminescent signal outputs and were employed sequentially to screen 7360 small molecule compounds leading to the identification of three putative YB-1 inhibitors.