Screening Of Drug Candidates Research Articles

Down-regulation of cathepsin S and matrix metalloproteinase-9 via Src, a non-receptor tyrosine kinase, suppresses triple-negative breast cancer growth and metastasis

Triple-negative breast cancer (TNBC) is a highly metastatic breast cancer with poor prognosis. In the present study, we demonstrated that Src, a non-receptor tyrosine kinase, might provide an effective therapeutic strategy to overcome TNBC invasion and metastasis, which are mediated via the synergistic action of the lysosomal enzyme cathepsin S (CTSS) and gelatinase MMP-9. Knock-down of MMP-9 and CTSS using siRNAs resulted in a synergistic suppression of MDA-MB-231 cell invasion, which was similarly observed with pharmacological inhibitors. During the screening of new drug candidates that suppress both CTSS and MMP-9, BJ-2302, a novel 7-azaindolin-2-one derivative, was discovered. Src, an upstream activator of both pathways (PI3K/Akt and Ras/Raf/ERK) responsible for the expression of CTSS and MMP-9, was identified as a high-affinity target of BJ-2302 (IC90: 3.23 µM) through a Src kinase assay and a drug affinity responsive target stability (DARTS) assay. BJ-2302 effectively suppressed MDA-MB-231 cell invasion (Matrigel invasion assay) and metastasis (chorioallantoic membrane assay xenografted with MDA-MB-231-luc2-tdTomato cancer cells). Unlike Z-FL-COCHO (potent CTSS inhibitor), BJ-2302 did not induce any cytotoxicity in MCF-10A normal breast epithelial cells. Additionally, BJ-2302 (1 mg/kg) strongly suppressed TNBC cell proliferation in vitro and tumor growth in a xenograft mouse tumor model. The anti-metastatic and anti-tumor effects of BJ-2302 were superior to those of Z-FL-COCHO (1 mg/kg) or batimastat (30 mg/kg), a pan-MMP inhibitor. In summary, inhibition of Src kinase suppressed TNBC tumor growth and metastasis, and Src inhibitors such as BJ-2302 may constitute a novel therapeutic tool to treat breast cancer that expresses high levels of CTSS and MMP-9.

A Robust Liposomal Platform for Direct Colorimetric Detection of Sphingomyelinase Enzyme and Inhibitors.

The enzyme sphingomyelinase (SMase) is an important biomarker for several diseases such as Niemann Pick’s, atherosclerosis, multiple sclerosis, and HIV. We present a two-component colorimetric SMase activity assay that is more sensitive and much faster than currently available commercial assays. Herein, SMase-triggered release of cysteine from a sphingomyelin (SM)-based liposome formulation with 60 mol % cholesterol causes gold nanoparticle (AuNP) aggregation, enabling colorimetric detection of SMase activities as low as 0.02 mU/mL, corresponding to 1.4 pM concentration. While the lipid composition offers a stable, nonleaky liposome platform with minimal background signal, high specificity toward SMase avoids cross-reactivity of other similar phospholipases. Notably, use of an SM-based liposome formulation accurately mimics the natural in vivo substrate: the cell membrane. We studied the physical rearrangement process of the lipid membrane during SMase-mediated hydrolysis of SM to ceramide using small- and wide-angle X-ray scattering. A change in lipid phase from a liquid to gel state bilayer with increasing concentration of ceramide accounts for the observed increase in membrane permeability and consequent release of encapsulated cysteine. We further demonstrated the effectiveness of the sensor in colorimetric screening of small-molecule drug candidates, paving the way for the identification of novel SMase inhibitors in minutes. Taken together, the simplicity, speed, sensitivity, and naked-eye readout of this assay offer huge potential in point-of-care diagnostics and high-throughput drug screening.

Abstract 3861: 3D ex vivo PDX cell model screening to better predict in vivo outcome

Abstract Patient-derived xenograft (PDX) models have been highly demanded in preclinical drug discovery and development due to several advantages over conventional 2D cell culture system: 1) reflection of the heterogeneity, molecular and histopathologic signatures of the original tumor than cell lines or genetically engineered mouse models, and 2) certain degree of correlation of their drug-response profiles with clinical response. Certain limitations of using PDX models, however, do exist, including low throughput in candidate drug screening, lack of dose-response curves, high cost and time-consuming studies, and progressive loss of human-derived stromal elements over passages. To overcome these disadvantages, we sought to develop ex vivo 3D assay format on cells isolated from early passage PDX models, and provide genetic mutation information to better interpret results. Moreover, we attempted to incorporate immunotherapy strategy into the 3D system as well. We have recently built up an ex vivo cell bank containing more than 300 frozen ex vivo tumor cells dissociated from freshly isolated PDX tumor tissues. We have collected five panels of such frozen ex vivo cells, each panel representing more than 50 models in a specific tumor type. SOC compounds corresponding to each unique tumor panel were tested, and will be discussed. Moreover, we have established a 3D immune cell and ex vivo somatic tumor cell co-culture system to evaluate drug efficacy of immune checkpoint inhibitors aPD1, aPDL1 and CTLA4 antibodies either as single agent or in combination with small-molecule inhibitors. The data will be presented. In summary, we have developed a robust and reproducible 3D ex vivo assay platform for medium-throughput compound screening with bioinformatics information for data interpretation. Citation Format: Xiaoxi Xu, Zhongliang Li, Yan Liu, Fanxiu Meng, Yu Lu, Songling Zhang, Chunlan Dong, Frank Xing, Qian Shi. 3D ex vivo PDX cell model screening to better predict in vivo outcome [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 3861.

Abstract 2107: A novel real-time cell imaging assay to quantify macrophage efferocytosis

Abstract Tumor-associated macrophages (TAMs) are found in the microenvironment of solid tumors, representing one of the most abundant immune cell types within tumor stroma. Studies have demonstrated that the presence of TAMs correlates with tumor progression and poor prognosis. The engulfment of apoptotic tumor cells by TAMs (a phagocytic process known as efferocytosis) results in clearance of neoplastic antigens, which prevents antigen presentation and activation of effector T cells. Additionally, it has been shown that TAMs produce cytokines that create an immunosuppressive environment that facilitates tumor evasion of immune surveillance and promotes tumor growth. Furthermore, TAMs have been reported to be key players in the promotion of tumor angiogenesis and metastasis. Since TAMs play such an important role in cancer progression, inhibition of their function in the tumor microenvironment becomes an attractive approach of cancer immunotherapy. Traditionally, quantifying efferocytosis in vitro has been a technically challenging task. Our lab has established a novel high-throughput assay that can be used to screen drug candidates that inhibit TAM efferocytosis. Our new assay uses the IncuCyte ZOOM real-time imaging platform to visualize macrophage efferocytosis of apoptotic cells that are labeled with a pH-sensitive probe (pHrodo) that only emits fluorescence in acidic enviroments. This technology enables us to quantify phagocytic events of apoptotic cells that have been processed into the phagolysosome. By using this method, we quantitatively characterized the efferocytosis activity of TAM-like macrophages that were differentiated from primary human monocytes. We tested several agents (including small-molecule compounds and antibodies) and quantified their activities in blocking efferocytosis of TAMs via IC50 concentrations and potency. This new high-throughput assay platform yields highly robust and reproducible data (Z'=0.69), is fully automated, noninvasive (no washing, fixing or lifting of cells), and works with low cell numbers. Our results show that our efferocytosis assay facilitates high-throughput functional screening and can be utilized to identify and characterize new cancer drug candidates, as well as enables research of efferocytosis mechanisms and functions of phagocytic cells. Citation Format: Daniel Bravo, Jianyong Wang, Yongchang Shi. A novel real-time cell imaging assay to quantify macrophage efferocytosis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 2107.

Quantitative Evaluation of Cytochrome P450 3A4 Inhibition and Hepatotoxicity in HepaRG 3-D Spheroids.

Predicting drug-drug interactions (DDIs) is an important step during drug development to avoid unexpected side effects. Cytochrome P450 (CYP) 3A4 is the most abundant human hepatic phase I enzyme, which metabolizes >50% of therapeutic drugs. Therefore, it is essential to test the potential of a drug candidate to induce CYP3A4 expression or inhibit its activity. Recently, 3-dimensional (3-D) mammalian cell culture models have been adopted in drug discovery research to assess toxicity, DDIs, and pharmacokinetics. In this study, we applied a human 3-D spheroid culture protocol using HepaRG cells combined with liquid chromatography-tandem mass spectrometry (LC-MS/MS) to assess its ability to predict CYP3A4 inhibition. Levels of midazolam, a specific substrate of CYP3A4, were used to determine the long-term metabolic capacity of CYP3A4. Midazolam was decreased in the 3-D HepaRG culture system by ∼80% over 7 days, whereas its primary metabolite, 1-hydroxymidazolam, increased by ∼40%. Next, we assessed hepatotoxicity by determining the cytotoxicity of known hepatotoxicants in HepaRG spheroids, HepG2 cells, and primary human hepatocytes. Significant differences in cytotoxicity were detected in the system using 3-D HepaRG spheroids. These results suggest that 3-D HepaRG spheroids are a good model for prediction of CYP inhibition and hepatotoxicity in screening of early drug candidates.

An In Vitro Model for Candida albicans⁻Streptococcus gordonii Biofilms on Titanium Surfaces.

The oral cavity serves as a nutrient-rich haven for over 600 species of microorganisms. Although many are essential to maintaining the oral microbiota, some can cause oral infections such as caries, periodontitis, mucositis, and endodontic infections, and this is further exacerbated with dental implants. Most of these infections are mixed species in nature and associated with a biofilm mode of growth. Here, after optimization of different parameters including cell density, growth media, and incubation conditions, we have developed an in vitro model of C. albicans–S. gordonii mixed-species biofilms on titanium discs that is relevant to infections of peri-implant diseases. Our results indicate a synergistic effect for the development of biofilms when both microorganisms were seeded together, confirming the existence of beneficial, mutualistic cross-kingdom interactions for biofilm formation. The morphological and architectural features of these dual-species biofilms formed on titanium were determined using scanning electron microscopy (SEM) and confocal laser scanning microscopy (CLSM). Mixed biofilms formed on titanium discs showed a high level of resistance to combination therapy with antifungal and antibacterial drugs. This model can serve as a platform for further analyses of complex fungal/bacterial biofilms and can also be applied to screening of new drug candidates against mixed-species biofilms.

Comparison of a Rat Primary Cell-Based Blood-Brain Barrier Model With Epithelial and Brain Endothelial Cell Lines: Gene Expression and Drug Transport

Cell culture-based blood-brain barrier (BBB) models are useful tools for screening of CNS drug candidates. Cell sources for BBB models include primary brain endothelial cells or immortalized brain endothelial cell lines. Despite their well-known differences, epithelial cell lines are also used as surrogate models for testing neuropharmaceuticals. The aim of the present study was to compare the expression of selected BBB related genes including tight junction proteins, solute carriers (SLC), ABC transporters, metabolic enzymes and to describe the paracellular properties of nine different culture models. To establish a primary BBB model rat brain capillary endothelial cells were co-cultured with rat pericytes and astrocytes (EPA). As other BBB and surrogate models four brain endothelial cells lines, rat GP8 and RBE4 cells, and human hCMEC/D3 cells with or without lithium treatment (D3 and D3L), and four epithelial cell lines, native human intestinal Caco-2 and high P-glycoprotein expressing vinblastine-selected VB-Caco-2 cells, native MDCK and MDR1 transfected MDCK canine kidney cells were used. To test transporter functionality, the permeability of 12 molecules, glucopyranose, valproate, baclofen, gabapentin, probenecid, salicylate, rosuvastatin, pravastatin, atorvastatin, tacrine, donepezil, was also measured in the EPA and epithelial models. Among the junctional protein genes, the expression level of occludin was high in all models except the GP8 and RBE4 cells, and each model expressed a unique claudin pattern. Major BBB efflux (P-glycoprotein or ABCB1) and influx transporters (GLUT-1, LAT-1) were present in all models at mRNA levels. The transcript of BCRP (ABCG2) was not expressed in MDCK, GP8 and RBE4 cells. The absence of gene expression of important BBB efflux and influx transporters BCRP, MRP6, -9, MCT6, -8, PHT2, OATPs in one or both types of epithelial models suggests that Caco-2 or MDCK models are not suitable to test drug candidates which are substrates of these transporters. Brain endothelial cell lines GP8, RBE4, D3 and D3L did not form a restrictive paracellular barrier necessary for screening small molecular weight pharmacons. Therefore, among the tested culture models, the primary cell-based EPA model is suitable for the functional analysis of the BBB.

Affinity capillary electrophoresis for identification of active drug candidates in myotonic dystrophy type 1

Myotonic dystrophy type 1 (DM1) is an autosomal dominantly inherited degenerative disease with a slow progression. At the present, there is no commercially available treatment, but sustained effort is currently undertaken for the development of a promising lead compound. In the present paper we report the development of a fast, versatile, and cost-effective affinity capillary electrophoresis (ACE) method for the screening and identification of potential drug candidates targeting pathological ARN probes relevant for DM1. The affinity studies were conducted in physiologically relevant conditions using 50mM HEPES buffer (pH7.4) in a fused silica capillary dynamically coated with poly(ethylene oxide), by testing a library of potential ligands against (CUG)50 RNA as target probe with a total run time of 4-5h/ligand. For the most promising ligands, their affinity parameters were assessed and some results formerly reported on the affinity of pentamidine (PTMD) and neomycin against CUG repeats were confirmed. To the best of the authors' knowledge, the estimated binding stoichiometry for some of the tested compounds (i.e., ~ 121:1 for PTMD against the tested RNA probe) is reported for the first time. Additionally, the potential of a novel pentamidine like compound, namely 1,2-ethane bis-1-amino-4-benzamidine (EBAB) with much lower in vivo toxicity than its parent compound has also been confirmed studying its effect on a live cell model by fluorescence microscopy. Further tests, such as the evaluation of the rescue in the mis-splicing of the involved genes, can be performed to corroborate the potential therapeutic value of EBAB in DM1 treatment. Graphical abstract ᅟ.

Polymer coating on a micropillar chip for robust attachment of PuraMatrix peptide hydrogel for 3D hepatic cell culture

For better mimicking tissues in vivo and developing predictive cell models for high-throughput screening (HTS) of potential drug candidates, three-dimensional (3D) cell cultures have been performed in various hydrogels. In this study, we have investigated several polymer coating materials to robustly attach PuraMatrix peptide hydrogel on a micropillar chip for 3D culture of Hep3B human hepatic cells, which can be used as a tool for high-throughput assessment of compound hepatotoxicity. Among several amphiphilic polymers with maleic anhydride groups tested, 0.01% (w/v) poly(maleic anhydride-alt-1-octadecene) (PMA-OD) provided superior coating properties with no PuraMatrix spot detachment from the micropillar chip and no air bubble entrapment in a complementary microwell chip. To maintain Hep3B cell viability in PuraMatrix gel on the chip, gelation conditions were optimized in the presence of additional salts, at different seeding densities, and for growth medium washes. As a result, salts in growth media were sufficient for gelation, and relatively high cell seeding at 6 million cells/mL and two media washes for pH neutralization were required. With optimized 3D cell culture conditions, controlled gene expression and compound toxicity assessment were successfully demonstrated by using recombinant adenoviruses carrying genes for green and red fluorescent proteins as well as six model compounds. Overall, PuraMatrix hydrogel on the chip was suitable for 3D cell encapsulation, gene expression, and rapid toxicity assessment.

Contemporary hydrogen deuterium exchange mass spectrometry.

Hydrogen/deuterium exchange (HDX) mass spectrometry (MS) emerged as a tool for biochemistry and structural biology around 25 years ago. It has since become a key approach for studying protein dynamics, protein-ligand interactions, membrane proteins and intrinsically disordered proteins (IDPs). In HDX labeling, proteins are exposed to deuterated solvent (usually D2O) for a variable 'labeling time', resulting in isotope exchange of unprotected labile protons on the amide backbone and amino acid side chains. By comparing the levels of deuterium uptake in different regions of a protein, information on conformational and dynamic changes in the system can be acquired. When coupled with MS, HDX is suitable for probing allosteric effects in catalysis and ligand binding, epitope mapping, validation of biosimilars, drug candidate screening and mapping membrane-protein interactions among many other bioanalytical applications. This review introduces HDX-MS via a brief description of HDX-MS development, followed by an overview of HDX theory and ultimately an outline of methods and procedures involved in performing HDX-MS experiments.

Rationalizing Drug Response in Cancer Cell Lines

Cancer cell lines (CCLs) play an important role in the initial stages of drug discovery allowing, among others, for the screening of drug candidates. As CCL panels continue to grow in size and diversity, many polymorphisms in genes encoding drug-metabolizing enzymes, transporters and drug targets, as well as disease-related genes have been linked to altered drug sensitivity. However, identifying the correlation between this variability and pharmacological responses remains challenging due to the heterogeneity of cancer biology and the intricate interplay between cell lines and drug molecules. Here, we propose a network-based strategy that exploits information on gene expression and somatic mutations of CCLs to group cells according to their molecular similarity. We then identify genes that are characteristic of each cluster and correlate their status with drug response. We find that CCLs with similar characteristic active network regions present specific responses to certain drugs, and identify a limited set of genes that might be directly involved in drug sensitivity or resistance.

Expression Analysis of Prostaglandin E and F Receptors in Rat Uterus, Mesenteric Artery and Uterine Artery for Development of a Surrogate Assay of Uterine Contractility

Preterm labor occurs in nearly 10% of U.S. pregnancies and is the leading cause of neonatal morbidity and mortality worldwide. Prostaglandins, specifically of the E and F series, play a key role in myometrial contractility and have been recognized as activators of parturition. As such, modulation of select prostaglandin signaling pathways provides a potential approach to pharmaceutical intervention of preterm labor. Prostaglandin E2 is the most abundantly produced prostanoid and functions through four subtypes of G protein coupled receptors (EP1, EP2, EP3, and EP4). It is generally accepted that EP1 and EP3 serve as pro‐contractility receptors while EP2 and EP4 are relaxatory receptors that promote myometrial quiescence. Prostaglandin F2α (PGF2α) functions through the FP receptor and plays an essential role in uterine contractility during preterm or term labor and delivery. The dynamicity and complexity of prostaglandin pharmacology is an important factor to consider during assay development for the testing of molecules which may not be selective to one receptor subtype.Translational ex vivo assays that enhance throughput of drug candidate screening and decrease the use of experimental animals are increasingly desirable. The objective of this research was to determine the relevance of employing either mesenteric resistance artery or uterine artery segments as surrogate tissues to the uterus in the evaluation of prostaglandin‐induced smooth muscle contraction. The relative expression of EP1, EP2, EP3, EP4, and FP receptor mRNA was determined by RT‐qPCR and compared between the uterine body, uterine artery, and mesenteric artery in the rat. Additionally, the efficacy of PGF2α in eliciting contraction was measured by isometric wire myography and compared between the uterine and mesenteric artery.The results of this study demonstrate that rat mesenteric artery may have utility as a model in the screening of prostaglandin receptor‐targeting molecules. Together, these findings will contribute to the identification of suitable and efficient ex vivo assays by which new pharmacological approaches for the treatment of preterm labor can be evaluated.Support or Funding InformationFerring Research Institute, San Diego, CAThis abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal.

A Systematic Prediction of Drug-Target Interactions Using Molecular Fingerprints and Protein Sequences.

Drug-Target Interactions (DTI) play a crucial role in discovering new drug candidates and finding new proteins to target for drug development. Although the number of detected DTI obtained by high-throughput techniques has been increasing, the number of known DTI is still limited. On the other hand, the experimental methods for detecting the interactions among drugs and proteins are costly and inefficient. Therefore, computational approaches for predicting DTI are drawing increasing attention in recent years. In this paper, we report a novel computational model for predicting the DTI using extremely randomized trees model and protein amino acids information. More specifically, the protein sequence is represented as a Pseudo Substitution Matrix Representation (Pseudo-SMR) descriptor in which the influence of biological evolutionary information is retained. For the representation of drug molecules, a novel fingerprint feature vector is utilized to describe its substructure information. Then the DTI pair is characterized by concatenating the two vector spaces of protein sequence and drug substructure. Finally, the proposed method is explored for predicting the DTI on four benchmark datasets: Enzyme, Ion Channel, GPCRs and Nuclear Receptor. The experimental results demonstrate that this method achieves promising prediction accuracies of 89.85%, 87.87%, 82.99% and 81.67%, respectively. For further evaluation, we compared the performance of Extremely Randomized Trees model with that of the state-of-the-art Support Vector Machine classifier. And we also compared the proposed model with existing computational models, and confirmed 15 potential drug-target interactions by looking for existing databases. The experiment results show that the proposed method is feasible and promising for predicting drug-target interactions for new drug candidate screening based on sizeable features.

Modelling ischemia-reperfusion injury (IRI) in vitro using metabolically matured induced pluripotent stem cell-derived cardiomyocytes.

Coronary intervention following ST-segment elevation myocardial infarction (STEMI) is the treatment of choice for reducing cardiomyocyte death but paradoxically leads to reperfusion injury. Pharmacological post-conditioning is an attractive approach to minimize Ischemia-Reperfusion Injury (IRI), but candidate drugs identified in IRI animal models have performed poorly in human clinical trials, highlighting the need for a human cell-based model of IRI. In this work, we show that when we imposed sequential hypoxia and reoxygenation episodes [mimicking the ischemia (I) and reperfusion (R) events] to immature human pluripotent stem cell-derived cardiomyocytes (hPSC-CMs), they display significant hypoxia resistance and minimal cell death (∼5%). Metabolic maturation of hPSC-CMs for 8 days substantially increased their sensitivity to changes in oxygen concentration and led to up to ∼30% cell death post-hypoxia and reoxygenation. To mimic the known transient changes in the interstitial tissue microenvironment during an IRI event in vivo, we tested a new in vitro IRI model protocol that required glucose availability and lowering of media pH during the ischemic episode, resulting in a significant increase in cell death in vitro (∼60%). Finally, we confirm that in this new physiologically matched IRI in vitro model, pharmacological post-conditioning reduces reperfusion-induced hPSC-CM cell death by 50%. Our results indicate that in recapitulating key aspects of an in vivo IRI event, our in vitro model can serve as a useful method for the study of IRI and the validation and screening of human specific pharmacological post-conditioning drug candidates.

Prediction of Drug-Plasma Protein Binding Using Artificial Intelligence Based Algorithms.

Plasma protein binding (PPB) has vital importance in the characterization of drug distribution in the systemic circulation. Unfavorable PPB can pose a negative effect on clinical development of promising drug candidates. The drug distribution properties should be considered at the initial phases of the drug design and development. Therefore, PPB prediction models are receiving an increased attention. In the current study, we present a systematic approach using Support vector machine, Artificial neural network, k- nearest neighbor, Probabilistic neural network, Partial least square and Linear discriminant analysis to relate various in vitro and in silico molecular descriptors to a diverse dataset of 736 drugs/drug-like compounds. The overall accuracy of Support vector machine with Radial basis function kernel came out to be comparatively better than the rest of the applied algorithms. The training set accuracy, validation set accuracy, precision, sensitivity, specificity and F1 score for the Suprort vector machine was found to be 89.73%, 89.97%, 92.56%, 87.26%, 91.97% and 0.898, respectively. This model can potentially be useful in screening of relevant drug candidates at the preliminary stages of drug design and development.

Cell-Based Kinetic Target-Guided Synthesis of an Enzyme Inhibitor.

Finding a new drug candidate for a selected target is an expensive and time-consuming process. Target guided-synthesis, or in situ click chemistry, is a concept where the drug target is used to template the formation of its own inhibitors from reactive building blocks. This could simplify the identification of drug candidates. However, with the exception of one example of an RNA-target, target-guided synthesis has always employed purified targets. This limits the number of targets that can be screened by the method. By applying methods from the field of metabolomics, we demonstrate that target-guided synthesis with protein targets also can be performed directly in cell-based systems. These methods offer new possibilities to conduct screening for drug candidates of difficult protein targets in cellular environments.

Identification of protective postexposure mycobacterial vaccine antigens using an immunosuppression-based reactivation model in the zebrafish.

ABSTRACTRoughly one third of the human population carries a latent Mycobacterium tuberculosis infection, with a 5-10% lifetime risk of reactivation to active tuberculosis and further spreading the disease. The mechanisms leading to the reactivation of a latent Mycobacterium tuberculosis infection are insufficiently understood. Here, we used a natural fish pathogen, Mycobacterium marinum, to model the reactivation of a mycobacterial infection in the adult zebrafish (Danio rerio). A low-dose intraperitoneal injection (∼40 colony-forming units) led to a latent infection, with mycobacteria found in well-organized granulomas surrounded by a thick layer of fibrous tissue. A latent infection could be reactivated by oral dexamethasone treatment, which led to disruption of the granuloma structures and dissemination of bacteria. This was associated with the depletion of lymphocytes, especially CD4+ T cells. Using this model, we verified that ethambutol is effective against an active disease but not a latent infection. In addition, we screened 15 mycobacterial antigens as postexposure DNA vaccines, of which RpfB and MMAR_4207 reduced bacterial burdens upon reactivation, as did the Ag85-ESAT-6 combination. In conclusion, the adult zebrafish-M. marinum infection model provides a feasible tool for examining the mechanisms of reactivation in mycobacterial infections, and for screening vaccine and drug candidates.This article has an associated First Person interview with the first author of the paper.

To Boil an Egg: Substrate Binding Affects Critical Stability in Thermal Unfolding of Proteins.

Thermal unfolding of proteins is used extensively in screening of drug candidates because molecular interactions with ligands and substrates affect strongly protein stability, transition temperature, and cooperativity. We use synchrotron radiation circular dichroism to monitor the thermal evolution of secondary structure in proteins as they approach the melting point and the impact of substrate on their thermal behavior. Using Landau free energy expansion, we quantify transition strength and proximity to a critical point through the relative separation τ+ between the transition temperature Tm and the spinodal T+, obtained from the equation of state. The weakest transition was observed in lysozyme with τ+ = -0.0167 followed by holo albumin with τ+ = -0.0208 with the strongest transition in monomeric apo albumin τ+ = -0.0242. A structural transition at 45 °C in apo albumin leads to a noncooperative melt with τ+ = -0.00532 and amyloidogenic increase in beta content.

Soft Computing Tools for Virtual Drug Discovery

Abstract In this paper, we describe how several soft computing tools can be used to assist in high throughput screening of potential drug candidates. Individual small molecules (ligands) are assessed for their potential to bind to specific proteins (receptors). Committees of multilayer networks are used to classify protein-ligand complexes as good binders or bad binders, based on selected chemical descriptors. The novel aspects of this paper include the use of statistical analyses on the weights of single layer networks to select the appropriate descriptors, the use of Monte Carlo cross-validation to provide confidence measures of network performance (and also to identify problems in the data), the addition of new chemical descriptors to improve network accuracy, and the use of Self Organizing Maps to analyze the performance of the trained network and identify anomalies. We demonstrate the procedures on a large practical data set, and use them to discover a promising characteristic of the data. We also perform virtual screenings with the trained networks on a number of benchmark sets and analyze the results.

In vitro assessment of chemotherapy-induced neuronal toxicity

Neurotoxicity is a major concern during drug development, and together with liver and cardio-toxicity, it is one of the main causes of clinical drug attrition. Current pre-clinical models may not sufficiently identify and predict the risk for central or peripheral nervous system toxicity. One such example is clinically dose-limiting neuropathic effects after the administration of chemotherapeutic agents. Thus, the need to establish novel in vitro tools to evaluate the risk of neurotoxicities, such as neuropathy, remains unmet in drug discovery. Though in vitro studies have been conducted using primary and immortalized cell lines, some limitations include the utility for higher throughput methodologies, method reproducibility, and species extrapolation. As a novel alternative, human induced-pluripotent stem cell (iPSC)-derived neurons appear promising for testing new drug candidates. These iPSC-derived neurons are readily available and can be manipulated as required. Here, we describe a novel approach to assess neurotoxicity caused by different classes of chemotherapeutics using kinetic monitoring of neurite dynamic changes and apoptosis in human iPSC-neurons. These studies show promising changes in neurite dynamics in response to clinical inducers of neuropathy, as well as the ability to rank-order and gather mechanistic insight into class-specific compound induced neurotoxicity. This platform can be utilized in early drug development, as part of a weight of evidence approach, to screen drug candidates, and potentially reduce clinical attrition due to neurotoxicity.