ResearchPad - drug-discovery https://www.researchpad.co Default RSS Feed en-us © 2020 Newgen KnowledgeWorks <![CDATA[Targeting the Small GTPase Superfamily through Their Regulatory Proteins]]> https://www.researchpad.co/article/elastic_article_10768 What a PAIN: Small GTPases have been notoriously difficult targets for small molecule and biologic therapeutics. This review explores the molecules targeting the GEF, GAP, and GDI GTPase regulatory proteins. It identifies issues in the chemical strategies, including PAINs motifs, insufficient potency, and lack of selectivity, whilst also providing thoughts on how this field will develop in the future.

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<![CDATA[Development of Glucose Transporter (GLUT) Inhibitors]]> https://www.researchpad.co/article/elastic_article_8235 Potent glucose transporter (GLUT) inhibitors have been developed over the last years. This Minireview serves as an overview of the origin (natural products, natural product‐inspired, non‐natural compounds, and virtual screening) of these molecules.John Wiley & Sons, Ltd.

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<![CDATA[From worms to fish to mice]]> https://www.researchpad.co/article/N38577ced-03dc-45b1-8b00-37d57a5512fc An multi-species approach can be used to identify small molecules with properties that might prove useful for the treatment of some neuromuscular diseases.

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<![CDATA[Lupus patient decisions about clinical trial participation: a qualitative evaluation of perceptions, facilitators and barriers]]> https://www.researchpad.co/article/N5ec0b436-29ab-43a0-986b-73cc3a2f1ef4

Objective

Although SLE disproportionately affects minority racial groups, they are significantly under-represented in clinical trials in the USA. This may lead to misleading conclusions in race-based subgroup analyses. We conducted focus groups to evaluate the perceptions of diverse patients with lupus about clinical trial participation.

Methods

A qualitative research design employed three 90 min focus groups led by a trained moderator and guided by the Theory of Planned Behaviour. Open-ended questions about trial participation included advantages and disadvantages (behavioural beliefs), approving and disapproving significant others (normative beliefs), and participation enhancers and barriers (control beliefs). Discussions were recorded, transcribed and analysed to identify emerging themes.

Results

Patients with SLE (n=23) aged 21–72, with increased proportion of minority groups (65%), participated. Reported advantages of trial participation included altruism and personal benefit. Disadvantages included uncertainties, disappointment, information burden, and life–health balance. Although some patients had discussed research participation with approving or disapproving family or friends, self-approval superseded external approval. Barriers included logistics and time, and facilitators included flexibility in scheduling, advance notice of studies, streamlined forms, and hope for SLE improvement.

Conclusions

Knowledge about potential benefits of clinical trial participation was high. Minority patients demonstrated confidence in making their own informed decisions, but major barriers for all participants included burdensome forms, travel, childcare, and work. These suggest a major impact on minority and all recruitment from behavioural and control aspects, which should be considered in the logistics of trial design. This does not minimise the potential importance of improved access and education about clinical research.

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<![CDATA[Dual antivascular function of human fibulin‐3 variant, a potential new drug discovery strategy for glioblastoma]]> https://www.researchpad.co/article/N9228408d-e536-4593-a591-092b519321cd

Abstract

The ECM protein EFEMP1 (fibulin‐3) is associated with all types of solid tumor through its cell context‐dependent dual function. A variant of fibulin‐3 was engineered by truncation and mutation to alleviate its oncogenic function, specifically the proinvasive role in glioblastoma multiforme (GBM) cells at stem‐like state. ZR30 is an in vitro synthesized 39‐kDa protein of human fibulin‐3 variant. It has a therapeutic effect in intracranial xenograft models of human GBM, through suppression of epidermal growth factor receptor/AKT and NOTCH1/AKT signaling in GBM cells and extracellular MMP2 activation. Glioblastoma multiforme is highly vascular, with leaky blood vessels formed by tumor cells expressing endothelial cell markers, including CD31. Here we studied GBM intracranial xenografts, 2 weeks after intratumoral injection of ZR30 or PBS, by CD31 immunohistochemistry. We found a 70% reduction of blood vessel density in ZR30‐treated xenografts compared with that of PBS‐treated ones. Matrigel plug assays showed the effect of ZR30 on suppressing angiogenesis. We further studied the effect of ZR30 on genes involved in endothelial transdifferentiation (ETD), in 7 primary cultures derived from 3 GBMs under different culture conditions. Two GBM cultures formed mesh structures with upregulation of ETD genes shortly after culture in Matrigel Matrix, and ZR30 suppressed both. ZR30 also downregulated ETD genes in two GBM cultures with high expression of these genes. In conclusion, multifaceted tumor suppression effects of human fibulin‐3 variant include both suppression of angiogenesis and vasculogenic mimicry in GBM.

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<![CDATA[A Novel G Protein–Biased Agonist at the δ Opioid Receptor with Analgesic Efficacy in Models of Chronic Pain]]> https://www.researchpad.co/article/Ndbf44d9a-3acc-48a2-b199-860a528a7685

Agonists at the δ opioid receptor are known to be potent antihyperalgesics in chronic pain models and effective in models of anxiety and depression. However, some δ opioid agonists have proconvulsant properties while tolerance to the therapeutic effects can develop. Previous evidence indicates that different agonists acting at the δ opioid receptor differentially engage signaling and regulatory pathways with significant effects on behavioral outcomes. As such, interest is now growing in the development of biased agonists as a potential means to target specific signaling pathways and potentially improve the therapeutic profile of δ opioid agonists. Here, we report on PN6047 (3-[[4-(dimethylcarbamoyl)phenyl]-[1-(thiazol-5-ylmethyl)-4-piperidylidene]methyl]benzamide), a novel G protein–biased and selective δ opioid agonist. In cell-based assays, PN6047 fully engages G protein signaling but is a partial agonist in both the arrestin recruitment and internalization assays. PN6047 is effective in rodent models of chronic pain but shows no detectable analgesic tolerance following prolonged treatment. In addition, PN6047 exhibited antidepressant-like activity in the forced swim test, and importantly, the drug had no effect on chemically induced seizures. PN6047 did not exhibit reward-like properties in the conditioned place preference test or induce respiratory depression. Thus, δ opioid ligands with limited arrestin signaling such as PN6047 may be therapeutically beneficial in the treatment of chronic pain states.

SIGNIFICANCE STATEMENT

PN6047 (3-[[4-(dimethylcarbamoyl)phenyl]-[1-(thiazol-5-ylmethyl)-4-piperidylidene]methyl]benzamide) is a selective, G protein–biased δ opioid agonist with efficacy in preclinical models of chronic pain. No analgesic tolerance was observed after prolonged treatment, and PN6047 does not display proconvulsant activity or other opioid-mediated adverse effects. Our data suggest that δ opioid ligands with limited arrestin signaling will be beneficial in the treatment of chronic pain.

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<![CDATA[Biophysical screening methods for extracellular domain peptide receptors, application to natriuretic peptide receptor C ligands]]> https://www.researchpad.co/article/N29391856-ac33-4cdf-8e4d-a17e84e8ba00

Abstract

Endothelium‐derived C‐type natriuretic peptide possesses cytoprotective and anti‐atherogenic functions that regulate vascular homeostasis. The vasoprotective effects of C‐type natriuretic peptide are somewhat mediated by the natriuretic peptide receptor C, suggesting that this receptor represents a novel therapeutic target for the treatment of cardiovascular diseases. In order to facilitate our drug discovery efforts, we have optimized an array of biophysical methods including surface plasmon resonance, fluorescence polarization and thermal shift assays to aid in the design, assessment and characterization of small molecule agonist interactions with natriuretic peptide receptors. Assay conditions are investigated to explore the feasibility and dynamic range of each method, and peptide‐based agonists and antagonists are used as controls to validate these conditions. Once established, each technique was compared and contrasted with respect to their drug discovery utility. We foresee that such techniques will facilitate the discovery and development of potential therapeutic agents for NPR‐C and other large extracellular domain membrane receptors.

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<![CDATA[Potassium response and homeostasis in Mycobacterium tuberculosis modulates environmental adaptation and is important for host colonization]]> https://www.researchpad.co/article/5c61e93cd5eed0c48496fa58

Successful host colonization by bacteria requires sensing and response to the local ionic milieu, and coordination of responses with the maintenance of ionic homeostasis in the face of changing conditions. We previously discovered that Mycobacterium tuberculosis (Mtb) responds synergistically to chloride (Cl-) and pH, as cues to the immune status of its host. This raised the intriguing concept of abundant ions as important environmental signals, and we have now uncovered potassium (K+) as an ion that can significantly impact colonization by Mtb. The bacterium has a unique transcriptional response to changes in environmental K+ levels, with both distinct and shared regulatory mechanisms controlling Mtb response to the ionic signals of K+, Cl-, and pH. We demonstrate that intraphagosomal K+ levels increase during macrophage phagosome maturation, and find using a novel fluorescent K+-responsive reporter Mtb strain that K+ is not limiting during macrophage infection. Disruption of Mtb K+ homeostasis by deletion of the Trk K+ uptake system results in dampening of the bacterial response to pH and Cl-, and attenuation in host colonization, both in primary murine bone marrow-derived macrophages and in vivo in a murine model of Mtb infection. Our study reveals how bacterial ionic homeostasis can impact environmental ionic responses, and highlights the important role that abundant ions can play during host colonization by Mtb.

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<![CDATA[Prediction of ultra-high-order antibiotic combinations based on pairwise interactions]]> https://www.researchpad.co/article/5c5b52b4d5eed0c4842bcea4

Drug combinations are a promising approach to achieve high efficacy at low doses and to overcome resistance. Drug combinations are especially useful when drugs cannot achieve effectiveness at tolerable doses, as occurs in cancer and tuberculosis (TB). However, discovery of effective drug combinations faces the challenge of combinatorial explosion, in which the number of possible combinations increases exponentially with the number of drugs and doses. A recent advance, called the dose model, uses a mathematical formula to overcome combinatorial explosion by reducing the problem to a feasible quadratic one: using data on drug pairs at a few doses, the dose model accurately predicts the effect of combinations of three and four drugs at all doses. The dose model has not yet been tested on higher-order combinations beyond four drugs. To address this, we measured the effect of combinations of up to ten antibiotics on E. coli growth, and of up to five tuberculosis (TB) drugs on the growth of M. tuberculosis. We find that the dose model accurately predicts the effect of these higher-order combinations, including cases of strong synergy and antagonism. This study supports the view that the interactions between drug pairs carries key information that largely determines higher-order interactions. Therefore, systematic study of pairwise drug interactions is a compelling strategy to prioritize drug regimens in high-dimensional spaces.

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<![CDATA[Open notebook science can maximize impact for rare disease projects]]> https://www.researchpad.co/article/5c58d65dd5eed0c484031ce9

Transparency lies at the heart of the open lab notebook movement. Open notebook scientists publish laboratory experiments and findings in the public domain in real time, without restrictions or omissions. Research on rare diseases is especially amenable to the open notebook model because it can both increase scientific impact and serve as a mechanism to engage patient groups in the scientific process. Here, I outline and describe my own success with my open notebook project, LabScribbles, as well as other efforts included in the openlabnotebooks.org initiative.

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<![CDATA[Screening-based approach to discover effective platinum-based chemotherapies for cancers with poor prognosis]]> https://www.researchpad.co/article/5c59ff02d5eed0c4841358d8

Drug combinations are extensively used to treat cancer and are often selected according to complementary mechanisms. Here, we describe a cell-based high-throughput screening assay for identification of synergistic combinations between broadly applied platinum-based chemotherapeutics and drugs from a library composed of 1280 chemically and pharmacologically diverse (mostly FDA approved) compounds. The assay was performed on chemoresistant cell lines derived from lung (A549) and pancreatic (PANC-1) carcinoma, where platinum-based combination regimens are currently applied though with limited success. The synergistic combinations identified during the screening were validated by synergy quantification using the combination index method and via high content fluorescent microscopy analysis. New promising synergistic combinations discovered using this approach include compounds currently not used as anticancer drugs, such as cisplatin or carboplatin with hycanthone and cisplatin with spironolactone in pancreatic carcinoma, and carboplatin and deferoxamine in non-small cell lung cancer. Strong synergy between cisplatin or carboplatin and topotecan in PANC-1 cells, compared to A549 cells, suggests that this combination, currently used in lung cancer treatment regimens, could be applied to pancreatic carcinoma as well. Several drugs used to treat diseases other than cancer, including pyrvinium pamoate, auranofin, terfenadine and haloprogin, showed strong cytotoxicity on their own and synergistic interactions with platinum drugs. This study demonstrates that non-obvious drug combinations that would not be selected based on complementary mechanisms can be identified via high-throughput screening.

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<![CDATA[Synthetic lethality guiding selection of drug combinations in ovarian cancer]]> https://www.researchpad.co/article/5c57e6d4d5eed0c484ef3f0b

Background

Synthetic lethality describes a relationship between two genes where single loss of either gene does not trigger significant impact on cell viability, but simultaneous loss of both gene functions results in lethality. Targeting synthetic lethal interactions with drug combinations promises increased efficacy in tumor therapy.

Materials and methods

We established a set of synthetic lethal interactions using publicly available data from yeast screens which were mapped to their respective human orthologs using information from orthology databases. This set of experimental synthetic lethal interactions was complemented by a set of predicted synthetic lethal interactions based on a set of protein meta-data like e.g. molecular pathway assignment. Based on the combined set, we evaluated drug combinations used in late stage clinical development (clinical phase III and IV trials) or already in clinical use for ovarian cancer with respect to their effect on synthetic lethal interactions. We furthermore identified a set of drug combinations currently not being tested in late stage ovarian cancer clinical trials that however have impact on synthetic lethal interactions thus being worth of further investigations regarding their therapeutic potential in ovarian cancer.

Results

Twelve of the tested drug combinations addressed a synthetic lethal interaction with the anti-VEGF inhibitor bevacizumab in combination with paclitaxel being the most studied drug combination addressing the synthetic lethal pair between VEGFA and BCL2. The set of 84 predicted drug combinations for example holds the combination of the PARP inhibitor olaparib and paclitaxel, which showed efficacy in phase II clinical studies.

Conclusion

A set of drug combinations currently not tested in late stage ovarian cancer clinical trials was identified having impact on synthetic lethal interactions thus being worth of further investigations regarding their therapeutic potential in ovarian cancer.

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<![CDATA[Polypharmacy in outpatients with relapsing-remitting multiple sclerosis: A single-center study]]> https://www.researchpad.co/article/5c53699fd5eed0c484a4620b

Background

Multiple sclerosis (MS) is an immune-mediated disease of the central nervous system. Given the chronic and heterogenous nature of the disease, treatment with various therapies is a frequent scenario in clinical practice. In persons with chronic morbidity such as MS patients, polypharmacy can give rise to considerable health problems.

Objectives

The aim of the present study was to examine the frequency of polypharmacy among relapsing-remitting (RR) MS patients as well as to analyse sociodemographic and clinical factors, which might be associated with polypharmacy (use of five or more medications). Differences in medication between MS patients with and without secondary illnesses (PwSI and Pw/oSI), between men and women and between patients with and without polypharmacy (PwP and Pw/oP) were examined.

Methods

For 145 RRMS outpatients, we prospectively collected data by means of anamnesis, patient records, clinical examination and a structured patient interview. This was followed by comparative analyses of various patient subgroups (PwP vs. Pw/oP, PwSI vs. Pw/oSI, men vs. women).

Results

The proportion of included MS patients with polypharmacy (use of ≥5 medications) was 30.3%. PwP were significantly older than Pw/oP (45.9 vs. 41.7 years), had a lower level of education and showed a significantly higher median EDSS score (3.0 vs. 2.0). Comorbidities (p<0.001; odds ratio [OR] = 6.293) and higher EDSS scores (p = 0.029; OR = 1.440) were associated with a higher risk of polypharmacy. The proportion of polypharmacy among PwSI was approximately four times higher than among Pw/oSI (46.8% vs. 11.8%). Particularly in the use of antihypertensives, gastrointestinal drugs and dietary supplements, there were differences between Pw/oP and PwP.

Conclusion

We found a high burden of polypharmacy in patients with RRMS. This particularly applies to more severely disabled MS patients who suffer from comorbidities.

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<![CDATA[Using the drug-protein interactome to identify anti-ageing compounds for humans]]> https://www.researchpad.co/article/5c3fa5f7d5eed0c484caa9c2

Advancing age is the dominant risk factor for most of the major killer diseases in developed countries. Hence, ameliorating the effects of ageing may prevent multiple diseases simultaneously. Drugs licensed for human use against specific diseases have proved to be effective in extending lifespan and healthspan in animal models, suggesting that there is scope for drug repurposing in humans. New bioinformatic methods to identify and prioritise potential anti-ageing compounds for humans are therefore of interest. In this study, we first used drug-protein interaction information, to rank 1,147 drugs by their likelihood of targeting ageing-related gene products in humans. Among 19 statistically significant drugs, 6 have already been shown to have pro-longevity properties in animal models (p < 0.001). Using the targets of each drug, we established their association with ageing at multiple levels of biological action including pathways, functions and protein interactions. Finally, combining all the data, we calculated a ranked list of drugs that identified tanespimycin, an inhibitor of HSP-90, as the top-ranked novel anti-ageing candidate. We experimentally validated the pro-longevity effect of tanespimycin through its HSP-90 target in Caenorhabditis elegans.

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<![CDATA[A rapid method for post-antibiotic bacterial susceptibility testing]]> https://www.researchpad.co/article/5c40f7bdd5eed0c4843867df

Antibiotic susceptibility testing is often performed to determine the most effective antibiotic treatment for a bacterial infection, or perhaps to determine if a particular strain of bacteria is becoming drug resistant. Such tests, and others used to determine efficacy of candidate antibiotics during the drug discovery process, have resulted in a demand for more rapid susceptibility testing methods. Here, we have developed a susceptibility test that utilizes chemiluminescent determination of ATP release from bacteria and the overall optical density (OD600) of the bacterial solution. Bacteria release ATP during a growth phase or when they are lysed in the presence of an effective antibiotic. Because optical density increases during growth phase, but does not change during bacterial lysing, an increase in the ATP:optical density ratio after the bacteria have reached the log phase of growth (which is steady) would indicate antibiotic efficacy. Specifically, after allowing a kanamycin-resistant strain of Escherichia coli (E.coli) to pass through the growth phase and reach steady state, the addition of levofloxacin, an antibiotic to which E. coli is susceptible, resulted in a significant increase in the ATP:OD600 ratio in comparison to the use of kanamycin alone (1.80 +/- 0.50 vs. 1.12 +/- 0.28). This difference could be measured 20 minutes after the addition of the antibiotic, to which the bacteria are susceptible, to the bacterial sample. Furthermore, this method also proved useful with gram positive bacteria, as the addition of kanamycin to a chloramphenicol-resistant strain of Bacillus subtilis (B. subtilis) resulted in an ATP:OD600 ratio of 2.14 +/- 0.26 in comparison to 0.62 +/- 0.05 for bacteria not subjected to the antibiotic to which the bacteria are susceptible. Collectively, these results suggest that measurement of the ATP:OD600 ratio may provide a susceptibility test for antibiotic efficacy that is more rapid and quantitative than currently accepted techniques.

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<![CDATA[Did relaxing clinical trial regulation enhance the stock of scientific knowledge in India? Not necessarily]]> https://www.researchpad.co/article/5c37b7a4d5eed0c48449078d

The increasing amount of clinical research conducted outside the “traditional” countries raises questions about the benefits of hosting offshored clinical research. The extent to which trials contribute to the scientific knowledge base and, in particular, whether there are differences between different types of trials remain open questions. By examining a change in clinical trial regulations in India, a country often viewed as a first-choice offshoring location, we study how the relaxation of clinical trial regulations affects the number and the type of clinical trials as well as the domestic scientific knowledge base. Based on trial data from ClinicalTrials.gov and data on associated publication activities, our empirical analysis suggests that, despite an initial increase in the number of clinical trials, relaxing clinical trial regulations has a limited impact on the domestic scientific knowledge base. More specifically, the number of Indian researchers involved in the production of trial-related scientific knowledge remains modest. Furthermore, the potential to learn from the additional trials appears to be limited: the influx of phase 3 trials—mainly sponsored by Western-pharmaceutical firms—is accompanied by a lower likelihood that the trial results will be used in Indian researchers’ subsequent research activities when compared to phase 3 trials with preceding phase 2 trials, as was required before the regulatory change. Overall, our results contradict expectations that relaxing the regulatory requirements for conducting late-stage clinical trials is an appropriate means of supporting the development of the domestic scientific knowledge base.

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<![CDATA[The integration of pharmacophore-based 3D QSAR modeling and virtual screening in safety profiling: A case study to identify antagonistic activities against adenosine receptor, A2A, using 1,897 known drugs]]> https://www.researchpad.co/article/5c37b7a7d5eed0c4844907ff

Safety pharmacology screening against a wide range of unintended vital targets using in vitro assays is crucial to understand off-target interactions with drug candidates. With the increasing demand for in vitro assays, ligand- and structure-based virtual screening approaches have been evaluated for potential utilization in safety profiling. Although ligand based approaches have been actively applied in retrospective analysis or prospectively within well-defined chemical space during the early discovery stage (i.e., HTS screening and lead optimization), virtual screening is rarely implemented in later stage of drug discovery (i.e., safety). Here we present a case study to evaluate ligand-based 3D QSAR models built based on in vitro antagonistic activity data against adenosine receptor 2A (A2A). The resulting models, obtained from 268 chemically diverse compounds, were used to test a set of 1,897 chemically distinct drugs, simulating the real-world challenge of safety screening when presented with novel chemistry and a limited training set. Due to the unique requirements of safety screening versus discovery screening, the limitations of 3D QSAR methods (i.e., chemotypes, dependence on large training set, and prone to false positives) are less critical than early discovery screen. We demonstrated that 3D QSAR modeling can be effectively applied in safety assessment prior to in vitro assays, even with chemotypes that are drastically different from training compounds. It is also worth noting that our model is able to adequately make the mechanistic distinction between agonists and antagonists, which is important to inform subsequent in vivo studies. Overall, we present an in-depth analysis of the appropriate utilization and interpretation of pharmacophore-based 3D QSAR models for safety screening.

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<![CDATA[Predicting protein targets for drug-like compounds using transcriptomics]]> https://www.researchpad.co/article/5c141e77d5eed0c484d26bce

An expanded chemical space is essential for improved identification of small molecules for emerging therapeutic targets. However, the identification of targets for novel compounds is biased towards the synthesis of known scaffolds that bind familiar protein families, limiting the exploration of chemical space. To change this paradigm, we validated a new pipeline that identifies small molecule-protein interactions and works even for compounds lacking similarity to known drugs. Based on differential mRNA profiles in multiple cell types exposed to drugs and in which gene knockdowns (KD) were conducted, we showed that drugs induce gene regulatory networks that correlate with those produced after silencing protein-coding genes. Next, we applied supervised machine learning to exploit drug-KD signature correlations and enriched our predictions using an orthogonal structure-based screen. As a proof-of-principle for this regimen, top-10/top-100 target prediction accuracies of 26% and 41%, respectively, were achieved on a validation of set 152 FDA-approved drugs and 3104 potential targets. We then predicted targets for 1680 compounds and validated chemical interactors with four targets that have proven difficult to chemically modulate, including non-covalent inhibitors of HRAS and KRAS. Importantly, drug-target interactions manifest as gene expression correlations between drug treatment and both target gene KD and KD of genes that act up- or down-stream of the target, even for relatively weak binders. These correlations provide new insights on the cellular response of disrupting protein interactions and highlight the complex genetic phenotypes of drug treatment. With further refinement, our pipeline may accelerate the identification and development of novel chemical classes by screening compound-target interactions.

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<![CDATA[PathFX provides mechanistic insights into drug efficacy and safety for regulatory review and therapeutic development]]> https://www.researchpad.co/article/5c141eabd5eed0c484d27adc

Failure to demonstrate efficacy and safety issues are important reasons that drugs do not reach the market. An incomplete understanding of how drugs exert their effects hinders regulatory and pharmaceutical industry projections of a drug’s benefits and risks. Signaling pathways mediate drug response and while many signaling molecules have been characterized for their contribution to disease or their role in drug side effects, our knowledge of these pathways is incomplete. To better understand all signaling molecules involved in drug response and the phenotype associations of these molecules, we created a novel method, PathFX, a non-commercial entity, to identify these pathways and drug-related phenotypes. We benchmarked PathFX by identifying drugs’ marketed disease indications and reported a sensitivity of 41%, a 2.7-fold improvement over similar approaches. We then used PathFX to strengthen signals for drug-adverse event pairs occurring in the FDA Adverse Event Reporting System (FAERS) and also identified opportunities for drug repurposing for new diseases based on interaction paths that associated a marketed drug to that disease. By discovering molecular interaction pathways, PathFX improved our understanding of drug associations to safety and efficacy phenotypes. The algorithm may provide a new means to improve regulatory and therapeutic development decisions.

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<![CDATA[Gene landscape and correlation between B-cell infiltration and programmed death ligand 1 expression in lung adenocarcinoma patients from The Cancer Genome Atlas data set]]> https://www.researchpad.co/article/5c12cf0cd5eed0c484913dd4

Tumor-infiltrating lymphocytes are related to positive clinical prognoses in numerous cancer types. Programmed death ligand 1 (PD-L1), a mediator of the PD-1 receptor, plays an inhibitory role in cancer immune responses. PD-L1 upregulation can impede infiltrating T-cell functions in lung adenocarcinoma (LUAD), a lung cancer subtype. However, associations between the expression of PD-L1 and infiltration of B cells (a major immunoregulatory cell) remain unknown. Therefore, we investigated the role of infiltrating B cells in LUAD progression and its correlation with PD-L1 expression. The Cancer Genome Atlas (TCGA) LUAD data set was used to explore associations among B-cell infiltration, PD-L1 expression, clinical outcome, and gene landscape. Gene set enrichment analysis was used to explore putative signaling pathways and candidate genes. The drug enrichment analysis was used to identify candidate genes and the related drugs. We found that high B-cell infiltration was correlated with better prognoses; however, PD-L1 may interfere with the survival advantage in patients with high B-cell infiltration. The gene landscape was characterized comprehensively, with distinct PD-L1 levels in cell populations with high B-cell infiltration. We obtained five upregulated signaling pathways from the gene landscape: apoptosis, tumor necrosis factor (TNF)-α signaling via nuclear factor (NF)-κB, apical surface, interferon-α response, and KRAS signaling. Moreover, four candidate genes and their related target drugs were also identified, namely interleukin-2β receptor (IL2RB), IL-2γ receptor (IL2RG), Toll-like receptor 8 (TLR8), and TNF. These findings suggest that tumor-infiltrating B cells could act as a clinical factor in anti-PD-L1 immunotherapy for LUAD.

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