Automated recycling of chemistry for virtual screening and library design.
Vainio, Mikko J; Kogej, Thierry; Raubacher, Florian
2012-07-23
An early stage drug discovery project needs to identify a number of chemically diverse and attractive compounds. These hit compounds are typically found through high-throughput screening campaigns. The diversity of the chemical libraries used in screening is therefore important. In this study, we describe a virtual high-throughput screening system called Virtual Library. The system automatically "recycles" validated synthetic protocols and available starting materials to generate a large number of virtual compound libraries, and allows for fast searches in the generated libraries using a 2D fingerprint based screening method. Virtual Library links the returned virtual hit compounds back to experimental protocols to quickly assess the synthetic accessibility of the hits. The system can be used as an idea generator for library design to enrich the screening collection and to explore the structure-activity landscape around a specific active compound.
Ellingson, Sally R; Dakshanamurthy, Sivanesan; Brown, Milton; Smith, Jeremy C; Baudry, Jerome
2014-04-25
In this paper we give the current state of high-throughput virtual screening. We describe a case study of using a task-parallel MPI (Message Passing Interface) version of Autodock4 [1], [2] to run a virtual high-throughput screen of one-million compounds on the Jaguar Cray XK6 Supercomputer at Oak Ridge National Laboratory. We include a description of scripts developed to increase the efficiency of the predocking file preparation and postdocking analysis. A detailed tutorial, scripts, and source code for this MPI version of Autodock4 are available online at http://www.bio.utk.edu/baudrylab/autodockmpi.htm.
A web-based platform for virtual screening.
Watson, Paul; Verdonk, Marcel; Hartshorn, Michael J
2003-09-01
A fully integrated, web-based, virtual screening platform has been developed to allow rapid virtual screening of large numbers of compounds. ORACLE is used to store information at all stages of the process. The system includes a large database of historical compounds from high throughput screenings (HTS) chemical suppliers, ATLAS, containing over 3.1 million unique compounds with their associated physiochemical properties (ClogP, MW, etc.). The database can be screened using a web-based interface to produce compound subsets for virtual screening or virtual library (VL) enumeration. In order to carry out the latter task within ORACLE a reaction data cartridge has been developed. Virtual libraries can be enumerated rapidly using the web-based interface to the cartridge. The compound subsets can be seamlessly submitted for virtual screening experiments, and the results can be viewed via another web-based interface allowing ad hoc querying of the virtual screening data stored in ORACLE.
1001 Ways to run AutoDock Vina for virtual screening
NASA Astrophysics Data System (ADS)
Jaghoori, Mohammad Mahdi; Bleijlevens, Boris; Olabarriaga, Silvia D.
2016-03-01
Large-scale computing technologies have enabled high-throughput virtual screening involving thousands to millions of drug candidates. It is not trivial, however, for biochemical scientists to evaluate the technical alternatives and their implications for running such large experiments. Besides experience with the molecular docking tool itself, the scientist needs to learn how to run it on high-performance computing (HPC) infrastructures, and understand the impact of the choices made. Here, we review such considerations for a specific tool, AutoDock Vina, and use experimental data to illustrate the following points: (1) an additional level of parallelization increases virtual screening throughput on a multi-core machine; (2) capturing of the random seed is not enough (though necessary) for reproducibility on heterogeneous distributed computing systems; (3) the overall time spent on the screening of a ligand library can be improved by analysis of factors affecting execution time per ligand, including number of active torsions, heavy atoms and exhaustiveness. We also illustrate differences among four common HPC infrastructures: grid, Hadoop, small cluster and multi-core (virtual machine on the cloud). Our analysis shows that these platforms are suitable for screening experiments of different sizes. These considerations can guide scientists when choosing the best computing platform and set-up for their future large virtual screening experiments.
1001 Ways to run AutoDock Vina for virtual screening.
Jaghoori, Mohammad Mahdi; Bleijlevens, Boris; Olabarriaga, Silvia D
2016-03-01
Large-scale computing technologies have enabled high-throughput virtual screening involving thousands to millions of drug candidates. It is not trivial, however, for biochemical scientists to evaluate the technical alternatives and their implications for running such large experiments. Besides experience with the molecular docking tool itself, the scientist needs to learn how to run it on high-performance computing (HPC) infrastructures, and understand the impact of the choices made. Here, we review such considerations for a specific tool, AutoDock Vina, and use experimental data to illustrate the following points: (1) an additional level of parallelization increases virtual screening throughput on a multi-core machine; (2) capturing of the random seed is not enough (though necessary) for reproducibility on heterogeneous distributed computing systems; (3) the overall time spent on the screening of a ligand library can be improved by analysis of factors affecting execution time per ligand, including number of active torsions, heavy atoms and exhaustiveness. We also illustrate differences among four common HPC infrastructures: grid, Hadoop, small cluster and multi-core (virtual machine on the cloud). Our analysis shows that these platforms are suitable for screening experiments of different sizes. These considerations can guide scientists when choosing the best computing platform and set-up for their future large virtual screening experiments.
A kinase-focused compound collection: compilation and screening strategy.
Sun, Dongyu; Chuaqui, Claudio; Deng, Zhan; Bowes, Scott; Chin, Donovan; Singh, Juswinder; Cullen, Patrick; Hankins, Gretchen; Lee, Wen-Cherng; Donnelly, Jason; Friedman, Jessica; Josiah, Serene
2006-06-01
Lead identification by high-throughput screening of large compound libraries has been supplemented with virtual screening and focused compound libraries. To complement existing approaches for lead identification at Biogen Idec, a kinase-focused compound collection was designed, developed and validated. Two strategies were adopted to populate the compound collection: a ligand shape-based virtual screening and a receptor-based approach (structural interaction fingerprint). Compounds selected with the two approaches were cherry-picked from an existing high-throughput screening compound library, ordered from suppliers and supplemented with specific medicinal compounds from internal programs. Promising hits and leads have been generated from the kinase-focused compound collection against multiple kinase targets. The principle of the collection design and screening strategy was validated and the use of the kinase-focused compound collection for lead identification has been added to existing strategies.
Lee, Hyun; Mittal, Anuradha; Patel, Kavankumar; Gatuz, Joseph L; Truong, Lena; Torres, Jaime; Mulhearn, Debbie C; Johnson, Michael E
2014-01-01
We have used a combination of virtual screening (VS) and high-throughput screening (HTS) techniques to identify novel, non-peptidic small molecule inhibitors against human SARS-CoV 3CLpro. A structure-based VS approach integrating docking and pharmacophore based methods was employed to computationally screen 621,000 compounds from the ZINC library. The screening protocol was validated using known 3CLpro inhibitors and was optimized for speed, improved selectivity, and for accommodating receptor flexibility. Subsequently, a fluorescence-based enzymatic HTS assay was developed and optimized to experimentally screen approximately 41,000 compounds from four structurally diverse libraries chosen mainly based on the VS results. False positives from initial HTS hits were eliminated by a secondary orthogonal binding analysis using surface plasmon resonance (SPR). The campaign identified a reversible small molecule inhibitor exhibiting mixed-type inhibition with a K(i) value of 11.1 μM. Together, these results validate our protocols as suitable approaches to screen virtual and chemical libraries, and the newly identified compound reported in our study represents a promising structural scaffold to pursue for further SARS-CoV 3CLpro inhibitor development. Copyright © 2013. Published by Elsevier Ltd.
GPURFSCREEN: a GPU based virtual screening tool using random forest classifier.
Jayaraj, P B; Ajay, Mathias K; Nufail, M; Gopakumar, G; Jaleel, U C A
2016-01-01
In-silico methods are an integral part of modern drug discovery paradigm. Virtual screening, an in-silico method, is used to refine data models and reduce the chemical space on which wet lab experiments need to be performed. Virtual screening of a ligand data model requires large scale computations, making it a highly time consuming task. This process can be speeded up by implementing parallelized algorithms on a Graphical Processing Unit (GPU). Random Forest is a robust classification algorithm that can be employed in the virtual screening. A ligand based virtual screening tool (GPURFSCREEN) that uses random forests on GPU systems has been proposed and evaluated in this paper. This tool produces optimized results at a lower execution time for large bioassay data sets. The quality of results produced by our tool on GPU is same as that on a regular serial environment. Considering the magnitude of data to be screened, the parallelized virtual screening has a significantly lower running time at high throughput. The proposed parallel tool outperforms its serial counterpart by successfully screening billions of molecules in training and prediction phases.
This virtual FIFRA SAP meeting will be discus questions on Continuing Development of Alternative High-Throughput Screens to Determine Endocrine Disruption, focusing on Androgen Receptor, Steroidogenesis, and Thyroid Pathways
DOVIS: an implementation for high-throughput virtual screening using AutoDock.
Zhang, Shuxing; Kumar, Kamal; Jiang, Xiaohui; Wallqvist, Anders; Reifman, Jaques
2008-02-27
Molecular-docking-based virtual screening is an important tool in drug discovery that is used to significantly reduce the number of possible chemical compounds to be investigated. In addition to the selection of a sound docking strategy with appropriate scoring functions, another technical challenge is to in silico screen millions of compounds in a reasonable time. To meet this challenge, it is necessary to use high performance computing (HPC) platforms and techniques. However, the development of an integrated HPC system that makes efficient use of its elements is not trivial. We have developed an application termed DOVIS that uses AutoDock (version 3) as the docking engine and runs in parallel on a Linux cluster. DOVIS can efficiently dock large numbers (millions) of small molecules (ligands) to a receptor, screening 500 to 1,000 compounds per processor per day. Furthermore, in DOVIS, the docking session is fully integrated and automated in that the inputs are specified via a graphical user interface, the calculations are fully integrated with a Linux cluster queuing system for parallel processing, and the results can be visualized and queried. DOVIS removes most of the complexities and organizational problems associated with large-scale high-throughput virtual screening, and provides a convenient and efficient solution for AutoDock users to use this software in a Linux cluster platform.
Shankar, Manoharan; Priyadharshini, Ramachandran; Gunasekaran, Paramasamy
2009-08-01
An image analysis-based method for high throughput screening of an alpha-amylase mutant library using chromogenic assays was developed. Assays were performed in microplates and high resolution images of the assay plates were read using the Virtual Microplate Reader (VMR) script to quantify the concentration of the chromogen. This method is fast and sensitive in quantifying 0.025-0.3 mg starch/ml as well as 0.05-0.75 mg glucose/ml. It was also an effective screening method for improved alpha-amylase activity with a coefficient of variance of 18%.
ChemHTPS - A virtual high-throughput screening program suite for the chemical and materials sciences
NASA Astrophysics Data System (ADS)
Afzal, Mohammad Atif Faiz; Evangelista, William; Hachmann, Johannes
The discovery of new compounds, materials, and chemical reactions with exceptional properties is the key for the grand challenges in innovation, energy and sustainability. This process can be dramatically accelerated by means of the virtual high-throughput screening (HTPS) of large-scale candidate libraries. The resulting data can further be used to study the underlying structure-property relationships and thus facilitate rational design capability. This approach has been extensively used for many years in the drug discovery community. However, the lack of openly available virtual HTPS tools is limiting the use of these techniques in various other applications such as photovoltaics, optoelectronics, and catalysis. Thus, we developed ChemHTPS, a general-purpose, comprehensive and user-friendly suite, that will allow users to efficiently perform large in silico modeling studies and high-throughput analyses in these applications. ChemHTPS also includes a massively parallel molecular library generator which offers a multitude of options to customize and restrict the scope of the enumerated chemical space and thus tailor it for the demands of specific applications. To streamline the non-combinatorial exploration of chemical space, we incorporate genetic algorithms into the framework. In addition to implementing smarter algorithms, we also focus on the ease of use, workflow, and code integration to make this technology more accessible to the community.
Developing science gateways for drug discovery in a grid environment.
Pérez-Sánchez, Horacio; Rezaei, Vahid; Mezhuyev, Vitaliy; Man, Duhu; Peña-García, Jorge; den-Haan, Helena; Gesing, Sandra
2016-01-01
Methods for in silico screening of large databases of molecules increasingly complement and replace experimental techniques to discover novel compounds to combat diseases. As these techniques become more complex and computationally costly we are faced with an increasing problem to provide the research community of life sciences with a convenient tool for high-throughput virtual screening on distributed computing resources. To this end, we recently integrated the biophysics-based drug-screening program FlexScreen into a service, applicable for large-scale parallel screening and reusable in the context of scientific workflows. Our implementation is based on Pipeline Pilot and Simple Object Access Protocol and provides an easy-to-use graphical user interface to construct complex workflows, which can be executed on distributed computing resources, thus accelerating the throughput by several orders of magnitude.
The U.S. EPA’s ToxCastTM program has screened over a thousand chemicals for potential toxicity using hundreds of high-throughput, in vitro assays. The U.S. EPA’s Virtual Liver (v-Liver™) is a cellular systems model of hepatic tissues that enables the estimation of in vivo effects...
Accessible high-throughput virtual screening molecular docking software for students and educators.
Jacob, Reed B; Andersen, Tim; McDougal, Owen M
2012-05-01
We survey low cost high-throughput virtual screening (HTVS) computer programs for instructors who wish to demonstrate molecular docking in their courses. Since HTVS programs are a useful adjunct to the time consuming and expensive wet bench experiments necessary to discover new drug therapies, the topic of molecular docking is core to the instruction of biochemistry and molecular biology. The availability of HTVS programs coupled with decreasing costs and advances in computer hardware have made computational approaches to drug discovery possible at institutional and non-profit budgets. This paper focuses on HTVS programs with graphical user interfaces (GUIs) that use either DOCK or AutoDock for the prediction of DockoMatic, PyRx, DockingServer, and MOLA since their utility has been proven by the research community, they are free or affordable, and the programs operate on a range of computer platforms.
Library fingerprints: a novel approach to the screening of virtual libraries.
Klon, Anthony E; Diller, David J
2007-01-01
We propose a novel method to prioritize libraries for combinatorial synthesis and high-throughput screening that assesses the viability of a particular library on the basis of the aggregate physical-chemical properties of the compounds using a naïve Bayesian classifier. This approach prioritizes collections of related compounds according to the aggregate values of their physical-chemical parameters in contrast to single-compound screening. The method is also shown to be useful in screening existing noncombinatorial libraries when the compounds in these libraries have been previously clustered according to their molecular graphs. We show that the method used here is comparable or superior to the single-compound virtual screening of combinatorial libraries and noncombinatorial libraries and is superior to the pairwise Tanimoto similarity searching of a collection of combinatorial libraries.
A high-throughput screening approach for the optoelectronic properties of conjugated polymers.
Wilbraham, Liam; Berardo, Enrico; Turcani, Lukas; Jelfs, Kim E; Zwijnenburg, Martijn A
2018-06-25
We propose a general high-throughput virtual screening approach for the optical and electronic properties of conjugated polymers. This approach makes use of the recently developed xTB family of low-computational-cost density functional tight-binding methods from Grimme and co-workers, calibrated here to (TD-)DFT data computed for a representative diverse set of (co-)polymers. Parameters drawn from the resulting calibration using a linear model can then be applied to the xTB derived results for new polymers, thus generating near DFT-quality data with orders of magnitude reduction in computational cost. As a result, after an initial computational investment for calibration, this approach can be used to quickly and accurately screen on the order of thousands of polymers for target applications. We also demonstrate that the (opto)electronic properties of the conjugated polymers show only a very minor variation when considering different conformers and that the results of high-throughput screening are therefore expected to be relatively insensitive with respect to the conformer search methodology applied.
Virtual High-Throughput Screening for Matrix Metalloproteinase Inhibitors.
Choi, Jun Yong; Fuerst, Rita
2017-01-01
Structure-based virtual screening (SBVS) is a common method for the fast identification of hit structures at the beginning of a medicinal chemistry program in drug discovery. The SBVS, described in this manuscript, is focused on finding small molecule hits that can be further utilized as a starting point for the development of inhibitors of matrix metalloproteinase 13 (MMP-13) via structure-based molecular design. We intended to identify a set of structurally diverse hits, which occupy all subsites (S1'-S3', S2, and S3) centering the zinc containing binding site of MMP-13, by the virtual screening of a chemical library comprising more than ten million commercially available compounds. In total, 23 compounds were found as potential MMP-13 inhibitors using Glide docking followed by the analysis of the structural interaction fingerprints (SIFt) of the docked structures.
Damm-Ganamet, Kelly L; Bembenek, Scott D; Venable, Jennifer W; Castro, Glenda G; Mangelschots, Lieve; Peeters, Daniëlle C G; Mcallister, Heather M; Edwards, James P; Disepio, Daniel; Mirzadegan, Taraneh
2016-05-12
Here, we report a high-throughput virtual screening (HTVS) study using phosphoinositide 3-kinase (both PI3Kγ and PI3Kδ). Our initial HTVS results of the Janssen corporate database identified small focused libraries with hit rates at 50% inhibition showing a 50-fold increase over those from a HTS (high-throughput screen). Further, applying constraints based on "chemically intuitive" hydrogen bonds and/or positional requirements resulted in a substantial improvement in the hit rates (versus no constraints) and reduced docking time. While we find that docking scoring functions are not capable of providing a reliable relative ranking of a set of compounds, a prioritization of groups of compounds (e.g., low, medium, and high) does emerge, which allows for the chemistry efforts to be quickly focused on the most viable candidates. Thus, this illustrates that it is not always necessary to have a high correlation between a computational score and the experimental data to impact the drug discovery process.
Virtual Embryo: Systems Modeling in Developmental Toxicity
High-throughput screening (HTS) studies are providing a rich source of data that can be applied to chemical profiling to address sensitivity and specificity of molecular targets, biological pathways, cellular and developmental processes. EPA’s ToxCast project is testing 960 uniq...
Performance Studies on Distributed Virtual Screening
Krüger, Jens; de la Garza, Luis; Kohlbacher, Oliver; Nagel, Wolfgang E.
2014-01-01
Virtual high-throughput screening (vHTS) is an invaluable method in modern drug discovery. It permits screening large datasets or databases of chemical structures for those structures binding possibly to a drug target. Virtual screening is typically performed by docking code, which often runs sequentially. Processing of huge vHTS datasets can be parallelized by chunking the data because individual docking runs are independent of each other. The goal of this work is to find an optimal splitting maximizing the speedup while considering overhead and available cores on Distributed Computing Infrastructures (DCIs). We have conducted thorough performance studies accounting not only for the runtime of the docking itself, but also for structure preparation. Performance studies were conducted via the workflow-enabled science gateway MoSGrid (Molecular Simulation Grid). As input we used benchmark datasets for protein kinases. Our performance studies show that docking workflows can be made to scale almost linearly up to 500 concurrent processes distributed even over large DCIs, thus accelerating vHTS campaigns significantly. PMID:25032219
Wang, Yi; Hess, Tamara Noelle; Jones, Victoria; Zhou, Joe Zhongxiang; McNeil, Michael R.; McCammon, J. Andrew
2011-01-01
The complex and highly impermeable cell wall of Mycobacterium tuberculosis (Mtb) is largely responsible for the ability of the mycobacterium to resist the action of chemical therapeutics. An L-rhamnosyl residue, which occupies an important anchoring position in the Mtb cell wall, is an attractive target for novel anti-tuberculosis drugs. In this work, we report a virtual screening (VS) study targeting Mtb dTDP-deoxy-L-lyxo-4-hexulose reductase (RmlD), the last enzyme in the L-rhamnosyl synthesis pathway. Through two rounds of VS, we have identified four RmlD inhibitors with half inhibitory concentrations of 0.9-25 μM, and whole-cell minimum inhibitory concentrations of 20-200 μg/ml. Compared with our previous high throughput screening targeting another enzyme involved in L-rhamnosyl synthesis, virtual screening produced higher hit rates, supporting the use of computational methods in future anti-tuberculosis drug discovery efforts. PMID:22014548
Modeling limb-bud dysmorphogenesis in a predictive virtual embryo model
ToxCast is profiling the bioactivity of thousands of chemicals based on high-throughput screening (HTS) and computational methods that integrate knowledge of biological systems and in vivo toxicities (www.epa.gov/ncct/toxcast/). Many ToxCast assays assess signaling pathways and c...
Speck-Planche, Alejandro; Cordeiro, M N D S
2014-02-10
Escherichia coli remains one of the principal pathogens that cause nosocomial infections, medical conditions that are increasingly common in healthcare facilities. E. coli is intrinsically resistant to many antibiotics, and multidrug-resistant strains have emerged recently. Chemoinformatics has been a great ally of experimental methodologies such as high-throughput screening, playing an important role in the discovery of effective antibacterial agents. However, there is no approach that can design safer anti-E. coli agents, because of the multifactorial nature and complexity of bacterial diseases and the lack of desirable ADMET (absorption, distribution, metabolism, elimination, and toxicity) profiles as a major cause of disapproval of drugs. In this work, we introduce the first multitasking model based on quantitative-structure biological effect relationships (mtk-QSBER) for simultaneous virtual prediction of anti-E. coli activities and ADMET properties of drugs and/or chemicals under many experimental conditions. The mtk-QSBER model was developed from a large and heterogeneous data set of more than 37800 cases, exhibiting overall accuracies of >95% in both training and prediction (validation) sets. The utility of our mtk-QSBER model was demonstrated by performing virtual prediction of properties for the investigational drug avarofloxacin (AVX) under 260 different experimental conditions. Results converged with the experimental evidence, confirming the remarkable anti-E. coli activities and safety of AVX. Predictions also showed that our mtk-QSBER model can be a promising computational tool for virtual screening of desirable anti-E. coli agents, and this chemoinformatic approach could be extended to the search for safer drugs with defined pharmacological activities.
Su, Hao; Yan, Ji; Xu, Jian; Fan, Xi-Zhen; Sun, Xian-Lin; Chen, Kang-Yu
2015-08-01
Pulmonary hypertension (PH) is a devastating disease characterized by progressive elevation of pulmonary arterial pressure and vascular resistance due to pulmonary vasoconstriction and vessel remodeling. The activation of RhoA/Rho-kinase (ROCK) pathway plays a central role in the pathologic progression of PH and thus the Rho kinase, an essential effector of the ROCK pathway, is considered as a potential therapeutic target to attenuate PH. In the current study, a synthetic pipeline is used to discover new potent Rho inhibitors from various natural products. In the pipeline, the stepwise high-throughput virtual screening, quantitative structure-activity relationship (QSAR)-based rescoring, and kinase assay were integrated. The screening was performed against a structurally diverse, drug-like natural product library, from which six identified compounds were tested to determine their inhibitory potencies agonist Rho by using a standard kinase assay protocol. With this scheme, we successfully identified two potent Rho inhibitors, namely phloretin and baicalein, with activity values of IC50 = 0.22 and 0.95 μM, respectively. Structural examination suggested that complicated networks of non-bonded interactions such as hydrogen bonding, hydrophobic forces, and van der Waals contacts across the complex interfaces of Rho kinase are formed with the screened compounds.
VIRTUAL EMBRYO: SYSTEMS MODELING IN DEVELOPMENTAL TOXICITY - Symposium: SOT 2012
High-throughput screening (HTS) studies are providing a rich source of data that can be applied to in vitro profiling of chemical compounds for biological activity and potential toxicity. Chemical profiling in ToxCast covered 965 drugs-chemicals in over 500 diverse assays testing...
Virtual Embryo: Systems Modeling in Developmental Toxicity
High-throughput and high-content screening (HTS-HCS) studies are providing a rich source of data that can be applied to in vitro profiling of chemical compounds for biological activity and potential toxicity. EPA’s ToxCast™ project, and the broader Tox21 consortium, in addition t...
AutoClickChem: click chemistry in silico.
Durrant, Jacob D; McCammon, J Andrew
2012-01-01
Academic researchers and many in industry often lack the financial resources available to scientists working in "big pharma." High costs include those associated with high-throughput screening and chemical synthesis. In order to address these challenges, many researchers have in part turned to alternate methodologies. Virtual screening, for example, often substitutes for high-throughput screening, and click chemistry ensures that chemical synthesis is fast, cheap, and comparatively easy. Though both in silico screening and click chemistry seek to make drug discovery more feasible, it is not yet routine to couple these two methodologies. We here present a novel computer algorithm, called AutoClickChem, capable of performing many click-chemistry reactions in silico. AutoClickChem can be used to produce large combinatorial libraries of compound models for use in virtual screens. As the compounds of these libraries are constructed according to the reactions of click chemistry, they can be easily synthesized for subsequent testing in biochemical assays. Additionally, in silico modeling of click-chemistry products may prove useful in rational drug design and drug optimization. AutoClickChem is based on the pymolecule toolbox, a framework that may facilitate the development of future python-based programs that require the manipulation of molecular models. Both the pymolecule toolbox and AutoClickChem are released under the GNU General Public License version 3 and are available for download from http://autoclickchem.ucsd.edu.
AutoClickChem: Click Chemistry in Silico
Durrant, Jacob D.; McCammon, J. Andrew
2012-01-01
Academic researchers and many in industry often lack the financial resources available to scientists working in “big pharma.” High costs include those associated with high-throughput screening and chemical synthesis. In order to address these challenges, many researchers have in part turned to alternate methodologies. Virtual screening, for example, often substitutes for high-throughput screening, and click chemistry ensures that chemical synthesis is fast, cheap, and comparatively easy. Though both in silico screening and click chemistry seek to make drug discovery more feasible, it is not yet routine to couple these two methodologies. We here present a novel computer algorithm, called AutoClickChem, capable of performing many click-chemistry reactions in silico. AutoClickChem can be used to produce large combinatorial libraries of compound models for use in virtual screens. As the compounds of these libraries are constructed according to the reactions of click chemistry, they can be easily synthesized for subsequent testing in biochemical assays. Additionally, in silico modeling of click-chemistry products may prove useful in rational drug design and drug optimization. AutoClickChem is based on the pymolecule toolbox, a framework that may facilitate the development of future python-based programs that require the manipulation of molecular models. Both the pymolecule toolbox and AutoClickChem are released under the GNU General Public License version 3 and are available for download from http://autoclickchem.ucsd.edu. PMID:22438795
Hristozov, Dimitar P; Oprea, Tudor I; Gasteiger, Johann
2007-01-01
Four different ligand-based virtual screening scenarios are studied: (1) prioritizing compounds for subsequent high-throughput screening (HTS); (2) selecting a predefined (small) number of potentially active compounds from a large chemical database; (3) assessing the probability that a given structure will exhibit a given activity; (4) selecting the most active structure(s) for a biological assay. Each of the four scenarios is exemplified by performing retrospective ligand-based virtual screening for eight different biological targets using two large databases--MDDR and WOMBAT. A comparison between the chemical spaces covered by these two databases is presented. The performance of two techniques for ligand--based virtual screening--similarity search with subsequent data fusion (SSDF) and novelty detection with Self-Organizing Maps (ndSOM) is investigated. Three different structure representations--2,048-dimensional Daylight fingerprints, topological autocorrelation weighted by atomic physicochemical properties (sigma electronegativity, polarizability, partial charge, and identity) and radial distribution functions weighted by the same atomic physicochemical properties--are compared. Both methods were found applicable in scenario one. The similarity search was found to perform slightly better in scenario two while the SOM novelty detection is preferred in scenario three. No method/descriptor combination achieved significant success in scenario four.
Virtual Liver: Quantitative Dose-Response Using Systems Biology
The U.S. EPA’s ToxCast™ program uses hundreds of high-throughput, in vitro assays to screen chemicals in order to rapidly identify signatures of toxicity. These assays measure the in vitro concentrations at which cellular pathways are perturbed by chemicals. The U.S. EPA’s Virtu...
SYNOPSIS: The question of how tissues and organs are shaped during development is crucial for understanding human birth defects. Data from high-throughput screening assays on human stem cells may be utilized predict developmental toxicity with reasonable accuracy. Other types of ...
Influence relevance voting: an accurate and interpretable virtual high throughput screening method.
Swamidass, S Joshua; Azencott, Chloé-Agathe; Lin, Ting-Wan; Gramajo, Hugo; Tsai, Shiou-Chuan; Baldi, Pierre
2009-04-01
Given activity training data from high-throughput screening (HTS) experiments, virtual high-throughput screening (vHTS) methods aim to predict in silico the activity of untested chemicals. We present a novel method, the Influence Relevance Voter (IRV), specifically tailored for the vHTS task. The IRV is a low-parameter neural network which refines a k-nearest neighbor classifier by nonlinearly combining the influences of a chemical's neighbors in the training set. Influences are decomposed, also nonlinearly, into a relevance component and a vote component. The IRV is benchmarked using the data and rules of two large, open, competitions, and its performance compared to the performance of other participating methods, as well as of an in-house support vector machine (SVM) method. On these benchmark data sets, IRV achieves state-of-the-art results, comparable to the SVM in one case, and significantly better than the SVM in the other, retrieving three times as many actives in the top 1% of its prediction-sorted list. The IRV presents several other important advantages over SVMs and other methods: (1) the output predictions have a probabilistic semantic; (2) the underlying inferences are interpretable; (3) the training time is very short, on the order of minutes even for very large data sets; (4) the risk of overfitting is minimal, due to the small number of free parameters; and (5) additional information can easily be incorporated into the IRV architecture. Combined with its performance, these qualities make the IRV particularly well suited for vHTS.
Role of Open Source Tools and Resources in Virtual Screening for Drug Discovery.
Karthikeyan, Muthukumarasamy; Vyas, Renu
2015-01-01
Advancement in chemoinformatics research in parallel with availability of high performance computing platform has made handling of large scale multi-dimensional scientific data for high throughput drug discovery easier. In this study we have explored publicly available molecular databases with the help of open-source based integrated in-house molecular informatics tools for virtual screening. The virtual screening literature for past decade has been extensively investigated and thoroughly analyzed to reveal interesting patterns with respect to the drug, target, scaffold and disease space. The review also focuses on the integrated chemoinformatics tools that are capable of harvesting chemical data from textual literature information and transform them into truly computable chemical structures, identification of unique fragments and scaffolds from a class of compounds, automatic generation of focused virtual libraries, computation of molecular descriptors for structure-activity relationship studies, application of conventional filters used in lead discovery along with in-house developed exhaustive PTC (Pharmacophore, Toxicophores and Chemophores) filters and machine learning tools for the design of potential disease specific inhibitors. A case study on kinase inhibitors is provided as an example.
Gómez-Bombarelli, Rafael; Aguilera-Iparraguirre, Jorge; Hirzel, Timothy D; Duvenaud, David; Maclaurin, Dougal; Blood-Forsythe, Martin A; Chae, Hyun Sik; Einzinger, Markus; Ha, Dong-Gwang; Wu, Tony; Markopoulos, Georgios; Jeon, Soonok; Kang, Hosuk; Miyazaki, Hiroshi; Numata, Masaki; Kim, Sunghan; Huang, Wenliang; Hong, Seong Ik; Baldo, Marc; Adams, Ryan P; Aspuru-Guzik, Alán
2016-10-01
Virtual screening is becoming a ground-breaking tool for molecular discovery due to the exponential growth of available computer time and constant improvement of simulation and machine learning techniques. We report an integrated organic functional material design process that incorporates theoretical insight, quantum chemistry, cheminformatics, machine learning, industrial expertise, organic synthesis, molecular characterization, device fabrication and optoelectronic testing. After exploring a search space of 1.6 million molecules and screening over 400,000 of them using time-dependent density functional theory, we identified thousands of promising novel organic light-emitting diode molecules across the visible spectrum. Our team collaboratively selected the best candidates from this set. The experimentally determined external quantum efficiencies for these synthesized candidates were as large as 22%.
NASA Astrophysics Data System (ADS)
Gómez-Bombarelli, Rafael; Aguilera-Iparraguirre, Jorge; Hirzel, Timothy D.; Duvenaud, David; MacLaurin, Dougal; Blood-Forsythe, Martin A.; Chae, Hyun Sik; Einzinger, Markus; Ha, Dong-Gwang; Wu, Tony; Markopoulos, Georgios; Jeon, Soonok; Kang, Hosuk; Miyazaki, Hiroshi; Numata, Masaki; Kim, Sunghan; Huang, Wenliang; Hong, Seong Ik; Baldo, Marc; Adams, Ryan P.; Aspuru-Guzik, Alán
2016-10-01
Virtual screening is becoming a ground-breaking tool for molecular discovery due to the exponential growth of available computer time and constant improvement of simulation and machine learning techniques. We report an integrated organic functional material design process that incorporates theoretical insight, quantum chemistry, cheminformatics, machine learning, industrial expertise, organic synthesis, molecular characterization, device fabrication and optoelectronic testing. After exploring a search space of 1.6 million molecules and screening over 400,000 of them using time-dependent density functional theory, we identified thousands of promising novel organic light-emitting diode molecules across the visible spectrum. Our team collaboratively selected the best candidates from this set. The experimentally determined external quantum efficiencies for these synthesized candidates were as large as 22%.
web cellHTS2: a web-application for the analysis of high-throughput screening data.
Pelz, Oliver; Gilsdorf, Moritz; Boutros, Michael
2010-04-12
The analysis of high-throughput screening data sets is an expanding field in bioinformatics. High-throughput screens by RNAi generate large primary data sets which need to be analyzed and annotated to identify relevant phenotypic hits. Large-scale RNAi screens are frequently used to identify novel factors that influence a broad range of cellular processes, including signaling pathway activity, cell proliferation, and host cell infection. Here, we present a web-based application utility for the end-to-end analysis of large cell-based screening experiments by cellHTS2. The software guides the user through the configuration steps that are required for the analysis of single or multi-channel experiments. The web-application provides options for various standardization and normalization methods, annotation of data sets and a comprehensive HTML report of the screening data analysis, including a ranked hit list. Sessions can be saved and restored for later re-analysis. The web frontend for the cellHTS2 R/Bioconductor package interacts with it through an R-server implementation that enables highly parallel analysis of screening data sets. web cellHTS2 further provides a file import and configuration module for common file formats. The implemented web-application facilitates the analysis of high-throughput data sets and provides a user-friendly interface. web cellHTS2 is accessible online at http://web-cellHTS2.dkfz.de. A standalone version as a virtual appliance and source code for platforms supporting Java 1.5.0 can be downloaded from the web cellHTS2 page. web cellHTS2 is freely distributed under GPL.
O'Malley, Sean; Sareth, Sina; Jiao, Guan-Sheng; Kim, Seongjin; Thai, April; Cregar-Hernandez, Lynne; McKasson, Linda; Margosiak, Stephen A; Johnson, Alan T
2013-05-01
A novel method for applying high-throughput docking to challenging metalloenzyme targets is described. The method utilizes information-based virtual transformation of library carboxylates to hydroxamic acids prior to docking, followed by compound acquisition, one-pot (two steps) chemical synthesis and in vitro screening. In two experiments targeting the botulinum neurotoxin serotype A metalloprotease light chain, hit rates of 32% and 18% were observed. Copyright © 2013 Elsevier Ltd. All rights reserved.
Applications of SHAPES screening in drug discovery.
Lepre, Christopher A; Peng, Jeffrey; Fejzo, Jasna; Abdul-Manan, Norzehan; Pocas, Jennifer; Jacobs, Marc; Xie, Xiaoling; Moore, Jonathan M
2002-12-01
The SHAPES strategy combines nuclear magnetic resonance (NMR) screening of a library of small drug-like molecules with a variety of complementary methods, such as virtual screening, high throughput enzymatic assays, combinatorial chemistry, X-ray crystallography, and molecular modeling, in a directed search for new medicinal chemistry leads. In the past few years, the SHAPES strategy has found widespread utility in pharmaceutical research. To illustrate a variety of different implementations of the method, we will focus in this review on recent applications of the SHAPES strategy in several drug discovery programs at Vertex Pharmaceuticals.
Virtual Liver: Evaluating the Impact of Hepatic Microdosimetry for ToxCast Chemicals
The U.S. EPA’s ToxCastTM program uses hundreds of high-throughput, in vitro assays to screen chemicals for potential toxicity. The assays are used to probe in vitro concentrations at which target cellular pathways and processes are perturbed by these chemicals. The U.S. EPA’s Vir...
Alexander, Nathan; Woetzel, Nils; Meiler, Jens
2011-02-01
Clustering algorithms are used as data analysis tools in a wide variety of applications in Biology. Clustering has become especially important in protein structure prediction and virtual high throughput screening methods. In protein structure prediction, clustering is used to structure the conformational space of thousands of protein models. In virtual high throughput screening, databases with millions of drug-like molecules are organized by structural similarity, e.g. common scaffolds. The tree-like dendrogram structure obtained from hierarchical clustering can provide a qualitative overview of the results, which is important for focusing detailed analysis. However, in practice it is difficult to relate specific components of the dendrogram directly back to the objects of which it is comprised and to display all desired information within the two dimensions of the dendrogram. The current work presents a hierarchical agglomerative clustering method termed bcl::Cluster. bcl::Cluster utilizes the Pymol Molecular Graphics System to graphically depict dendrograms in three dimensions. This allows simultaneous display of relevant biological molecules as well as additional information about the clusters and the members comprising them.
Hu, Jun; Liu, Zi; Yu, Dong-Jun; Zhang, Yang
2018-02-15
Sequence-order independent structural comparison, also called structural alignment, of small ligand molecules is often needed for computer-aided virtual drug screening. Although many ligand structure alignment programs are proposed, most of them build the alignments based on rigid-body shape comparison which cannot provide atom-specific alignment information nor allow structural variation; both abilities are critical to efficient high-throughput virtual screening. We propose a novel ligand comparison algorithm, LS-align, to generate fast and accurate atom-level structural alignments of ligand molecules, through an iterative heuristic search of the target function that combines inter-atom distance with mass and chemical bond comparisons. LS-align contains two modules of Rigid-LS-align and Flexi-LS-align, designed for rigid-body and flexible alignments, respectively, where a ligand-size independent, statistics-based scoring function is developed to evaluate the similarity of ligand molecules relative to random ligand pairs. Large-scale benchmark tests are performed on prioritizing chemical ligands of 102 protein targets involving 1,415,871 candidate compounds from the DUD-E (Database of Useful Decoys: Enhanced) database, where LS-align achieves an average enrichment factor (EF) of 22.0 at the 1% cutoff and the AUC score of 0.75, which are significantly higher than other state-of-the-art methods. Detailed data analyses show that the advanced performance is mainly attributed to the design of the target function that combines structural and chemical information to enhance the sensitivity of recognizing subtle difference of ligand molecules and the introduces of structural flexibility that help capture the conformational changes induced by the ligand-receptor binding interactions. These data demonstrate a new avenue to improve the virtual screening efficiency through the development of sensitive ligand structural alignments. http://zhanglab.ccmb.med.umich.edu/LS-align/. njyudj@njust.edu.cn or zhng@umich.edu. Supplementary data are available at Bioinformatics online.
Bayesian Models Leveraging Bioactivity and Cytotoxicity Information for Drug Discovery
Ekins, Sean; Reynolds, Robert C.; Kim, Hiyun; Koo, Mi-Sun; Ekonomidis, Marilyn; Talaue, Meliza; Paget, Steve D.; Woolhiser, Lisa K.; Lenaerts, Anne J.; Bunin, Barry A.; Connell, Nancy; Freundlich, Joel S.
2013-01-01
SUMMARY Identification of unique leads represents a significant challenge in drug discovery. This hurdle is magnified in neglected diseases such as tuberculosis. We have leveraged public high-throughput screening (HTS) data, to experimentally validate virtual screening approach employing Bayesian models built with bioactivity information (single-event model) as well as bioactivity and cytotoxicity information (dual-event model). We virtually screen a commercial library and experimentally confirm actives with hit rates exceeding typical HTS results by 1-2 orders of magnitude. The first dual-event Bayesian model identified compounds with antitubercular whole-cell activity and low mammalian cell cytotoxicity from a published set of antimalarials. The most potent hit exhibits the in vitro activity and in vitro/in vivo safety profile of a drug lead. These Bayesian models offer significant economies in time and cost to drug discovery. PMID:23521795
IspE Inhibitors Identified by a Combination of In Silico and In Vitro High-Throughput Screening
Tidten-Luksch, Naomi; Grimaldi, Raffaella; Torrie, Leah S.; Frearson, Julie A.; Hunter, William N.; Brenk, Ruth
2012-01-01
CDP-ME kinase (IspE) contributes to the non-mevalonate or deoxy-xylulose phosphate (DOXP) pathway for isoprenoid precursor biosynthesis found in many species of bacteria and apicomplexan parasites. IspE has been shown to be essential by genetic methods and since it is absent from humans it constitutes a promising target for antimicrobial drug development. Using in silico screening directed against the substrate binding site and in vitro high-throughput screening directed against both, the substrate and co-factor binding sites, non-substrate-like IspE inhibitors have been discovered and structure-activity relationships were derived. The best inhibitors in each series have high ligand efficiencies and favourable physico-chemical properties rendering them promising starting points for drug discovery. Putative binding modes of the ligands were suggested which are consistent with established structure-activity relationships. The applied screening methods were complementary in discovering hit compounds, and a comparison of both approaches highlights their strengths and weaknesses. It is noteworthy that compounds identified by virtual screening methods provided the controls for the biochemical screens. PMID:22563402
Don, Rob; Ioset, Jean-Robert
2014-01-01
The Drugs for Neglected Diseases initiative (DNDi) has defined and implemented an early discovery strategy over the last few years, in fitting with its virtual R&D business model. This strategy relies on a medium- to high-throughput phenotypic assay platform to expedite the screening of compound libraries accessed through its collaborations with partners from the pharmaceutical industry. We review the pragmatic approaches used to select compound libraries for screening against kinetoplastids, taking into account screening capacity. The advantages, limitations and current achievements in identifying new quality series for further development into preclinical candidates are critically discussed, together with attractive new approaches currently under investigation.
Saxena, Shalini; Durgam, Laxman; Guruprasad, Lalitha
2018-05-14
Development of new antimalarial drugs continues to be of huge importance because of the resistance of malarial parasite towards currently used drugs. Due to the reliance of parasite on glycolysis for energy generation, glycolytic enzymes have played important role as potential targets for the development of new drugs. Plasmodium falciparum lactate dehydrogenase (PfLDH) is a key enzyme for energy generation of malarial parasites and is considered to be a potential antimalarial target. Presently, there are nearly 15 crystal structures bound with inhibitors and substrate that are available in the protein data bank (PDB). In the present work, we attempted to consider multiple crystal structures with bound inhibitors showing affinity in the range of 1.4 × 10 2 -1.3 × 10 6 nM efficacy and optimized the pharmacophore based on the energy involved in binding termed as e-pharmacophore mapping. A high throughput virtual screening (HTVS) combined with molecular docking, ADME predictions and molecular dynamics simulation led to the identification of 20 potential compounds which could be further developed as novel inhibitors for PfLDH.
DPubChem: a web tool for QSAR modeling and high-throughput virtual screening.
Soufan, Othman; Ba-Alawi, Wail; Magana-Mora, Arturo; Essack, Magbubah; Bajic, Vladimir B
2018-06-14
High-throughput screening (HTS) performs the experimental testing of a large number of chemical compounds aiming to identify those active in the considered assay. Alternatively, faster and cheaper methods of large-scale virtual screening are performed computationally through quantitative structure-activity relationship (QSAR) models. However, the vast amount of available HTS heterogeneous data and the imbalanced ratio of active to inactive compounds in an assay make this a challenging problem. Although different QSAR models have been proposed, they have certain limitations, e.g., high false positive rates, complicated user interface, and limited utilization options. Therefore, we developed DPubChem, a novel web tool for deriving QSAR models that implement the state-of-the-art machine-learning techniques to enhance the precision of the models and enable efficient analyses of experiments from PubChem BioAssay database. DPubChem also has a simple interface that provides various options to users. DPubChem predicted active compounds for 300 datasets with an average geometric mean and F 1 score of 76.68% and 76.53%, respectively. Furthermore, DPubChem builds interaction networks that highlight novel predicted links between chemical compounds and biological assays. Using such a network, DPubChem successfully suggested a novel drug for the Niemann-Pick type C disease. DPubChem is freely available at www.cbrc.kaust.edu.sa/dpubchem .
The essential roles of chemistry in high-throughput screening triage
Dahlin, Jayme L; Walters, Michael A
2015-01-01
It is increasingly clear that academic high-throughput screening (HTS) and virtual HTS triage suffers from a lack of scientists trained in the art and science of early drug discovery chemistry. Many recent publications report the discovery of compounds by screening that are most likely artifacts or promiscuous bioactive compounds, and these results are not placed into the context of previous studies. For HTS to be most successful, it is our contention that there must exist an early partnership between biologists and medicinal chemists. Their combined skill sets are necessary to design robust assays and efficient workflows that will weed out assay artifacts, false positives, promiscuous bioactive compounds and intractable screening hits, efforts that ultimately give projects a better chance at identifying truly useful chemical matter. Expertise in medicinal chemistry, cheminformatics and purification sciences (analytical chemistry) can enhance the post-HTS triage process by quickly removing these problematic chemotypes from consideration, while simultaneously prioritizing the more promising chemical matter for follow-up testing. It is only when biologists and chemists collaborate effectively that HTS can manifest its full promise. PMID:25163000
De Simone, Angela; Mancini, Francesca; Cosconati, Sandro; Marinelli, Luciana; La Pietra, Valeria; Novellino, Ettore; Andrisano, Vincenza
2013-01-25
In the present work, a human recombinant BACE1 immobilized enzyme reactor (hrBACE1-IMER) has been applied for the sensitive fast screening of 38 compounds selected through a virtual screening approach. HrBACE1-IMER was inserted into a liquid chromatograph coupled with a fluorescent detector. A fluorogenic peptide substrate (M-2420), containing the β-secretase site of the Swedish mutation of APP, was injected and cleaved in the on-line HPLC-hrBACE1-IMER system, giving rise to the fluorescent product. The compounds of the library were tested for their ability to inhibit BACE1 in the immobilized format and to reduce the area related to the chromatographic peak of the fluorescent enzymatic product. The results were validated in solution by using two different FRET methods. Due to the efficient virtual screening methodology, more than fifty percent of the selected compounds showed a measurable inhibitory activity. One of the most active compound (a bis-indanone derivative) was characterized in terms of IC(50) and K(i) determination on the hrBACE1-IMER. Thus, the hrBACE1-IMER has been confirmed as a valid tool for the throughput screening of different chemical entities with potency lower than 30μM for the fast hits' selection and for mode of action determination. Copyright © 2012 Elsevier B.V. All rights reserved.
Covalent Docking of Large Libraries for the Discovery of Chemical Probes
London, Nir; Miller, Rand M.; Krishnan, Shyam; Uchida, Kenji; Irwin, John J.; Eidam, Oliv; Gibold, Lucie; Cimermančič, Peter; Bonnet, Richard; Shoichet, Brian K.; Taunton, Jack
2014-01-01
Chemical probes that form a covalent bond with a protein target often show enhanced selectivity, potency, and utility for biological studies. Despite these advantages, protein-reactive compounds are usually avoided in high-throughput screening campaigns. Here we describe a general method (DOCKovalent) for screening large virtual libraries of electrophilic small molecules. We apply this method prospectively to discover reversible covalent fragments that target distinct protein nucleophiles, including the catalytic serine of AmpC β-lactamase and noncatalytic cysteines in RSK2, MSK1, and JAK3 kinases. We identify submicromolar to low-nanomolar hits with high ligand efficiency, cellular activity and selectivity, including the first reported reversible covalent inhibitors of JAK3. Crystal structures of inhibitor complexes with AmpC and RSK2 confirm the docking predictions and guide further optimization. As covalent virtual screening may have broad utility for the rapid discovery of chemical probes, we have made the method freely available through an automated web server (http://covalent.docking.org). PMID:25344815
Covalent docking of large libraries for the discovery of chemical probes.
London, Nir; Miller, Rand M; Krishnan, Shyam; Uchida, Kenji; Irwin, John J; Eidam, Oliv; Gibold, Lucie; Cimermančič, Peter; Bonnet, Richard; Shoichet, Brian K; Taunton, Jack
2014-12-01
Chemical probes that form a covalent bond with a protein target often show enhanced selectivity, potency and utility for biological studies. Despite these advantages, protein-reactive compounds are usually avoided in high-throughput screening campaigns. Here we describe a general method (DOCKovalent) for screening large virtual libraries of electrophilic small molecules. We apply this method prospectively to discover reversible covalent fragments that target distinct protein nucleophiles, including the catalytic serine of AmpC β-lactamase and noncatalytic cysteines in RSK2, MSK1 and JAK3 kinases. We identify submicromolar to low-nanomolar hits with high ligand efficiency, cellular activity and selectivity, including what are to our knowledge the first reported reversible covalent inhibitors of JAK3. Crystal structures of inhibitor complexes with AmpC and RSK2 confirm the docking predictions and guide further optimization. As covalent virtual screening may have broad utility for the rapid discovery of chemical probes, we have made the method freely available through an automated web server (http://covalent.docking.org/).
DockoMatic: automated peptide analog creation for high throughput virtual screening.
Jacob, Reed B; Bullock, Casey W; Andersen, Tim; McDougal, Owen M
2011-10-01
The purpose of this manuscript is threefold: (1) to describe an update to DockoMatic that allows the user to generate cyclic peptide analog structure files based on protein database (pdb) files, (2) to test the accuracy of the peptide analog structure generation utility, and (3) to evaluate the high throughput capacity of DockoMatic. The DockoMatic graphical user interface interfaces with the software program Treepack to create user defined peptide analogs. To validate this approach, DockoMatic produced cyclic peptide analogs were tested for three-dimensional structure consistency and binding affinity against four experimentally determined peptide structure files available in the Research Collaboratory for Structural Bioinformatics database. The peptides used to evaluate this new functionality were alpha-conotoxins ImI, PnIA, and their published analogs. Peptide analogs were generated by DockoMatic and tested for their ability to bind to X-ray crystal structure models of the acetylcholine binding protein originating from Aplysia californica. The results, consisting of more than 300 simulations, demonstrate that DockoMatic predicts the binding energy of peptide structures to within 3.5 kcal mol(-1), and the orientation of bound ligand compares to within 1.8 Å root mean square deviation for ligand structures as compared to experimental data. Evaluation of high throughput virtual screening capacity demonstrated that Dockomatic can collect, evaluate, and summarize the output of 10,000 AutoDock jobs in less than 2 hours of computational time, while 100,000 jobs requires approximately 15 hours and 1,000,000 jobs is estimated to take up to a week. Copyright © 2011 Wiley Periodicals, Inc.
Cheng, Chao-Sheng; Jia, Kai-Fan; Chen, Ting; Chang, Shun-Ya; Lin, Ming-Shen; Yin, Hsien-Sheng
2013-01-01
Helicobacter pylori is a major etiologic agent associated with the development and maintenance of human gastritis. The goal of this study was to develop novel antibiotics against H. pylori, and we thus targeted H. pylori phosphopantetheine adenylyltransferase (HpPPAT). PPAT catalyzes the penultimate step in coenzyme A biosynthesis. Its inactivation effectively prevents bacterial viability, making it an attractive target for antibacterial drug discovery. We employed virtual high-throughput screening and the HpPPAT crystal structure to identify compounds in the PubChem database that might act as inhibitors of HpPPAT. d-amethopterin is a potential inhibitor for blocking HpPPAT activity and suppressing H. pylori viability. Following treatment with d-amethopterin, H. pylori exhibited morphological characteristics associated with cell death. d-amethopterin is a mixed inhibitor of HpPPAT activity; it simultaneously occupies the HpPPAT 4'-phosphopantetheine- and ATP-binding sites. Its binding affinity is in the micromolar range, implying that it is sufficiently potent to serve as a lead compound in subsequent drug development. Characterization of the d-amethopterin and HpPPAT interaction network in a docked model will allow us to initiate rational drug optimization to improve the inhibitory efficacy of d-amethopterin. We anticipate that novel, potent, and selective HpPPAT inhibitors will emerge for the treatment of H. pylori infection. PMID:24040220
Human stem cells and drug screening: opportunities and challenges.
Ebert, Allison D; Svendsen, Clive N
2010-05-01
High-throughput screening technologies are widely used in the early stages of drug discovery to rapidly evaluate the properties of thousands of compounds. However, they generally rely on testing compound libraries on highly proliferative immortalized or cancerous cell lines, which do not necessarily provide an accurate indication of the effects of compounds in normal human cells or the specific cell type under study. Recent advances in stem cell technology have the potential to allow production of a virtually limitless supply of normal human cells that can be differentiated into any specific cell type. Moreover, using induced pluripotent stem cell technology, they can also be generated from patients with specific disease traits, enabling more relevant modelling and drug screens. This article discusses the opportunities and challenges for the use of stem cells in drug screening with a focus on induced pluripotent stem cells.
Kavlock, Robert; Dix, David
2010-02-01
Computational toxicology is the application of mathematical and computer models to help assess chemical hazards and risks to human health and the environment. Supported by advances in informatics, high-throughput screening (HTS) technologies, and systems biology, the U.S. Environmental Protection Agency EPA is developing robust and flexible computational tools that can be applied to the thousands of chemicals in commerce, and contaminant mixtures found in air, water, and hazardous-waste sites. The Office of Research and Development (ORD) Computational Toxicology Research Program (CTRP) is composed of three main elements. The largest component is the National Center for Computational Toxicology (NCCT), which was established in 2005 to coordinate research on chemical screening and prioritization, informatics, and systems modeling. The second element consists of related activities in the National Health and Environmental Effects Research Laboratory (NHEERL) and the National Exposure Research Laboratory (NERL). The third and final component consists of academic centers working on various aspects of computational toxicology and funded by the U.S. EPA Science to Achieve Results (STAR) program. Together these elements form the key components in the implementation of both the initial strategy, A Framework for a Computational Toxicology Research Program (U.S. EPA, 2003), and the newly released The U.S. Environmental Protection Agency's Strategic Plan for Evaluating the Toxicity of Chemicals (U.S. EPA, 2009a). Key intramural projects of the CTRP include digitizing legacy toxicity testing information toxicity reference database (ToxRefDB), predicting toxicity (ToxCast) and exposure (ExpoCast), and creating virtual liver (v-Liver) and virtual embryo (v-Embryo) systems models. U.S. EPA-funded STAR centers are also providing bioinformatics, computational toxicology data and models, and developmental toxicity data and models. The models and underlying data are being made publicly available through the Aggregated Computational Toxicology Resource (ACToR), the Distributed Structure-Searchable Toxicity (DSSTox) Database Network, and other U.S. EPA websites. While initially focused on improving the hazard identification process, the CTRP is placing increasing emphasis on using high-throughput bioactivity profiling data in systems modeling to support quantitative risk assessments, and in developing complementary higher throughput exposure models. This integrated approach will enable analysis of life-stage susceptibility, and understanding of the exposures, pathways, and key events by which chemicals exert their toxicity in developing systems (e.g., endocrine-related pathways). The CTRP will be a critical component in next-generation risk assessments utilizing quantitative high-throughput data and providing a much higher capacity for assessing chemical toxicity than is currently available.
Mishra, Vinita; Pathak, Chandramani
2018-05-29
Toll-like receptor 4 (TLR4) is a member of Toll-Like Receptors (TLRs) family that serves as a receptor for bacterial lipopolysaccharide (LPS). TLR4 alone cannot recognize LPS without aid of co-receptor myeloid differentiation factor-2 (MD-2). Binding of LPS with TLR4 forms a LPS-TLR4-MD-2 complex and directs downstream signaling for activation of immune response, inflammation and NF-κB activation. Activation of TLR4 signaling is associated with various pathophysiological consequences. Therefore, targeting protein-protein interaction (PPI) in TLR4-MD-2 complex formation could be an attractive therapeutic approach for targeting inflammatory disorders. The aim of present study was directed to identify small molecule PPI inhibitors (SMPPIIs) using pharmacophore mapping-based approach of computational drug discovery. Here, we had retrieved the information about the hot spot residues and their pharmacophoric features at both primary (TLR4-MD-2) and dimerization (MD-2-TLR4*) protein-protein interaction interfaces in TLR4-MD-2 homo-dimer complex using in silico methods. Promising candidates were identified after virtual screening, which may restrict TLR4-MD-2 protein-protein interaction. In silico off-target profiling over the virtually screened compounds revealed other possible molecular targets. Two of the virtually screened compounds (C11 and C15) were predicted to have an inhibitory concentration in μM range after HYDE assessment. Molecular dynamics simulation study performed for these two compounds in complex with target protein confirms the stability of the complex. After virtual high throughput screening we found selective hTLR4-MD-2 inhibitors, which may have therapeutic potential to target chronic inflammatory diseases.
Benchmarking Ligand-Based Virtual High-Throughput Screening with the PubChem Database
Butkiewicz, Mariusz; Lowe, Edward W.; Mueller, Ralf; Mendenhall, Jeffrey L.; Teixeira, Pedro L.; Weaver, C. David; Meiler, Jens
2013-01-01
With the rapidly increasing availability of High-Throughput Screening (HTS) data in the public domain, such as the PubChem database, methods for ligand-based computer-aided drug discovery (LB-CADD) have the potential to accelerate and reduce the cost of probe development and drug discovery efforts in academia. We assemble nine data sets from realistic HTS campaigns representing major families of drug target proteins for benchmarking LB-CADD methods. Each data set is public domain through PubChem and carefully collated through confirmation screens validating active compounds. These data sets provide the foundation for benchmarking a new cheminformatics framework BCL::ChemInfo, which is freely available for non-commercial use. Quantitative structure activity relationship (QSAR) models are built using Artificial Neural Networks (ANNs), Support Vector Machines (SVMs), Decision Trees (DTs), and Kohonen networks (KNs). Problem-specific descriptor optimization protocols are assessed including Sequential Feature Forward Selection (SFFS) and various information content measures. Measures of predictive power and confidence are evaluated through cross-validation, and a consensus prediction scheme is tested that combines orthogonal machine learning algorithms into a single predictor. Enrichments ranging from 15 to 101 for a TPR cutoff of 25% are observed. PMID:23299552
Honegr, Jan; Dolezal, Rafael; Malinak, David; Benkova, Marketa; Soukup, Ondrej; Almeida, Joyce S F D de; Franca, Tanos C C; Kuca, Kamil; Prymula, Roman
2018-01-04
In order to identify novel lead structures for human toll-like receptor 4 ( h TLR4) modulation virtual high throughput screening by a peta-flops-scale supercomputer has been performed. Based on the in silico studies, a series of 12 compounds related to tryptamine was rationally designed to retain suitable molecular geometry for interaction with the h TLR4 binding site as well as to satisfy general principles of drug-likeness. The proposed compounds were synthesized, and tested by in vitro and ex vivo experiments, which revealed that several of them are capable to stimulate h TLR4 in vitro up to 25% activity of Monophosphoryl lipid A. The specific affinity of the in vitro most potent substance was confirmed by surface plasmon resonance direct-binding experiments. Moreover, two compounds from the series show also significant ability to elicit production of interleukin 6.
2014-01-01
Background Measures of similarity for chemical molecules have been developed since the dawn of chemoinformatics. Molecular similarity has been measured by a variety of methods including molecular descriptor based similarity, common molecular fragments, graph matching and 3D methods such as shape matching. Similarity measures are widespread in practice and have proven to be useful in drug discovery. Because of our interest in electrostatics and high throughput ligand-based virtual screening, we sought to exploit the information contained in atomic coordinates and partial charges of a molecule. Results A new molecular descriptor based on partial charges is proposed. It uses the autocorrelation function and linear binning to encode all atoms of a molecule into two rotation-translation invariant vectors. Combined with a scoring function, the descriptor allows to rank-order a database of compounds versus a query molecule. The proposed implementation is called ACPC (AutoCorrelation of Partial Charges) and released in open source. Extensive retrospective ligand-based virtual screening experiments were performed and other methods were compared with in order to validate the method and associated protocol. Conclusions While it is a simple method, it performed remarkably well in experiments. At an average speed of 1649 molecules per second, it reached an average median area under the curve of 0.81 on 40 different targets; hence validating the proposed protocol and implementation. PMID:24887178
NASA Astrophysics Data System (ADS)
Maffucci, Irene; Hu, Xiao; Fumagalli, Valentina; Contini, Alessandro
2018-03-01
Nwat-MMGBSA is a variant of MM-PB/GBSA based on the inclusion of a number of explicit water molecules that are the closest to the ligand in each frame of a molecular dynamics trajectory. This method demonstrated improved correlations between calculated and experimental binding energies in both protein-protein interactions and ligand-receptor complexes, in comparison to the standard MM-GBSA. A protocol optimization, aimed to maximize efficacy and efficiency, is discussed here considering penicillopepsin, HIV1-protease, and BCL-XL as test cases. Calculations were performed in triplicates on both classic HPC environments and on standard workstations equipped by a GPU card, evidencing no statistical differences in the results. No relevant differences in correlation to experiments were also observed when performing Nwat-MMGBSA calculations on 4 ns or 1 ns long trajectories. A fully automatic workflow for structure-based virtual screening, performing from library set-up to docking and Nwat-MMGBSA rescoring, has then been developed. The protocol has been tested against no rescoring or standard MM-GBSA rescoring within a retrospective virtual screening of inhibitors of AmpC β-lactamase and of the Rac1-Tiam1 protein-protein interaction. In both cases, Nwat-MMGBSA rescoring provided a statistically significant increase in the ROC AUCs of between 20% and 30%, compared to docking scoring or to standard MM-GBSA rescoring.
Jeankumar, Variam Ullas; Reshma, Rudraraju Srilakshmi; Vats, Rahul; Janupally, Renuka; Saxena, Shalini; Yogeeswari, Perumal; Sriram, Dharmarajan
2016-10-21
A structure based medium throughput virtual screening campaign of BITS-Pilani in house chemical library to identify novel binders of Mycobacterium tuberculosis gyrase ATPase domain led to the discovery of a quinoline scaffold. Further medicinal chemistry explorations on the right hand core of the early hit, engendered a potent lead demonstrating superior efficacy both in the enzyme and whole cell screening assay. The binding affinity shown at the enzyme level was further corroborated by biophysical characterization techniques. Early pharmacokinetic evaluation of the optimized analogue was encouraging and provides interesting potential for further optimization. Copyright © 2016 Elsevier Masson SAS. All rights reserved.
Virtual High-Throughput Screening To Identify Novel Activin Antagonists
Zhu, Jie; Mishra, Rama K.; Schiltz, Gary E.; Makanji, Yogeshwar; Scheidt, Karl A.; Mazar, Andrew P.; Woodruff, Teresa K.
2015-01-01
Activin belongs to the TGFβ superfamily, which is associated with several disease conditions, including cancer-related cachexia, preterm labor with delivery, and osteoporosis. Targeting activin and its related signaling pathways holds promise as a therapeutic approach to these diseases. A small-molecule ligand-binding groove was identified in the interface between the two activin βA subunits and was used for a virtual high-throughput in silico screening of the ZINC database to identify hits. Thirty-nine compounds without significant toxicity were tested in two well-established activin assays: FSHβ transcription and HepG2 cell apoptosis. This screening workflow resulted in two lead compounds: NUCC-474 and NUCC-555. These potential activin antagonists were then shown to inhibit activin A-mediated cell proliferation in ex vivo ovary cultures. In vivo testing showed that our most potent compound (NUCC-555) caused a dose-dependent decrease in FSH levels in ovariectomized mice. The Blitz competition binding assay confirmed target binding of NUCC-555 to the activin A:ActRII that disrupts the activin A:ActRII complex’s binding with ALK4-ECD-Fc in a dose-dependent manner. The NUCC-555 also specifically binds to activin A compared with other TGFβ superfamily member myostatin (GDF8). These data demonstrate a new in silico-based strategy for identifying small-molecule activin antagonists. Our approach is the first to identify a first-in-class small-molecule antagonist of activin binding to ALK4, which opens a completely new approach to inhibiting the activity of TGFβ receptor superfamily members. in addition, the lead compound can serve as a starting point for lead optimization toward the goal of a compound that may be effective in activin-mediated diseases. PMID:26098096
DockoMatic 2.0: high throughput inverse virtual screening and homology modeling.
Bullock, Casey; Cornia, Nic; Jacob, Reed; Remm, Andrew; Peavey, Thomas; Weekes, Ken; Mallory, Chris; Oxford, Julia T; McDougal, Owen M; Andersen, Timothy L
2013-08-26
DockoMatic is a free and open source application that unifies a suite of software programs within a user-friendly graphical user interface (GUI) to facilitate molecular docking experiments. Here we describe the release of DockoMatic 2.0; significant software advances include the ability to (1) conduct high throughput inverse virtual screening (IVS); (2) construct 3D homology models; and (3) customize the user interface. Users can now efficiently setup, start, and manage IVS experiments through the DockoMatic GUI by specifying receptor(s), ligand(s), grid parameter file(s), and docking engine (either AutoDock or AutoDock Vina). DockoMatic automatically generates the needed experiment input files and output directories and allows the user to manage and monitor job progress. Upon job completion, a summary of results is generated by Dockomatic to facilitate interpretation by the user. DockoMatic functionality has also been expanded to facilitate the construction of 3D protein homology models using the Timely Integrated Modeler (TIM) wizard. The wizard TIM provides an interface that accesses the basic local alignment search tool (BLAST) and MODELER programs and guides the user through the necessary steps to easily and efficiently create 3D homology models for biomacromolecular structures. The DockoMatic GUI can be customized by the user, and the software design makes it relatively easy to integrate additional docking engines, scoring functions, or third party programs. DockoMatic is a free comprehensive molecular docking software program for all levels of scientists in both research and education.
Ballester, Pedro J.; Mangold, Martina; Howard, Nigel I.; Robinson, Richard L. Marchese; Abell, Chris; Blumberger, Jochen; Mitchell, John B. O.
2012-01-01
One of the initial steps of modern drug discovery is the identification of small organic molecules able to inhibit a target macromolecule of therapeutic interest. A small proportion of these hits are further developed into lead compounds, which in turn may ultimately lead to a marketed drug. A commonly used screening protocol used for this task is high-throughput screening (HTS). However, the performance of HTS against antibacterial targets has generally been unsatisfactory, with high costs and low rates of hit identification. Here, we present a novel computational methodology that is able to identify a high proportion of structurally diverse inhibitors by searching unusually large molecular databases in a time-, cost- and resource-efficient manner. This virtual screening methodology was tested prospectively on two versions of an antibacterial target (type II dehydroquinase from Mycobacterium tuberculosis and Streptomyces coelicolor), for which HTS has not provided satisfactory results and consequently practically all known inhibitors are derivatives of the same core scaffold. Overall, our protocols identified 100 new inhibitors, with calculated Ki ranging from 4 to 250 μM (confirmed hit rates are 60% and 62% against each version of the target). Most importantly, over 50 new active molecular scaffolds were discovered that underscore the benefits that a wide application of prospectively validated in silico screening tools is likely to bring to antibacterial hit identification. PMID:22933186
Ballester, Pedro J; Mangold, Martina; Howard, Nigel I; Robinson, Richard L Marchese; Abell, Chris; Blumberger, Jochen; Mitchell, John B O
2012-12-07
One of the initial steps of modern drug discovery is the identification of small organic molecules able to inhibit a target macromolecule of therapeutic interest. A small proportion of these hits are further developed into lead compounds, which in turn may ultimately lead to a marketed drug. A commonly used screening protocol used for this task is high-throughput screening (HTS). However, the performance of HTS against antibacterial targets has generally been unsatisfactory, with high costs and low rates of hit identification. Here, we present a novel computational methodology that is able to identify a high proportion of structurally diverse inhibitors by searching unusually large molecular databases in a time-, cost- and resource-efficient manner. This virtual screening methodology was tested prospectively on two versions of an antibacterial target (type II dehydroquinase from Mycobacterium tuberculosis and Streptomyces coelicolor), for which HTS has not provided satisfactory results and consequently practically all known inhibitors are derivatives of the same core scaffold. Overall, our protocols identified 100 new inhibitors, with calculated K(i) ranging from 4 to 250 μM (confirmed hit rates are 60% and 62% against each version of the target). Most importantly, over 50 new active molecular scaffolds were discovered that underscore the benefits that a wide application of prospectively validated in silico screening tools is likely to bring to antibacterial hit identification.
Aparna, Vasudevan; Dineshkumar, Kesavan; Mohanalakshmi, Narasumani; Velmurugan, Devadasan; Hopper, Waheeta
2014-01-01
Pseudomonas aeruginosa and Escherichia coli are resistant to wide range of antibiotics rendering the treatment of infections very difficult. A main mechanism attributed to the resistance is the function of efflux pumps. MexAB-OprM and AcrAB-TolC are the tripartite efflux pump assemblies, responsible for multidrug resistance in P. aeruginosa and E. coli respectively. Substrates that are more susceptible for efflux are predicted to have a common pharmacophore feature map. In this study, a new criterion of excluding compounds with efflux substrate-like features was used, thereby refining the selection process and enriching the inhibitor identification process. An in-house database of phytochemicals was created and screened using high-throughput virtual screening against AcrB and MexB proteins and filtered by matching with the common pharmacophore models (AADHR, ADHNR, AAHNR, AADHN, AADNR, AAADN, AAADR, AAANR, AAAHN, AAADD and AAADH) generated using known efflux substrates. Phytochemical hits that matched with any one or more of the efflux substrate models were excluded from the study. Hits that do not have features similar to the efflux substrate models were docked using XP docking against the AcrB and MexB proteins. The best hits of the XP docking were validated by checkerboard synergy assay and ethidium bromide accumulation assay for their efflux inhibition potency. Lanatoside C and diadzein were filtered based on the synergistic potential and validated for their efflux inhibition potency using ethidium bromide accumulation study. These compounds exhibited the ability to increase the accumulation of ethidium bromide inside the bacterial cell as evidenced by these increase in fluorescence in the presence of the compounds. With this good correlation between in silico screening and positive efflux inhibitory activity in vitro, the two compounds, lanatoside C and diadzein could be promising efflux pump inhibitors and effective to use in combination therapy against drug resistant strains of P. aeruginosa and E. coli. PMID:25025665
Aparna, Vasudevan; Dineshkumar, Kesavan; Mohanalakshmi, Narasumani; Velmurugan, Devadasan; Hopper, Waheeta
2014-01-01
Pseudomonas aeruginosa and Escherichia coli are resistant to wide range of antibiotics rendering the treatment of infections very difficult. A main mechanism attributed to the resistance is the function of efflux pumps. MexAB-OprM and AcrAB-TolC are the tripartite efflux pump assemblies, responsible for multidrug resistance in P. aeruginosa and E. coli respectively. Substrates that are more susceptible for efflux are predicted to have a common pharmacophore feature map. In this study, a new criterion of excluding compounds with efflux substrate-like features was used, thereby refining the selection process and enriching the inhibitor identification process. An in-house database of phytochemicals was created and screened using high-throughput virtual screening against AcrB and MexB proteins and filtered by matching with the common pharmacophore models (AADHR, ADHNR, AAHNR, AADHN, AADNR, AAADN, AAADR, AAANR, AAAHN, AAADD and AAADH) generated using known efflux substrates. Phytochemical hits that matched with any one or more of the efflux substrate models were excluded from the study. Hits that do not have features similar to the efflux substrate models were docked using XP docking against the AcrB and MexB proteins. The best hits of the XP docking were validated by checkerboard synergy assay and ethidium bromide accumulation assay for their efflux inhibition potency. Lanatoside C and diadzein were filtered based on the synergistic potential and validated for their efflux inhibition potency using ethidium bromide accumulation study. These compounds exhibited the ability to increase the accumulation of ethidium bromide inside the bacterial cell as evidenced by these increase in fluorescence in the presence of the compounds. With this good correlation between in silico screening and positive efflux inhibitory activity in vitro, the two compounds, lanatoside C and diadzein could be promising efflux pump inhibitors and effective to use in combination therapy against drug resistant strains of P. aeruginosa and E. coli.
Computational discovery of picomolar Q(o) site inhibitors of cytochrome bc1 complex.
Hao, Ge-Fei; Wang, Fu; Li, Hui; Zhu, Xiao-Lei; Yang, Wen-Chao; Huang, Li-Shar; Wu, Jia-Wei; Berry, Edward A; Yang, Guang-Fu
2012-07-11
A critical challenge to the fragment-based drug discovery (FBDD) is its low-throughput nature due to the necessity of biophysical method-based fragment screening. Herein, a method of pharmacophore-linked fragment virtual screening (PFVS) was successfully developed. Its application yielded the first picomolar-range Q(o) site inhibitors of the cytochrome bc(1) complex, an important membrane protein for drug and fungicide discovery. Compared with the original hit compound 4 (K(i) = 881.80 nM, porcine bc(1)), the most potent compound 4f displayed 20 507-fold improved binding affinity (K(i) = 43.00 pM). Compound 4f was proved to be a noncompetitive inhibitor with respect to the substrate cytochrome c, but a competitive inhibitor with respect to the substrate ubiquinol. Additionally, we determined the crystal structure of compound 4e (K(i) = 83.00 pM) bound to the chicken bc(1) at 2.70 Å resolution, providing a molecular basis for understanding its ultrapotency. To our knowledge, this study is the first application of the FBDD method in the discovery of picomolar inhibitors of a membrane protein. This work demonstrates that the novel PFVS approach is a high-throughput drug discovery method, independent of biophysical screening techniques.
Developing Hypothetical Inhibition Mechanism of Novel Urea Transporter B Inhibitor
NASA Astrophysics Data System (ADS)
Li, Min; Tou, Weng Ieong; Zhou, Hong; Li, Fei; Ren, Huiwen; Chen, Calvin Yu-Chian; Yang, Baoxue
2014-07-01
Urea transporter B (UT-B) is a membrane channel protein that specifically transports urea. UT-B null mouse exhibited urea selective urine concentrating ability deficiency, which suggests the potential clinical applications of the UT-B inhibitors as novel diuretics. Primary high-throughput virtual screening (HTVS) of 50000 small-molecular drug-like compounds identified 2319 hit compounds. These 2319 compounds were screened by high-throughput screening using an erythrocyte osmotic lysis assay. Based on the pharmacological data, putative UT-B binding sites were identified by structure-based drug design and validated by ligand-based and QSAR model. Additionally, UT-B structural and functional characteristics under inhibitors treated and untreated conditions were simulated by molecular dynamics (MD). As the result, we identified four classes of compounds with UT-B inhibitory activity and predicted a human UT-B model, based on which computative binding sites were identified and validated. A novel potential mechanism of UT-B inhibitory activity was discovered by comparing UT-B from different species. Results suggest residue PHE198 in rat and mouse UT-B might block the inhibitor migration pathway. Inhibitory mechanisms of UT-B inhibitors and the functions of key residues in UT-B were proposed. The binding site analysis provides a structural basis for lead identification and optimization of UT-B inhibitors.
High-throughput screening based on label-free detection of small molecule microarrays
NASA Astrophysics Data System (ADS)
Zhu, Chenggang; Fei, Yiyan; Zhu, Xiangdong
2017-02-01
Based on small-molecule microarrays (SMMs) and oblique-incidence reflectivity difference (OI-RD) scanner, we have developed a novel high-throughput drug preliminary screening platform based on label-free monitoring of direct interactions between target proteins and immobilized small molecules. The screening platform is especially attractive for screening compounds against targets of unknown function and/or structure that are not compatible with functional assay development. In this screening platform, OI-RD scanner serves as a label-free detection instrument which is able to monitor about 15,000 biomolecular interactions in a single experiment without the need to label any biomolecule. Besides, SMMs serves as a novel format for high-throughput screening by immobilization of tens of thousands of different compounds on a single phenyl-isocyanate functionalized glass slide. Based on the high-throughput screening platform, we sequentially screened five target proteins (purified target proteins or cell lysate containing target protein) in high-throughput and label-free mode. We found hits for respective target protein and the inhibition effects for some hits were confirmed by following functional assays. Compared to traditional high-throughput screening assay, the novel high-throughput screening platform has many advantages, including minimal sample consumption, minimal distortion of interactions through label-free detection, multi-target screening analysis, which has a great potential to be a complementary screening platform in the field of drug discovery.
Boehm, Markus; Wu, Tong-Ying; Claussen, Holger; Lemmen, Christian
2008-04-24
Large collections of combinatorial libraries are an integral element in today's pharmaceutical industry. It is of great interest to perform similarity searches against all virtual compounds that are synthetically accessible by any such library. Here we describe the successful application of a new software tool CoLibri on 358 combinatorial libraries based on validated reaction protocols to create a single chemistry space containing over 10 (12) possible products. Similarity searching with FTrees-FS allows the systematic exploration of this space without the need to enumerate all product structures. The search result is a set of virtual hits which are synthetically accessible by one or more of the existing reaction protocols. Grouping these virtual hits by their synthetic protocols allows the rapid design and synthesis of multiple follow-up libraries. Such library ideas support hit-to-lead design efforts for tasks like follow-up from high-throughput screening hits or scaffold hopping from one hit to another attractive series.
Johnson, David K.; Karanicolas, John
2016-01-01
Protein-protein interactions play important roles in virtually all cellular processes, making them enticing targets for modulation by small-molecule therapeutics: specific examples have been well validated in diseases ranging from cancer and autoimmune disorders, to bacterial and viral infections. Despite several notable successes, however, overall these remain a very challenging target class. Protein interaction sites are especially challenging for computational approaches, because the target protein surface often undergoes a conformational change to enable ligand binding: this confounds traditional approaches for virtual screening. Through previous studies, we demonstrated that biased “pocket optimization” simulations could be used to build collections of low-energy pocket-containing conformations, starting from an unbound protein structure. Here, we demonstrate that these pockets can further be used to identify ligands that complement the protein surface. To do so, we first build from a given pocket its “exemplar”: a perfect, but non-physical, pseudo-ligand that would optimally match the shape and chemical features of the pocket. In our previous studies, we used these exemplars to quantitatively compare protein surface pockets to one another. Here, we now introduce this exemplar as a template for pharmacophore-based screening of chemical libraries. Through a series of benchmark experiments, we demonstrate that this approach exhibits comparable performance as traditional docking methods for identifying known inhibitors acting at protein interaction sites. However, because this approach is predicated on ligand/exemplar overlays, and thus does not require explicit calculation of protein-ligand interactions, exemplar screening provides a tremendous speed advantage over docking: 6 million compounds can be screened in about 15 minutes on a single 16-core, dual-GPU computer. The extreme speed at which large compound libraries can be traversed easily enables screening against a “pocket-optimized” ensemble of protein conformations, which in turn facilitates identification of more diverse classes of active compounds for a given protein target. PMID:26726827
DockoMatic 2.0: High Throughput Inverse Virtual Screening and Homology Modeling
Bullock, Casey; Cornia, Nic; Jacob, Reed; Remm, Andrew; Peavey, Thomas; Weekes, Ken; Mallory, Chris; Oxford, Julia T.; McDougal, Owen M.; Andersen, Timothy L.
2013-01-01
DockoMatic is a free and open source application that unifies a suite of software programs within a user-friendly Graphical User Interface (GUI) to facilitate molecular docking experiments. Here we describe the release of DockoMatic 2.0; significant software advances include the ability to: (1) conduct high throughput Inverse Virtual Screening (IVS); (2) construct 3D homology models; and (3) customize the user interface. Users can now efficiently setup, start, and manage IVS experiments through the DockoMatic GUI by specifying a receptor(s), ligand(s), grid parameter file(s), and docking engine (either AutoDock or AutoDock Vina). DockoMatic automatically generates the needed experiment input files and output directories, and allows the user to manage and monitor job progress. Upon job completion, a summary of results is generated by Dockomatic to facilitate interpretation by the user. DockoMatic functionality has also been expanded to facilitate the construction of 3D protein homology models using the Timely Integrated Modeler (TIM) wizard. The wizard TIM provides an interface that accesses the basic local alignment search tool (BLAST) and MODELLER programs, and guides the user through the necessary steps to easily and efficiently create 3D homology models for biomacromolecular structures. The DockoMatic GUI can be customized by the user, and the software design makes it relatively easy to integrate additional docking engines, scoring functions, or third party programs. DockoMatic is a free comprehensive molecular docking software program for all levels of scientists in both research and education. PMID:23808933
Pietiainen, Vilja; Saarela, Jani; von Schantz, Carina; Turunen, Laura; Ostling, Paivi; Wennerberg, Krister
2014-05-01
The High Throughput Biomedicine (HTB) unit at the Institute for Molecular Medicine Finland FIMM was established in 2010 to serve as a national and international academic screening unit providing access to state of the art instrumentation for chemical and RNAi-based high throughput screening. The initial focus of the unit was multiwell plate based chemical screening and high content microarray-based siRNA screening. However, over the first four years of operation, the unit has moved to a more flexible service platform where both chemical and siRNA screening is performed at different scales primarily in multiwell plate-based assays with a wide range of readout possibilities with a focus on ultraminiaturization to allow for affordable screening for the academic users. In addition to high throughput screening, the equipment of the unit is also used to support miniaturized, multiplexed and high throughput applications for other types of research such as genomics, sequencing and biobanking operations. Importantly, with the translational research goals at FIMM, an increasing part of the operations at the HTB unit is being focused on high throughput systems biological platforms for functional profiling of patient cells in personalized and precision medicine projects.
Application of ToxCast High-Throughput Screening and ...
Slide presentation at the SETAC annual meeting on High-Throughput Screening and Modeling Approaches to Identify Steroidogenesis Distruptors Slide presentation at the SETAC annual meeting on High-Throughput Screening and Modeling Approaches to Identify Steroidogenssis Distruptors
Chaput, Ludovic; Martinez-Sanz, Juan; Quiniou, Eric; Rigolet, Pascal; Saettel, Nicolas; Mouawad, Liliane
2016-01-01
In drug design, one may be confronted to the problem of finding hits for targets for which no small inhibiting molecules are known and only low-throughput experiments are available (like ITC or NMR studies), two common difficulties encountered in a typical academic setting. Using a virtual screening strategy like docking can alleviate some of the problems and save a considerable amount of time by selecting only top-ranking molecules, but only if the method is very efficient, i.e. when a good proportion of actives are found in the 1-10 % best ranked molecules. The use of several programs (in our study, Gold, Surflex, FlexX and Glide were considered) shows a divergence of the results, which presents a difficulty in guiding the experiments. To overcome this divergence and increase the yield of the virtual screening, we created the standard deviation consensus (SDC) and variable SDC (vSDC) methods, consisting of the intersection of molecule sets from several virtual screening programs, based on the standard deviations of their ranking distributions. SDC allowed us to find hits for two new protein targets by testing only 9 and 11 small molecules from a chemical library of circa 15,000 compounds. Furthermore, vSDC, when applied to the 102 proteins of the DUD-E benchmarking database, succeeded in finding more hits than any of the four isolated programs for 13-60 % of the targets. In addition, when only 10 molecules of each of the 102 chemical libraries were considered, vSDC performed better in the number of hits found, with an improvement of 6-24 % over the 10 best-ranked molecules given by the individual docking programs.Graphical abstractIn drug design, for a given target and a given chemical library, the results obtained with different virtual screening programs are divergent. So how to rationally guide the experimental tests, especially when only a few number of experiments can be made? The variable Standard Deviation Consensus (vSDC) method was developed to answer this issue. Left panel the vSDC principle consists of intersecting molecule sets, chosen on the basis of the standard deviations of their ranking distributions, obtained from various virtual screening programs. In this study Glide, Gold, FlexX and Surflex were used and tested on the 102 targets of the DUD-E database. Right panel Comparison of the average percentage of hits found with vSDC and each of the four programs, when only 10 molecules from each of the 102 chemical libraries of the DUD-E database were considered. On average, vSDC was capable of finding 38 % of the findable hits, against 34 % for Glide, 32 % for Gold, 16 % for FlexX and 14 % for Surflex, showing that with vSDC, it was possible to overcome the unpredictability of the virtual screening results and to improve them.
Fragment-based drug discovery and molecular docking in drug design.
Wang, Tao; Wu, Mian-Bin; Chen, Zheng-Jie; Chen, Hua; Lin, Jian-Ping; Yang, Li-Rong
2015-01-01
Fragment-based drug discovery (FBDD) has caused a revolution in the process of drug discovery and design, with many FBDD leads being developed into clinical trials or approved in the past few years. Compared with traditional high-throughput screening, it displays obvious advantages such as efficiently covering chemical space, achieving higher hit rates, and so forth. In this review, we focus on the most recent developments of FBDD for improving drug discovery, illustrating the process and the importance of FBDD. In particular, the computational strategies applied in the process of FBDD and molecular-docking programs are highlighted elaborately. In most cases, docking is used for predicting the ligand-receptor interaction modes and hit identification by structurebased virtual screening. The successful cases of typical significance and the hits identified most recently are discussed.
High Throughput Transcriptomics: From screening to pathways
The EPA ToxCast effort has screened thousands of chemicals across hundreds of high-throughput in vitro screening assays. The project is now leveraging high-throughput transcriptomic (HTTr) technologies to substantially expand its coverage of biological pathways. The first HTTr sc...
20180311 - High Throughput Transcriptomics: From screening to pathways (SOT 2018)
The EPA ToxCast effort has screened thousands of chemicals across hundreds of high-throughput in vitro screening assays. The project is now leveraging high-throughput transcriptomic (HTTr) technologies to substantially expand its coverage of biological pathways. The first HTTr sc...
Approaches to virtual screening and screening library selection.
Wildman, Scott A
2013-01-01
The ease of access to virtual screening (VS) software in recent years has resulted in a large increase in literature reports. Over 300 publications in the last year report the use of virtual screening techniques to identify new chemical matter or present the development of new virtual screening techniques. The increased use is accompanied by a corresponding increase in misuse and misinterpretation of virtual screening results. This review aims to identify many of the common difficulties associated with virtual screening and allow researchers to better assess the reliability of their virtual screening effort.
Karthikeyan, Muthukumarasamy; Pandit, Yogesh; Pandit, Deepak; Vyas, Renu
2015-01-01
Virtual screening is an indispensable tool to cope with the massive amount of data being tossed by the high throughput omics technologies. With the objective of enhancing the automation capability of virtual screening process a robust portal termed MegaMiner has been built using the cloud computing platform wherein the user submits a text query and directly accesses the proposed lead molecules along with their drug-like, lead-like and docking scores. Textual chemical structural data representation is fraught with ambiguity in the absence of a global identifier. We have used a combination of statistical models, chemical dictionary and regular expression for building a disease specific dictionary. To demonstrate the effectiveness of this approach, a case study on malaria has been carried out in the present work. MegaMiner offered superior results compared to other text mining search engines, as established by F score analysis. A single query term 'malaria' in the portlet led to retrieval of related PubMed records, protein classes, drug classes and 8000 scaffolds which were internally processed and filtered to suggest new molecules as potential anti-malarials. The results obtained were validated by docking the virtual molecules into relevant protein targets. It is hoped that MegaMiner will serve as an indispensable tool for not only identifying hidden relationships between various biological and chemical entities but also for building better corpus and ontologies.
High-throughput screening (HTS) and modeling of the retinoid ...
Presentation at the Retinoids Review 2nd workshop in Brussels, Belgium on the application of high throughput screening and model to the retinoid system Presentation at the Retinoids Review 2nd workshop in Brussels, Belgium on the application of high throughput screening and model to the retinoid system
Trainable structure-activity relationship model for virtual screening of CYP3A4 inhibition.
Didziapetris, Remigijus; Dapkunas, Justas; Sazonovas, Andrius; Japertas, Pranas
2010-11-01
A new structure-activity relationship model predicting the probability for a compound to inhibit human cytochrome P450 3A4 has been developed using data for >800 compounds from various literature sources and tested on PubChem screening data. Novel GALAS (Global, Adjusted Locally According to Similarity) modeling methodology has been used, which is a combination of baseline global QSAR model and local similarity based corrections. GALAS modeling method allows forecasting the reliability of prediction thus defining the model applicability domain. For compounds within this domain the statistical results of the final model approach the data consistency between experimental data from literature and PubChem datasets with the overall accuracy of 89%. However, the original model is applicable only for less than a half of PubChem database. Since the similarity correction procedure of GALAS modeling method allows straightforward model training, the possibility to expand the applicability domain has been investigated. Experimental data from PubChem dataset served as an example of in-house high-throughput screening data. The model successfully adapted itself to both data classified using the same and different IC₅₀ threshold compared with the training set. In addition, adjustment of the CYP3A4 inhibition model to compounds with a novel chemical scaffold has been demonstrated. The reported GALAS model is proposed as a useful tool for virtual screening of compounds for possible drug-drug interactions even prior to the actual synthesis.
NASA Astrophysics Data System (ADS)
Banavath, Hemanth Naick; Sharma, Om Prakash; Kumar, Muthuvel Suresh; Baskaran, R.
2014-11-01
BCR-ABL tyrosine kinase plays a major role in the pathogenesis of chronic myeloid leukemia (CML) and is a proven target for drug development. Currently available drugs in the market are effective against CML; however, side-effects and drug-resistant mutations in BCR-ABL limit their full potential. Using high throughput virtual screening approach, we have screened several small molecule databases and docked against wild-type and drug resistant T315I mutant BCR-ABL. Drugs that are currently available, such as imatinib and ponatinib, were also docked against BCR-ABL protein to set a cutoff value for our screening. Selected lead compounds were further evaluated for chemical reactivity employing density functional theory approach, all selected ligands shows HLG value > 0.09900 and the binding free energy between protein-ligand complex interactions obtained was rescored using MM-GBSA. The selected compounds showed least ΔG score -71.53 KJ/mol to maximum -126.71 KJ/mol in both wild type and drug resistant T315I mutant BCR-ABL. Following which, the stability of the docking complexes were evaluated by molecular dynamics simulation (MD) using GROMACS4.5.5. Results uncovered seven lead molecules, designated with Drug-Bank and PubChem ids as DB07107, DB06977, ST013616, DB04200, ST007180 ST019342, and DB01172, which shows docking scores higher than imatinib and ponatinib.
NASA Astrophysics Data System (ADS)
Tian, Zhen; Liu, Jiyuan; Zhang, Yalin
2016-03-01
Given the advantages of behavioral disruption application in pest control and the damage of Cydia pomonella, due progresses have not been made in searching active semiochemicals for codling moth. In this research, 31 candidate semiochemicals were ranked for their binding potential to Cydia pomonella pheromone binding protein 2 (CpomPBP2) by simulated docking, and this sorted result was confirmed by competitive binding assay. This high predicting accuracy of virtual screening led to the construction of a rapid and viable method for semiochemicals searching. By reference to binding mode analyses, hydrogen bond and hydrophobic interaction were suggested to be two key factors in determining ligand affinity, so is the length of molecule chain. So it is concluded that semiochemicals of appropriate chain length with hydroxyl group or carbonyl group at one head tended to be favored by CpomPBP2. Residues involved in binding with each ligand were pointed out as well, which were verified by computational alanine scanning mutagenesis. Progress made in the present study helps establish an efficient method for predicting potentially active compounds and prepares for the application of high-throughput virtual screening in searching semiochemicals by taking insights into binding mode analyses.
Tian, Zhen; Liu, Jiyuan; Zhang, Yalin
2016-01-01
Given the advantages of behavioral disruption application in pest control and the damage of Cydia pomonella, due progresses have not been made in searching active semiochemicals for codling moth. In this research, 31 candidate semiochemicals were ranked for their binding potential to Cydia pomonella pheromone binding protein 2 (CpomPBP2) by simulated docking, and this sorted result was confirmed by competitive binding assay. This high predicting accuracy of virtual screening led to the construction of a rapid and viable method for semiochemicals searching. By reference to binding mode analyses, hydrogen bond and hydrophobic interaction were suggested to be two key factors in determining ligand affinity, so is the length of molecule chain. So it is concluded that semiochemicals of appropriate chain length with hydroxyl group or carbonyl group at one head tended to be favored by CpomPBP2. Residues involved in binding with each ligand were pointed out as well, which were verified by computational alanine scanning mutagenesis. Progress made in the present study helps establish an efficient method for predicting potentially active compounds and prepares for the application of high-throughput virtual screening in searching semiochemicals by taking insights into binding mode analyses. PMID:26928635
Strategic and Operational Plan for Integrating Transcriptomics ...
Plans for incorporating high throughput transcriptomics into the current high throughput screening activities at NCCT; the details are in the attached slide presentation presentation on plans for incorporating high throughput transcriptomics into the current high throughput screening activities at NCCT, given at the OECD meeting on June 23, 2016
Mobility for GCSS-MC through virtual PCs
2017-06-01
their productivity. Mobile device access to GCSS-MC would allow Marines to access a required program for their mission using a form of computing ...network throughput applications with a device running on various operating systems with limited computational ability. The use of VPCs leads to a...reduced need for network throughput and faster overall execution. 14. SUBJECT TERMS GCSS-MC, enterprise resource planning, virtual personal computer
Dawes, Timothy D; Turincio, Rebecca; Jones, Steven W; Rodriguez, Richard A; Gadiagellan, Dhireshan; Thana, Peter; Clark, Kevin R; Gustafson, Amy E; Orren, Linda; Liimatta, Marya; Gross, Daniel P; Maurer, Till; Beresini, Maureen H
2016-02-01
Acoustic droplet ejection (ADE) as a means of transferring library compounds has had a dramatic impact on the way in which high-throughput screening campaigns are conducted in many laboratories. Two Labcyte Echo ADE liquid handlers form the core of the compound transfer operation in our 1536-well based ultra-high-throughput screening (uHTS) system. Use of these instruments has promoted flexibility in compound formatting in addition to minimizing waste and eliminating compound carryover. We describe the use of ADE for the generation of assay-ready plates for primary screening as well as for follow-up dose-response evaluations. Custom software has enabled us to harness the information generated by the ADE instrumentation. Compound transfer via ADE also contributes to the screening process outside of the uHTS system. A second fully automated ADE-based system has been used to augment the capacity of the uHTS system as well as to permit efficient use of previously picked compound aliquots for secondary assay evaluations. Essential to the utility of ADE in the high-throughput screening process is the high quality of the resulting data. Examples of data generated at various stages of high-throughput screening campaigns are provided. Advantages and disadvantages of the use of ADE in high-throughput screening are discussed. © 2015 Society for Laboratory Automation and Screening.
NASA Astrophysics Data System (ADS)
Malik, Ruchi; Bunkar, Devendra; Choudhary, Bhanwar Singh; Srivastava, Shubham; Mehta, Pakhuri; Sharma, Manish
2016-10-01
Human semen is principal vehicle for transmission of HIV-1 and other enveloped viruses. Several endogenous peptides present in semen, including a 39-amino acid fragments of prostatic acid phosphatase (PAP248-286) assemble into amyloid fibrils named as semen-derived enhancer of viral infection (SEVI) that promote virion attachment to target cells which dramatically enhance HIV virus infection by up to 105-fold. Epigallocatechin-3-gallate (EGCG), a polyphenolic compound, is the major catechin found in green tea which disaggregates existing SEVI fibers, and inhibits the formation of SEVI fibers. The aim of this study was to screen a number of relevant polyphenols to develop a rational approach for designing PAP248-286 aggregation inhibitors as potential anti-HIV agents. The molecular docking based virtual screening results showed that polyphenolic compounds 2-6 possessed good docking score and interacted well with the active site residues of PAP248-286. Amino acid residues of binding site namely; Lys255, Ser256, Leu258 and Asn265 are involved in binding of these compounds. In silico ADMET prediction studies on these hits were also found to be promising. Polyphenolic compounds 2-6 identified as hits may act as novel leads for inhibiting aggregation of PAP248-286 into SEVI.
Han, Lianyi; Wang, Yanli; Bryant, Stephen H
2008-09-25
Recent advances in high-throughput screening (HTS) techniques and readily available compound libraries generated using combinatorial chemistry or derived from natural products enable the testing of millions of compounds in a matter of days. Due to the amount of information produced by HTS assays, it is a very challenging task to mine the HTS data for potential interest in drug development research. Computational approaches for the analysis of HTS results face great challenges due to the large quantity of information and significant amounts of erroneous data produced. In this study, Decision Trees (DT) based models were developed to discriminate compound bioactivities by using their chemical structure fingerprints provided in the PubChem system http://pubchem.ncbi.nlm.nih.gov. The DT models were examined for filtering biological activity data contained in four assays deposited in the PubChem Bioassay Database including assays tested for 5HT1a agonists, antagonists, and HIV-1 RT-RNase H inhibitors. The 10-fold Cross Validation (CV) sensitivity, specificity and Matthews Correlation Coefficient (MCC) for the models are 57.2 approximately 80.5%, 97.3 approximately 99.0%, 0.4 approximately 0.5 respectively. A further evaluation was also performed for DT models built for two independent bioassays, where inhibitors for the same HIV RNase target were screened using different compound libraries, this experiment yields enrichment factor of 4.4 and 9.7. Our results suggest that the designed DT models can be used as a virtual screening technique as well as a complement to traditional approaches for hits selection.
Integration of Lead Discovery Tactics and the Evolution of the Lead Discovery Toolbox.
Leveridge, Melanie; Chung, Chun-Wa; Gross, Jeffrey W; Phelps, Christopher B; Green, Darren
2018-06-01
There has been much debate around the success rates of various screening strategies to identify starting points for drug discovery. Although high-throughput target-based and phenotypic screening has been the focus of this debate, techniques such as fragment screening, virtual screening, and DNA-encoded library screening are also increasingly reported as a source of new chemical equity. Here, we provide examples in which integration of more than one screening approach has improved the campaign outcome and discuss how strengths and weaknesses of various methods can be used to build a complementary toolbox of approaches, giving researchers the greatest probability of successfully identifying leads. Among others, we highlight case studies for receptor-interacting serine/threonine-protein kinase 1 and the bromo- and extra-terminal domain family of bromodomains. In each example, the unique insight or chemistries individual approaches provided are described, emphasizing the synergy of information obtained from the various tactics employed and the particular question each tactic was employed to answer. We conclude with a short prospective discussing how screening strategies are evolving, what this screening toolbox might look like in the future, how to maximize success through integration of multiple tactics, and scenarios that drive selection of one combination of tactics over another.
High Throughput Screening For Hazard and Risk of Environmental Contaminants
High throughput toxicity testing provides detailed mechanistic information on the concentration response of environmental contaminants in numerous potential toxicity pathways. High throughput screening (HTS) has several key advantages: (1) expense orders of magnitude less than an...
Virtual Screening with AutoDock: Theory and Practice
Cosconati, Sandro; Forli, Stefano; Perryman, Alex L.; Harris, Rodney; Goodsell, David S.; Olson, Arthur J.
2011-01-01
Importance to the field Virtual screening is a computer-based technique for identifying promising compounds to bind to a target molecule of known structure. Given the rapidly increasing number of protein and nucleic acid structures, virtual screening continues to grow as an effective method for the discovery of new inhibitors and drug molecules. Areas covered in this review We describe virtual screening methods that are available in the AutoDock suite of programs, and several of our successes in using AutoDock virtual screening in pharmaceutical lead discovery. What the reader will gain A general overview of the challenges of virtual screening is presented, along with the tools available in the AutoDock suite of programs for addressing these challenges. Take home message Virtual screening is an effective tool for the discovery of compounds for use as leads in drug discovery, and the free, open source program AutoDock is an effective tool for virtual screening. PMID:21532931
High-throughput, image-based screening of pooled genetic variant libraries
Emanuel, George; Moffitt, Jeffrey R.; Zhuang, Xiaowei
2018-01-01
Image-based, high-throughput screening of genetic perturbations will advance both biology and biotechnology. We report a high-throughput screening method that allows diverse genotypes and corresponding phenotypes to be imaged in numerous individual cells. We achieve genotyping by introducing barcoded genetic variants into cells and using massively multiplexed FISH to measure the barcodes. We demonstrated this method by screening mutants of the fluorescent protein YFAST, yielding brighter and more photostable YFAST variants. PMID:29083401
Hierarchical virtual screening approaches in small molecule drug discovery.
Kumar, Ashutosh; Zhang, Kam Y J
2015-01-01
Virtual screening has played a significant role in the discovery of small molecule inhibitors of therapeutic targets in last two decades. Various ligand and structure-based virtual screening approaches are employed to identify small molecule ligands for proteins of interest. These approaches are often combined in either hierarchical or parallel manner to take advantage of the strength and avoid the limitations associated with individual methods. Hierarchical combination of ligand and structure-based virtual screening approaches has received noteworthy success in numerous drug discovery campaigns. In hierarchical virtual screening, several filters using ligand and structure-based approaches are sequentially applied to reduce a large screening library to a number small enough for experimental testing. In this review, we focus on different hierarchical virtual screening strategies and their application in the discovery of small molecule modulators of important drug targets. Several virtual screening studies are discussed to demonstrate the successful application of hierarchical virtual screening in small molecule drug discovery. Copyright © 2014 Elsevier Inc. All rights reserved.
CrossCheck: an open-source web tool for high-throughput screen data analysis.
Najafov, Jamil; Najafov, Ayaz
2017-07-19
Modern high-throughput screening methods allow researchers to generate large datasets that potentially contain important biological information. However, oftentimes, picking relevant hits from such screens and generating testable hypotheses requires training in bioinformatics and the skills to efficiently perform database mining. There are currently no tools available to general public that allow users to cross-reference their screen datasets with published screen datasets. To this end, we developed CrossCheck, an online platform for high-throughput screen data analysis. CrossCheck is a centralized database that allows effortless comparison of the user-entered list of gene symbols with 16,231 published datasets. These datasets include published data from genome-wide RNAi and CRISPR screens, interactome proteomics and phosphoproteomics screens, cancer mutation databases, low-throughput studies of major cell signaling mediators, such as kinases, E3 ubiquitin ligases and phosphatases, and gene ontological information. Moreover, CrossCheck includes a novel database of predicted protein kinase substrates, which was developed using proteome-wide consensus motif searches. CrossCheck dramatically simplifies high-throughput screen data analysis and enables researchers to dig deep into the published literature and streamline data-driven hypothesis generation. CrossCheck is freely accessible as a web-based application at http://proteinguru.com/crosscheck.
Cheminformatics in Drug Discovery, an Industrial Perspective.
Chen, Hongming; Kogej, Thierry; Engkvist, Ola
2018-05-18
Cheminformatics has established itself as a core discipline within large scale drug discovery operations. It would be impossible to handle the amount of data generated today in a small molecule drug discovery project without persons skilled in cheminformatics. In addition, due to increased emphasis on "Big Data", machine learning and artificial intelligence, not only in the society in general, but also in drug discovery, it is expected that the cheminformatics field will be even more important in the future. Traditional areas like virtual screening, library design and high-throughput screening analysis are highlighted in this review. Applying machine learning in drug discovery is an area that has become very important. Applications of machine learning in early drug discovery has been extended from predicting ADME properties and target activity to tasks like de novo molecular design and prediction of chemical reactions. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.
Early phase drug discovery: cheminformatics and computational techniques in identifying lead series.
Duffy, Bryan C; Zhu, Lei; Decornez, Hélène; Kitchen, Douglas B
2012-09-15
Early drug discovery processes rely on hit finding procedures followed by extensive experimental confirmation in order to select high priority hit series which then undergo further scrutiny in hit-to-lead studies. The experimental cost and the risk associated with poor selection of lead series can be greatly reduced by the use of many different computational and cheminformatic techniques to sort and prioritize compounds. We describe the steps in typical hit identification and hit-to-lead programs and then describe how cheminformatic analysis assists this process. In particular, scaffold analysis, clustering and property calculations assist in the design of high-throughput screening libraries, the early analysis of hits and then organizing compounds into series for their progression from hits to leads. Additionally, these computational tools can be used in virtual screening to design hit-finding libraries and as procedures to help with early SAR exploration. Copyright © 2012 Elsevier Ltd. All rights reserved.
ToxCast Workflow: High-throughput screening assay data processing, analysis and management (SOT)
US EPA’s ToxCast program is generating data in high-throughput screening (HTS) and high-content screening (HCS) assays for thousands of environmental chemicals, for use in developing predictive toxicity models. Currently the ToxCast screening program includes over 1800 unique c...
A simple and sensitive high-throughput GFP screening in woody and herbaceous plants.
Hily, Jean-Michel; Liu, Zongrang
2009-03-01
Green fluorescent protein (GFP) has been used widely as a powerful bioluminescent reporter, but its visualization by existing methods in tissues or whole plants and its utilization for high-throughput screening remains challenging in many species. Here, we report a fluorescence image analyzer-based method for GFP detection and its utility for high-throughput screening of transformed plants. Of three detection methods tested, the Typhoon fluorescence scanner was able to detect GFP fluorescence in all Arabidopsis thaliana tissues and apple leaves, while regular fluorescence microscopy detected it only in Arabidopsis flowers and siliques but barely in the leaves of either Arabidopsis or apple. The hand-held UV illumination method failed in all tissues of both species. Additionally, the Typhoon imager was able to detect GFP fluorescence in both green and non-green tissues of Arabidopsis seedlings as well as in imbibed seeds, qualifying it as a high-throughput screening tool, which was further demonstrated by screening the seedlings of primary transformed T(0) seeds. Of the 30,000 germinating Arabidopsis seedlings screened, at least 69 GFP-positive lines were identified, accounting for an approximately 0.23% transformation efficiency. About 14,000 seedlings grown in 16 Petri plates could be screened within an hour, making the screening process significantly more efficient and robust than any other existing high-throughput screening method for transgenic plants.
Metabolomics Approach for Toxicity Screening of Volatile Substances
In 2007 the National Research Council envisioned the need for inexpensive, high throughput, cell based toxicity testing methods relevant to human health. High Throughput Screening (HTS) in vitro screening approaches have addressed these problems by using robotics. However, the ch...
Alginate Immobilization of Metabolic Enzymes (AIME) for High-Throughput Screening Assays (SOT)
Alginate Immobilization of Metabolic Enzymes (AIME) for High-Throughput Screening Assays DE DeGroot, RS Thomas, and SO SimmonsNational Center for Computational Toxicology, US EPA, Research Triangle Park, NC USAThe EPA’s ToxCast program utilizes a wide variety of high-throughput s...
Wasko, Michael J; Pellegrene, Kendy A; Madura, Jeffry D; Surratt, Christopher K
2015-01-01
Hundreds of millions of U.S. dollars are invested in the research and development of a single drug. Lead compound development is an area ripe for new design strategies. Therapeutic lead candidates have been traditionally found using high-throughput in vitro pharmacological screening, a costly method for assaying thousands of compounds. This approach has recently been augmented by virtual screening (VS), which employs computer models of the target protein to narrow the search for possible leads. A variant of VS is fragment-based drug design (FBDD), an emerging in silico lead discovery method that introduces low-molecular weight fragments, rather than intact compounds, into the binding pocket of the receptor model. These fragments serve as starting points for "growing" the lead candidate. Current efforts in virtual FBDD within central nervous system (CNS) targets are reviewed, as is a recent rule-based optimization strategy in which new molecules are generated within a 3D receptor-binding pocket using the fragment as a scaffold. This process not only places special emphasis on creating synthesizable molecules but also exposes computational questions worth addressing. Fragment-based methods provide a viable, relatively low-cost alternative for therapeutic lead discovery and optimization that can be applied to CNS targets to augment current design strategies.
Wasko, Michael J.; Pellegrene, Kendy A.; Madura, Jeffry D.; Surratt, Christopher K.
2015-01-01
Hundreds of millions of U.S. dollars are invested in the research and development of a single drug. Lead compound development is an area ripe for new design strategies. Therapeutic lead candidates have been traditionally found using high-throughput in vitro pharmacological screening, a costly method for assaying thousands of compounds. This approach has recently been augmented by virtual screening (VS), which employs computer models of the target protein to narrow the search for possible leads. A variant of VS is fragment-based drug design (FBDD), an emerging in silico lead discovery method that introduces low-molecular weight fragments, rather than intact compounds, into the binding pocket of the receptor model. These fragments serve as starting points for “growing” the lead candidate. Current efforts in virtual FBDD within central nervous system (CNS) targets are reviewed, as is a recent rule-based optimization strategy in which new molecules are generated within a 3D receptor-binding pocket using the fragment as a scaffold. This process not only places special emphasis on creating synthesizable molecules but also exposes computational questions worth addressing. Fragment-based methods provide a viable, relatively low-cost alternative for therapeutic lead discovery and optimization that can be applied to CNS targets to augment current design strategies. PMID:26441817
Molecular Docking and Drug Discovery in β-Adrenergic Receptors.
Vilar, Santiago; Sobarzo-Sanchez, Eduardo; Santana, Lourdes; Uriarte, Eugenio
2017-01-01
Evolution in computer engineering, availability of increasing amounts of data and the development of new and fast docking algorithms and software have led to improved molecular simulations with crucial applications in virtual high-throughput screening and drug discovery. Moreover, analysis of protein-ligand recognition through molecular docking has become a valuable tool in drug design. In this review, we focus on the applicability of molecular docking on a particular class of G protein-coupled receptors: the β-adrenergic receptors, which are relevant targets in clinic for the treatment of asthma and cardiovascular diseases. We describe the binding site in β-adrenergic receptors to understand key factors in ligand recognition along with the proteins activation process. Moreover, we focus on the discovery of new lead compounds that bind the receptors, on the evaluation of virtual screening using the active/ inactive binding site states, and on the structural optimization of known families of binders to improve β-adrenergic affinity. We also discussed strengths and challenges related to the applicability of molecular docking in β-adrenergic receptors. Molecular docking is a valuable technique in computational chemistry to deeply analyze ligand recognition and has led to important breakthroughs in drug discovery and design in the field of β-adrenergic receptors. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.
Use of Natural Products as Chemical Library for Drug Discovery and Network Pharmacology
Gu, Jiangyong; Gui, Yuanshen; Chen, Lirong; Yuan, Gu; Lu, Hui-Zhe; Xu, Xiaojie
2013-01-01
Background Natural products have been an important source of lead compounds for drug discovery. How to find and evaluate bioactive natural products is critical to the achievement of drug/lead discovery from natural products. Methodology We collected 19,7201 natural products structures, reported biological activities and virtual screening results. Principal component analysis was employed to explore the chemical space, and we found that there was a large portion of overlap between natural products and FDA-approved drugs in the chemical space, which indicated that natural products had large quantity of potential lead compounds. We also explored the network properties of natural product-target networks and found that polypharmacology was greatly enriched to those compounds with large degree and high betweenness centrality. In order to make up for a lack of experimental data, high throughput virtual screening was employed. All natural products were docked to 332 target proteins of FDA-approved drugs. The most potential natural products for drug discovery and their indications were predicted based on a docking score-weighted prediction model. Conclusions Analysis of molecular descriptors, distribution in chemical space and biological activities of natural products was conducted in this article. Natural products have vast chemical diversity, good drug-like properties and can interact with multiple cellular target proteins. PMID:23638153
Computational Toxicology at the US EPA | Science Inventory ...
Computational toxicology is the application of mathematical and computer models to help assess chemical hazards and risks to human health and the environment. Supported by advances in informatics, high-throughput screening (HTS) technologies, and systems biology, EPA is developing robust and flexible computational tools that can be applied to the thousands of chemicals in commerce, and contaminant mixtures found in America’s air, water, and hazardous-waste sites. The ORD Computational Toxicology Research Program (CTRP) is composed of three main elements. The largest component is the National Center for Computational Toxicology (NCCT), which was established in 2005 to coordinate research on chemical screening and prioritization, informatics, and systems modeling. The second element consists of related activities in the National Health and Environmental Effects Research Laboratory (NHEERL) and the National Exposure Research Laboratory (NERL). The third and final component consists of academic centers working on various aspects of computational toxicology and funded by the EPA Science to Achieve Results (STAR) program. Key intramural projects of the CTRP include digitizing legacy toxicity testing information toxicity reference database (ToxRefDB), predicting toxicity (ToxCast™) and exposure (ExpoCast™), and creating virtual liver (v-Liver™) and virtual embryo (v-Embryo™) systems models. The models and underlying data are being made publicly available t
An Automated High-Throughput System to Fractionate Plant Natural Products for Drug Discovery
Tu, Ying; Jeffries, Cynthia; Ruan, Hong; Nelson, Cynthia; Smithson, David; Shelat, Anang A.; Brown, Kristin M.; Li, Xing-Cong; Hester, John P.; Smillie, Troy; Khan, Ikhlas A.; Walker, Larry; Guy, Kip; Yan, Bing
2010-01-01
The development of an automated, high-throughput fractionation procedure to prepare and analyze natural product libraries for drug discovery screening is described. Natural products obtained from plant materials worldwide were extracted and first prefractionated on polyamide solid-phase extraction cartridges to remove polyphenols, followed by high-throughput automated fractionation, drying, weighing, and reformatting for screening and storage. The analysis of fractions with UPLC coupled with MS, PDA and ELSD detectors provides information that facilitates characterization of compounds in active fractions. Screening of a portion of fractions yielded multiple assay-specific hits in several high-throughput cellular screening assays. This procedure modernizes the traditional natural product fractionation paradigm by seamlessly integrating automation, informatics, and multimodal analytical interrogation capabilities. PMID:20232897
Development of CXCR4 modulators by virtual HTS of a novel amide-sulfamide compound library.
Bai, Renren; Shi, Qi; Liang, Zhongxing; Yoon, Younghyoun; Han, Yiran; Feng, Amber; Liu, Shuangping; Oum, Yoonhyeun; Yun, C Chris; Shim, Hyunsuk
2017-01-27
CXCR4 plays a crucial role in recruitment of inflammatory cells to inflammation sites at the beginning of the disease process. Modulating CXCR4 functions presents a new avenue for anti-inflammatory strategies. However, using CXCR4 antagonists for a long term usage presents potential serious side effect due to their stem cell mobilizing property. We have been developing partial CXCR4 antagonists without such property. A new computer-aided drug design program, the FRESH workflow, was used for anti-CXCR4 lead compound discovery and optimization, which coupled both compound library building and CXCR4 docking screens in one campaign. Based on the designed parent framework, 30 prioritized amide-sulfamide structures were obtained after systemic filtering and docking screening. Twelve compounds were prepared from the top-30 list. Most synthesized compounds exhibited good to excellent binding affinity to CXCR4. Compounds Ig and Im demonstrated notable in vivo suppressive activity against xylene-induced mouse ear inflammation (with 56% and 54% inhibition). Western blot analyses revealed that Ig significantly blocked CXCR4/CXCL12-mediated phosphorylation of Akt. Moreover, Ig attenuated the amount of TNF-α secreted by pathogenic E. coli-infected macrophages. More importantly, Ig had no observable cytotoxicity. Our results demonstrated that FRESH virtual high throughput screening program of targeted chemical class could successfully find potent lead compounds, and the amide-sulfamide pharmacophore was a novel and effective framework blocking CXCR4 function. Copyright © 2016 Elsevier Masson SAS. All rights reserved.
Inhibition of Retinoblastoma Protein Inactivation
2017-11-01
SUBJECT TERMS cell cycle, Retinoblastoma protein, E2F transcription factor, high throughput screen, drug discovery, x-ray crystallography 16. SECURITY...screening by x-ray crystallography . 2.0 KEYWORDS Retinoblastoma (Rb) pathway, E2F transcription factor, cancer, cell-cycle inhibition, activation...modulation, inhibition, high throughput screening, fragment-based screening, x-ray crystallography . 3.0 ACCOMPLISHMENTS Summary: We
Computational Modeling and Simulation of Developmental ...
SYNOPSIS: The question of how tissues and organs are shaped during development is crucial for understanding human birth defects. Data from high-throughput screening assays on human stem cells may be utilized predict developmental toxicity with reasonable accuracy. Other types of models are necessary, however, for mechanism-specific analysis because embryogenesis requires precise timing and control. Agent-based modeling and simulation (ABMS) is an approach to virtually reconstruct these dynamics, cell-by-cell and interaction-by-interaction. Using ABMS, HTS lesions from ToxCast can be integrated with patterning systems heuristically to propagate key events This presentation to FDA-CFSAN will update progress on the applications of in silico modeling tools and approaches for assessing developmental toxicity.
Huang, Kuo-Sen; Mark, David; Gandenberger, Frank Ulrich
2006-01-01
The plate::vision is a high-throughput multimode reader capable of reading absorbance, fluorescence, fluorescence polarization, time-resolved fluorescence, and luminescence. Its performance has been shown to be quite comparable with other readers. When the reader is integrated into the plate::explorer, an ultrahigh-throughput screening system with event-driven software and parallel plate-handling devices, it becomes possible to run complicated assays with kinetic readouts in high-density microtiter plate formats for high-throughput screening. For the past 5 years, we have used the plate::vision and the plate::explorer to run screens and have generated more than 30 million data points. Their throughput, performance, and robustness have speeded up our drug discovery process greatly.
Lessons from high-throughput protein crystallization screening: 10 years of practical experience
JR, Luft; EH, Snell; GT, DeTitta
2011-01-01
Introduction X-ray crystallography provides the majority of our structural biological knowledge at a molecular level and in terms of pharmaceutical design is a valuable tool to accelerate discovery. It is the premier technique in the field, but its usefulness is significantly limited by the need to grow well-diffracting crystals. It is for this reason that high-throughput crystallization has become a key technology that has matured over the past 10 years through the field of structural genomics. Areas covered The authors describe their experiences in high-throughput crystallization screening in the context of structural genomics and the general biomedical community. They focus on the lessons learnt from the operation of a high-throughput crystallization screening laboratory, which to date has screened over 12,500 biological macromolecules. They also describe the approaches taken to maximize the success while minimizing the effort. Through this, the authors hope that the reader will gain an insight into the efficient design of a laboratory and protocols to accomplish high-throughput crystallization on a single-, multiuser-laboratory or industrial scale. Expert Opinion High-throughput crystallization screening is readily available but, despite the power of the crystallographic technique, getting crystals is still not a solved problem. High-throughput approaches can help when used skillfully; however, they still require human input in the detailed analysis and interpretation of results to be more successful. PMID:22646073
Genome-wide RNAi Screening to Identify Host Factors That Modulate Oncolytic Virus Therapy.
Allan, Kristina J; Mahoney, Douglas J; Baird, Stephen D; Lefebvre, Charles A; Stojdl, David F
2018-04-03
High-throughput genome-wide RNAi (RNA interference) screening technology has been widely used for discovering host factors that impact virus replication. Here we present the application of this technology to uncovering host targets that specifically modulate the replication of Maraba virus, an oncolytic rhabdovirus, and vaccinia virus with the goal of enhancing therapy. While the protocol has been tested for use with oncolytic Maraba virus and oncolytic vaccinia virus, this approach is applicable to other oncolytic viruses and can also be utilized for identifying host targets that modulate virus replication in mammalian cells in general. This protocol describes the development and validation of an assay for high-throughput RNAi screening in mammalian cells, the key considerations and preparation steps important for conducting a primary high-throughput RNAi screen, and a step-by-step guide for conducting a primary high-throughput RNAi screen; in addition, it broadly outlines the methods for conducting secondary screen validation and tertiary validation studies. The benefit of high-throughput RNAi screening is that it allows one to catalogue, in an extensive and unbiased fashion, host factors that modulate any aspect of virus replication for which one can develop an in vitro assay such as infectivity, burst size, and cytotoxicity. It has the power to uncover biotherapeutic targets unforeseen based on current knowledge.
Dockres: a computer program that analyzes the output of virtual screening of small molecules
2010-01-01
Background This paper describes a computer program named Dockres that is designed to analyze and summarize results of virtual screening of small molecules. The program is supplemented with utilities that support the screening process. Foremost among these utilities are scripts that run the virtual screening of a chemical library on a large number of processors in parallel. Methods Dockres and some of its supporting utilities are written Fortran-77; other utilities are written as C-shell scripts. They support the parallel execution of the screening. The current implementation of the program handles virtual screening with Autodock-3 and Autodock-4, but can be extended to work with the output of other programs. Results Analysis of virtual screening by Dockres led to both active and selective lead compounds. Conclusions Analysis of virtual screening was facilitated and enhanced by Dockres in both the authors' laboratories as well as laboratories elsewhere. PMID:20205801
Microfluidics for cell-based high throughput screening platforms - A review.
Du, Guansheng; Fang, Qun; den Toonder, Jaap M J
2016-01-15
In the last decades, the basic techniques of microfluidics for the study of cells such as cell culture, cell separation, and cell lysis, have been well developed. Based on cell handling techniques, microfluidics has been widely applied in the field of PCR (Polymerase Chain Reaction), immunoassays, organ-on-chip, stem cell research, and analysis and identification of circulating tumor cells. As a major step in drug discovery, high-throughput screening allows rapid analysis of thousands of chemical, biochemical, genetic or pharmacological tests in parallel. In this review, we summarize the application of microfluidics in cell-based high throughput screening. The screening methods mentioned in this paper include approaches using the perfusion flow mode, the droplet mode, and the microarray mode. We also discuss the future development of microfluidic based high throughput screening platform for drug discovery. Copyright © 2015 Elsevier B.V. All rights reserved.
Development and Validation of an Automated High-Throughput System for Zebrafish In Vivo Screenings
Virto, Juan M.; Holgado, Olaia; Diez, Maria; Izpisua Belmonte, Juan Carlos; Callol-Massot, Carles
2012-01-01
The zebrafish is a vertebrate model compatible with the paradigms of drug discovery. The small size and transparency of zebrafish embryos make them amenable for the automation necessary in high-throughput screenings. We have developed an automated high-throughput platform for in vivo chemical screenings on zebrafish embryos that includes automated methods for embryo dispensation, compound delivery, incubation, imaging and analysis of the results. At present, two different assays to detect cardiotoxic compounds and angiogenesis inhibitors can be automatically run in the platform, showing the versatility of the system. A validation of these two assays with known positive and negative compounds, as well as a screening for the detection of unknown anti-angiogenic compounds, have been successfully carried out in the system developed. We present a totally automated platform that allows for high-throughput screenings in a vertebrate organism. PMID:22615792
In Vitro Toxicity Screening Technique for Volatile Substances Using Flow-Through System#
In 2007 the National Research Council envisioned the need for inexpensive, high throughput, cell based toxicity testing methods relevant to human health. High Throughput Screening (HTS) in vitro screening approaches have addressed these problems by using robotics. However the cha...
Inhibition of Retinoblastoma Protein Inactivation
2016-09-01
Retinoblastoma protein, E2F transcription factor, high throughput screen, drug discovery, x-ray crystallography 16. SECURITY CLASSIFICATION OF: 17...developed a method to perform fragment based screening by x-ray crystallography . 2.0 KEYWORDS Retinoblastoma (Rb) pathway, E2F transcription factor...cancer, cell-cycle inhibition, activation, modulation, inhibition, high throughput screening, fragment-based screening, x-ray crystallography
Vizeacoumar, Franco J.; van Dyk, Nydia; S.Vizeacoumar, Frederick; Cheung, Vincent; Li, Jingjing; Sydorskyy, Yaroslav; Case, Nicolle; Li, Zhijian; Datti, Alessandro; Nislow, Corey; Raught, Brian; Zhang, Zhaolei; Frey, Brendan; Bloom, Kerry
2010-01-01
We describe the application of a novel screening approach that combines automated yeast genetics, synthetic genetic array (SGA) analysis, and a high-content screening (HCS) system to examine mitotic spindle morphogenesis. We measured numerous spindle and cellular morphological parameters in thousands of single mutants and corresponding sensitized double mutants lacking genes known to be involved in spindle function. We focused on a subset of genes that appear to define a highly conserved mitotic spindle disassembly pathway, which is known to involve Ipl1p, the yeast aurora B kinase, as well as the cell cycle regulatory networks mitotic exit network (MEN) and fourteen early anaphase release (FEAR). We also dissected the function of the kinetochore protein Mcm21p, showing that sumoylation of Mcm21p regulates the enrichment of Ipl1p and other chromosomal passenger proteins to the spindle midzone to mediate spindle disassembly. Although we focused on spindle disassembly in a proof-of-principle study, our integrated HCS-SGA method can be applied to virtually any pathway, making it a powerful means for identifying specific cellular functions. PMID:20065090
Droplet microfluidic technology for single-cell high-throughput screening.
Brouzes, Eric; Medkova, Martina; Savenelli, Neal; Marran, Dave; Twardowski, Mariusz; Hutchison, J Brian; Rothberg, Jonathan M; Link, Darren R; Perrimon, Norbert; Samuels, Michael L
2009-08-25
We present a droplet-based microfluidic technology that enables high-throughput screening of single mammalian cells. This integrated platform allows for the encapsulation of single cells and reagents in independent aqueous microdroplets (1 pL to 10 nL volumes) dispersed in an immiscible carrier oil and enables the digital manipulation of these reactors at a very high-throughput. Here, we validate a full droplet screening workflow by conducting a droplet-based cytotoxicity screen. To perform this screen, we first developed a droplet viability assay that permits the quantitative scoring of cell viability and growth within intact droplets. Next, we demonstrated the high viability of encapsulated human monocytic U937 cells over a period of 4 days. Finally, we developed an optically-coded droplet library enabling the identification of the droplets composition during the assay read-out. Using the integrated droplet technology, we screened a drug library for its cytotoxic effect against U937 cells. Taken together our droplet microfluidic platform is modular, robust, uses no moving parts, and has a wide range of potential applications including high-throughput single-cell analyses, combinatorial screening, and facilitating small sample analyses.
The University of New Mexico Center for Molecular Discovery
Edwards, Bruce S.; Gouveia, Kristine; Oprea, Tudor I.; Sklar, Larry A.
2015-01-01
The University of New Mexico Center for Molecular Discovery (UNMCMD) is an academic research center that specializes in discovery using high throughput flow cytometry (HTFC) integrated with virtual screening, as well as knowledge mining and drug informatics. With a primary focus on identifying small molecules that can be used as chemical probes and as leads for drug discovery, it is a central core resource for research and translational activities at UNM that supports implementation and management of funded screening projects as well as “up-front” services such as consulting for project design and implementation, assistance in assay development and generation of preliminary data for pilot projects in support of competitive grant applications. The HTFC platform in current use represents advanced, proprietary technology developed at UNM that is now routinely capable of processing bioassays arrayed in 96-, 384- and 1536-well formats at throughputs of 60,000 or more wells per day. Key programs at UNMCMD include screening of research targets submitted by the international community through NIH’s Molecular Libraries Program; a multi-year effort involving translational partnerships at UNM directed towards drug repurposing - identifying new uses for clinically approved drugs; and a recently established personalized medicine initiative for advancing cancer therapy by the application of “smart” oncology drugs in selected patients based on response patterns of their cancer cells in vitro. UNMCMD discoveries, innovation, and translation have contributed to a wealth of inventions, patents, licenses and publications, as well as startup companies, clinical trials and a multiplicity of domestic and international collaborative partnerships to further the research enterprise. PMID:24409953
The University of New Mexico Center for Molecular Discovery.
Edwards, Bruce S; Gouveia, Kristine; Oprea, Tudor I; Sklar, Larry A
2014-03-01
The University of New Mexico Center for Molecular Discovery (UNMCMD) is an academic research center that specializes in discovery using high throughput flow cytometry (HTFC) integrated with virtual screening, as well as knowledge mining and drug informatics. With a primary focus on identifying small molecules that can be used as chemical probes and as leads for drug discovery, it is a central core resource for research and translational activities at UNM that supports implementation and management of funded screening projects as well as "up-front" services such as consulting for project design and implementation, assistance in assay development and generation of preliminary data for pilot projects in support of competitive grant applications. The HTFC platform in current use represents advanced, proprietary technology developed at UNM that is now routinely capable of processing bioassays arrayed in 96-, 384- and 1536-well formats at throughputs of 60,000 or more wells per day. Key programs at UNMCMD include screening of research targets submitted by the international community through NIH's Molecular Libraries Program; a multi-year effort involving translational partnerships at UNM directed towards drug repurposing - identifying new uses for clinically approved drugs; and a recently established personalized medicine initiative for advancing cancer therapy by the application of "smart" oncology drugs in selected patients based on response patterns of their cancer cells in vitro. UNMCMD discoveries, innovation, and translation have contributed to a wealth of inventions, patents, licenses and publications, as well as startup companies, clinical trials and a multiplicity of domestic and international collaborative partnerships to further the research enterprise.
Discovery of novel inhibitors for DHODH via virtual screening and X-ray crystallographic structures
DOE Office of Scientific and Technical Information (OSTI.GOV)
McLean, Larry R.; Zhang, Ying; Degnen, William
2010-10-28
Amino-benzoic acid derivatives 1-4 were found to be inhibitors for DHODH by virtual screening, biochemical, and X-ray crystallographic studies. X-ray structures showed that 1 and 2 bind to DHODH as predicted by virtual screening, but 3 and 4 were found to be structurally different from the corresponding compounds initially identified by virtual screening.
Meirson, Tomer; Samson, Abraham O; Gil-Henn, Hava
2017-01-01
The non-receptor tyrosine kinase proline-rich tyrosine kinase 2 (Pyk2) is a critical mediator of signaling from cell surface growth factor and adhesion receptors to cell migration, proliferation, and survival. Emerging evidence indicates that signaling by Pyk2 regulates hematopoietic cell response, bone density, neuronal degeneration, angiogenesis, and cancer. These physiological and pathological roles of Pyk2 warrant it as a valuable therapeutic target for invasive cancers, osteoporosis, Alzheimer’s disease, and inflammatory cellular response. Despite its potential as a therapeutic target, no potent and selective inhibitor of Pyk2 is available at present. As a first step toward discovering specific potential inhibitors of Pyk2, we used an in silico high-throughput screening approach. A virtual library of six million lead-like compounds was docked against four different high-resolution Pyk2 kinase domain crystal structures and further selected for predicted potency and ligand efficiency. Ligand selectivity for Pyk2 over focal adhesion kinase (FAK) was evaluated by comparative docking of ligands and measurement of binding free energy so as to obtain 40 potential candidates. Finally, the structural flexibility of a subset of the docking complexes was evaluated by molecular dynamics simulation, followed by intermolecular interaction analysis. These compounds may be considered as promising leads for further development of highly selective Pyk2 inhibitors. PMID:28572720
NASA Astrophysics Data System (ADS)
Afzal, Mohammad Atif Faiz; Cheng, Chong; Hachmann, Johannes
Organic materials with refractive index (RI) values higher than 1.7 have attracted considerable interest in recent years due to the tremendous potential for their application in optical, optometric, and optoelectronic devices, and thus for shaping technological innovation in numerous related areas. Our work is concerned with creating predictive models for the optical properties of organic polymers, which will guide our experimentalist partners and allow them to target the most promising candidates. The RI model is developed based on a synergistic combination of first-principles electronic structure theory and machine learning techniques. The RI values predicted for common polymers using this model are in very good agreement with the experimental values. We also benchmark different DFT approximations along with various basis sets for their predictive performance in this model. We demonstrate that this combination of first-principles and data modeling is both successful and highly economical in determining the RI values of a wide range of organic polymers. To accelerate the development process, we cast this modeling approach into the high-throughput screening, materials informatics, and rational design framework that is developed in the group. This framework is a powerful tool and has shown to be highly promising for rapidly identifying polymer candidates with exceptional RI values as well as discovering design rules for advanced materials.
High-throughput screening (HTS) for potential thyroid–disrupting chemicals requires a system of assays to capture multiple molecular-initiating events (MIEs) that converge on perturbed thyroid hormone (TH) homeostasis. Screening for MIEs specific to TH-disrupting pathways is limi...
The toxicity-testing paradigm has evolved to include high-throughput (HT) methods for addressing the increasing need to screen hundreds to thousands of chemicals rapidly. Approaches that involve in vitro screening assays, in silico predictions of exposure concentrations, and phar...
Bruno, Andrew E.; Ruby, Amanda M.; Luft, Joseph R.; Grant, Thomas D.; Seetharaman, Jayaraman; Montelione, Gaetano T.; Hunt, John F.; Snell, Edward H.
2014-01-01
Many bioscience fields employ high-throughput methods to screen multiple biochemical conditions. The analysis of these becomes tedious without a degree of automation. Crystallization, a rate limiting step in biological X-ray crystallography, is one of these fields. Screening of multiple potential crystallization conditions (cocktails) is the most effective method of probing a proteins phase diagram and guiding crystallization but the interpretation of results can be time-consuming. To aid this empirical approach a cocktail distance coefficient was developed to quantitatively compare macromolecule crystallization conditions and outcome. These coefficients were evaluated against an existing similarity metric developed for crystallization, the C6 metric, using both virtual crystallization screens and by comparison of two related 1,536-cocktail high-throughput crystallization screens. Hierarchical clustering was employed to visualize one of these screens and the crystallization results from an exopolyphosphatase-related protein from Bacteroides fragilis, (BfR192) overlaid on this clustering. This demonstrated a strong correlation between certain chemically related clusters and crystal lead conditions. While this analysis was not used to guide the initial crystallization optimization, it led to the re-evaluation of unexplained peaks in the electron density map of the protein and to the insertion and correct placement of sodium, potassium and phosphate atoms in the structure. With these in place, the resulting structure of the putative active site demonstrated features consistent with active sites of other phosphatases which are involved in binding the phosphoryl moieties of nucleotide triphosphates. The new distance coefficient, CDcoeff, appears to be robust in this application, and coupled with hierarchical clustering and the overlay of crystallization outcome, reveals information of biological relevance. While tested with a single example the potential applications related to crystallography appear promising and the distance coefficient, clustering, and hierarchal visualization of results undoubtedly have applications in wider fields. PMID:24971458
NASA Astrophysics Data System (ADS)
Gómez-Bombarelli, Rafael; Aguilera-Iparraguirre, Jorge; Hirzel, Timothy D.; Ha, Dong-Gwang; Einzinger, Markus; Wu, Tony; Baldo, Marc A.; Aspuru-Guzik, Alán.
2016-09-01
Discovering new OLED emitters requires many experiments to synthesize candidates and test performance in devices. Large scale computer simulation can greatly speed this search process but the problem remains challenging enough that brute force application of massive computing power is not enough to successfully identify novel structures. We report a successful High Throughput Virtual Screening study that leveraged a range of methods to optimize the search process. The generation of candidate structures was constrained to contain combinatorial explosion. Simulations were tuned to the specific problem and calibrated with experimental results. Experimentalists and theorists actively collaborated such that experimental feedback was regularly utilized to update and shape the computational search. Supervised machine learning methods prioritized candidate structures prior to quantum chemistry simulation to prevent wasting compute on likely poor performers. With this combination of techniques, each multiplying the strength of the search, this effort managed to navigate an area of molecular space and identify hundreds of promising OLED candidate structures. An experimentally validated selection of this set shows emitters with external quantum efficiencies as high as 22%.
Little is known about the developmental toxicity of the expansive chemical landscape in existence today. Significant efforts are being made to apply novel methods to predict developmental activity of chemicals utilizing high-throughput screening (HTS) and high-content screening (...
Using uncertainty quantification, we aim to improve the quality of modeling data from high throughput screening assays for use in risk assessment. ToxCast is a large-scale screening program that analyzes thousands of chemicals using over 800 assays representing hundreds of bioche...
The U.S. EPA’s Endocrine Disruptor Screening Program (EDSP) and Office of Research and Development (ORD) are currently developing high throughput assays to screen chemicals that may alter the thyroid hormone pathway. One potential target in this pathway is the sodium iodide...
The U.S. EPA’s Endocrine Disruptor Screening Program (EDSP) and Office of Research and Development (ORD) are currently developing high throughput assays to screen chemicals that may alter the thyroid hormone pathway. One potential target in this pathway is the sodium iodide sympo...
Zhu, Shiyou; Li, Wei; Liu, Jingze; Chen, Chen-Hao; Liao, Qi; Xu, Ping; Xu, Han; Xiao, Tengfei; Cao, Zhongzheng; Peng, Jingyu; Yuan, Pengfei; Brown, Myles; Liu, Xiaole Shirley; Wei, Wensheng
2017-01-01
CRISPR/Cas9 screens have been widely adopted to analyse coding gene functions, but high throughput screening of non-coding elements using this method is more challenging, because indels caused by a single cut in non-coding regions are unlikely to produce a functional knockout. A high-throughput method to produce deletions of non-coding DNA is needed. Herein, we report a high throughput genomic deletion strategy to screen for functional long non-coding RNAs (lncRNAs) that is based on a lentiviral paired-guide RNA (pgRNA) library. Applying our screening method, we identified 51 lncRNAs that can positively or negatively regulate human cancer cell growth. We individually validated 9 lncRNAs using CRISPR/Cas9-mediated genomic deletion and functional rescue, CRISPR activation or inhibition, and gene expression profiling. Our high-throughput pgRNA genome deletion method should enable rapid identification of functional mammalian non-coding elements. PMID:27798563
Investigation of MM-PBSA rescoring of docking poses.
Thompson, David C; Humblet, Christine; Joseph-McCarthy, Diane
2008-05-01
Target-based virtual screening is increasingly used to generate leads for targets for which high quality three-dimensional (3D) structures are available. To allow large molecular databases to be screened rapidly, a tiered scoring scheme is often employed whereby a simple scoring function is used as a fast filter of the entire database and a more rigorous and time-consuming scoring function is used to rescore the top hits to produce the final list of ranked compounds. Molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) approaches are currently thought to be quite effective at incorporating implicit solvation into the estimation of ligand binding free energies. In this paper, the ability of a high-throughput MM-PBSA rescoring function to discriminate between correct and incorrect docking poses is investigated in detail. Various initial scoring functions are used to generate docked poses for a subset of the CCDC/Astex test set and to dock one set of actives/inactives from the DUD data set. The effectiveness of each of these initial scoring functions is discussed. Overall, the ability of the MM-PBSA rescoring function to (i) regenerate the set of X-ray complexes when docking the bound conformation of the ligand, (ii) regenerate the X-ray complexes when docking conformationally expanded databases for each ligand which include "conformation decoys" of the ligand, and (iii) enrich known actives in a virtual screen for the mineralocorticoid receptor in the presence of "ligand decoys" is assessed. While a pharmacophore-based molecular docking approach, PhDock, is used to carry out the docking, the results are expected to be general to use with any docking method.
Induced pluripotent stem cells for regenerative cardiovascular therapies and biomedical discovery.
Nsair, Ali; MacLellan, W Robb
2011-04-30
The discovery of induced pluripotent stem cells (iPSC) has, in the short time since their discovery, revolutionized the field of stem cell biology. This technology allows the generation of a virtually unlimited supply of cells with pluripotent potential similar to that of embryonic stem cells (ESC). However, in contrast to ESC, iPSC are not subject to the same ethical concerns and can be easily generated from living individuals. For the first time, patient-specific iPSC can be generated and offer a supply of genetically identical cells that can be differentiated into all somatic cell types for potential use in regenerative therapies or drug screening and testing. As the techniques for generation of iPSC lines are constantly evolving, new uses for human iPSC are emerging from in-vitro disease modeling to high throughput drug discovery and screening. This technology promises to revolutionize the field of medicine and offers new hope for understanding and treatment of numerous diseases. Copyright © 2011 Elsevier B.V. All rights reserved.
Gozalbes, Rafael; Carbajo, Rodrigo J; Pineda-Lucena, Antonio
2010-01-01
In the last decade, fragment-based drug discovery (FBDD) has evolved from a novel approach in the search of new hits to a valuable alternative to the high-throughput screening (HTS) campaigns of many pharmaceutical companies. The increasing relevance of FBDD in the drug discovery universe has been concomitant with an implementation of the biophysical techniques used for the detection of weak inhibitors, e.g. NMR, X-ray crystallography or surface plasmon resonance (SPR). At the same time, computational approaches have also been progressively incorporated into the FBDD process and nowadays several computational tools are available. These stretch from the filtering of huge chemical databases in order to build fragment-focused libraries comprising compounds with adequate physicochemical properties, to more evolved models based on different in silico methods such as docking, pharmacophore modelling, QSAR and virtual screening. In this paper we will review the parallel evolution and complementarities of biophysical techniques and computational methods, providing some representative examples of drug discovery success stories by using FBDD.
Enabling Large-Scale Design, Synthesis and Validation of Small Molecule Protein-Protein Antagonists
Koes, David; Khoury, Kareem; Huang, Yijun; Wang, Wei; Bista, Michal; Popowicz, Grzegorz M.; Wolf, Siglinde; Holak, Tad A.; Dömling, Alexander; Camacho, Carlos J.
2012-01-01
Although there is no shortage of potential drug targets, there are only a handful known low-molecular-weight inhibitors of protein-protein interactions (PPIs). One problem is that current efforts are dominated by low-yield high-throughput screening, whose rigid framework is not suitable for the diverse chemotypes present in PPIs. Here, we developed a novel pharmacophore-based interactive screening technology that builds on the role anchor residues, or deeply buried hot spots, have in PPIs, and redesigns these entry points with anchor-biased virtual multicomponent reactions, delivering tens of millions of readily synthesizable novel compounds. Application of this approach to the MDM2/p53 cancer target led to high hit rates, resulting in a large and diverse set of confirmed inhibitors, and co-crystal structures validate the designed compounds. Our unique open-access technology promises to expand chemical space and the exploration of the human interactome by leveraging in-house small-scale assays and user-friendly chemistry to rationally design ligands for PPIs with known structure. PMID:22427896
Knowledge-driven lead discovery.
Pirard, Bernard
2005-11-01
Virtual screening encompasses several computational approaches which have proven valuable for identifying novel leads. These approaches rely on available information. Herein, we review recent successful applications of virtual screening. The extension of virtual screening methodologies to target families is also briefly discussed.
Saxena, Shalini; Abdullah, Maaged; Sriram, Dharmarajan; Guruprasad, Lalitha
2017-10-17
MurG (Rv2153c) is a key player in the biosynthesis of the peptidoglycan layer in Mycobacterium tuberculosis (Mtb). This work is an attempt to highlight the structural and functional relationship of Mtb MurG, the three-dimensional (3D) structure of protein was constructed by homology modelling using Discovery Studio 3.5 software. The quality and consistency of generated model was assessed by PROCHECK, ProSA and ERRAT. Later, the model was optimized by molecular dynamics (MD) simulations and the optimized model complex with substrate Uridine-diphosphate-N-acetylglucosamine (UD1) facilitated us to employ structure-based virtual screening approach to obtain new hits from Asinex database using energy-optimized pharmacophore modelling (e-pharmacophore). The pharmacophore model was validated using enrichment calculations, and finally, validated model was employed for high-throughput virtual screening and molecular docking to identify novel Mtb MurG inhibitors. This study led to the identification of 10 potential compounds with good fitness, docking score, which make important interactions with the protein active site. The 25 ns MD simulations of three potential lead compounds with protein confirmed that the structure was stable and make several non-bonding interactions with amino acids, such as Leu290, Met310 and Asn167. Hence, we concluded that the identified compounds may act as new leads for the design of Mtb MurG inhibitors.
NASA Astrophysics Data System (ADS)
Chen, Xing-Ru; Wang, Xiao-Ting; Hao, Mei-Qi; Zhou, Yong-Hui; Cui, Wen-Qiang; Xing, Xiao-Xu; Xu, Chang-Geng; Bai, Jing-Wen; Li, Yan-Hua
2017-11-01
The imidazole glycerophosphate dehydratase (IGPD) protein is a therapeutic target for herbicide discovery. It is also regarded as a possible target in Staphylococcus xylosus (S. xylosus) for solving mastitis in the dairy cow. The 3D structure of IGPD protein is essential for discovering novel inhibitors during high-throughput virtual screening. However, to date, the 3D structure of IGPD protein of S. xylosus has not been solved. In this study, a series of computational techniques including homology modeling, Ramachandran Plots, and Verify 3D were performed in order to construct an appropriate 3D model of IGPD protein of S. xylosus. Nine hits were identified from 2500 compounds by docking studies. Then, these 9 compounds were first tested in vitro in S. xylosus biofilm formation using crystal violet staining. One of the potential compounds, baicalin was shown to significantly inhibit S. xylosus biofilm formation. Finally, the baicalin was further evaluated, which showed better inhibition of biofilm formation capability in S. xylosus by scanning electron microscopy. Hence, we have predicted the structure of IGPD protein of S. xylosus using computational techniques. We further discovered the IGPD protein was targeted by baicalin compound which inhibited the biofilm formation in S. xylosus. Our findings here would provide implications for the further development of novel IGPD inhibitors for the treatment of dairy mastitis.
Chen, Xing-Ru; Wang, Xiao-Ting; Hao, Mei-Qi; Zhou, Yong-Hui; Cui, Wen-Qiang; Xing, Xiao-Xu; Xu, Chang-Geng; Bai, Jing-Wen; Li, Yan-Hua
2017-01-01
The imidazole glycerophosphate dehydratase (IGPD) protein is a therapeutic target for herbicide discovery. It is also regarded as a possible target in Staphylococcus xylosus ( S. xylosus ) for solving mastitis in the dairy cow. The 3D structure of IGPD protein is essential for discovering novel inhibitors during high-throughput virtual screening. However, to date, the 3D structure of IGPD protein of S. xylosus has not been solved. In this study, a series of computational techniques including homology modeling, Ramachandran Plots, and Verify 3D were performed in order to construct an appropriate 3D model of IGPD protein of S. xylosus . Nine hits were identified from 2,500 compounds by docking studies. Then, these nine compounds were first tested in vitro in S. xylosus biofilm formation using crystal violet staining. One of the potential compounds, baicalin was shown to significantly inhibit S. xylosus biofilm formation. Finally, the baicalin was further evaluated, which showed better inhibition of biofilm formation capability in S. xylosus by scanning electron microscopy. Hence, we have predicted the structure of IGPD protein of S. xylosus using computational techniques. We further discovered the IGPD protein was targeted by baicalin compound which inhibited the biofilm formation in S. xylosus . Our findings here would provide implications for the further development of novel IGPD inhibitors for the treatment of dairy mastitis.
High speed all optical networks
NASA Technical Reports Server (NTRS)
Chlamtac, Imrich; Ganz, Aura
1990-01-01
An inherent problem of conventional point-to-point wide area network (WAN) architectures is that they cannot translate optical transmission bandwidth into comparable user available throughput due to the limiting electronic processing speed of the switching nodes. The first solution to wavelength division multiplexing (WDM) based WAN networks that overcomes this limitation is presented. The proposed Lightnet architecture takes into account the idiosyncrasies of WDM switching/transmission leading to an efficient and pragmatic solution. The Lightnet architecture trades the ample WDM bandwidth for a reduction in the number of processing stages and a simplification of each switching stage, leading to drastically increased effective network throughputs. The principle of the Lightnet architecture is the construction and use of virtual topology networks, embedded in the original network in the wavelength domain. For this construction Lightnets utilize the new concept of lightpaths which constitute the links of the virtual topology. Lightpaths are all-optical, multihop, paths in the network that allow data to be switched through intermediate nodes using high throughput passive optical switches. The use of the virtual topologies and the associated switching design introduce a number of new ideas, which are discussed in detail.
Yoshii, Yukie; Furukawa, Takako; Waki, Atsuo; Okuyama, Hiroaki; Inoue, Masahiro; Itoh, Manabu; Zhang, Ming-Rong; Wakizaka, Hidekatsu; Sogawa, Chizuru; Kiyono, Yasushi; Yoshii, Hiroshi; Fujibayashi, Yasuhisa; Saga, Tsuneo
2015-05-01
Anti-cancer drug development typically utilizes high-throughput screening with two-dimensional (2D) cell culture. However, 2D culture induces cellular characteristics different from tumors in vivo, resulting in inefficient drug development. Here, we report an innovative high-throughput screening system using nanoimprinting 3D culture to simulate in vivo conditions, thereby facilitating efficient drug development. We demonstrated that cell line-based nanoimprinting 3D screening can more efficiently select drugs that effectively inhibit cancer growth in vivo as compared to 2D culture. Metabolic responses after treatment were assessed using positron emission tomography (PET) probes, and revealed similar characteristics between the 3D spheroids and in vivo tumors. Further, we developed an advanced method to adopt cancer cells from patient tumor tissues for high-throughput drug screening with nanoimprinting 3D culture, which we termed Cancer tissue-Originated Uniformed Spheroid Assay (COUSA). This system identified drugs that were effective in xenografts of the original patient tumors. Nanoimprinting 3D spheroids showed low permeability and formation of hypoxic regions inside, similar to in vivo tumors. Collectively, the nanoimprinting 3D culture provides easy-handling high-throughput drug screening system, which allows for efficient drug development by mimicking the tumor environment. The COUSA system could be a useful platform for drug development with patient cancer cells. Copyright © 2015 Elsevier Ltd. All rights reserved.
Wicht, Kathryn J; Combrinck, Jill M; Smith, Peter J; Egan, Timothy J
2015-08-15
A large quantity of high throughput screening (HTS) data for antimalarial activity has become available in recent years. This includes both phenotypic and target-based activity. Realising the maximum value of these data remains a challenge. In this respect, methods that allow such data to be used for virtual screening maximise efficiency and reduce costs. In this study both in vitro antimalarial activity and inhibitory data for β-haematin formation, largely obtained from publically available sources, has been used to develop Bayesian models for inhibitors of β-haematin formation and in vitro antimalarial activity. These models were used to screen two in silico compound libraries. In the first, the 1510 U.S. Food and Drug Administration approved drugs available on PubChem were ranked from highest to lowest Bayesian score based on a training set of β-haematin inhibiting compounds active against Plasmodium falciparum that did not include any of the clinical antimalarials or close analogues. The six known clinical antimalarials that inhibit β-haematin formation were ranked in the top 2.1% of compounds. Furthermore, the in vitro antimalarial hit-rate for this prioritised set of compounds was found to be 81% in the case of the subset where activity data are available in PubChem. In the second, a library of about 5000 commercially available compounds (Aldrich(CPR)) was virtually screened for ability to inhibit β-haematin formation and then for in vitro antimalarial activity. A selection of 34 compounds was purchased and tested, of which 24 were predicted to be β-haematin inhibitors. The hit rate for inhibition of β-haematin formation was found to be 25% and a third of these were active against P. falciparum, corresponding to enrichments estimated at about 25- and 140-fold relative to random screening, respectively. Copyright © 2014 Elsevier Ltd. All rights reserved.
Mizutani, Miho Yamada; Itai, Akiko
2004-09-23
A method of easily finding ligands, with a variety of core structures, for a given target macromolecule would greatly contribute to the rapid identification of novel lead compounds for drug development. We have developed an efficient method for discovering ligand candidates from a number of flexible compounds included in databases, when the three-dimensional (3D) structure of the drug target is available. The method, named ADAM&EVE, makes use of our automated docking method ADAM, which has already been reported. Like ADAM, ADAM&EVE takes account of the flexibility of each molecule in databases, by exploring the conformational space fully and continuously. Database screening has been made much faster than with ADAM through the tuning of parameters, so that computational screening of several hundred thousand compounds is possible in a practical time. Promising ligand candidates can be selected according to various criteria based on the docking results and characteristics of compounds. Furthermore, we have developed a new tool, EVE-MAKE, for automatically preparing the additional compound data necessary for flexible docking calculation, prior to 3D database screening. Among several successful cases of lead discovery by ADAM&EVE, the finding of novel acetylcholinesterase (AChE) inhibitors is presented here. We performed a virtual screening of about 160 000 commercially available compounds against the X-ray crystallographic structure of AChE. Among 114 compounds that could be purchased and assayed, 35 molecules with various core structures showed inhibitory activities with IC(50) values less than 100 microM. Thirteen compounds had IC(50) values between 0.5 and 10 microM, and almost all their core structures are very different from those of known inhibitors. The results demonstrate the effectiveness and validity of the ADAM&EVE approach and provide a starting point for development of novel drugs to treat Alzheimer's disease.
AOPs & Biomarkers: Bridging High Throughput Screening and Regulatory Decision Making.
As high throughput screening (HTS) approaches play a larger role in toxicity testing, computational toxicology has emerged as a critical component in interpreting the large volume of data produced. Computational models for this purpose are becoming increasingly more sophisticated...
Schieferstein, Jeremy M.; Pawate, Ashtamurthy S.; Wan, Frank; Sheraden, Paige N.; Broecker, Jana; Ernst, Oliver P.; Gennis, Robert B.
2017-01-01
Elucidating and clarifying the function of membrane proteins ultimately requires atomic resolution structures as determined most commonly by X-ray crystallography. Many high impact membrane protein structures have resulted from advanced techniques such as in meso crystallization that present technical difficulties for the set-up and scale-out of high-throughput crystallization experiments. In prior work, we designed a novel, low-throughput X-ray transparent microfluidic device that automated the mixing of protein and lipid by diffusion for in meso crystallization trials. Here, we report X-ray transparent microfluidic devices for high-throughput crystallization screening and optimization that overcome the limitations of scale and demonstrate their application to the crystallization of several membrane proteins. Two complementary chips are presented: (1) a high-throughput screening chip to test 192 crystallization conditions in parallel using as little as 8 nl of membrane protein per well and (2) a crystallization optimization chip to rapidly optimize preliminary crystallization hits through fine-gradient re-screening. We screened three membrane proteins for new in meso crystallization conditions, identifying several preliminary hits that we tested for X-ray diffraction quality. Further, we identified and optimized the crystallization condition for a photosynthetic reaction center mutant and solved its structure to a resolution of 3.5 Å. PMID:28469762
Hedvat, Michael; Emdad, Luni; Das, Swadesh K; Kim, Keetae; Dasgupta, Santanu; Thomas, Shibu; Hu, Bin; Zhu, Shan; Dash, Rupesh; Quinn, Bridget A; Oyesanya, Regina A; Kegelman, Timothy P; Sokhi, Upneet K; Sarkar, Siddik; Erdogan, Eda; Menezes, Mitchell E; Bhoopathi, Praveen; Wang, Xiang-Yang; Pomper, Martin G; Wei, Jun; Wu, Bainan; Stebbins, John L; Diaz, Paul W; Reed, John C; Pellecchia, Maurizio; Sarkar, Devanand; Fisher, Paul B
2012-11-01
Structure-based modeling combined with rational drug design, and high throughput screening approaches offer significant potential for identifying and developing lead compounds with therapeutic potential. The present review focuses on these two approaches using explicit examples based on specific derivatives of Gossypol generated through rational design and applications of a cancer-specificpromoter derived from Progression Elevated Gene-3. The Gossypol derivative Sabutoclax (BI-97C1) displays potent anti-tumor activity against a diverse spectrum of human tumors. The model of the docked structure of Gossypol bound to Bcl-XL provided a virtual structure-activity-relationship where appropriate modifications were predicted on a rational basis. These structure-based studies led to the isolation of Sabutoclax, an optically pure isomer of Apogossypol displaying superior efficacy and reduced toxicity. These studies illustrate the power of combining structure-based modeling with rational design to predict appropriate derivatives of lead compounds to be empirically tested and evaluated for bioactivity. Another approach to cancer drug discovery utilizes a cancer-specific promoter as readouts of the transformed state. The promoter region of Progression Elevated Gene-3 is such a promoter with cancer-specific activity. The specificity of this promoter has been exploited as a means of constructing cancer terminator viruses that selectively kill cancer cells and as a systemic imaging modality that specifically visualizes in vivo cancer growth with no background from normal tissues. Screening of small molecule inhibitors that suppress the Progression Elevated Gene-3-promoter may provide relevant lead compounds for cancer therapy that can be combined with further structure-based approaches leading to the development of novel compounds for cancer therapy.
Lyons, Eli; Sheridan, Paul; Tremmel, Georg; Miyano, Satoru; Sugano, Sumio
2017-10-24
High-throughput screens allow for the identification of specific biomolecules with characteristics of interest. In barcoded screens, DNA barcodes are linked to target biomolecules in a manner allowing for the target molecules making up a library to be identified by sequencing the DNA barcodes using Next Generation Sequencing. To be useful in experimental settings, the DNA barcodes in a library must satisfy certain constraints related to GC content, homopolymer length, Hamming distance, and blacklisted subsequences. Here we report a novel framework to quickly generate large-scale libraries of DNA barcodes for use in high-throughput screens. We show that our framework dramatically reduces the computation time required to generate large-scale DNA barcode libraries, compared with a naїve approach to DNA barcode library generation. As a proof of concept, we demonstrate that our framework is able to generate a library consisting of one million DNA barcodes for use in a fragment antibody phage display screening experiment. We also report generating a general purpose one billion DNA barcode library, the largest such library yet reported in literature. Our results demonstrate the value of our novel large-scale DNA barcode library generation framework for use in high-throughput screening applications.
Kittelmann, Jörg; Ottens, Marcel; Hubbuch, Jürgen
2015-04-15
High-throughput batch screening technologies have become an important tool in downstream process development. Although continuative miniaturization saves time and sample consumption, there is yet no screening process described in the 384-well microplate format. Several processes are established in the 96-well dimension to investigate protein-adsorbent interactions, utilizing between 6.8 and 50 μL resin per well. However, as sample consumption scales with resin volumes and throughput scales with experiments per microplate, they are limited in costs and saved time. In this work, a new method for in-well resin quantification by optical means, applicable in the 384-well format, and resin volumes as small as 0.1 μL is introduced. A HTS batch isotherm process is described, utilizing this new method in combination with optical sample volume quantification for screening of isotherm parameters in 384-well microplates. Results are qualified by confidence bounds determined by bootstrap analysis and a comprehensive Monte Carlo study of error propagation. This new approach opens the door to a variety of screening processes in the 384-well format on HTS stations, higher quality screening data and an increase in throughput. Copyright © 2015 Elsevier B.V. All rights reserved.
Joslin, John; Gilligan, James; Anderson, Paul; Garcia, Catherine; Sharif, Orzala; Hampton, Janice; Cohen, Steven; King, Miranda; Zhou, Bin; Jiang, Shumei; Trussell, Christopher; Dunn, Robert; Fathman, John W; Snead, Jennifer L; Boitano, Anthony E; Nguyen, Tommy; Conner, Michael; Cooke, Mike; Harris, Jennifer; Ainscow, Ed; Zhou, Yingyao; Shaw, Chris; Sipes, Dan; Mainquist, James; Lesley, Scott
2018-05-01
The goal of high-throughput screening is to enable screening of compound libraries in an automated manner to identify quality starting points for optimization. This often involves screening a large diversity of compounds in an assay that preserves a connection to the disease pathology. Phenotypic screening is a powerful tool for drug identification, in that assays can be run without prior understanding of the target and with primary cells that closely mimic the therapeutic setting. Advanced automation and high-content imaging have enabled many complex assays, but these are still relatively slow and low throughput. To address this limitation, we have developed an automated workflow that is dedicated to processing complex phenotypic assays for flow cytometry. The system can achieve a throughput of 50,000 wells per day, resulting in a fully automated platform that enables robust phenotypic drug discovery. Over the past 5 years, this screening system has been used for a variety of drug discovery programs, across many disease areas, with many molecules advancing quickly into preclinical development and into the clinic. This report will highlight a diversity of approaches that automated flow cytometry has enabled for phenotypic drug discovery.
Shape-Based Virtual Screening with Volumetric Aligned Molecular Shapes
Koes, David Ryan; Camacho, Carlos J.
2014-01-01
Shape-based virtual screening is an established and effective method for identifying small molecules that are similar in shape and function to a reference ligand. We describe a new method of shape-based virtual screening, volumetric aligned molecular shapes (VAMS). VAMS uses efficient data structures to encode and search molecular shapes. We demonstrate that VAMS is an effective method for shape-based virtual screening and that it can be successfully used as a pre-filter to accelerate more computationally demanding search algorithms. Unique to VAMS is a novel minimum/maximum shape constraint query for precisely specifying the desired molecular shape. Shape constraint searches in VAMS are particularly efficient and millions of shapes can be searched in a fraction of a second. We compare the performance of VAMS with two other shape-based virtual screening algorithms a benchmark of 102 protein targets consisting of more than 32 million molecular shapes and find that VAMS provides a competitive trade-off between run-time performance and virtual screening performance. PMID:25049193
Computational methods in drug discovery
Leelananda, Sumudu P
2016-01-01
The process for drug discovery and development is challenging, time consuming and expensive. Computer-aided drug discovery (CADD) tools can act as a virtual shortcut, assisting in the expedition of this long process and potentially reducing the cost of research and development. Today CADD has become an effective and indispensable tool in therapeutic development. The human genome project has made available a substantial amount of sequence data that can be used in various drug discovery projects. Additionally, increasing knowledge of biological structures, as well as increasing computer power have made it possible to use computational methods effectively in various phases of the drug discovery and development pipeline. The importance of in silico tools is greater than ever before and has advanced pharmaceutical research. Here we present an overview of computational methods used in different facets of drug discovery and highlight some of the recent successes. In this review, both structure-based and ligand-based drug discovery methods are discussed. Advances in virtual high-throughput screening, protein structure prediction methods, protein–ligand docking, pharmacophore modeling and QSAR techniques are reviewed. PMID:28144341
Computational methods in drug discovery.
Leelananda, Sumudu P; Lindert, Steffen
2016-01-01
The process for drug discovery and development is challenging, time consuming and expensive. Computer-aided drug discovery (CADD) tools can act as a virtual shortcut, assisting in the expedition of this long process and potentially reducing the cost of research and development. Today CADD has become an effective and indispensable tool in therapeutic development. The human genome project has made available a substantial amount of sequence data that can be used in various drug discovery projects. Additionally, increasing knowledge of biological structures, as well as increasing computer power have made it possible to use computational methods effectively in various phases of the drug discovery and development pipeline. The importance of in silico tools is greater than ever before and has advanced pharmaceutical research. Here we present an overview of computational methods used in different facets of drug discovery and highlight some of the recent successes. In this review, both structure-based and ligand-based drug discovery methods are discussed. Advances in virtual high-throughput screening, protein structure prediction methods, protein-ligand docking, pharmacophore modeling and QSAR techniques are reviewed.
Quality control methodology for high-throughput protein-protein interaction screening.
Vazquez, Alexei; Rual, Jean-François; Venkatesan, Kavitha
2011-01-01
Protein-protein interactions are key to many aspects of the cell, including its cytoskeletal structure, the signaling processes in which it is involved, or its metabolism. Failure to form protein complexes or signaling cascades may sometimes translate into pathologic conditions such as cancer or neurodegenerative diseases. The set of all protein interactions between the proteins encoded by an organism constitutes its protein interaction network, representing a scaffold for biological function. Knowing the protein interaction network of an organism, combined with other sources of biological information, can unravel fundamental biological circuits and may help better understand the molecular basics of human diseases. The protein interaction network of an organism can be mapped by combining data obtained from both low-throughput screens, i.e., "one gene at a time" experiments and high-throughput screens, i.e., screens designed to interrogate large sets of proteins at once. In either case, quality controls are required to deal with the inherent imperfect nature of experimental assays. In this chapter, we discuss experimental and statistical methodologies to quantify error rates in high-throughput protein-protein interactions screens.
[Chemical databases and virtual screening].
Rognan, Didier; Bonnet, Pascal
2014-12-01
A prerequisite to any virtual screening is the definition of compound libraries to be screened. As we describe here, various sources are available. The selection of the proper library is usually project-dependent but at least as important as the screening method itself. This review details the main compound libraries that are available for virtual screening and guide the reader to the best possible selection according to its needs. © 2014 médecine/sciences – Inserm.
High-Throughput/High-Content Screening Assays with Engineered Nanomaterials in ToxCast
High-throughput and high-content screens are attractive approaches for prioritizing nanomaterial hazards and informing targeted testing due to the impracticality of using traditional toxicological testing on the large numbers and varieties of nanomaterials. The ToxCast program a...
Screening for endocrine-disrupting chemicals (EDCs) requires sensitive, scalable assays. Current high-throughput screening (HTPS) approaches for estrogenic and androgenic activity yield rapid results, but many are not sensitive to physiological hormone concentrations, suggesting ...
Development of a thyroperoxidase inhibition assay for high-throughput screening
High-throughput screening (HTPS) assays to detect inhibitors of thyroperoxidase (TPO), the enzymatic catalyst for thyroid hormone (TH) synthesis, are not currently available. Herein we describe the development of a HTPS TPO inhibition assay. Rat thyroid microsomes and a fluores...
High-throughput screening, predictive modeling and computational embryology - Abstract
High-throughput screening (HTS) studies are providing a rich source of data that can be applied to chemical profiling to address sensitivity and specificity of molecular targets, biological pathways, cellular and developmental processes. EPA’s ToxCast project is testing 960 uniq...
Picking Cell Lines for High-Throughput Transcriptomic Toxicity Screening (SOT)
High throughput, whole genome transcriptomic profiling is a promising approach to comprehensively evaluate chemicals for potential biological effects. To be useful for in vitro toxicity screening, gene expression must be quantified in a set of representative cell types that captu...
Fragment screening of cyclin G-associated kinase by weak affinity chromatography.
Meiby, Elinor; Knapp, Stefan; Elkins, Jonathan M; Ohlson, Sten
2012-11-01
Fragment-based drug discovery (FBDD) has become a new strategy for drug discovery where lead compounds are evolved from small molecules. These fragments form low affinity interactions (dissociation constant (K(D)) = mM - μM) with protein targets, which require fragment screening methods of sufficient sensitivity. Weak affinity chromatography (WAC) is a promising new technology for fragment screening based on selective retention of fragments by a drug target. Kinases are a major pharmaceutical target, and FBDD has been successfully applied to several of these targets. In this work, we have demonstrated the potential to use WAC in combination with mass spectrometry (MS) detection for fragment screening of a kinase target-cyclin G-associated kinase (GAK). One hundred seventy fragments were selected for WAC screening by virtual screening of a commercial fragment library against the ATP-binding site of five different proteins. GAK protein was immobilized on a capillary HPLC column, and compound binding was characterized by frontal affinity chromatography. Compounds were screened in sets of 13 or 14, in combination with MS detection for enhanced throughput. Seventy-eight fragments (46 %) with K(D) < 200 μM were detected, including a few highly efficient GAK binders (K(D) of 2 μM; ligand efficiency = 0.51). Of special interest is that chiral screening by WAC may be possible, as two stereoisomeric fragments, which both contained one chiral center, demonstrated twin peaks. This ability, in combination with the robustness, sensitivity, and simplicity of WAC makes it a new method for fragment screening of considerable potential.
NASA Astrophysics Data System (ADS)
Wang, Youwei; Zhang, Wenqing; Chen, Lidong; Shi, Siqi; Liu, Jianjun
2017-12-01
Li-ion batteries are a key technology for addressing the global challenge of clean renewable energy and environment pollution. Their contemporary applications, for portable electronic devices, electric vehicles, and large-scale power grids, stimulate the development of high-performance battery materials with high energy density, high power, good safety, and long lifetime. High-throughput calculations provide a practical strategy to discover new battery materials and optimize currently known material performances. Most cathode materials screened by the previous high-throughput calculations cannot meet the requirement of practical applications because only capacity, voltage and volume change of bulk were considered. It is important to include more structure-property relationships, such as point defects, surface and interface, doping and metal-mixture and nanosize effects, in high-throughput calculations. In this review, we established quantitative description of structure-property relationships in Li-ion battery materials by the intrinsic bulk parameters, which can be applied in future high-throughput calculations to screen Li-ion battery materials. Based on these parameterized structure-property relationships, a possible high-throughput computational screening flow path is proposed to obtain high-performance battery materials.
Wang, Youwei; Zhang, Wenqing; Chen, Lidong; Shi, Siqi; Liu, Jianjun
2017-01-01
Li-ion batteries are a key technology for addressing the global challenge of clean renewable energy and environment pollution. Their contemporary applications, for portable electronic devices, electric vehicles, and large-scale power grids, stimulate the development of high-performance battery materials with high energy density, high power, good safety, and long lifetime. High-throughput calculations provide a practical strategy to discover new battery materials and optimize currently known material performances. Most cathode materials screened by the previous high-throughput calculations cannot meet the requirement of practical applications because only capacity, voltage and volume change of bulk were considered. It is important to include more structure-property relationships, such as point defects, surface and interface, doping and metal-mixture and nanosize effects, in high-throughput calculations. In this review, we established quantitative description of structure-property relationships in Li-ion battery materials by the intrinsic bulk parameters, which can be applied in future high-throughput calculations to screen Li-ion battery materials. Based on these parameterized structure-property relationships, a possible high-throughput computational screening flow path is proposed to obtain high-performance battery materials.
Teng, Y. G.; Berger, W. T.; Nesbitt, N. M.; ...
2015-07-27
Botulinum neurotoxins (BoNTs) are among the most potent biological toxin known to humans, and are classified as Category A bioterrorism agents by the Centers for Disease Control and prevention (CDC). There are seven known BoNT serotypes (A-G) which have been thus far identified in literature. BoNTs have been shown to block neurotransmitter release by cleaving proteins of the soluble NSF attachment protein receptor (SNARE) complex. Disruption of the SNARE complex precludes motor neuron failure which ultimately results in flaccid paralysis in humans and animals. Currently, there are no effective therapeutic treatments against the neurotoxin light chain (LC) after translocation intomore » the cytosols of motor neurons. In this work, high-throughput virtual screening was employed to screen a library of commercially available compounds from ZINC database against BoNT/A-LC. Among the hit compounds from the in-silico screening, two lead compounds were identified and found to have potent inhibitory activity against BoNT/A-LC in vitro, as well as in Neuro-2a cells. A few analogues of the lead compounds were synthesized and their potency examined. One of these analogues showed an enhanced activity than the lead compounds« less
Building a virtual ligand screening pipeline using free software: a survey.
Glaab, Enrico
2016-03-01
Virtual screening, the search for bioactive compounds via computational methods, provides a wide range of opportunities to speed up drug development and reduce the associated risks and costs. While virtual screening is already a standard practice in pharmaceutical companies, its applications in preclinical academic research still remain under-exploited, in spite of an increasing availability of dedicated free databases and software tools. In this survey, an overview of recent developments in this field is presented, focusing on free software and data repositories for screening as alternatives to their commercial counterparts, and outlining how available resources can be interlinked into a comprehensive virtual screening pipeline using typical academic computing facilities. Finally, to facilitate the set-up of corresponding pipelines, a downloadable software system is provided, using platform virtualization to integrate pre-installed screening tools and scripts for reproducible application across different operating systems. © The Author 2015. Published by Oxford University Press.
Building a virtual ligand screening pipeline using free software: a survey
2016-01-01
Virtual screening, the search for bioactive compounds via computational methods, provides a wide range of opportunities to speed up drug development and reduce the associated risks and costs. While virtual screening is already a standard practice in pharmaceutical companies, its applications in preclinical academic research still remain under-exploited, in spite of an increasing availability of dedicated free databases and software tools. In this survey, an overview of recent developments in this field is presented, focusing on free software and data repositories for screening as alternatives to their commercial counterparts, and outlining how available resources can be interlinked into a comprehensive virtual screening pipeline using typical academic computing facilities. Finally, to facilitate the set-up of corresponding pipelines, a downloadable software system is provided, using platform virtualization to integrate pre-installed screening tools and scripts for reproducible application across different operating systems. PMID:26094053
Development of Drugs for Epstein - Barr virus using High-Throughput in silico Virtual Screening
Li, Ning; Thompson, Scott; Jiang, Hualiang; Lieberman, Paul M.; Luo, Cheng
2010-01-01
Importance of the field Epstein-Barr virus (EBV) is a ubiquitious human herpesvirus that is causally associated with endemic forms of Burkitt’s lymphoma (BL), nasopharyngeal carcinoma, and lymphoproliferative disease in immunosuppressed individuals. On a global scale, EBV infects over 90% of the adult population and is responsible for ~1% of all human cancers. To date, there is no efficacious drug or therapy for the treatment of EBV infection and EBV-related diseases. Areas covered in this review In this review, we discuss the existing anti-EBV inhibitors and those under development. We discuss the value of different molecular targets, including EBV lytic DNA replication enzymes, as well as proteins that are expressed exclusively during latent infection, like EBNA1 and LMP1. Since the atomic structure of the EBNA1 DNA binding domain has been described, it is an attractive target for in silico methods of drug design and small molecule screening. We discuss the use of computational methods that can greatly facilitate the development of novel inhibitors and how in silico screening methods can be applied to target proteins with known structures, like EBNA1, to treat EBV infection and disease. What the reader will gain The reader will be familiarized with the problems in targeting of EBV for inhibition by small molecules and how computational methods can greatly facilitate this process. Take home message Despite the impressive efficacy of nucleoside analogues for the treatment of herpesvirus lytic infection, there remain few effective treatments for latent infections. Since EBV-latent infection persists within and contributes to the formation of EBV-associated cancers, targeting EBV latent proteins is an unmet medical need. High throughput in silico screening can accelerate the process of drug discovery for novel and selective agents that inhibit EBV latent infection and associated disease. PMID:22822721
State of the Art High-Throughput Approaches to Genotoxicity: Flow Micronucleus, Ames II, GreenScreen and Comet (Presented by Dr. Marilyn J. Aardema, Chief Scientific Advisor, Toxicology, Dr. Leon Stankowski, et. al. (6/28/2012)
Incorporating Human Dosimetry and Exposure into High-Throughput In Vitro Toxicity Screening
Many chemicals in commerce today have undergone limited or no safety testing. To reduce the number of untested chemicals and prioritize limited testing resources, several governmental programs are using high-throughput in vitro screens for assessing chemical effects across multip...
Environmental Impact on Vascular Development Predicted by High Throughput Screening
Understanding health risks to embryonic development from exposure to environmental chemicals is a significant challenge given the diverse chemical landscape and paucity of data for most of these compounds. High throughput screening (HTS) in EPA’s ToxCastTM project provides vast d...
AOPs and Biomarkers: Bridging High Throughput Screening and Regulatory Decision Making
As high throughput screening (HTS) plays a larger role in toxicity testing, camputational toxicology has emerged as a critical component in interpreting the large volume of data produced. Computational models designed to quantify potential adverse effects based on HTS data will b...
tcpl: The ToxCast Pipeline for High-Throughput Screening Data
Motivation: The large and diverse high-throughput chemical screening efforts carried out by the US EPAToxCast program requires an efficient, transparent, and reproducible data pipeline.Summary: The tcpl R package and its associated MySQL database provide a generalized platform fo...
High-throughput screening, predictive modeling and computational embryology
High-throughput screening (HTS) studies are providing a rich source of data that can be applied to profile thousands of chemical compounds for biological activity and potential toxicity. EPA’s ToxCast™ project, and the broader Tox21 consortium, in addition to projects worldwide,...
High-throughput in vitro toxicity screening can provide an efficient way to identify potential biological targets for chemicals. However, relying on nominal assay concentrations may misrepresent potential in vivo effects of these chemicals due to differences in bioavailability, c...
NASA Astrophysics Data System (ADS)
Mondal, Sudip; Hegarty, Evan; Martin, Chris; Gökçe, Sertan Kutal; Ghorashian, Navid; Ben-Yakar, Adela
2016-10-01
Next generation drug screening could benefit greatly from in vivo studies, using small animal models such as Caenorhabditis elegans for hit identification and lead optimization. Current in vivo assays can operate either at low throughput with high resolution or with low resolution at high throughput. To enable both high-throughput and high-resolution imaging of C. elegans, we developed an automated microfluidic platform. This platform can image 15 z-stacks of ~4,000 C. elegans from 96 different populations using a large-scale chip with a micron resolution in 16 min. Using this platform, we screened ~100,000 animals of the poly-glutamine aggregation model on 25 chips. We tested the efficacy of ~1,000 FDA-approved drugs in improving the aggregation phenotype of the model and identified four confirmed hits. This robust platform now enables high-content screening of various C. elegans disease models at the speed and cost of in vitro cell-based assays.
ERIC Educational Resources Information Center
Kraemer, Sara; Thorn, Christopher A.
2010-01-01
The purpose of this exploratory study was to identify and describe some of the dimensions of scientific collaborations using high throughput computing (HTC) through the lens of a virtual team performance framework. A secondary purpose was to assess the viability of using a virtual team performance framework to study scientific collaborations using…
High-throughput screening and small animal models, where are we?
Giacomotto, Jean; Ségalat, Laurent
2010-01-01
Current high-throughput screening methods for drug discovery rely on the existence of targets. Moreover, most of the hits generated during screenings turn out to be invalid after further testing in animal models. To by-pass these limitations, efforts are now being made to screen chemical libraries on whole animals. One of the most commonly used animal model in biology is the murine model Mus musculus. However, its cost limit its use in large-scale therapeutic screening. In contrast, the nematode Caenorhabditis elegans, the fruit fly Drosophila melanogaster, and the fish Danio rerio are gaining momentum as screening tools. These organisms combine genetic amenability, low cost and culture conditions that are compatible with large-scale screens. Their main advantage is to allow high-throughput screening in a whole-animal context. Moreover, their use is not dependent on the prior identification of a target and permits the selection of compounds with an improved safety profile. This review surveys the versatility of these animal models for drug discovery and discuss the options available at this day. PMID:20423335
High-throughput and high-content screens are attractive approaches for prioritizing nanomaterial hazards and informing targeted testing due to the impracticality of using traditional toxicological testing on the large numbers and varieties of nanomaterials. The ToxCast program a...
The US EPA’s ToxCast program is designed to assess chemical perturbations of molecular and cellular endpoints using a variety of high-throughput screening (HTS) assays. However, existing HTS assays have limited or no xenobiotic metabolism which could lead to a mischaracterization...
Defining the taxonomic domain of applicability for mammalian-based high-throughput screening assays
Cell-based high throughput screening (HTS) technologies are becoming mainstream in chemical safety evaluations. The US Environmental Protection Agency (EPA) Toxicity Forecaster (ToxCastTM) and the multi-agency Tox21 Programs have been at the forefront in advancing this science, m...
High-Throughput Screening of a Luciferase Reporter of Gene Silencing on the Inactive X Chromosome.
Keegan, Alissa; Plath, Kathrin; Damoiseaux, Robert
2018-01-01
Assays of luciferase gene activity are a sensitive and quantitative reporter system suited to high-throughput screening. We adapted a luciferase assay to a screening strategy for identifying factors that reactivate epigenetically silenced genes. This epigenetic luciferase reporter is subject to endogenous gene silencing mechanisms on the inactive X chromosome (Xi) in primary mouse cells and thus captures the multilayered nature of chromatin silencing in development. Here, we describe the optimization of an Xi-linked luciferase reactivation assay in 384-well format and adaptation of the assay for high-throughput siRNA and chemical screening. Xi-luciferase reactivation screening has applications in stem cell biology and cancer therapy. We have used the approach described here to identify chromatin-modifying proteins and to identify drug combinations that enhance the gene reactivation activity of the DNA demethylating drug 5-aza-2'-deoxycytidine.
Rotem, Asaf; Janzer, Andreas; Izar, Benjamin; Ji, Zhe; Doench, John G.; Garraway, Levi A.; Struhl, Kevin
2015-01-01
Colony formation in soft agar is the gold-standard assay for cellular transformation in vitro, but it is unsuited for high-throughput screening. Here, we describe an assay for cellular transformation that involves growth in low attachment (GILA) conditions and is strongly correlated with the soft-agar assay. Using GILA, we describe high-throughput screens for drugs and genes that selectively inhibit or increase transformation, but not proliferation. Such molecules are unlikely to be found through conventional drug screening, and they include kinase inhibitors and drugs for noncancer diseases. In addition to known oncogenes, the genetic screen identifies genes that contribute to cellular transformation. Lastly, we demonstrate the ability of Food and Drug Administration-approved noncancer drugs to selectively kill ovarian cancer cells derived from patients with chemotherapy-resistant disease, suggesting this approach may provide useful information for personalized cancer treatment. PMID:25902495
Rotem, Asaf; Janzer, Andreas; Izar, Benjamin; Ji, Zhe; Doench, John G; Garraway, Levi A; Struhl, Kevin
2015-05-05
Colony formation in soft agar is the gold-standard assay for cellular transformation in vitro, but it is unsuited for high-throughput screening. Here, we describe an assay for cellular transformation that involves growth in low attachment (GILA) conditions and is strongly correlated with the soft-agar assay. Using GILA, we describe high-throughput screens for drugs and genes that selectively inhibit or increase transformation, but not proliferation. Such molecules are unlikely to be found through conventional drug screening, and they include kinase inhibitors and drugs for noncancer diseases. In addition to known oncogenes, the genetic screen identifies genes that contribute to cellular transformation. Lastly, we demonstrate the ability of Food and Drug Administration-approved noncancer drugs to selectively kill ovarian cancer cells derived from patients with chemotherapy-resistant disease, suggesting this approach may provide useful information for personalized cancer treatment.
Reynolds, Christopher R; Muggleton, Stephen H; Sternberg, Michael J E
2015-01-01
The use of virtual screening has become increasingly central to the drug development pipeline, with ligand-based virtual screening used to screen databases of compounds to predict their bioactivity against a target. These databases can only represent a small fraction of chemical space, and this paper describes a method of exploring synthetic space by applying virtual reactions to promising compounds within a database, and generating focussed libraries of predicted derivatives. A ligand-based virtual screening tool Investigational Novel Drug Discovery by Example (INDDEx) is used as the basis for a system of virtual reactions. The use of virtual reactions is estimated to open up a potential space of 1.21×1012 potential molecules. A de novo design algorithm known as Partial Logical-Rule Reactant Selection (PLoRRS) is introduced and incorporated into the INDDEx methodology. PLoRRS uses logical rules from the INDDEx model to select reactants for the de novo generation of potentially active products. The PLoRRS method is found to increase significantly the likelihood of retrieving molecules similar to known actives with a p-value of 0.016. Case studies demonstrate that the virtual reactions produce molecules highly similar to known actives, including known blockbuster drugs. PMID:26583052
DEC Ada interface to Screen Management Guidelines (SMG)
NASA Technical Reports Server (NTRS)
Laomanachareon, Somsak; Lekkos, Anthony A.
1986-01-01
DEC's Screen Management Guidelines are the Run-Time Library procedures that perform terminal-independent screen management functions on a VT100-class terminal. These procedures assist users in designing, composing, and keeping track of complex images on a video screen. There are three fundamental elements in the screen management model: the pasteboard, the virtual display, and the virtual keyboard. The pasteboard is like a two-dimensional area on which a user places and manipulates screen displays. The virtual display is a rectangular part of the terminal screen to which a program writes data with procedure calls. The virtual keyboard is a logical structure for input operation associated with a physical keyboard. SMG can be called by all major VAX languages. Through Ada, predefined language Pragmas are used to interface with SMG. These features and elements of SMG are briefly discussed.
Bharat, Amrita; Blanchard, Jan E.; Brown, Eric D.
2014-01-01
The synthesis of ribosomes is an essential process, which is aided by a variety of transacting factors in bacteria. Among these is a group of GTPases essential for bacterial viability and emerging as promising targets for new antibacterial agents. Herein, we describe a robust high-throughput screening process for inhibitors of one such GTPase, the Escherichia coli EngA protein. The primary screen employed an assay of phosphate production in 384-well density. Reaction conditions were chosen to maximize sensitivity for the discovery of competitive inhibitors while maintaining a strong signal amplitude and low noise. In a pilot screen of 31,800 chemical compounds, 44 active compounds were identified. Further, we describe the elimination of non-specific inhibitors that were detergent-sensitive or reactive as well as those that interfered with the high-throughput phosphate assay. Four inhibitors survived these common counter-screens for non-specificity but these chemicals were also inhibitors of the unrelated enzyme dihydrofolate reductase, suggesting that they too were promiscuously active. The high-throughput screen of the EngA protein described here provides a meticulous pilot study in the search for specific inhibitors of GTPases involved in ribosome biogenesis. PMID:23606650
Lee, Ju Hee; Chen, Hongxiang; Kolev, Vihren; Aull, Katherine H.; Jung, Inhee; Wang, Jun; Miyamoto, Shoko; Hosoi, Junichi; Mandinova, Anna; Fisher, David E.
2014-01-01
Skin pigmentation is a complex process including melanogenesis within melanocytes and melanin transfer to the keratinocytes. To develop a comprehensive screening method for novel pigmentation regulators, we used immortalized melanocytes and keratinocytes in co-culture to screen large numbers of compounds. High-throughput screening plates were subjected to digital automated microscopy to quantify the pigmentation via brightfield microscopy. Compounds with pigment suppression were secondarily tested for their effects on expression of MITF and several pigment regulatory genes, and further validated in terms of non-toxicity to keratinocytes/melanocytes and dose dependent activity. The results demonstrate a high-throughput, high-content screening approach, which is applicable to the analysis of large chemical libraries using a co-culture system. We identified candidate pigmentation inhibitors from 4,000 screened compounds including zoxazolamine, 3-methoxycatechol, and alpha-mangostin, which were also shown to modulate expression of MITF and several key pigmentation factors, and are worthy of further evaluation for potential translation to clinical use. PMID:24438532
Microscale screening systems for 3D cellular microenvironments: platforms, advances, and challenges
Montanez-Sauri, Sara I.; Beebe, David J.; Sung, Kyung Eun
2015-01-01
The increasing interest in studying cells using more in vivo-like three-dimensional (3D) microenvironments has created a need for advanced 3D screening platforms with enhanced functionalities and increased throughput. 3D screening platforms that better mimic in vivo microenvironments with enhanced throughput would provide more in-depth understanding of the complexity and heterogeneity of microenvironments. The platforms would also better predict the toxicity and efficacy of potential drugs in physiologically relevant conditions. Traditional 3D culture models (e.g. spinner flasks, gyratory rotation devices, non-adhesive surfaces, polymers) were developed to create 3D multicellular structures. However, these traditional systems require large volumes of reagents and cells, and are not compatible with high throughput screening (HTS) systems. Microscale technology offers the miniaturization of 3D cultures and allows efficient screening of various conditions. This review will discuss the development, most influential works, and current advantages and challenges of microscale culture systems for screening cells in 3D microenvironments. PMID:25274061
DOE Office of Scientific and Technical Information (OSTI.GOV)
Su, Hui
2001-01-01
Laser-induced fluorescence detection is one of the most sensitive detection techniques and it has found enormous applications in various areas. The purpose of this research was to develop detection approaches based on laser-induced fluorescence detection in two different areas, heterogeneous catalysts screening and single cell study. First, we introduced laser-induced imaging (LIFI) as a high-throughput screening technique for heterogeneous catalysts to explore the use of this high-throughput screening technique in discovery and study of various heterogeneous catalyst systems. This scheme is based on the fact that the creation or the destruction of chemical bonds alters the fluorescence properties of suitablymore » designed molecules. By irradiating the region immediately above the catalytic surface with a laser, the fluorescence intensity of a selected product or reactant can be imaged by a charge-coupled device (CCD) camera to follow the catalytic activity as a function of time and space. By screening the catalytic activity of vanadium pentoxide catalysts in oxidation of naphthalene, we demonstrated LIFI has good detection performance and the spatial and temporal resolution needed for high-throughput screening of heterogeneous catalysts. The sample packing density can reach up to 250 x 250 subunits/cm 2 for 40-μm wells. This experimental set-up also can screen solid catalysts via near infrared thermography detection.« less
Hevener, Kirk E.; Mehboob, Shahila; Su, Pin-Chih; Truong, Kent; Boci, Teuta; Deng, Jiangping; Ghassemi, Mahmood; Cook, James L.; Johnson, Michael E.
2011-01-01
Enoyl-acyl carrier protein (ACP) reductase, FabI, is a key enzyme in the bacterial fatty acid biosynthesis pathway (FAS II). FabI is an NADH-dependent oxidoreductase that acts to reduce enoyl-ACP substrates in a final step of the pathway. The absence of this enzyme in humans makes it an attractive target for the development of new antibacterial agents. FabI is known to be unresponsive to structure-based design efforts due to a high degree of induced fit and a mobile flexible loop encompassing the active site. Here we discuss the development, validation, and careful application of a ligand-based virtual screen used for the identification of novel inhibitors of the Francisella tularensis FabI target. In this study, four known classes of FabI inhibitors were used as templates for virtual screens that involved molecular shape and electrostatic matching. The program ROCS was used to search a high-throughput screening library for compounds that matched any of the four molecular shape queries. Matching compounds were further refined using the program EON, which compares and scores compounds by matching electrostatic properties. Using these techniques, 50 compounds were selected, ordered, and tested. The tested compounds possessed novel chemical scaffolds when compared to the input query compounds. Several hits with low micromolar activity were identified and follow-up scaffold-based searches resulted in the identification of a lead series with sub-micromolar enzyme inhibition, high ligand efficiency, and a novel scaffold. Additionally, one of the most active compounds showed promising whole-cell antibacterial activity against several Gram-positive and Gram-negative species, including the target pathogen. The results of a preliminary structure-activity relationship analysis are presented. PMID:22098466
Results from rodent and non-rodent prenatal developmental toxicity tests for over 300 chemicals have been curated into the relational database ToxRefDB. These same chemicals have been run in concentration-response format through over 500 high-throughput screening assays assessin...
SeqAPASS to evaluate conservation of high-throughput screening targets across non-mammalian species
Cell-based high-throughput screening (HTS) and computational technologies are being applied as tools for toxicity testing in the 21st century. The U.S. Environmental Protection Agency (EPA) embraced these technologies and created the ToxCast Program in 2007, which has served as a...
Evaluation of food-relevant chemicals in the ToxCast high-throughput screening program
There are thousands of chemicals that are directly added to or come in contact with food, many of which have undergone little to no toxicological evaluation. The ToxCast high-throughput screening (HTS) program has evaluated over 1,800 chemicals in concentration-response across ~8...
In vitro based assays are used to identify potential endocrine disrupting chemicals. Thyroperoxidase (TPO), an enzyme essential for thyroid hormone (TH) synthesis, is a target site for disruption of the thyroid axis for which a high-throughput screening (HTPS) assay has recently ...
Predictive Model of Rat Reproductive Toxicity from ToxCast High Throughput Screening
The EPA ToxCast research program uses high throughput screening for bioactivity profiling and predicting the toxicity of large numbers of chemicals. ToxCast Phase‐I tested 309 well‐characterized chemicals in over 500 assays for a wide range of molecular targets and cellular respo...
In vitro, high-throughput approaches have been widely recommended as an approach to screen chemicals for the potential to cause developmental neurotoxicity and prioritize them for additional testing. The choice of cellular models for such an approach will have important ramificat...
AbstractHigh-throughput methods are useful for rapidly screening large numbers of chemicals for biological activity, including the perturbation of pathways that may lead to adverse cellular effects. In vitro assays for the key events of neurodevelopment, including apoptosis, may ...
We demonstrate a computational network model that integrates 18 in vitro, high-throughput screening assays measuring estrogen receptor (ER) binding, dimerization, chromatin binding, transcriptional activation and ER-dependent cell proliferation. The network model uses activity pa...
Kakarala, Kavita Kumari; Jamil, Kaiser
2015-02-01
Drug resistance and drug-associated toxicity are the primary causes for withdrawal of many drugs, although patient recovery is satisfactory in many instances. Interestingly, the use of phytochemicals in the treatment of cancer as an alternative to synthetic drugs comes with a host of advantages; minimum side effects, good human absorption and low toxicity to normal cells. Protease activated receptor 1 (PAR1) has been established as a promising target in many diseases including various cancers. Strong evidences suggest its role in metastasis also. There are no natural compounds known to inhibit its activity, so we aimed to identify phytochemicals with antagonist activity against PAR1. We screened phytochemicals from Naturally Occurring Plant-based Anticancer Compound-Activity-Target database (NPACT, http://crdd.osdd.net/raghava/npact/ ) against PAR1 using virtual screening workflow of Schrödinger software. It analyzes pharmaceutically relevant properties using Qikprop and calculates binding energy using Glide at three accuracy levels (high-throughput virtual screening, standard precision and extra precision). Our study led to the identification of phytochemicals, which showed interaction with at least one experimentally determined active site residue of PAR1, showed no violations to Lipinski's rule of five along with predicted high human absorption. Furthermore, structural interaction fingerprint analysis indicated that the residues H255, D256, E260, S344, V257, L258, L262, Y337 and S344 may play an important role in the hydrogen bond interactions of the phytochemicals screened. Of these residues, H255 and L258 residues were experimentally proved to be important for antagonist binding. The residues Y183, L237, L258, L262, F271, L332, L333, Y337, L340, A349, Y350, A352, and Y353 showed maximum hydrophobic interactions with the phytochemicals screened. The results of this work suggest that phytochemicals Reissantins D, 24,25-dihydro-27-desoxywithaferin A, Isoguaiacin, 20-hydroxy-12-deoxyphorbol angelate, etc. could be potential antagonist of PAR1. However, further experimental studies are necessary to validate their antagonistic activity against PAR1.
Buckner, Diana; Wilson, Suzanne; Kurk, Sandra; Hardy, Michele; Miessner, Nicole; Jutila, Mark A
2006-09-01
Innate immune system stimulants (innate adjuvants) offer complementary approaches to vaccines and antimicrobial compounds to increase host resistance to infection. The authors established fetal bovine intestinal epithelial cell (BIEC) cultures to screen natural product and synthetic compound libraries for novel mucosal adjuvants. They showed that BIECs from fetal intestine maintained an in vivo phenotype as reflected in cytokeratin expression, expression of antigens restricted to intestinal enterocytes, and induced interleukin-8 (IL-8) production. BIECs could be infected by and support replication of bovine rotavirus. A semi-high-throughput enzyme-linked immunosorbent assay-based assay that measured IL-8 production by BIECs was established and used to screen commercially available natural compounds for novel adjuvant activity. Five novel hits were identified, demonstrating the utility of the assay for selecting and screening new epithelial cell adjuvants. Although the identified compounds had not previously been shown to induce IL-8 production in epithelial cells, other known functions for 3 of the 5 were consistent with this activity. Statistical analysis of the throughput data demonstrated that the assay is adaptable to a high-throughput format for screening both synthetic and natural product derived compound libraries.
Novel Acoustic Loading of a Mass Spectrometer: Toward Next-Generation High-Throughput MS Screening.
Sinclair, Ian; Stearns, Rick; Pringle, Steven; Wingfield, Jonathan; Datwani, Sammy; Hall, Eric; Ghislain, Luke; Majlof, Lars; Bachman, Martin
2016-02-01
High-throughput, direct measurement of substrate-to-product conversion by label-free detection, without the need for engineered substrates or secondary assays, could be considered the "holy grail" of drug discovery screening. Mass spectrometry (MS) has the potential to be part of this ultimate screening solution, but is constrained by the limitations of existing MS sample introduction modes that cannot meet the throughput requirements of high-throughput screening (HTS). Here we report data from a prototype system (Echo-MS) that uses acoustic droplet ejection (ADE) to transfer femtoliter-scale droplets in a rapid, precise, and accurate fashion directly into the MS. The acoustic source can load samples into the MS from a microtiter plate at a rate of up to three samples per second. The resulting MS signal displays a very sharp attack profile and ions are detected within 50 ms of activation of the acoustic transducer. Additionally, we show that the system is capable of generating multiply charged ion species from simple peptides and large proteins. The combination of high speed and low sample volume has significant potential within not only drug discovery, but also other areas of the industry. © 2015 Society for Laboratory Automation and Screening.
Break-up of droplets in a concentrated emulsion flowing through a narrow constriction
NASA Astrophysics Data System (ADS)
Kim, Minkyu; Rosenfeld, Liat; Tang, Sindy; Tang Lab Team
2014-11-01
Droplet microfluidics has enabled a wide range of high throughput screening applications. Compared with other technologies such as robotic screening technology, droplet microfluidics has 1000 times higher throughput, which makes the technology one of the most promising platforms for the ultrahigh throughput screening applications. Few studies have considered the throughput of the droplet interrogation process, however. In this research, we show that the probability of break-up increases with increasing flow rate, entrance angle to the constriction, and size of the drops. Since single drops do not break at the highest flow rate used in the system, break-ups occur primarily from the interactions between highly packed droplets close to each other. Moreover, the probabilistic nature of the break-up process arises from the stochastic variations in the packing configuration. Our results can be used to calculate the maximum throughput of the serial interrogation process. For 40 pL-drops, the highest throughput with less than 1% droplet break-up was measured to be approximately 7,000 drops per second. In addition, the results are useful for understanding the behavior of concentrated emulsions in applications such as mobility control in enhanced oil recovery.
Wang, Youwei; Zhang, Wenqing; Chen, Lidong; Shi, Siqi; Liu, Jianjun
2017-01-01
Abstract Li-ion batteries are a key technology for addressing the global challenge of clean renewable energy and environment pollution. Their contemporary applications, for portable electronic devices, electric vehicles, and large-scale power grids, stimulate the development of high-performance battery materials with high energy density, high power, good safety, and long lifetime. High-throughput calculations provide a practical strategy to discover new battery materials and optimize currently known material performances. Most cathode materials screened by the previous high-throughput calculations cannot meet the requirement of practical applications because only capacity, voltage and volume change of bulk were considered. It is important to include more structure–property relationships, such as point defects, surface and interface, doping and metal-mixture and nanosize effects, in high-throughput calculations. In this review, we established quantitative description of structure–property relationships in Li-ion battery materials by the intrinsic bulk parameters, which can be applied in future high-throughput calculations to screen Li-ion battery materials. Based on these parameterized structure–property relationships, a possible high-throughput computational screening flow path is proposed to obtain high-performance battery materials. PMID:28458737
Creation of a small high-throughput screening facility.
Flak, Tod
2009-01-01
The creation of a high-throughput screening facility within an organization is a difficult task, requiring a substantial investment of time, money, and organizational effort. Major issues to consider include the selection of equipment, the establishment of data analysis methodologies, and the formation of a group having the necessary competencies. If done properly, it is possible to build a screening system in incremental steps, adding new pieces of equipment and data analysis modules as the need grows. Based upon our experience with the creation of a small screening service, we present some guidelines to consider in planning a screening facility.
Abreu, Rui Mv; Froufe, Hugo Jc; Queiroz, Maria João Rp; Ferreira, Isabel Cfr
2010-10-28
Virtual screening of small molecules using molecular docking has become an important tool in drug discovery. However, large scale virtual screening is time demanding and usually requires dedicated computer clusters. There are a number of software tools that perform virtual screening using AutoDock4 but they require access to dedicated Linux computer clusters. Also no software is available for performing virtual screening with Vina using computer clusters. In this paper we present MOLA, an easy-to-use graphical user interface tool that automates parallel virtual screening using AutoDock4 and/or Vina in bootable non-dedicated computer clusters. MOLA automates several tasks including: ligand preparation, parallel AutoDock4/Vina jobs distribution and result analysis. When the virtual screening project finishes, an open-office spreadsheet file opens with the ligands ranked by binding energy and distance to the active site. All results files can automatically be recorded on an USB-flash drive or on the hard-disk drive using VirtualBox. MOLA works inside a customized Live CD GNU/Linux operating system, developed by us, that bypass the original operating system installed on the computers used in the cluster. This operating system boots from a CD on the master node and then clusters other computers as slave nodes via ethernet connections. MOLA is an ideal virtual screening tool for non-experienced users, with a limited number of multi-platform heterogeneous computers available and no access to dedicated Linux computer clusters. When a virtual screening project finishes, the computers can just be restarted to their original operating system. The originality of MOLA lies on the fact that, any platform-independent computer available can he added to the cluster, without ever using the computer hard-disk drive and without interfering with the installed operating system. With a cluster of 10 processors, and a potential maximum speed-up of 10x, the parallel algorithm of MOLA performed with a speed-up of 8,64× using AutoDock4 and 8,60× using Vina.
Liu, Chi; He, Gu; Jiang, Qinglin; Han, Bo; Peng, Cheng
2013-01-01
Methione tRNA synthetase (MetRS) is an essential enzyme involved in protein biosynthesis in all living organisms and is a potential antibacterial target. In the current study, the structure-based pharmacophore (SBP)-guided method has been suggested to generate a comprehensive pharmacophore of MetRS based on fourteen crystal structures of MetRS-inhibitor complexes. In this investigation, a hybrid protocol of a virtual screening method, comprised of pharmacophore model-based virtual screening (PBVS), rigid and flexible docking-based virtual screenings (DBVS), is used for retrieving new MetRS inhibitors from commercially available chemical databases. This hybrid virtual screening approach was then applied to screen the Specs (202,408 compounds) database, a structurally diverse chemical database. Fifteen hit compounds were selected from the final hits and shifted to experimental studies. These results may provide important information for further research of novel MetRS inhibitors as antibacterial agents. PMID:23839093
Ramasamy, Thilagavathi; Selvam, Chelliah
2015-10-15
Virtual screening has become an important tool in drug discovery process. Structure based and ligand based approaches are generally used in virtual screening process. To date, several benchmark sets for evaluating the performance of the virtual screening tool are available. In this study, our aim is to compare the performance of both structure based and ligand based virtual screening methods. Ten anti-cancer targets and their corresponding benchmark sets from 'Demanding Evaluation Kits for Objective In silico Screening' (DEKOIS) library were selected. X-ray crystal structures of protein-ligand complexes were selected based on their resolution. Openeye tools such as FRED, vROCS were used and the results were carefully analyzed. At EF1%, vROCS produced better results but at EF5% and EF10%, both FRED and ROCS produced almost similar results. It was noticed that the enrichment factor values were decreased while going from EF1% to EF5% and EF10% in many cases. Published by Elsevier Ltd.
tcpl: the ToxCast pipeline for high-throughput screening data.
Filer, Dayne L; Kothiya, Parth; Setzer, R Woodrow; Judson, Richard S; Martin, Matthew T
2017-02-15
Large high-throughput screening (HTS) efforts are widely used in drug development and chemical toxicity screening. Wide use and integration of these data can benefit from an efficient, transparent and reproducible data pipeline. Summary: The tcpl R package and its associated MySQL database provide a generalized platform for efficiently storing, normalizing and dose-response modeling of large high-throughput and high-content chemical screening data. The novel dose-response modeling algorithm has been tested against millions of diverse dose-response series, and robustly fits data with outliers and cytotoxicity-related signal loss. tcpl is freely available on the Comprehensive R Archive Network under the GPL-2 license. martin.matt@epa.gov. Published by Oxford University Press 2016. This work is written by US Government employees and is in the public domain in the US.
Chemical perturbation of vascular development is a putative toxicity pathway which may result in developmental toxicity. EPA’s high-throughput screening (HTS) ToxCast program contains assays which measure cellular signals and biological processes critical for blood vessel develop...
An industrial engineering approach to laboratory automation for high throughput screening
Menke, Karl C.
2000-01-01
Across the pharmaceutical industry, there are a variety of approaches to laboratory automation for high throughput screening. At Sphinx Pharmaceuticals, the principles of industrial engineering have been applied to systematically identify and develop those automated solutions that provide the greatest value to the scientists engaged in lead generation. PMID:18924701
Evaluation of High-throughput Genotoxicity Assays Used in Profiling the US EPA ToxCast Chemicals
Three high-throughput screening (HTS) genotoxicity assays-GreenScreen HC GADD45a-GFP (Gentronix Ltd.), CellCiphr p53 (Cellumen Inc.) and CellSensor p53RE-bla (Invitrogen Corp.)-were used to analyze the collection of 320 predominantly pesticide active compounds being tested in Pha...
Collaborative Core Research Program for Chemical-Biological Warfare Defense
2015-01-04
Discovery through High Throughput Screening (HTS) and Fragment-Based Drug Design (FBDD...Discovery through High Throughput Screening (HTS) and Fragment-Based Drug Design (FBDD) Current pharmaceutical approaches involving drug discovery...structural analysis and docking program generally known as fragment based drug design (FBDD). The main advantage of using these approaches is that
PLASMA PROTEIN PROFILING AS A HIGH THROUGHPUT TOOL FOR CHEMICAL SCREENING USING A SMALL FISH MODEL
Hudson, R. Tod, Michael J. Hemmer, Kimberly A. Salinas, Sherry S. Wilkinson, James Watts, James T. Winstead, Peggy S. Harris, Amy Kirkpatrick and Calvin C. Walker. In press. Plasma Protein Profiling as a High Throughput Tool for Chemical Screening Using a Small Fish Model (Abstra...
Virtual screening of compound libraries.
Cerqueira, Nuno M F S A; Sousa, Sérgio F; Fernandes, Pedro A; Ramos, Maria João
2009-01-01
During the last decade, Virtual Screening (VS) has definitively established itself as an important part of the drug discovery and development process. VS involves the selection of likely drug candidates from large libraries of chemical structures by using computational methodologies, but the generic definition of VS encompasses many different methodologies. This chapter provides an introduction to the field by reviewing a variety of important aspects, including the different types of virtual screening methods, and the several steps required for a successful virtual screening campaign within a state-of-the-art approach, from target selection to postfilter application. This analysis is further complemented with a small collection important VS success stories.
Protein tyrosine phosphatases: Ligand interaction analysis and optimisation of virtual screening.
Ghattas, Mohammad A; Atatreh, Noor; Bichenkova, Elena V; Bryce, Richard A
2014-07-01
Docking-based virtual screening is an established component of structure-based drug discovery. Nevertheless, scoring and ranking of computationally docked ligand libraries still suffer from many false positives. Identifying optimal docking parameters for a target protein prior to virtual screening can improve experimental hit rates. Here, we examine protocols for virtual screening against the important but challenging class of drug target, protein tyrosine phosphatases. In this study, common interaction features were identified from analysis of protein-ligand binding geometries of more than 50 complexed phosphatase crystal structures. It was found that two interactions were consistently formed across all phosphatase inhibitors: (1) a polar contact with the conserved arginine residue, and (2) at least one interaction with the P-loop backbone amide. In order to investigate the significance of these features on phosphatase-ligand binding, a series of seeded virtual screening experiments were conducted on three phosphatase enzymes, PTP1B, Cdc25b and IF2. It was observed that when the conserved arginine and P-loop amide interactions were used as pharmacophoric constraints during docking, enrichment of the virtual screen significantly increased in the three studied phosphatases, by up to a factor of two in some cases. Additionally, the use of such pharmacophoric constraints considerably improved the ability of docking to predict the inhibitor's bound pose, decreasing RMSD to the crystallographic geometry by 43% on average. Constrained docking improved enrichment of screens against both open and closed conformations of PTP1B. Incorporation of an ordered water molecule in PTP1B screening was also found to generally improve enrichment. The knowledge-based computational strategies explored here can potentially inform structure-based design of new phosphatase inhibitors using docking-based virtual screening. Copyright © 2014 Elsevier Inc. All rights reserved.
Caraus, Iurie; Alsuwailem, Abdulaziz A; Nadon, Robert; Makarenkov, Vladimir
2015-11-01
Significant efforts have been made recently to improve data throughput and data quality in screening technologies related to drug design. The modern pharmaceutical industry relies heavily on high-throughput screening (HTS) and high-content screening (HCS) technologies, which include small molecule, complementary DNA (cDNA) and RNA interference (RNAi) types of screening. Data generated by these screening technologies are subject to several environmental and procedural systematic biases, which introduce errors into the hit identification process. We first review systematic biases typical of HTS and HCS screens. We highlight that study design issues and the way in which data are generated are crucial for providing unbiased screening results. Considering various data sets, including the publicly available ChemBank data, we assess the rates of systematic bias in experimental HTS by using plate-specific and assay-specific error detection tests. We describe main data normalization and correction techniques and introduce a general data preprocessing protocol. This protocol can be recommended for academic and industrial researchers involved in the analysis of current or next-generation HTS data. © The Author 2015. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.
Conformational analysis by intersection: CONAN.
Smellie, Andrew; Stanton, Robert; Henne, Randy; Teig, Steve
2003-01-15
As high throughput techniques in chemical synthesis and screening improve, more demands are placed on computer assisted design and virtual screening. Many of these computational methods require one or more three-dimensional conformations for molecules, creating a demand for a conformational analysis tool that can rapidly and robustly cover the low-energy conformational spaces of small molecules. A new algorithm of intersection is presented here, which quickly generates (on average <0.5 seconds/stereoisomer) a complete description of the low energy conformational space of a small molecule. The molecule is first decomposed into nonoverlapping nodes N (usually rings) and overlapping paths P with conformations (N and P) generated in an offline process. In a second step the node and path data are combined to form distinct conformers of the molecule. Finally, heuristics are applied after intersection to generate a small representative collection of conformations that span the conformational space. In a study of approximately 97,000 randomly selected molecules from the MDDR, results are presented that explore these conformations and their ability to cover low-energy conformational space. Copyright 2002 Wiley Periodicals, Inc. J Comput Chem 24: 10-20, 2003
Ligand.Info small-molecule Meta-Database.
von Grotthuss, Marcin; Koczyk, Grzegorz; Pas, Jakub; Wyrwicz, Lucjan S; Rychlewski, Leszek
2004-12-01
Ligand.Info is a compilation of various publicly available databases of small molecules. The total size of the Meta-Database is over 1 million entries. The compound records contain calculated three-dimensional coordinates and sometimes information about biological activity. Some molecules have information about FDA drug approving status or about anti-HIV activity. Meta-Database can be downloaded from the http://Ligand.Info web page. The database can also be screened using a Java-based tool. The tool can interactively cluster sets of molecules on the user side and automatically download similar molecules from the server. The application requires the Java Runtime Environment 1.4 or higher, which can be automatically downloaded from Sun Microsystems or Apple Computer and installed during the first use of Ligand.Info on desktop systems, which support Java (Ms Windows, Mac OS, Solaris, and Linux). The Ligand.Info Meta-Database can be used for virtual high-throughput screening of new potential drugs. Presented examples showed that using a known antiviral drug as query the system was able to find others antiviral drugs and inhibitors.
Taylor, Jessica; Woodcock, Simon
2015-09-01
For more than a decade, RNA interference (RNAi) has brought about an entirely new approach to functional genomics screening. Enabling high-throughput loss-of-function (LOF) screens against the human genome, identifying new drug targets, and significantly advancing experimental biology, RNAi is a fast, flexible technology that is compatible with existing high-throughput systems and processes; however, the recent advent of clustered regularly interspaced palindromic repeats (CRISPR)-Cas, a powerful new precise genome-editing (PGE) technology, has opened up vast possibilities for functional genomics. CRISPR-Cas is novel in its simplicity: one piece of easily engineered guide RNA (gRNA) is used to target a gene sequence, and Cas9 expression is required in the cells. The targeted double-strand break introduced by the gRNA-Cas9 complex is highly effective at removing gene expression compared to RNAi. Together with the reduced cost and complexity of CRISPR-Cas, there is the realistic opportunity to use PGE to screen for phenotypic effects in a total gene knockout background. This review summarizes the exciting development of CRISPR-Cas as a high-throughput screening tool, comparing its future potential to that of well-established RNAi screening techniques, and highlighting future challenges and opportunities within these disciplines. We conclude that the two technologies actually complement rather than compete with each other, enabling greater understanding of the genome in relation to drug discovery. © 2015 Society for Laboratory Automation and Screening.
Virtual screening methods as tools for drug lead discovery from large chemical libraries.
Ma, X H; Zhu, F; Liu, X; Shi, Z; Zhang, J X; Yang, S Y; Wei, Y Q; Chen, Y Z
2012-01-01
Virtual screening methods have been developed and explored as useful tools for searching drug lead compounds from chemical libraries, including large libraries that have become publically available. In this review, we discussed the new developments in exploring virtual screening methods for enhanced performance in searching large chemical libraries, their applications in screening libraries of ~ 1 million or more compounds in the last five years, the difficulties in their applications, and the strategies for further improving these methods.
High throughput and miniaturised systems for biodegradability assessments.
Cregut, Mickael; Jouanneau, Sulivan; Brillet, François; Durand, Marie-José; Sweetlove, Cyril; Chenèble, Jean-Charles; L'Haridon, Jacques; Thouand, Gérald
2014-01-01
The society demands safer products with a better ecological profile. Regulatory criteria have been developed to prevent risks for human health and the environment, for example, within the framework of the European regulation REACH (Regulation (EC) No 1907, 2006). This has driven industry to consider the development of high throughput screening methodologies for assessing chemical biodegradability. These new screening methodologies must be scalable for miniaturisation, reproducible and as reliable as existing procedures for enhanced biodegradability assessment. Here, we evaluate two alternative systems that can be scaled for high throughput screening and conveniently miniaturised to limit costs in comparison with traditional testing. These systems are based on two dyes as follows: an invasive fluorescent dyes that serves as a cellular activity marker (a resazurin-like dye reagent) and a noninvasive fluorescent oxygen optosensor dye (an optical sensor). The advantages and limitations of these platforms for biodegradability assessment are presented. Our results confirm the feasibility of these systems for evaluating and screening chemicals for ready biodegradability. The optosensor is a miniaturised version of a component already used in traditional ready biodegradability testing, whereas the resazurin dye offers an interesting new screening mechanism for chemical concentrations greater than 10 mg/l that are not amenable to traditional closed bottle tests. The use of these approaches allows generalisation of high throughput screening methodologies to meet the need of developing new compounds with a favourable ecological profile and also assessment for regulatory purpose.
Micropillar arrays as a high-throughput screening platform for therapeutics in multiple sclerosis.
Mei, Feng; Fancy, Stephen P J; Shen, Yun-An A; Niu, Jianqin; Zhao, Chao; Presley, Bryan; Miao, Edna; Lee, Seonok; Mayoral, Sonia R; Redmond, Stephanie A; Etxeberria, Ainhoa; Xiao, Lan; Franklin, Robin J M; Green, Ari; Hauser, Stephen L; Chan, Jonah R
2014-08-01
Functional screening for compounds that promote remyelination represents a major hurdle in the development of rational therapeutics for multiple sclerosis. Screening for remyelination is problematic, as myelination requires the presence of axons. Standard methods do not resolve cell-autonomous effects and are not suited for high-throughput formats. Here we describe a binary indicant for myelination using micropillar arrays (BIMA). Engineered with conical dimensions, micropillars permit resolution of the extent and length of membrane wrapping from a single two-dimensional image. Confocal imaging acquired from the base to the tip of the pillars allows for detection of concentric wrapping observed as 'rings' of myelin. The platform is formatted in 96-well plates, amenable to semiautomated random acquisition and automated detection and quantification. Upon screening 1,000 bioactive molecules, we identified a cluster of antimuscarinic compounds that enhance oligodendrocyte differentiation and remyelination. Our findings demonstrate a new high-throughput screening platform for potential regenerative therapeutics in multiple sclerosis.
Large-scale Topographical Screen for Investigation of Physical Neural-Guidance Cues
NASA Astrophysics Data System (ADS)
Li, Wei; Tang, Qing Yuan; Jadhav, Amol D.; Narang, Ankit; Qian, Wei Xian; Shi, Peng; Pang, Stella W.
2015-03-01
A combinatorial approach was used to present primary neurons with a large library of topographical features in the form of micropatterned substrate for high-throughput screening of physical neural-guidance cues that can effectively promote different aspects of neuronal development, including axon and dendritic outgrowth. Notably, the neuronal-guidance capability of specific features was automatically identified using a customized image processing software, thus significantly increasing the screening throughput with minimal subjective bias. Our results indicate that the anisotropic topographies promote axonal and in some cases dendritic extension relative to the isotropic topographies, while dendritic branching showed preference to plain substrates over the microscale features. The results from this work can be readily applied towards engineering novel biomaterials with precise surface topography that can serve as guidance conduits for neuro-regenerative applications. This novel topographical screening strategy combined with the automated processing capability can also be used for high-throughput screening of chemical or genetic regulatory factors in primary neurons.
Small molecule correctors of F508del-CFTR discovered by structure-based virtual screening
NASA Astrophysics Data System (ADS)
Kalid, Ori; Mense, Martin; Fischman, Sharon; Shitrit, Alina; Bihler, Hermann; Ben-Zeev, Efrat; Schutz, Nili; Pedemonte, Nicoletta; Thomas, Philip J.; Bridges, Robert J.; Wetmore, Diana R.; Marantz, Yael; Senderowitz, Hanoch
2010-12-01
Folding correctors of F508del-CFTR were discovered by in silico structure-based screening utilizing homology models of CFTR. The intracellular segment of CFTR was modeled and three cavities were identified at inter-domain interfaces: (1) Interface between the two Nucleotide Binding Domains (NBDs); (2) Interface between NBD1 and Intracellular Loop (ICL) 4, in the region of the F508 deletion; (3) multi-domain interface between NBD1:2:ICL1:2:4. We hypothesized that compounds binding at these interfaces may improve the stability of the protein, potentially affecting the folding yield or surface stability. In silico structure-based screening was performed at the putative binding-sites and a total of 496 candidate compounds from all three sites were tested in functional assays. A total of 15 compounds, representing diverse chemotypes, were identified as F508del folding correctors. This corresponds to a 3% hit rate, tenfold higher than hit rates obtained in corresponding high-throughput screening campaigns. The same binding sites also yielded potentiators and, most notably, compounds with a dual corrector-potentiator activity (dual-acting). Compounds harboring both activity types may prove to be better leads for the development of CF therapeutics than either pure correctors or pure potentiators. To the best of our knowledge this is the first report of structure-based discovery of CFTR modulators.
Tripathi, Pranav; Chaudhary, Ritu; Singh, Ajeet
2014-01-01
Conventionally, drugs are discovered by testing chemically synthesized compounds against a battery of in vivo biological screens. Information technology and Omic science enabled us for high throughput screening of compound libraries against biological targets and hits are then tested for efficacy in cells or animals. Chancroid, caused by Haemophilus ducreyi is a public health problem and has been recognized as a cofactor for Human Immunodeficiency Virus (HIV) transmission. It facilitates HIV transmission by providing an accessible portal entry, promoting viral shedding, and recruiting macrophages as well as CD4 cells to the skin. So, there is a requirement to develop an efficient drug to combat Chancroid that can also diminish HIV infection. In-silico screening of potential inhibitors against the target may facilitate in detection of the novel lead compounds for developing an effective chemo preventive strategy against Haemophilus ducreyi. The present study has investigated the effects of approximately 1100 natural compounds that inhibit three vital enzymes viz. Phosphoenolpyruvate phosphotransferase, Acetyl-coenzyme A carboxylase and Fructose 1, 6-bisphosphatase of Haemophilus ducreyi in reference to a commercial drug Rifabutin. Results reveal that the lead compound uses less energy to bind to target. The lead compound parillin has also been predicted as less immunogenic in comparison to Rifabutin. Further, better molecular dynamics, pharmacokinetics, pharmacodynamics and ADME-T properties establish it as an efficient chancroid preventer.
Weimar, M R; Cheung, J; Dey, D; McSweeney, C; Morrison, M; Kobayashi, Y; Whitman, W B; Carbone, V; Schofield, L R; Ronimus, R S; Cook, G M
2017-08-01
Hydrogenotrophic methanogens typically require strictly anaerobic culturing conditions in glass tubes with overpressures of H 2 and CO 2 that are both time-consuming and costly. To increase the throughput for screening chemical compound libraries, 96-well microtiter plate methods for the growth of a marine (environmental) methanogen Methanococcus maripaludis strain S2 and the rumen methanogen Methanobrevibacter species AbM4 were developed. A number of key parameters (inoculum size, reducing agents for medium preparation, assay duration, inhibitor solvents, and culture volume) were optimized to achieve robust and reproducible growth in a high-throughput microtiter plate format. The method was validated using published methanogen inhibitors and statistically assessed for sensitivity and reproducibility. The Sigma-Aldrich LOPAC library containing 1,280 pharmacologically active compounds and an in-house natural product library (120 compounds) were screened against M. maripaludis as a proof of utility. This screen identified a number of bioactive compounds, and MIC values were confirmed for some of them against M. maripaludis and M. AbM4. The developed method provides a significant increase in throughput for screening compound libraries and can now be used to screen larger compound libraries to discover novel methanogen-specific inhibitors for the mitigation of ruminant methane emissions. IMPORTANCE Methane emissions from ruminants are a significant contributor to global greenhouse gas emissions, and new technologies are required to control emissions in the agriculture technology (agritech) sector. The discovery of small-molecule inhibitors of methanogens using high-throughput phenotypic (growth) screening against compound libraries (synthetic and natural products) is an attractive avenue. However, phenotypic inhibitor screening is currently hindered by our inability to grow methanogens in a high-throughput format. We have developed, optimized, and validated a high-throughput 96-well microtiter plate assay for growing environmental and rumen methanogens. Using this platform, we identified several new inhibitors of methanogen growth, demonstrating the utility of this approach to fast track the development of methanogen-specific inhibitors for controlling ruminant methane emissions. Copyright © 2017 American Society for Microbiology.
USDA-ARS?s Scientific Manuscript database
The ability to rapidly screen a large number of individuals is the key to any successful plant breeding program. One of the primary bottlenecks in high throughput screening is the preparation of DNA samples, particularly the quantification and normalization of samples for downstream processing. A ...
Little information is available regarding the potential for many commercial chemicals to induce developmental toxicity. The mESC Adherent Cell Differentiation and Cytoxicity (ACDC) assay is a high-throughput screen used to close this data gap. Thus, ToxCast™ Phase I chemicals wer...
Confirmation of Test Chemicals Identified by a High-Throughput Screen (HTPS) as Sodium Iodide Symporter (NIS) Inhibitors in FRTL-5 Model S. Laws1, A. Buckalew1, J. Wang2, D. Hallinger1, A. Murr1, and T. Stoker1. 1Endocrin...
Computational toxicology is the application of mathematical and computer models to help assess chemical hazards and risks to human health and the environment. Supported by advances in informatics, high-throughput screening (HTS) technologies, and systems biology, the U.S. Environ...
Although progress has been made with HTS (high throughput screening) in profiling biological activity (e.g., EPA’s ToxCast™), challenges arise interpreting HTS results in the context of adversity & converting HTS assay concentrations to equivalent human doses for the broad domain...
Efficient and accurate adverse outcome pathway (AOP) based high-throughput screening (HTS) methods use a systems biology based approach to computationally model in vitro cellular and molecular data for rapid chemical prioritization; however, not all HTS assays are grounded by rel...
Using Adverse Outcome Pathway Analysis to Guide Development of High-Throughput Screening Assays for Thyroid-Disruptors Katie B. Paul1,2, Joan M. Hedge2, Daniel M. Rotroff4, Kevin M. Crofton4, Michael W. Hornung3, Steven O. Simmons2 1Oak Ridge Institute for Science Education Post...
Jiang, Rongzhong
2007-07-01
An electrochemical cell array was designed that contains a common air electrode and 16 microanodes for high throughput screening of both fuel cells (based on polymer electrolyte membrane) and metal/air batteries (based on liquid electrolyte). Electrode materials can easily be coated on the anodes of the electrochemical cell array and screened by switching a graphite probe from one cell to the others. The electrochemical cell array was used to study direct methanol fuel cells (DMFCs), including high throughput screening of electrode catalysts and determination of optimum operating conditions. For screening of DMFCs, there is about 6% relative standard deviation (percentage of standard deviation versus mean value) for discharge current from 10 to 20 mAcm(2). The electrochemical cell array was also used to study tin/air batteries. The effect of Cu content in the anode electrode on the discharge performance of the tin/air battery was investigated. The relative standard deviations for screening of metal/air battery (based on zinc/air) are 2.4%, 3.6%, and 5.1% for discharge current at 50, 100, and 150 mAcm(2), respectively.
A novel assay for monoacylglycerol hydrolysis suitable for high-throughput screening.
Brengdahl, Johan; Fowler, Christopher J
2006-12-01
A simple assay for monoacylglycerol hydrolysis suitable for high-throughput screening is described. The assay uses [(3)H]2-oleoylglycerol as substrate, with the tritium label in the glycerol part of the molecule and the use of phenyl sepharose gel to separate the hydrolyzed product ([(3)H]glycerol) from substrate. Using cytosolic fractions derived from rat cerebella as a source of hydrolytic activity, the assay gives the appropriate pH profile and sensitivity to inhibition with compounds known to inhibit hydrolysis of this substrate. The assay could also be adapted to a 96-well plate format, using C6 cells as the source of hydrolytic activity. Thus the assay is simple and appropriate for high-throughput screening of inhibitors of monoacylglycerol hydrolysis.
A virtual screening method for inhibitory peptides of Angiotensin I-converting enzyme.
Wu, Hongxi; Liu, Yalan; Guo, Mingrong; Xie, Jingli; Jiang, XiaMin
2014-09-01
Natural small peptides from foods have been proven to be efficient inhibitors of Angiotensin I-converting enzyme (ACE) for the regulation of blood pressure. The traditional ACE inhibitory peptides screening method is both time consuming and money costing, to the contrary, virtual screening method by computation can break these limitations. We establish a virtual screening method to obtain ACE inhibitory peptides with the help of Libdock module of Discovery Studio 3.5 software. A significant relationship between Libdock score and experimental IC(50) was found, Libdock score = 10.063 log(1/IC(50)) + 68.08 (R(2) = 0.62). The credibility of the relationship was confirmed by testing the coincidence of the estimated log(1/IC(50)) and measured log(1/IC(50)) (IC(50) is 50% inhibitory concentration toward ACE, in μmol/L) of 5 synthetic ACE inhibitory peptides, which was virtual hydrolyzed and screened from a kind of seafood, Phascolosoma esculenta. Accordingly, Libdock method is a valid IC(50) estimation tool and virtual screening method for small ACE inhibitory peptides. © 2014 Institute of Food Technologists®
Chan, Leo Li-Ying; Smith, Tim; Kumph, Kendra A; Kuksin, Dmitry; Kessel, Sarah; Déry, Olivier; Cribbes, Scott; Lai, Ning; Qiu, Jean
2016-10-01
To ensure cell-based assays are performed properly, both cell concentration and viability have to be determined so that the data can be normalized to generate meaningful and comparable results. Cell-based assays performed in immuno-oncology, toxicology, or bioprocessing research often require measuring of multiple samples and conditions, thus the current automated cell counter that uses single disposable counting slides is not practical for high-throughput screening assays. In the recent years, a plate-based image cytometry system has been developed for high-throughput biomolecular screening assays. In this work, we demonstrate a high-throughput AO/PI-based cell concentration and viability method using the Celigo image cytometer. First, we validate the method by comparing directly to Cellometer automated cell counter. Next, cell concentration dynamic range, viability dynamic range, and consistency are determined. The high-throughput AO/PI method described here allows for 96-well to 384-well plate samples to be analyzed in less than 7 min, which greatly reduces the time required for the single sample-based automated cell counter. In addition, this method can improve the efficiency for high-throughput screening assays, where multiple cell counts and viability measurements are needed prior to performing assays such as flow cytometry, ELISA, or simply plating cells for cell culture.
Knowing when to give up: early-rejection stratagems in ligand docking
NASA Astrophysics Data System (ADS)
Skone, Gwyn; Voiculescu, Irina; Cameron, Stephen
2009-10-01
Virtual screening is an important resource in the drug discovery community, of which protein-ligand docking is a significant part. Much software has been developed for this purpose, largely by biochemists and those in related disciplines, who pursue ever more accurate representations of molecular interactions. The resulting tools, however, are very processor-intensive. This paper describes some initial results from a project to review computational chemistry techniques for docking from a non-chemistry standpoint. An abstract blueprint for protein-ligand docking using empirical scoring functions is suggested, and this is used to discuss potential improvements. By introducing computer science tactics such as lazy function evaluation, dramatic increases to throughput can and have been realized using a real-world docking program. Naturally, they can be extended to any system that approximately corresponds to the architecture outlined.
High-Throughput RT-PCR for small-molecule screening assays
Bittker, Joshua A.
2012-01-01
Quantitative measurement of the levels of mRNA expression using real-time reverse transcription polymerase chain reaction (RT-PCR) has long been used for analyzing expression differences in tissue or cell lines of interest. This method has been used somewhat less frequently to measure the changes in gene expression due to perturbagens such as small molecules or siRNA. The availability of new instrumentation for liquid handling and real-time PCR analysis as well as the commercial availability of start-to-finish kits for RT-PCR has enabled the use of this method for high-throughput small-molecule screening on a scale comparable to traditional high-throughput screening (HTS) assays. This protocol focuses on the special considerations necessary for using quantitative RT-PCR as a primary small-molecule screening assay, including the different methods available for mRNA isolation and analysis. PMID:23487248
Gardner, J. Mark F.; Bell, Andrew S.; Parkinson, Tanya; Bickle, Quentin
2016-01-01
An estimated 600 million people are affected by the helminth disease schistosomiasis caused by parasites of the genus Schistosoma. There is currently only one drug recommended for treating schistosomiasis, praziquantel (PZQ), which is effective against adult worms but not against the juvenile stage. In an attempt to identify improved drugs for treating the disease, we have carried out high throughput screening of a number of small molecule libraries with the aim of identifying lead compounds with balanced activity against all life stages of Schistosoma. A total of almost 300,000 compounds were screened using a high throughput assay based on motility of worm larvae and image analysis of assay plates. Hits were screened against juvenile and adult worms to identify broadly active compounds and against a mammalian cell line to assess cytotoxicity. A number of compounds were identified as promising leads for further chemical optimization. PMID:27128493
Wang, Liping; Lee, Jianchao; Zhang, Meijuan; Duan, Qiannan; Zhang, Jiarui; Qi, Hailang
2016-02-18
A high-throughput screening (HTS) method based on fluorescence imaging (FI) was implemented to evaluate the catalytic performance of selenide-modified nano-TiO2. Chemical ink-jet printing (IJP) technology was reformed to fabricate a catalyst library comprising 1405 (Ni(a)Cu(b)Cd(c)Ce(d)In(e)Y(f))Se(x)/TiO2 (M6Se/Ti) composite photocatalysts. Nineteen M6Se/Tis were screened out from the 1405 candidates efficiently.
Adapting Document Similarity Measures for Ligand-Based Virtual Screening.
Himmat, Mubarak; Salim, Naomie; Al-Dabbagh, Mohammed Mumtaz; Saeed, Faisal; Ahmed, Ali
2016-04-13
Quantifying the similarity of molecules is considered one of the major tasks in virtual screening. There are many similarity measures that have been proposed for this purpose, some of which have been derived from document and text retrieving areas as most often these similarity methods give good results in document retrieval and can achieve good results in virtual screening. In this work, we propose a similarity measure for ligand-based virtual screening, which has been derived from a text processing similarity measure. It has been adopted to be suitable for virtual screening; we called this proposed measure the Adapted Similarity Measure of Text Processing (ASMTP). For evaluating and testing the proposed ASMTP we conducted several experiments on two different benchmark datasets: the Maximum Unbiased Validation (MUV) and the MDL Drug Data Report (MDDR). The experiments have been conducted by choosing 10 reference structures from each class randomly as queries and evaluate them in the recall of cut-offs at 1% and 5%. The overall obtained results are compared with some similarity methods including the Tanimoto coefficient, which are considered to be the conventional and standard similarity coefficients for fingerprint-based similarity calculations. The achieved results show that the performance of ligand-based virtual screening is better and outperforms the Tanimoto coefficients and other methods.
Evaluating the Predictivity of Virtual Screening for Abl Kinase Inhibitors to Hinder Drug Resistance
Gani, Osman A B S M; Narayanan, Dilip; Engh, Richard A
2013-01-01
Virtual screening methods are now widely used in early stages of drug discovery, aiming to rank potential inhibitors. However, any practical ligand set (of active or inactive compounds) chosen for deriving new virtual screening approaches cannot fully represent all relevant chemical space for potential new compounds. In this study, we have taken a retrospective approach to evaluate virtual screening methods for the leukemia target kinase ABL1 and its drug-resistant mutant ABL1-T315I. ‘Dual active’ inhibitors against both targets were grouped together with inactive ligands chosen from different decoy sets and tested with virtual screening approaches with and without explicit use of target structures (docking). We show how various scoring functions and choice of inactive ligand sets influence overall and early enrichment of the libraries. Although ligand-based methods, for example principal component analyses of chemical properties, can distinguish some decoy sets from active compounds, the addition of target structural information via docking improves enrichment, and explicit consideration of multiple target conformations (i.e. types I and II) achieves best enrichment of active versus inactive ligands, even without assuming knowledge of the binding mode. We believe that this study can be extended to other therapeutically important kinases in prospective virtual screening studies. PMID:23746052
Novel approaches for targeting the adenosine A2A receptor.
Yuan, Gengyang; Gedeon, Nicholas G; Jankins, Tanner C; Jones, Graham B
2015-01-01
The adenosine A2A receptor (A2AR) represents a drug target for a wide spectrum of diseases. Approaches for targeting this membrane-bound protein have been greatly advanced by new stabilization techniques. The resulting X-ray crystal structures and subsequent analyses provide deep insight to the A2AR from both static and dynamic perspectives. Application of this, along with other biophysical methods combined with fragment-based drug design (FBDD), has become a standard approach in targeting A2AR. Complementarities of in silico screening based- and biophysical screening assisted- FBDD are likely to feature in future approaches in identifying novel ligands against this key receptor. This review describes evolution of the above approaches for targeting A2AR and highlights key modulators identified. It includes a review of: adenosine receptor structures, homology modeling, X-ray structural analysis, rational drug design, biophysical methods, FBDD and in silico screening. As a drug target, the A2AR is attractive as its function plays a role in a wide spectrum of diseases including oncologic, inflammatory, Parkinson's and cardiovascular diseases. Although traditional approaches such as high-throughput screening and homology model-based virtual screening (VS) have played a role in targeting A2AR, numerous shortcomings have generally restricted their applications to specific ligand families. Using stabilization methods for crystallization, X-ray structures of A2AR have greatly accelerated drug discovery and influenced development of biophysical-in silico hybrid screening methods. Application of these new methods to other ARs and G-protein-coupled receptors is anticipated in the future.
Wu, Jianglai; Tang, Anson H. L.; Mok, Aaron T. Y.; Yan, Wenwei; Chan, Godfrey C. F.; Wong, Kenneth K. Y.; Tsia, Kevin K.
2017-01-01
Apart from the spatial resolution enhancement, scaling of temporal resolution, equivalently the imaging throughput, of fluorescence microscopy is of equal importance in advancing cell biology and clinical diagnostics. Yet, this attribute has mostly been overlooked because of the inherent speed limitation of existing imaging strategies. To address the challenge, we employ an all-optical laser-scanning mechanism, enabled by an array of reconfigurable spatiotemporally-encoded virtual sources, to demonstrate ultrafast fluorescence microscopy at line-scan rate as high as 8 MHz. We show that this technique enables high-throughput single-cell microfluidic fluorescence imaging at 75,000 cells/second and high-speed cellular 2D dynamical imaging at 3,000 frames per second, outperforming the state-of-the-art high-speed cameras and the gold-standard laser scanning strategies. Together with its wide compatibility to the existing imaging modalities, this technology could empower new forms of high-throughput and high-speed biological fluorescence microscopy that was once challenged. PMID:28966855
Ma, Xiao H; Jia, Jia; Zhu, Feng; Xue, Ying; Li, Ze R; Chen, Yu Z
2009-05-01
Machine learning methods have been explored as ligand-based virtual screening tools for facilitating drug lead discovery. These methods predict compounds of specific pharmacodynamic, pharmacokinetic or toxicological properties based on their structure-derived structural and physicochemical properties. Increasing attention has been directed at these methods because of their capability in predicting compounds of diverse structures and complex structure-activity relationships without requiring the knowledge of target 3D structure. This article reviews current progresses in using machine learning methods for virtual screening of pharmacodynamically active compounds from large compound libraries, and analyzes and compares the reported performances of machine learning tools with those of structure-based and other ligand-based (such as pharmacophore and clustering) virtual screening methods. The feasibility to improve the performance of machine learning methods in screening large libraries is discussed.
Choudhry, Priya
2016-01-01
Counting cells and colonies is an integral part of high-throughput screens and quantitative cellular assays. Due to its subjective and time-intensive nature, manual counting has hindered the adoption of cellular assays such as tumor spheroid formation in high-throughput screens. The objective of this study was to develop an automated method for quick and reliable counting of cells and colonies from digital images. For this purpose, I developed an ImageJ macro Cell Colony Edge and a CellProfiler Pipeline Cell Colony Counting, and compared them to other open-source digital methods and manual counts. The ImageJ macro Cell Colony Edge is valuable in counting cells and colonies, and measuring their area, volume, morphology, and intensity. In this study, I demonstrate that Cell Colony Edge is superior to other open-source methods, in speed, accuracy and applicability to diverse cellular assays. It can fulfill the need to automate colony/cell counting in high-throughput screens, colony forming assays, and cellular assays. PMID:26848849
High-throughput screening of filamentous fungi using nanoliter-range droplet-based microfluidics
NASA Astrophysics Data System (ADS)
Beneyton, Thomas; Wijaya, I. Putu Mahendra; Postros, Prexilia; Najah, Majdi; Leblond, Pascal; Couvent, Angélique; Mayot, Estelle; Griffiths, Andrew D.; Drevelle, Antoine
2016-06-01
Filamentous fungi are an extremely important source of industrial enzymes because of their capacity to secrete large quantities of proteins. Currently, functional screening of fungi is associated with low throughput and high costs, which severely limits the discovery of novel enzymatic activities and better production strains. Here, we describe a nanoliter-range droplet-based microfluidic system specially adapted for the high-throughput sceening (HTS) of large filamentous fungi libraries for secreted enzyme activities. The platform allowed (i) compartmentalization of single spores in ~10 nl droplets, (ii) germination and mycelium growth and (iii) high-throughput sorting of fungi based on enzymatic activity. A 104 clone UV-mutated library of Aspergillus niger was screened based on α-amylase activity in just 90 minutes. Active clones were enriched 196-fold after a single round of microfluidic HTS. The platform is a powerful tool for the development of new production strains with low cost, space and time footprint and should bring enormous benefit for improving the viability of biotechnological processes.
High Throughput Determination of Critical Human Dosing Parameters (SOT)
High throughput toxicokinetics (HTTK) is a rapid approach that uses in vitro data to estimate TK for hundreds of environmental chemicals. Reverse dosimetry (i.e., reverse toxicokinetics or RTK) based on HTTK data converts high throughput in vitro toxicity screening (HTS) data int...
High Throughput Determinations of Critical Dosing Parameters (IVIVE workshop)
High throughput toxicokinetics (HTTK) is an approach that allows for rapid estimations of TK for hundreds of environmental chemicals. HTTK-based reverse dosimetry (i.e, reverse toxicokinetics or RTK) is used in order to convert high throughput in vitro toxicity screening (HTS) da...
Optimization of high-throughput nanomaterial developmental toxicity testing in zebrafish embryos
Nanomaterial (NM) developmental toxicities are largely unknown. With an extensive variety of NMs available, high-throughput screening methods may be of value for initial characterization of potential hazard. We optimized a zebrafish embryo test as an in vivo high-throughput assay...
Heiger-Bernays, Wendy J; Wegner, Susanna; Dix, David J
2018-01-16
The presence of industrial chemicals, consumer product chemicals, and pharmaceuticals is well documented in waters in the U.S. and globally. Most of these chemicals lack health-protective guidelines and many have been shown to have endocrine bioactivity. There is currently no systematic or national prioritization for monitoring waters for chemicals with endocrine disrupting activity. We propose ambient water bioactivity concentrations (AWBCs) generated from high throughput data as a health-based screen for endocrine bioactivity of chemicals in water. The U.S. EPA ToxCast program has screened over 1800 chemicals for estrogen receptor (ER) and androgen receptor (AR) pathway bioactivity. AWBCs are calculated for 110 ER and 212 AR bioactive chemicals using high throughput ToxCast data from in vitro screening assays and predictive pathway models, high-throughput toxicokinetic data, and data-driven assumptions about consumption of water. Chemical-specific AWBCs are compared with measured water concentrations in data sets from the greater Denver area, Minnesota lakes, and Oregon waters, demonstrating a framework for identifying endocrine bioactive chemicals. This approach can be used to screen potential cumulative endocrine activity in drinking water and to inform prioritization of future monitoring, chemical testing and pollution prevention efforts.
Malik, Nasir; Efthymiou, Anastasia G; Mather, Karly; Chester, Nathaniel; Wang, Xiantao; Nath, Avindra; Rao, Mahendra S; Steiner, Joseph P
2014-12-01
Human primary neural tissue is a vital component for the quick and simple determination of chemical compound neurotoxicity in vitro. In particular, such tissue would be ideal for high-throughput screens that can be used to identify novel neurotoxic or neurotherapeutic compounds. We have previously established a high-throughput screening platform using human induced pluripotent stem cell (iPSC)-derived neural stem cells (NSCs) and neurons. In this study, we conducted a 2000 compound screen with human NSCs and rat cortical cells to identify compounds that are selectively toxic to each group. Approximately 100 of the tested compounds showed specific toxicity to human NSCs. A secondary screen of a small subset of compounds from the primary screen on human iPSCs, NSC-derived neurons, and fetal astrocytes validated the results from >80% of these compounds with some showing cell specific toxicity. Amongst those compounds were several cardiac glycosides, all of which were selectively toxic to the human cells. As the screen was able to reliably identify neurotoxicants, many with species and cell-type specificity, this study demonstrates the feasibility of this NSC-driven platform for higher-throughput neurotoxicity screens. Published by Elsevier B.V.
Chen, Haining; Li, Sijia; Hu, Yajiao; Chen, Guo; Jiang, Qinglin; Tong, Rongsheng; Zang, Zhihe; Cai, Lulu
2016-01-01
Rho-associated, coiled-coil containing protein kinase 1 (ROCK1) is an important regulator of focal adhesion, actomyosin contraction and cell motility. In this manuscript, a combination of the multi-complex-based pharmacophore (MCBP), molecular dynamics simulation and a hybrid protocol of a virtual screening method, comprised of multipharmacophore- based virtual screening (PBVS) and ensemble docking-based virtual screening (DBVS) methods were used for retrieving novel ROCK1 inhibitors from the natural products database embedded in the ZINC database. Ten hit compounds were selected from the hit compounds, and five compounds were tested experimentally. Thus, these results may provide valuable information for further discovery of more novel ROCK1 inhibitors.
IRAS: High-Throughput Identification of Novel Alternative Splicing Regulators.
Zheng, S
2016-01-01
Alternative splicing is a fundamental regulatory process of gene expression. Defects in alternative splicing can lead to various diseases, and modification of disease-causing splicing events presents great therapeutic promise. Splicing outcome is commonly affected by extracellular stimuli and signaling cascades that converge on RNA-binding splicing regulators. These trans-acting factors recognize cis-elements in pre-mRNA transcripts to affect spliceosome assembly and splice site choices. Identification of these splicing regulators and/or upstream modulators has been difficult and traditionally done by piecemeal. High-throughput screening strategies to find multiple regulators of exon splicing have great potential to accelerate the discovery process, but typically confront low sensitivity and low specificity of screening assays. Here we describe a unique screening strategy, IRAS (identifying regulators of alternative splicing), using a pair of dual-output minigene reporters to allow for sensitive detection of exon splicing changes. Each dual-output reporter produces green fluorescent protein (GFP) and red fluorescent protein (RFP) fluorescent signals to assay the two spliced isoforms exclusively. The two complementary minigene reporters alter GFP/RFP output ratios in the opposite direction in response to splicing change. Applying IRAS in cell-based high-throughput screens allows sensitive and specific identification of splicing regulators and modulators for any alternative exons of interest. In comparison to previous high-throughput screening methods, IRAS substantially enhances the specificity of the screening assay. This strategy significantly eliminates false positives without sacrificing sensitive identification of true regulators of splicing. © 2016 Elsevier Inc. All rights reserved.
Erickson, Heidi S
2012-09-28
The future of personalized medicine depends on the ability to efficiently and rapidly elucidate a reliable set of disease-specific molecular biomarkers. High-throughput molecular biomarker analysis methods have been developed to identify disease risk, diagnostic, prognostic, and therapeutic targets in human clinical samples. Currently, high throughput screening allows us to analyze thousands of markers from one sample or one marker from thousands of samples and will eventually allow us to analyze thousands of markers from thousands of samples. Unfortunately, the inherent nature of current high throughput methodologies, clinical specimens, and cost of analysis is often prohibitive for extensive high throughput biomarker analysis. This review summarizes the current state of high throughput biomarker screening of clinical specimens applicable to genetic epidemiology and longitudinal population-based studies with a focus on considerations related to biospecimens, laboratory techniques, and sample pooling. Copyright © 2012 John Wiley & Sons, Ltd.
Edwards, Bonnie; Lesnick, John; Wang, Jing; Tang, Nga; Peters, Carl
2016-02-01
Epigenetics continues to emerge as an important target class for drug discovery and cancer research. As programs scale to evaluate many new targets related to epigenetic expression, new tools and techniques are required to enable efficient and reproducible high-throughput epigenetic screening. Assay miniaturization increases screening throughput and reduces operating costs. Echo liquid handlers can transfer compounds, samples, reagents, and beads in submicroliter volumes to high-density assay formats using only acoustic energy-no contact or tips required. This eliminates tip costs and reduces the risk of reagent carryover. In this study, we demonstrate the miniaturization of a methyltransferase assay using Echo liquid handlers and two different assay technologies: AlphaLISA from PerkinElmer and EPIgeneous HTRF from Cisbio. © 2015 Society for Laboratory Automation and Screening.
Fluorescence-based high-throughput screening of dicer cleavage activity.
Podolska, Katerina; Sedlak, David; Bartunek, Petr; Svoboda, Petr
2014-03-01
Production of small RNAs by ribonuclease III Dicer is a key step in microRNA and RNA interference pathways, which employ Dicer-produced small RNAs as sequence-specific silencing guides. Further studies and manipulations of microRNA and RNA interference pathways would benefit from identification of small-molecule modulators. Here, we report a study of a fluorescence-based in vitro Dicer cleavage assay, which was adapted for high-throughput screening. The kinetic assay can be performed under single-turnover conditions (35 nM substrate and 70 nM Dicer) in a small volume (5 µL), which makes it suitable for high-throughput screening in a 1536-well format. As a proof of principle, a small library of bioactive compounds was analyzed, demonstrating potential of the assay.
A graph-based approach to construct target-focused libraries for virtual screening.
Naderi, Misagh; Alvin, Chris; Ding, Yun; Mukhopadhyay, Supratik; Brylinski, Michal
2016-01-01
Due to exorbitant costs of high-throughput screening, many drug discovery projects commonly employ inexpensive virtual screening to support experimental efforts. However, the vast majority of compounds in widely used screening libraries, such as the ZINC database, will have a very low probability to exhibit the desired bioactivity for a given protein. Although combinatorial chemistry methods can be used to augment existing compound libraries with novel drug-like compounds, the broad chemical space is often too large to be explored. Consequently, the trend in library design has shifted to produce screening collections specifically tailored to modulate the function of a particular target or a protein family. Assuming that organic compounds are composed of sets of rigid fragments connected by flexible linkers, a molecule can be decomposed into its building blocks tracking their atomic connectivity. On this account, we developed eSynth, an exhaustive graph-based search algorithm to computationally synthesize new compounds by reconnecting these building blocks following their connectivity patterns. We conducted a series of benchmarking calculations against the Directory of Useful Decoys, Enhanced database. First, in a self-benchmarking test, the correctness of the algorithm is validated with the objective to recover a molecule from its building blocks. Encouragingly, eSynth can efficiently rebuild more than 80 % of active molecules from their fragment components. Next, the capability to discover novel scaffolds is assessed in a cross-benchmarking test, where eSynth successfully reconstructed 40 % of the target molecules using fragments extracted from chemically distinct compounds. Despite an enormous chemical space to be explored, eSynth is computationally efficient; half of the molecules are rebuilt in less than a second, whereas 90 % take only about a minute to be generated. eSynth can successfully reconstruct chemically feasible molecules from molecular fragments. Furthermore, in a procedure mimicking the real application, where one expects to discover novel compounds based on a small set of already developed bioactives, eSynth is capable of generating diverse collections of molecules with the desired activity profiles. Thus, we are very optimistic that our effort will contribute to targeted drug discovery. eSynth is freely available to the academic community at www.brylinski.org/content/molecular-synthesis.Graphical abstractAssuming that organic compounds are composed of sets of rigid fragments connected by flexible linkers, a molecule can be decomposed into its building blocks tracking their atomic connectivity. Here, we developed eSynth, an automated method to synthesize new compounds by reconnecting these building blocks following the connectivity patterns via an exhaustive graph-based search algorithm. eSynth opens up a possibility to rapidly construct virtual screening libraries for targeted drug discovery.
NASA Astrophysics Data System (ADS)
Kamstra, Rhiannon L.; Dadgar, Saedeh; Wigg, John; Chowdhury, Morshed A.; Phenix, Christopher P.; Floriano, Wely B.
2014-11-01
Our group has recently demonstrated that virtual screening is a useful technique for the identification of target-specific molecular probes. In this paper, we discuss some of our proof-of-concept results involving two biologically relevant target proteins, and report the development of a computational script to generate large databases of fluorescence-labelled compounds for computer-assisted molecular design. The virtual screening of a small library of 1,153 fluorescently-labelled compounds against two targets, and the experimental testing of selected hits reveal that this approach is efficient at identifying molecular probes, and that the screening of a labelled library is preferred over the screening of base compounds followed by conjugation of confirmed hits. The automated script for library generation explores the known reactivity of commercially available dyes, such as NHS-esters, to create large virtual databases of fluorescence-tagged small molecules that can be easily synthesized in a laboratory. A database of 14,862 compounds, each tagged with the ATTO680 fluorophore was generated with the automated script reported here. This library is available for downloading and it is suitable for virtual ligand screening aiming at the identification of target-specific fluorescent molecular probes.
Spherical harmonics coefficients for ligand-based virtual screening of cyclooxygenase inhibitors.
Wang, Quan; Birod, Kerstin; Angioni, Carlo; Grösch, Sabine; Geppert, Tim; Schneider, Petra; Rupp, Matthias; Schneider, Gisbert
2011-01-01
Molecular descriptors are essential for many applications in computational chemistry, such as ligand-based similarity searching. Spherical harmonics have previously been suggested as comprehensive descriptors of molecular structure and properties. We investigate a spherical harmonics descriptor for shape-based virtual screening. We introduce and validate a partially rotation-invariant three-dimensional molecular shape descriptor based on the norm of spherical harmonics expansion coefficients. Using this molecular representation, we parameterize molecular surfaces, i.e., isosurfaces of spatial molecular property distributions. We validate the shape descriptor in a comprehensive retrospective virtual screening experiment. In a prospective study, we virtually screen a large compound library for cyclooxygenase inhibitors, using a self-organizing map as a pre-filter and the shape descriptor for candidate prioritization. 12 compounds were tested in vitro for direct enzyme inhibition and in a whole blood assay. Active compounds containing a triazole scaffold were identified as direct cyclooxygenase-1 inhibitors. This outcome corroborates the usefulness of spherical harmonics for representation of molecular shape in virtual screening of large compound collections. The combination of pharmacophore and shape-based filtering of screening candidates proved to be a straightforward approach to finding novel bioactive chemotypes with minimal experimental effort.
Schneider, Petra; Hoy, Benjamin; Wessler, Silja; Schneider, Gisbert
2011-01-01
Background The human pathogen Helicobacter pylori (H. pylori) is a main cause for gastric inflammation and cancer. Increasing bacterial resistance against antibiotics demands for innovative strategies for therapeutic intervention. Methodology/Principal Findings We present a method for structure-based virtual screening that is based on the comprehensive prediction of ligand binding sites on a protein model and automated construction of a ligand-receptor interaction map. Pharmacophoric features of the map are clustered and transformed in a correlation vector (‘virtual ligand’) for rapid virtual screening of compound databases. This computer-based technique was validated for 18 different targets of pharmaceutical interest in a retrospective screening experiment. Prospective screening for inhibitory agents was performed for the protease HtrA from the human pathogen H. pylori using a homology model of the target protein. Among 22 tested compounds six block E-cadherin cleavage by HtrA in vitro and result in reduced scattering and wound healing of gastric epithelial cells, thereby preventing bacterial infiltration of the epithelium. Conclusions/Significance This study demonstrates that receptor-based virtual screening with a permissive (‘fuzzy’) pharmacophore model can help identify small bioactive agents for combating bacterial infection. PMID:21483848
DOE Office of Scientific and Technical Information (OSTI.GOV)
Takamiya, Mari; Discovery Technology Laboratories, Sohyaku, Innovative Research Division, Mitsubishi Tanabe Pharma Corporation, Kawagishi, Toda-shi, Saitama; Sakurai, Masaaki
A high-throughput RapidFire mass spectrometry assay is described for elongation of very long-chain fatty acids family 6 (Elovl6). Elovl6 is a microsomal enzyme that regulates the elongation of C12-16 saturated and monounsaturated fatty acids. Elovl6 may be a new therapeutic target for fat metabolism disorders such as obesity, type 2 diabetes, and nonalcoholic steatohepatitis. To identify new Elovl6 inhibitors, we developed a high-throughput fluorescence screening assay in 1536-well format. However, a number of false positives caused by fluorescent interference have been identified. To pick up the real active compounds among the primary hits from the fluorescence assay, we developed amore » RapidFire mass spectrometry assay and a conventional radioisotope assay. These assays have the advantage of detecting the main products directly without using fluorescent-labeled substrates. As a result, 276 compounds (30%) of the primary hits (921 compounds) in a fluorescence ultra-high-throughput screening method were identified as common active compounds in these two assays. It is concluded that both methods are very effective to eliminate false positives. Compared with the radioisotope method using an expensive {sup 14}C-labeled substrate, the RapidFire mass spectrometry method using unlabeled substrates is a high-accuracy, high-throughput method. In addition, some of the hit compounds selected from the screening inhibited cellular fatty acid elongation in HEK293 cells expressing Elovl6 transiently. This result suggests that these compounds may be promising lead candidates for therapeutic drugs. Ultra-high-throughput fluorescence screening followed by a RapidFire mass spectrometry assay was a suitable strategy for lead discovery against Elovl6. - Highlights: • A novel assay for elongation of very-long-chain fatty acids 6 (Elovl6) is proposed. • RapidFire mass spectrometry (RF-MS) assay is useful to select real screening hits. • RF-MS assay is proved to be beneficial because of its high-throughput and accuracy. • A combination of fluorescent and RF-MS assays is effective for Elovl6 inhibitors.« less
Scaffold-Focused Virtual Screening: Prospective Application to the Discovery of TTK Inhibitors
2013-01-01
We describe and apply a scaffold-focused virtual screen based upon scaffold trees to the mitotic kinase TTK (MPS1). Using level 1 of the scaffold tree, we perform both 2D and 3D similarity searches between a query scaffold and a level 1 scaffold library derived from a 2 million compound library; 98 compounds from 27 unique top-ranked level 1 scaffolds are selected for biochemical screening. We show that this scaffold-focused virtual screen prospectively identifies eight confirmed active compounds that are structurally differentiated from the query compound. In comparison, 100 compounds were selected for biochemical screening using a virtual screen based upon whole molecule similarity resulting in 12 confirmed active compounds that are structurally similar to the query compound. We elucidated the binding mode for four of the eight confirmed scaffold hops to TTK by determining their protein–ligand crystal structures; each represents a ligand-efficient scaffold for inhibitor design. PMID:23672464
DOE Office of Scientific and Technical Information (OSTI.GOV)
Nicolae, Bogdan; Riteau, Pierre; Keahey, Kate
Storage elasticity on IaaS clouds is a crucial feature in the age of data-intensive computing, especially when considering fluctuations of I/O throughput. This paper provides a transparent solution that automatically boosts I/O bandwidth during peaks for underlying virtual disks, effectively avoiding over-provisioning without performance loss. The authors' proposal relies on the idea of leveraging short-lived virtual disks of better performance characteristics (and thus more expensive) to act during peaks as a caching layer for the persistent virtual disks where the application data is stored. Furthermore, they introduce a performance and cost prediction methodology that can be used both independently tomore » estimate in advance what trade-off between performance and cost is possible, as well as an optimization technique that enables better cache size selection to meet the desired performance level with minimal cost. The authors demonstrate the benefits of their proposal both for microbenchmarks and for two real-life applications using large-scale experiments.« less
HPPD: ligand- and target-based virtual screening on a herbicide target.
López-Ramos, Miriam; Perruccio, Francesca
2010-05-24
Hydroxyphenylpyruvate dioxygenase (HPPD) has proven to be a very successful target for the development of herbicides with bleaching properties, and today HPPD inhibitors are well established in the agrochemical market. Syngenta has a long history of HPPD-inhibitor research, and HPPD was chosen as a case study for the validation of diverse ligand- and target-based virtual screening approaches to identify compounds with inhibitory properties. Two-dimensional extended connectivity fingerprints, three-dimensional shape-based tools (ROCS, EON, and Phase-shape) and a pharmacophore approach (Phase) were used as ligand-based methods; Glide and Gold were used as target-based. Both the virtual screening utility and the scaffold-hopping ability of the screening tools were assessed. Particular emphasis was put on the specific pitfalls to take into account for the design of a virtual screening campaign in an agrochemical context, as compared to a pharmaceutical environment.
A Novel Approach for Efficient Pharmacophore-based Virtual Screening: Method and Applications
Dror, Oranit; Schneidman-Duhovny, Dina; Inbar, Yuval; Nussinov, Ruth; Wolfson, Haim J.
2009-01-01
Virtual screening is emerging as a productive and cost-effective technology in rational drug design for the identification of novel lead compounds. An important model for virtual screening is the pharmacophore. Pharmacophore is the spatial configuration of essential features that enable a ligand molecule to interact with a specific target receptor. In the absence of a known receptor structure, a pharmacophore can be identified from a set of ligands that have been observed to interact with the target receptor. Here, we present a novel computational method for pharmacophore detection and virtual screening. The pharmacophore detection module is able to: (i) align multiple flexible ligands in a deterministic manner without exhaustive enumeration of the conformational space, (ii) detect subsets of input ligands that may bind to different binding sites or have different binding modes, (iii) address cases where the input ligands have different affinities by defining weighted pharmacophores based on the number of ligands that share them, and (iv) automatically select the most appropriate pharmacophore candidates for virtual screening. The algorithm is highly efficient, allowing a fast exploration of the chemical space by virtual screening of huge compound databases. The performance of PharmaGist was successfully evaluated on a commonly used dataset of G-Protein Coupled Receptor alpha1A. Additionally, a large-scale evaluation using the DUD (directory of useful decoys) dataset was performed. DUD contains 2950 active ligands for 40 different receptors, with 36 decoy compounds for each active ligand. PharmaGist enrichment rates are comparable with other state-of-the-art tools for virtual screening. Availability The software is available for download. A user-friendly web interface for pharmacophore detection is available at http://bioinfo3d.cs.tau.ac.il/PharmaGist. PMID:19803502
Kirchmair, Johannes; Markt, Patrick; Distinto, Simona; Wolber, Gerhard; Langer, Thierry
2008-01-01
Within the last few years a considerable amount of evaluative studies has been published that investigate the performance of 3D virtual screening approaches. Thereby, in particular assessments of protein-ligand docking are facing remarkable interest in the scientific community. However, comparing virtual screening approaches is a non-trivial task. Several publications, especially in the field of molecular docking, suffer from shortcomings that are likely to affect the significance of the results considerably. These quality issues often arise from poor study design, biasing, by using improper or inexpressive enrichment descriptors, and from errors in interpretation of the data output. In this review we analyze recent literature evaluating 3D virtual screening methods, with focus on molecular docking. We highlight problematic issues and provide guidelines on how to improve the quality of computational studies. Since 3D virtual screening protocols are in general assessed by their ability to discriminate between active and inactive compounds, we summarize the impact of the composition and preparation of test sets on the outcome of evaluations. Moreover, we investigate the significance of both classic enrichment parameters and advanced descriptors for the performance of 3D virtual screening methods. Furthermore, we review the significance and suitability of RMSD as a measure for the accuracy of protein-ligand docking algorithms and of conformational space sub sampling algorithms.
When drug discovery meets web search: Learning to Rank for ligand-based virtual screening.
Zhang, Wei; Ji, Lijuan; Chen, Yanan; Tang, Kailin; Wang, Haiping; Zhu, Ruixin; Jia, Wei; Cao, Zhiwei; Liu, Qi
2015-01-01
The rapid increase in the emergence of novel chemical substances presents a substantial demands for more sophisticated computational methodologies for drug discovery. In this study, the idea of Learning to Rank in web search was presented in drug virtual screening, which has the following unique capabilities of 1). Applicable of identifying compounds on novel targets when there is not enough training data available for these targets, and 2). Integration of heterogeneous data when compound affinities are measured in different platforms. A standard pipeline was designed to carry out Learning to Rank in virtual screening. Six Learning to Rank algorithms were investigated based on two public datasets collected from Binding Database and the newly-published Community Structure-Activity Resource benchmark dataset. The results have demonstrated that Learning to rank is an efficient computational strategy for drug virtual screening, particularly due to its novel use in cross-target virtual screening and heterogeneous data integration. To the best of our knowledge, we have introduced here the first application of Learning to Rank in virtual screening. The experiment workflow and algorithm assessment designed in this study will provide a standard protocol for other similar studies. All the datasets as well as the implementations of Learning to Rank algorithms are available at http://www.tongji.edu.cn/~qiliu/lor_vs.html. Graphical AbstractThe analogy between web search and ligand-based drug discovery.
Rapid 2,2'-bicinchoninic-based xylanase assay compatible with high throughput screening
William R. Kenealy; Thomas W. Jeffries
2003-01-01
High-throughput screening requires simple assays that give reliable quantitative results. A microplate assay was developed for reducing sugar analysis that uses a 2,2'-bicinchoninic-based protein reagent. Endo-1,4-â-D-xylanase activity against oat spelt xylan was detected at activities of 0.002 to 0.011 IU ml−1. The assay is linear for sugar...
Fang, Hui; Xiao, Qing; Wu, Fanghui; Floreancig, Paul E.; Weber, Stephen G.
2010-01-01
A high-throughput screening system for homogeneous catalyst discovery has been developed by integrating a continuous-flow capillary-based microreactor with ultra-high pressure liquid chromatography (UHPLC) for fast online analysis. Reactions are conducted in distinct and stable zones in a flow stream that allows for time and temperature regulation. UHPLC detection at high temperature allows high throughput online determination of substrate, product, and byproduct concentrations. We evaluated the efficacies of a series of soluble acid catalysts for an intramolecular Friedel-Crafts addition into an acyliminium ion intermediate within one day and with minimal material investment. The effects of catalyst loading, reaction time, and reaction temperature were also screened. This system exhibited high reproducibility for high-throughput catalyst screening and allowed several acid catalysts for the reaction to be identified. Major side products from the reactions were determined through off-line mass spectrometric detection. Er(OTf)3, the catalyst that showed optimal efficiency in the screening, was shown to be effective at promoting the cyclization reaction on a preparative scale. PMID:20666502
Rioualen, Claire; Da Costa, Quentin; Chetrit, Bernard; Charafe-Jauffret, Emmanuelle; Ginestier, Christophe
2017-01-01
High-throughput RNAi screenings (HTS) allow quantifying the impact of the deletion of each gene in any particular function, from virus-host interactions to cell differentiation. However, there has been less development for functional analysis tools dedicated to RNAi analyses. HTS-Net, a network-based analysis program, was developed to identify gene regulatory modules impacted in high-throughput screenings, by integrating transcription factors-target genes interaction data (regulome) and protein-protein interaction networks (interactome) on top of screening z-scores. HTS-Net produces exhaustive HTML reports for results navigation and exploration. HTS-Net is a new pipeline for RNA interference screening analyses that proves better performance than simple gene rankings by z-scores, by re-prioritizing genes and replacing them in their biological context, as shown by the three studies that we reanalyzed. Formatted input data for the three studied datasets, source code and web site for testing the system are available from the companion web site at http://htsnet.marseille.inserm.fr/. We also compared our program with existing algorithms (CARD and hotnet2). PMID:28949986
Wang, Guangliang; Rajpurohit, Surendra K; Delaspre, Fabien; Walker, Steven L; White, David T; Ceasrine, Alexis; Kuruvilla, Rejji; Li, Ruo-jing; Shim, Joong S; Liu, Jun O; Parsons, Michael J; Mumm, Jeff S
2015-01-01
Whole-organism chemical screening can circumvent bottlenecks that impede drug discovery. However, in vivo screens have not attained throughput capacities possible with in vitro assays. We therefore developed a method enabling in vivo high-throughput screening (HTS) in zebrafish, termed automated reporter quantification in vivo (ARQiv). In this study, ARQiv was combined with robotics to fully actualize whole-organism HTS (ARQiv-HTS). In a primary screen, this platform quantified cell-specific fluorescent reporters in >500,000 transgenic zebrafish larvae to identify FDA-approved (Federal Drug Administration) drugs that increased the number of insulin-producing β cells in the pancreas. 24 drugs were confirmed as inducers of endocrine differentiation and/or stimulators of β-cell proliferation. Further, we discovered novel roles for NF-κB signaling in regulating endocrine differentiation and for serotonergic signaling in selectively stimulating β-cell proliferation. These studies demonstrate the power of ARQiv-HTS for drug discovery and provide unique insights into signaling pathways controlling β-cell mass, potential therapeutic targets for treating diabetes. DOI: http://dx.doi.org/10.7554/eLife.08261.001 PMID:26218223
High Throughput Screening for Inhibitors of Mycobacterium tuberculosis H37Rv
ANANTHAN, SUBRAMANIAM; FAALEOLEA, ELLEN R.; GOLDMAN, ROBERT C.; HOBRATH, JUDITH V.; KWONG, CECIL D.; LAUGHON, BARBARA E.; MADDRY, JOSEPH A.; MEHTA, ALKA; RASMUSSEN, LYNN; REYNOLDS, ROBERT C.; SECRIST, JOHN A.; SHINDO, NICE; SHOWE, DUSTIN N.; SOSA, MELINDA I.; SULING, WILLIAM J.; WHITE, E. LUCILE
2009-01-01
SUMMARY There is an urgent need for the discovery and development of new antitubercular agents that target new biochemical pathways and treat drug resistant forms of the disease. One approach to addressing this need is through high throughput screening of medicinally relevant libraries against the whole bacterium in order to discover a variety of new, active scaffolds that will stimulate new biological research and drug discovery. Through the Tuberculosis Antimicrobial Acquisition and Coordinating Facility (www.taacf.org), a large, medicinally relevant chemical library was screened against M. tuberculosis strain H37Rv. The screening methods and a medicinal chemistry analysis of the results are reported herein. PMID:19758845
Kim, Sung-Hou [Moraga, CA; Kim, Rosalind [Moraga, CA; Jancarik, Jamila [Walnut Creek, CA
2012-01-31
An optimum solubility screen in which a panel of buffers and many additives are provided in order to obtain the most homogeneous and monodisperse protein condition for protein crystallization. The present methods are useful for proteins that aggregate and cannot be concentrated prior to setting up crystallization screens. A high-throughput method using the hanging-drop method and vapor diffusion equilibrium and a panel of twenty-four buffers is further provided. Using the present methods, 14 poorly behaving proteins have been screened, resulting in 11 of the proteins having highly improved dynamic light scattering results allowing concentration of the proteins, and 9 were crystallized.
High-throughput screening for bioactive components from traditional Chinese medicine.
Zhu, Yanhui; Zhang, Zhiyun; Zhang, Meng; Mais, Dale E; Wang, Ming-Wei
2010-12-01
Throughout the centuries, traditional Chinese medicine has been a rich resource in the development of new drugs. Modern drug discovery, which relies increasingly on automated high throughput screening and quick hit-to-lead development, however, is confronted with the challenges of the chemical complexity associated with natural products. New technologies for biological screening as well as library building are in great demand in order to meet the requirements. Here we review the developments in these techniques under the perspective of their applicability in natural product drug discovery. Methods in library building, component characterizing, biological evaluation, and other screening methods including NMR and X-ray diffraction are discussed.
Evaluating High Throughput Toxicokinetics and Toxicodynamics for IVIVE (WC10)
High-throughput screening (HTS) generates in vitro data for characterizing potential chemical hazard. TK models are needed to allow in vitro to in vivo extrapolation (IVIVE) to real world situations. The U.S. EPA has created a public tool (R package “httk” for high throughput tox...
Lee, Dennis; Barnes, Stephen
2010-01-01
The need for new pharmacological agents is unending. Yet the drug discovery process has changed substantially over the past decade and continues to evolve in response to new technologies. There is presently a high demand to reduce discovery time by improving specific lab disciplines and developing new technology platforms in the area of cell-based assay screening. Here we present the developmental concept and early stage testing of the Ab-Sniffer, a novel fiber optic fluorescence device for high-throughput cytotoxicity screening using an immobilized whole cell approach. The fused silica fibers are chemically functionalized with biotin to provide interaction with fluorescently labeled, streptavidin functionalized alginate-chitosan microspheres. The microspheres are also functionalized with Concanavalin A to facilitate binding to living cells. By using lymphoma cells and rituximab in an adaptation of a well-known cytotoxicity protocol we demonstrate the utility of the Ab-Sniffer for functional screening of potential drug compounds rather than indirect, non-functional screening via binding assay. The platform can be extended to any assay capable of being tied to a fluorescence response including multiple target cells in each well of a multi-well plate for high-throughput screening.
Christodoulou, Eleni G.; Yang, Hai; Lademann, Franziska; Pilarsky, Christian; Beyer, Andreas; Schroeder, Michael
2017-01-01
Mutated KRAS plays an important role in many cancers. Although targeting KRAS directly is difficult, indirect inactivation via synthetic lethal partners (SLPs) is promising. Yet to date, there are no SLPs from high-throughput RNAi screening, which are supported by multiple screens. Here, we address this problem by aggregating and ranking data over three independent high-throughput screens. We integrate rankings by minimizing the displacement and by considering established methods such as RIGER and RSA. Our meta analysis reveals COPB2 as a potential SLP of KRAS with good support from all three screens. COPB2 is a coatomer subunit and its knock down has already been linked to disabled autophagy and reduced tumor growth. We confirm COPB2 as SLP in knock down experiments on pancreas and colorectal cancer cell lines. Overall, consistent integration of high throughput data can generate candidate synthetic lethal partners, which individual screens do not uncover. Concretely, we reveal and confirm that COPB2 is a synthetic lethal partner of KRAS and hence a promising cancer target. Ligands inhibiting COPB2 may, therefore, be promising new cancer drugs. PMID:28415695
Virtual screening using molecular simulations.
Yang, Tianyi; Wu, Johnny C; Yan, Chunli; Wang, Yuanfeng; Luo, Ray; Gonzales, Michael B; Dalby, Kevin N; Ren, Pengyu
2011-06-01
Effective virtual screening relies on our ability to make accurate prediction of protein-ligand binding, which remains a great challenge. In this work, utilizing the molecular-mechanics Poisson-Boltzmann (or Generalized Born) surface area approach, we have evaluated the binding affinity of a set of 156 ligands to seven families of proteins, trypsin β, thrombin α, cyclin-dependent kinase (CDK), cAMP-dependent kinase (PKA), urokinase-type plasminogen activator, β-glucosidase A, and coagulation factor Xa. The effect of protein dielectric constant in the implicit-solvent model on the binding free energy calculation is shown to be important. The statistical correlations between the binding energy calculated from the implicit-solvent approach and experimental free energy are in the range of 0.56-0.79 across all the families. This performance is better than that of typical docking programs especially given that the latter is directly trained using known binding data whereas the molecular mechanics is based on general physical parameters. Estimation of entropic contribution remains the barrier to accurate free energy calculation. We show that the traditional rigid rotor harmonic oscillator approximation is unable to improve the binding free energy prediction. Inclusion of conformational restriction seems to be promising but requires further investigation. On the other hand, our preliminary study suggests that implicit-solvent based alchemical perturbation, which offers explicit sampling of configuration entropy, can be a viable approach to significantly improve the prediction of binding free energy. Overall, the molecular mechanics approach has the potential for medium to high-throughput computational drug discovery. Copyright © 2011 Wiley-Liss, Inc.
Customizing G Protein-coupled receptor models for structure-based virtual screening.
de Graaf, Chris; Rognan, Didier
2009-01-01
This review will focus on the construction, refinement, and validation of G Protein-coupled receptor models for the purpose of structure-based virtual screening. Practical tips and tricks derived from concrete modeling and virtual screening exercises to overcome the problems and pitfalls associated with the different steps of the receptor modeling workflow will be presented. These examples will not only include rhodopsin-like (class A), but also secretine-like (class B), and glutamate-like (class C) receptors. In addition, the review will present a careful comparative analysis of current crystal structures and their implication on homology modeling. The following themes will be discussed: i) the use of experimental anchors in guiding the modeling procedure; ii) amino acid sequence alignments; iii) ligand binding mode accommodation and binding cavity expansion; iv) proline-induced kinks in transmembrane helices; v) binding mode prediction and virtual screening by receptor-ligand interaction fingerprint scoring; vi) extracellular loop modeling; vii) virtual filtering schemes. Finally, an overview of several successful structure-based screening shows that receptor models, despite structural inaccuracies, can be efficiently used to find novel ligands.
Live Virtual Constructive Distributed Test Environment Characterization Report
NASA Technical Reports Server (NTRS)
Murphy, Jim; Kim, Sam K.
2013-01-01
This report documents message latencies observed over various Live, Virtual, Constructive, (LVC) simulation environment configurations designed to emulate possible system architectures for the Unmanned Aircraft Systems (UAS) Integration in the National Airspace System (NAS) Project integrated tests. For each configuration, four scenarios with progressively increasing air traffic loads were used to determine system throughput and bandwidth impacts on message latency.
Inter-Individual Variability in High-Throughput Risk ...
We incorporate realistic human variability into an open-source high-throughput (HT) toxicokinetics (TK) modeling framework for use in a next-generation risk prioritization approach. Risk prioritization involves rapid triage of thousands of environmental chemicals, most which have little or no existing TK data. Chemicals are prioritized based on model estimates of hazard and exposure, to decide which chemicals should be first in line for further study. Hazard may be estimated with in vitro HT screening assays, e.g., U.S. EPA’s ToxCast program. Bioactive ToxCast concentrations can be extrapolated to doses that produce equivalent concentrations in body tissues using a reverse TK approach in which generic TK models are parameterized with 1) chemical-specific parameters derived from in vitro measurements and predicted from chemical structure; and 2) with physiological parameters for a virtual population. Here we draw physiological parameters from realistic estimates of distributions of demographic and anthropometric quantities in the modern U.S. population, based on the most recent CDC NHANES data. A Monte Carlo approach, accounting for the correlation structure in physiological parameters, is used to estimate ToxCast equivalent doses for the most sensitive portion of the population. To quantify risk, ToxCast equivalent doses are compared to estimates of exposure rates based on Bayesian inferences drawn from NHANES urinary analyte biomonitoring data. The inclusion
Stereo 3D vision adapter using commercial DIY goods
NASA Astrophysics Data System (ADS)
Sakamoto, Kunio; Ohara, Takashi
2009-10-01
The conventional display can show only one screen, but it is impossible to enlarge the size of a screen, for example twice. Meanwhile the mirror supplies us with the same image but this mirror image is usually upside down. Assume that the images on an original screen and a virtual screen in the mirror are completely different and both images can be displayed independently. It would be possible to enlarge a screen area twice. This extension method enables the observers to show the virtual image plane and to enlarge a screen area twice. Although the displaying region is doubled, this virtual display could not produce 3D images. In this paper, we present an extension method using a unidirectional diffusing image screen and an improvement for displaying a 3D image using orthogonal polarized image projection.
A catalog of putative adverse outcome pathways (AOPs) that ...
A number of putative AOPs for several distinct MIEs of thyroid disruption have been formulated for amphibian metamorphosis and fish swim bladder inflation. These have been entered into the AOP knowledgebase on the OECD WIKI. The EDSP has been actively advancing high-throughput screening for chemical activity toward estrogen, androgen and thyroid targets. However, it has been recently identified that coverage for thyroid-related targets is lagging behind estrogen and androgen assay coverage. As thyroid-related medium-high throughput assays are actively being developed for inclusion in the ToxCast chemical screening program, a parallel effort is underway to characterize putative adverse outcome pathways (AOPs) specific to these thyroid-related targets. This effort is intended to provide biological and ecological context that will enhance the utility of ToxCast high throughput screening data for hazard identification.
White, David T; Eroglu, Arife Unal; Wang, Guohua; Zhang, Liyun; Sengupta, Sumitra; Ding, Ding; Rajpurohit, Surendra K; Walker, Steven L; Ji, Hongkai; Qian, Jiang; Mumm, Jeff S
2017-01-01
The zebrafish has emerged as an important model for whole-organism small-molecule screening. However, most zebrafish-based chemical screens have achieved only mid-throughput rates. Here we describe a versatile whole-organism drug discovery platform that can achieve true high-throughput screening (HTS) capacities. This system combines our automated reporter quantification in vivo (ARQiv) system with customized robotics, and is termed ‘ARQiv-HTS’. We detail the process of establishing and implementing ARQiv-HTS: (i) assay design and optimization, (ii) calculation of sample size and hit criteria, (iii) large-scale egg production, (iv) automated compound titration, (v) dispensing of embryos into microtiter plates, and (vi) reporter quantification. We also outline what we see as best practice strategies for leveraging the power of ARQiv-HTS for zebrafish-based drug discovery, and address technical challenges of applying zebrafish to large-scale chemical screens. Finally, we provide a detailed protocol for a recently completed inaugural ARQiv-HTS effort, which involved the identification of compounds that elevate insulin reporter activity. Compounds that increased the number of insulin-producing pancreatic beta cells represent potential new therapeutics for diabetic patients. For this effort, individual screening sessions took 1 week to conclude, and sessions were performed iteratively approximately every other day to increase throughput. At the conclusion of the screen, more than a half million drug-treated larvae had been evaluated. Beyond this initial example, however, the ARQiv-HTS platform is adaptable to almost any reporter-based assay designed to evaluate the effects of chemical compounds in living small-animal models. ARQiv-HTS thus enables large-scale whole-organism drug discovery for a variety of model species and from numerous disease-oriented perspectives. PMID:27831568
Herington, Jennifer L.; Swale, Daniel R.; Brown, Naoko; Shelton, Elaine L.; Choi, Hyehun; Williams, Charles H.; Hong, Charles C.; Paria, Bibhash C.; Denton, Jerod S.; Reese, Jeff
2015-01-01
The uterine myometrium (UT-myo) is a therapeutic target for preterm labor, labor induction, and postpartum hemorrhage. Stimulation of intracellular Ca2+-release in UT-myo cells by oxytocin is a final pathway controlling myometrial contractions. The goal of this study was to develop a dual-addition assay for high-throughput screening of small molecular compounds, which could regulate Ca2+-mobilization in UT-myo cells, and hence, myometrial contractions. Primary murine UT-myo cells in 384-well plates were loaded with a Ca2+-sensitive fluorescent probe, and then screened for inducers of Ca2+-mobilization and inhibitors of oxytocin-induced Ca2+-mobilization. The assay exhibited robust screening statistics (Z´ = 0.73), DMSO-tolerance, and was validated for high-throughput screening against 2,727 small molecules from the Spectrum, NIH Clinical I and II collections of well-annotated compounds. The screen revealed a hit-rate of 1.80% for agonist and 1.39% for antagonist compounds. Concentration-dependent responses of hit-compounds demonstrated an EC50 less than 10μM for 21 hit-antagonist compounds, compared to only 7 hit-agonist compounds. Subsequent studies focused on hit-antagonist compounds. Based on the percent inhibition and functional annotation analyses, we selected 4 confirmed hit-antagonist compounds (benzbromarone, dipyridamole, fenoterol hydrobromide and nisoldipine) for further analysis. Using an ex vivo isometric contractility assay, each compound significantly inhibited uterine contractility, at different potencies (IC50). Overall, these results demonstrate for the first time that high-throughput small-molecules screening of myometrial Ca2+-mobilization is an ideal primary approach for discovering modulators of uterine contractility. PMID:26600013
DOE Office of Scientific and Technical Information (OSTI.GOV)
Su, Hui
2001-01-01
Laser-induced fluorescence detection is one of the most sensitive detection techniques and it has found enormous applications in various areas. The purpose of this research was to develop detection approaches based on laser-induced fluorescence detection in two different areas, heterogeneous catalysts screening and single cell study. First, the author introduced laser-induced imaging (LIFI) as a high-throughput screening technique for heterogeneous catalysts to explore the use of this high-throughput screening technique in discovery and study of various heterogeneous catalyst systems. This scheme is based on the fact that the creation or the destruction of chemical bonds alters the fluorescence properties ofmore » suitably designed molecules. By irradiating the region immediately above the catalytic surface with a laser, the fluorescence intensity of a selected product or reactant can be imaged by a charge-coupled device (CCD) camera to follow the catalytic activity as a function of time and space. By screening the catalytic activity of vanadium pentoxide catalysts in oxidation of naphthalene, they demonstrated LIFI has good detection performance and the spatial and temporal resolution needed for high-throughput screening of heterogeneous catalysts. The sample packing density can reach up to 250 x 250 subunits/cm 2 for 40-μm wells. This experimental set-up also can screen solid catalysts via near infrared thermography detection. In the second part of this dissertation, the author used laser-induced native fluorescence coupled with capillary electrophoresis (LINF-CE) and microscope imaging to study the single cell degranulation. On the basis of good temporal correlation with events observed through an optical microscope, they have identified individual peaks in the fluorescence electropherograms as serotonin released from the granular core on contact with the surrounding fluid.« less
The Adverse Outcome Pathway (AOP) framework provides a systematic way to describe linkages between molecular and cellular processes and organism or population level effects. The current AOP assembly methods however, are inefficient. Our goal is to generate computationally-pr...
Computational fragment-based screening using RosettaLigand: the SAMPL3 challenge
NASA Astrophysics Data System (ADS)
Kumar, Ashutosh; Zhang, Kam Y. J.
2012-05-01
SAMPL3 fragment based virtual screening challenge provides a valuable opportunity for researchers to test their programs, methods and screening protocols in a blind testing environment. We participated in SAMPL3 challenge and evaluated our virtual fragment screening protocol, which involves RosettaLigand as the core component by screening a 500 fragments Maybridge library against bovine pancreatic trypsin. Our study reaffirmed that the real test for any virtual screening approach would be in a blind testing environment. The analyses presented in this paper also showed that virtual screening performance can be improved, if a set of known active compounds is available and parameters and methods that yield better enrichment are selected. Our study also highlighted that to achieve accurate orientation and conformation of ligands within a binding site, selecting an appropriate method to calculate partial charges is important. Another finding is that using multiple receptor ensembles in docking does not always yield better enrichment than individual receptors. On the basis of our results and retrospective analyses from SAMPL3 fragment screening challenge we anticipate that chances of success in a fragment screening process could be increased significantly with careful selection of receptor structures, protein flexibility, sufficient conformational sampling within binding pocket and accurate assignment of ligand and protein partial charges.
McClure, Sean M; Ahl, Patrick L; Blue, Jeffrey T
2018-03-05
The purpose was to evaluate DSF for high throughput screening of protein thermal stability (unfolding/ aggregation) across a wide range of formulations. Particular focus was exploring PROTEOSTAT® - a commercially available fluorescent rotor dye - for detection of aggregation in surfactant containing formulations. Commonly used hydrophobic dyes (e.g. SYPRO™ Orange) interact with surfactants, complicating DSF measurements. CRM197 formulations were prepared and analyzed in standard 96-well plate rT-PCR system, using SYPRO™ Orange and PROTEOSTAT® dyes. Orthogonal techniques (DLS and IPF) are employed to confirm unfolding/aggregation in selected formulations. Selected formulations are subjected to non-thermal stresses (stirring and shaking) in plate based format to characterize aggregation with PROTEOSTAT®. Agreement is observed between SYPRO™ Orange (unfolding) and PROTEOSTAT® (aggregation) DSF melt temperatures across wide range of non-surfactant formulations. PROTEOSTAT® can clearly detect temperature induced aggregation in low concentration (0.2 mg/mL) CRM197 formulations containing surfactant. PROTEOSTAT® can be used to explore aggregation due to non-thermal stresses in plate based format amenable to high throughput screening. DSF measurements with complementary extrinsic dyes (PROTEOSTAT®, SYPRO™ Orange) are suitable for high throughput screening of antigen thermal stability, across a wide range of relevant formulation conditions - including surfactants -with standard, plate based rT-PCR instrumentation.
NASA Astrophysics Data System (ADS)
Polgár, Tímea; Menyhárd, Dóra K.; Keserű, György M.
2007-09-01
An effective virtual screening protocol was developed against an extended active site of CYP2C9, which was derived from X-ray structures complexed with flubiprofen and S-warfarin. Virtual screening has been effectively supported by our structure-based pharmacophore model. Importance of hot residues identified by mutation data and structural analysis was first estimated in an enrichment study. Key role of Arg108 and Phe114 in ligand binding was also underlined. Our screening protocol successfully identified 76% of known CYP2C9 ligands in the top 1% of the ranked database resulting 76-fold enrichment relative to random situation. Relevance of the protocol was further confirmed in selectivity studies, when 89% of CYP2C9 ligands were retrieved from a mixture of CYP2C9 and CYP2C8 ligands, while only 22% of CYP2C8 ligands were found applying the structure-based pharmacophore constraints. Moderate discrimination of CYP2C9 ligands from CYP2C18 and CYP2C19 ligands could also be achieved extending the application domain of our virtual screening protocol for the entire CYP2C family. Our findings further demonstrate the existence of an active site comprising of at least two binding pockets and strengthens the need of involvement of protein flexibility in virtual screening.
High throughput toxicology programs, such as ToxCast and Tox21, have provided biological effects data for thousands of chemicals at multiple concentrations. Compared to traditional, whole-organism approaches, high throughput assays are rapid and cost-effective, yet they generall...
The U.S. EPA, under its ExpoCast program, is developing high-throughput near-field modeling methods to estimate human chemical exposure and to provide real-world context to high-throughput screening (HTS) hazard data. These novel modeling methods include reverse methods to infer ...
Sense of presence and anxiety during virtual social interactions between a human and virtual humans.
Morina, Nexhmedin; Brinkman, Willem-Paul; Hartanto, Dwi; Emmelkamp, Paul M G
2014-01-01
Virtual reality exposure therapy (VRET) has been shown to be effective in treatment of anxiety disorders. Yet, there is lack of research on the extent to which interaction between the individual and virtual humans can be successfully implanted to increase levels of anxiety for therapeutic purposes. This proof-of-concept pilot study aimed at examining levels of the sense of presence and anxiety during exposure to virtual environments involving social interaction with virtual humans and using different virtual reality displays. A non-clinical sample of 38 participants was randomly assigned to either a head-mounted display (HMD) with motion tracker and sterescopic view condition or a one-screen projection-based virtual reality display condition. Participants in both conditions engaged in free speech dialogues with virtual humans controlled by research assistants. It was hypothesized that exposure to virtual social interactions will elicit moderate levels of sense of presence and anxiety in both groups. Further it was expected that participants in the HMD condition will report higher scores of sense of presence and anxiety than participants in the one-screen projection-based display condition. Results revealed that in both conditions virtual social interactions were associated with moderate levels of sense of presence and anxiety. Additionally, participants in the HMD condition reported significantly higher levels of presence than those in the one-screen projection-based display condition (p = .001). However, contrary to the expectations neither the average level of anxiety nor the highest level of anxiety during exposure to social virtual environments differed between the groups (p = .97 and p = .75, respectively). The findings suggest that virtual social interactions can be successfully applied in VRET to enhance sense of presence and anxiety. Furthermore, our results indicate that one-screen projection-based displays can successfully activate levels of anxiety in social virtual environments. The outcome can prove helpful in using low-cost projection-based virtual reality environments for treating individuals with social phobia.
A rapid enzymatic assay for high-throughput screening of adenosine-producing strains
Dong, Huina; Zu, Xin; Zheng, Ping; Zhang, Dawei
2015-01-01
Adenosine is a major local regulator of tissue function and industrially useful as precursor for the production of medicinal nucleoside substances. High-throughput screening of adenosine overproducers is important for industrial microorganism breeding. An enzymatic assay of adenosine was developed by combined adenosine deaminase (ADA) with indophenol method. The ADA catalyzes the cleavage of adenosine to inosine and NH3, the latter can be accurately determined by indophenol method. The assay system was optimized to deliver a good performance and could tolerate the addition of inorganic salts and many nutrition components to the assay mixtures. Adenosine could be accurately determined by this assay using 96-well microplates. Spike and recovery tests showed that this assay can accurately and reproducibly determine increases in adenosine in fermentation broth without any pretreatment to remove proteins and potentially interfering low-molecular-weight molecules. This assay was also applied to high-throughput screening for high adenosine-producing strains. The high selectivity and accuracy of the ADA assay provides rapid and high-throughput analysis of adenosine in large numbers of samples. PMID:25580842
Ion channel drug discovery and research: the automated Nano-Patch-Clamp technology.
Brueggemann, A; George, M; Klau, M; Beckler, M; Steindl, J; Behrends, J C; Fertig, N
2004-01-01
Unlike the genomics revolution, which was largely enabled by a single technological advance (high throughput sequencing), rapid advancement in proteomics will require a broader effort to increase the throughput of a number of key tools for functional analysis of different types of proteins. In the case of ion channels -a class of (membrane) proteins of great physiological importance and potential as drug targets- the lack of adequate assay technologies is felt particularly strongly. The available, indirect, high throughput screening methods for ion channels clearly generate insufficient information. The best technology to study ion channel function and screen for compound interaction is the patch clamp technique, but patch clamping suffers from low throughput, which is not acceptable for drug screening. A first step towards a solution is presented here. The nano patch clamp technology, which is based on a planar, microstructured glass chip, enables automatic whole cell patch clamp measurements. The Port-a-Patch is an automated electrophysiology workstation, which uses planar patch clamp chips. This approach enables high quality and high content ion channel and compound evaluation on a one-cell-at-a-time basis. The presented automation of the patch process and its scalability to an array format are the prerequisites for any higher throughput electrophysiology instruments.
High-Throughput Toxicity Testing: New Strategies for ...
In recent years, the food industry has made progress in improving safety testing methods focused on microbial contaminants in order to promote food safety. However, food industry toxicologists must also assess the safety of food-relevant chemicals including pesticides, direct additives, and food contact substances. With the rapidly growing use of new food additives, as well as innovation in food contact substance development, an interest in exploring the use of high-throughput chemical safety testing approaches has emerged. Currently, the field of toxicology is undergoing a paradigm shift in how chemical hazards can be evaluated. Since there are tens of thousands of chemicals in use, many of which have little to no hazard information and there are limited resources (namely time and money) for testing these chemicals, it is necessary to prioritize which chemicals require further safety testing to better protect human health. Advances in biochemistry and computational toxicology have paved the way for animal-free (in vitro) high-throughput screening which can characterize chemical interactions with highly specific biological processes. Screening approaches are not novel; in fact, quantitative high-throughput screening (qHTS) methods that incorporate dose-response evaluation have been widely used in the pharmaceutical industry. For toxicological evaluation and prioritization, it is the throughput as well as the cost- and time-efficient nature of qHTS that makes it
Chen, Can; Wang, Ting; Wu, Fengbo; Huang, Wei; He, Gu; Ouyang, Liang; Xiang, Mingli; Peng, Cheng; Jiang, Qinglin
2014-01-01
Compared with normal differentiated cells, cancer cells upregulate the expression of pyruvate kinase isozyme M2 (PKM2) to support glycolytic intermediates for anabolic processes, including the synthesis of nucleic acids, amino acids, and lipids. In this study, a combination of the structure-based pharmacophore modeling and a hybrid protocol of virtual screening methods comprised of pharmacophore model-based virtual screening, docking-based virtual screening, and in silico ADMET (absorption, distribution, metabolism, excretion and toxicity) analysis were used to retrieve novel PKM2 activators from commercially available chemical databases. Tetrahydroquinoline derivatives were identified as potential scaffolds of PKM2 activators. Thus, the hybrid virtual screening approach was applied to screen the focused tetrahydroquinoline derivatives embedded in the ZINC database. Six hit compounds were selected from the final hits and experimental studies were then performed. Compound 8 displayed a potent inhibitory effect on human lung cancer cells. Following treatment with Compound 8, cell viability, apoptosis, and reactive oxygen species (ROS) production were examined in A549 cells. Finally, we evaluated the effects of Compound 8 on mice xenograft tumor models in vivo. These results may provide important information for further research on novel PKM2 activators as antitumor agents. PMID:25214764
Screening for colon cancer; Colonoscopy - screening; Sigmoidoscopy - screening; Virtual colonoscopy - screening; Fecal immunochemical test; Stool DNA test; sDNA test; Colorectal cancer - screening; Rectal ...
Flachner, Beáta; Hajdú, István; Dobi, Krisztina; Lorincz, Zsolt; Cseh, Sándor; Dormán, György
2013-01-01
Target focused libraries can be rapidly selected by 2D virtual screening methods from multimillion compounds' repositories if structures of active compounds are available. In the present study a multi-step virtual and in vitro screening cascade is reported to select Melanin Concentrating Hormone Receptor-1 (MCHR1) antagonists. The 2D similarity search combined with physicochemical parameter filtering is suitable for selecting candidates from multimillion compounds' repository. The seeds of the first round virtual screening were collected from the literature and commercial databases, while the seeds of the second round were the hits of the first round. In vitro screening underlined the efficiency of our approach, as in the second screening round the hit rate (8.6 %) significantly improved compared to the first round (1.9%), reaching the antagonist activity even below 10 nM.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Garzoglio, Gabriele
The Fermilab Grid and Cloud Computing Department and the KISTI Global Science experimental Data hub Center propose a joint project. The goals are to enable scientific workflows of stakeholders to run on multiple cloud resources by use of (a) Virtual Infrastructure Automation and Provisioning, (b) Interoperability and Federat ion of Cloud Resources , and (c) High-Throughput Fabric Virtualization. This is a matching fund project in which Fermilab and KISTI will contribute equal resources .
Architectural design and simulation of a virtual memory
NASA Technical Reports Server (NTRS)
Kwok, G.; Chu, Y.
1971-01-01
Virtual memory is an imaginary main memory with a very large capacity which the programmer has at his disposal. It greatly contributes to the solution of the dynamic storage allocation problem. The architectural design of a virtual memory is presented which implements by hardware the idea of queuing and scheduling the page requests to a paging drum in such a way that the access of the paging drum is increased many times. With the design, an increase of up to 16 times in page transfer rate is achievable when the virtual memory is heavily loaded. This in turn makes feasible a great increase in the system throughput.
Automated Analysis of siRNA Screens of Virus Infected Cells Based on Immunofluorescence Microscopy
NASA Astrophysics Data System (ADS)
Matula, Petr; Kumar, Anil; Wörz, Ilka; Harder, Nathalie; Erfle, Holger; Bartenschlager, Ralf; Eils, Roland; Rohr, Karl
We present an image analysis approach as part of a high-throughput microscopy screening system based on cell arrays for the identification of genes involved in Hepatitis C and Dengue virus replication. Our approach comprises: cell nucleus segmentation, quantification of virus replication level in cells, localization of regions with transfected cells, cell classification by infection status, and quality assessment of an experiment. The approach is fully automatic and has been successfully applied to a large number of cell array images from screening experiments. The experimental results show a good agreement with the expected behavior of positive as well as negative controls and encourage the application to screens from further high-throughput experiments.
A Simple Method for High Throughput Chemical Screening in Caenorhabditis Elegans
Lucanic, Mark; Garrett, Theo; Gill, Matthew S.; Lithgow, Gordon J.
2018-01-01
Caenorhabditis elegans is a useful organism for testing chemical effects on physiology. Whole organism small molecule screens offer significant advantages for identifying biologically active chemical structures that can modify complex phenotypes such as lifespan. Described here is a simple protocol for producing hundreds of 96-well culture plates with fairly consistent numbers of C. elegans in each well. Next, we specified how to use these cultures to screen thousands of chemicals for effects on the lifespan of the nematode C. elegans. This protocol makes use of temperature sensitive sterile strains, agar plate conditions, and simple animal handling to facilitate the rapid and high throughput production of synchronized animal cultures for screening. PMID:29630057
McDonald, Peter R; Roy, Anuradha; Chaguturu, Rathnam
2011-07-01
The University of Kansas High-Throughput Screening (KU HTS) core is a state-of-the-art drug-discovery facility with an entrepreneurial open-service policy, which provides centralized resources supporting public- and private-sector research initiatives. The KU HTS core was established in 2002 at the University of Kansas with support from an NIH grant and the state of Kansas. It collaborates with investigators from national and international academic, nonprofit and pharmaceutical organizations in executing HTS-ready assay development and screening of chemical libraries for target validation, probe selection, hit identification and lead optimization. This is part two of a contribution from the KU HTS laboratory.
Daher, Ahmad; de Groot, John
2018-01-01
Tumor heterogeneity is a major factor in glioblastoma's poor response to therapy and seemingly inevitable recurrence. Only two glioblastoma drugs have received Food and Drug Administration approval since 1998, highlighting the urgent need for new therapies. Profiling "omics" analyses have helped characterize glioblastoma molecularly and have thus identified multiple molecular targets for precision medicine. These molecular targets have influenced clinical trial design; many "actionable" mutation-focused trials are underway, but because they have not yet led to therapeutic breakthroughs, new strategies for treating glioblastoma, especially those with a pharmacological functional component, remain in high demand. In that regard, high-throughput screening that allows for expedited preclinical drug testing and the use of GBM models that represent tumor heterogeneity more accurately than traditional cancer cell lines is necessary to maximize the successful translation of agents into the clinic. High-throughput screening has been successfully used in the testing, discovery, and validation of potential therapeutics in various cancer models, but it has not been extensively utilized in glioblastoma models. In this report, we describe the basic aspects of high-throughput screening and propose a modified high-throughput screening model in which ex vivo and in vivo drug testing is complemented by post-screening pharmacological, pan-omic analysis to expedite anti-glioma drugs' preclinical testing and develop predictive biomarker datasets that can aid in personalizing glioblastoma therapy and inform clinical trial design. Copyright © 2017 Elsevier Inc. All rights reserved.
Lagorce, David; Pencheva, Tania; Villoutreix, Bruno O; Miteva, Maria A
2009-11-13
Discovery of new bioactive molecules that could enter drug discovery programs or that could serve as chemical probes is a very complex and costly endeavor. Structure-based and ligand-based in silico screening approaches are nowadays extensively used to complement experimental screening approaches in order to increase the effectiveness of the process and facilitating the screening of thousands or millions of small molecules against a biomolecular target. Both in silico screening methods require as input a suitable chemical compound collection and most often the 3D structure of the small molecules has to be generated since compounds are usually delivered in 1D SMILES, CANSMILES or in 2D SDF formats. Here, we describe the new open source program DG-AMMOS which allows the generation of the 3D conformation of small molecules using Distance Geometry and their energy minimization via Automated Molecular Mechanics Optimization. The program is validated on the Astex dataset, the ChemBridge Diversity database and on a number of small molecules with known crystal structures extracted from the Cambridge Structural Database. A comparison with the free program Balloon and the well-known commercial program Omega generating the 3D of small molecules is carried out. The results show that the new free program DG-AMMOS is a very efficient 3D structure generator engine. DG-AMMOS provides fast, automated and reliable access to the generation of 3D conformation of small molecules and facilitates the preparation of a compound collection prior to high-throughput virtual screening computations. The validation of DG-AMMOS on several different datasets proves that generated structures are generally of equal quality or sometimes better than structures obtained by other tested methods.
In silico identification of potential inhibitors targeting Streptococcus mutans sortase A
Luo, Hao; Liang, Dan-Feng; Bao, Min-Yue; Sun, Rong; Li, Yuan-Yuan; Li, Jian-Zong; Wang, Xin; Lu, Kai-Min; Bao, Jin-Ku
2017-01-01
Dental caries is one of the most common chronic diseases and is caused by acid fermentation of bacteria adhered to the teeth. Streptococcus mutans (S. mutans) utilizes sortase A (SrtA) to anchor surface proteins to the cell wall and forms a biofilm to facilitate its adhesion to the tooth surface. Some plant natural products, especially several flavonoids, are effective inhibitors of SrtA. However, given the limited number of inhibitors and the development of drug resistance, the discovery of new inhibitors is urgent. Here, the high-throughput virtual screening approach was performed to identify new potential inhibitors of S. mutans SrtA. Two libraries were used for screening, and nine compounds that had the lowest scores were chosen for further molecular dynamics simulation, binding free energy analysis and absorption, distribution, metabolism, excretion and toxicity (ADMET) properties analysis. The results revealed that several similar compounds composed of benzofuran, thiadiazole and pyrrole, which exhibited good affinities and appropriate pharmacokinetic parameters, were potential inhibitors to impede the catalysis of SrtA. In addition, the carbonyl of these compounds can have a key role in the inhibition mechanism. These findings can provide a new strategy for microbial infection disease therapy. PMID:28358034
High throughput system for magnetic manipulation of cells, polymers, and biomaterials
Spero, Richard Chasen; Vicci, Leandra; Cribb, Jeremy; Bober, David; Swaminathan, Vinay; O’Brien, E. Timothy; Rogers, Stephen L.; Superfine, R.
2008-01-01
In the past decade, high throughput screening (HTS) has changed the way biochemical assays are performed, but manipulation and mechanical measurement of micro- and nanoscale systems have not benefited from this trend. Techniques using microbeads (particles ∼0.1–10 μm) show promise for enabling high throughput mechanical measurements of microscopic systems. We demonstrate instrumentation to magnetically drive microbeads in a biocompatible, multiwell magnetic force system. It is based on commercial HTS standards and is scalable to 96 wells. Cells can be cultured in this magnetic high throughput system (MHTS). The MHTS can apply independently controlled forces to 16 specimen wells. Force calibrations demonstrate forces in excess of 1 nN, predicted force saturation as a function of pole material, and powerlaw dependence of F∼r−2.7±0.1. We employ this system to measure the stiffness of SR2+ Drosophila cells. MHTS technology is a key step toward a high throughput screening system for micro- and nanoscale biophysical experiments. PMID:19044357
Sarvagalla, Sailu; Singh, Vivek Kumar; Ke, Yi-Yu; Shiao, Hui-Yi; Lin, Wen-Hsing; Hsieh, Hsing-Pang; Hsu, John T A; Coumar, Mohane Selvaraj
2015-01-01
Furanopyrimidine 1 (IC50 = 273 nM, LE = 0.36, LELP = 10.28) was recently identified by high-throughput screening (HTS) of an in-house library (125,000 compounds) as an Aurora kinase inhibitor. Structure-based hit optimization resulted in lead molecules with in vivo efficacy in a mouse tumour xenograft model, but no oral bioavailability. This is attributed to "molecular obesity", a common problem during hit to lead evolution during which degradation of important molecular properties such as molecular weight (MW) and lipophilicity occurs. This could be effectively tackled by the right choice of hit compounds for optimization. In this regard, ligand efficiency (LE) and ligand efficiency dependent lipophilicity (LELP) indices are more often used to choose fragment-like hits for optimization. To identify hits with appropriate LE, we used a MW cut-off <250, and pyrazole structure to filter HTS library. Next, structure-based virtual screening using software (Libdock and Glide) in the Aurora A crystal structure (PDB ID: 3E5A) was carried out, and the top scoring 18 compounds tested for Aurora A enzyme inhibition. This resulted in the identification of a novel tetrahydro-pyrazolo-isoquinoline hit 7 (IC50 = 852 nM, LE = 0.44, LELP = 8.36) with fragment-like properties suitable for further hit optimization. Moreover, hit 7 was found to be selective for Aurora A (Aurora B IC50 = 35,150 nM) and the possible reasons for selectivity investigated by docking two tautomeric forms (2H- and 3H-pyrazole) of 7 in Auroras A and B (PDB ID: 4AF3) crystal structures. This docking study shows that the major 3H-pyrazole tautomer of 7 binds in Aurora A stronger than in Aurora B.
NASA Astrophysics Data System (ADS)
Sarvagalla, Sailu; Singh, Vivek Kumar; Ke, Yi-Yu; Shiao, Hui-Yi; Lin, Wen-Hsing; Hsieh, Hsing-Pang; Hsu, John T. A.; Coumar, Mohane Selvaraj
2015-01-01
Furanopyrimidine 1 (IC50 = 273 nM, LE = 0.36, LELP = 10.28) was recently identified by high-throughput screening (HTS) of an in-house library (125,000 compounds) as an Aurora kinase inhibitor. Structure-based hit optimization resulted in lead molecules with in vivo efficacy in a mouse tumour xenograft model, but no oral bioavailability. This is attributed to "molecular obesity", a common problem during hit to lead evolution during which degradation of important molecular properties such as molecular weight (MW) and lipophilicity occurs. This could be effectively tackled by the right choice of hit compounds for optimization. In this regard, ligand efficiency (LE) and ligand efficiency dependent lipophilicity (LELP) indices are more often used to choose fragment-like hits for optimization. To identify hits with appropriate LE, we used a MW cut-off <250, and pyrazole structure to filter HTS library. Next, structure-based virtual screening using software (Libdock and Glide) in the Aurora A crystal structure (PDB ID: 3E5A) was carried out, and the top scoring 18 compounds tested for Aurora A enzyme inhibition. This resulted in the identification of a novel tetrahydro-pyrazolo-isoquinoline hit 7 (IC50 = 852 nM, LE = 0.44, LELP = 8.36) with fragment-like properties suitable for further hit optimization. Moreover, hit 7 was found to be selective for Aurora A (Aurora B IC50 = 35,150 nM) and the possible reasons for selectivity investigated by docking two tautomeric forms (2 H- and 3 H-pyrazole) of 7 in Auroras A and B (PDB ID: 4AF3) crystal structures. This docking study shows that the major 3 H-pyrazole tautomer of 7 binds in Aurora A stronger than in Aurora B.
Microfluidic cell chips for high-throughput drug screening
Chi, Chun-Wei; Ahmed, AH Rezwanuddin; Dereli-Korkut, Zeynep; Wang, Sihong
2016-01-01
The current state of screening methods for drug discovery is still riddled with several inefficiencies. Although some widely used high-throughput screening platforms may enhance the drug screening process, their cost and oversimplification of cell–drug interactions pose a translational difficulty. Microfluidic cell-chips resolve many issues found in conventional HTS technology, providing benefits such as reduced sample quantity and integration of 3D cell culture physically more representative of the physiological/pathological microenvironment. In this review, we introduce the advantages of microfluidic devices in drug screening, and outline the critical factors which influence device design, highlighting recent innovations and advances in the field including a summary of commercialization efforts on microfluidic cell chips. Future perspectives of microfluidic cell devices are also provided based on considerations of present technological limitations and translational barriers. PMID:27071838
2009-09-01
onset and averaged across all excited units tested (mean ± SE). 7 SUPPLEMENTAL EXPERIMENTAL PROCEDURES Virus design and production...to baseline level 355 ± 505 ms later. The level of post -light firing did not vary with repeated light exposure (p > 0.7, paired t- test comparing...High-Throughput Screening of Therapeutic Neural Stimulation Targets: Toward Principles of Preventing and Treating Post - Traumatic Stress Disorder
Microarray Detection of Duplex and Triplex DNA Binders with DNA-Modified Gold Nanoparticles
Lytton-Jean, Abigail K. R.; Han, Min Su; Mirkin, Chad A.
2008-01-01
We have designed a chip-based assay, using microarray technology, for determining the relative binding affinities of duplex and triplex DNA binders. This assay combines the high discrimination capabilities afforded by DNA-modified Au nanoparticles with the high-throughput capabilities of DNA microarrays. The detection and screening of duplex DNA binders are important because these molecules, in many cases, are potential anticancer agents as well as toxins. Triplex DNA binders are also promising drug candidates. These molecules, in conjunction with triplex forming oligonucleotides, could potentially be used to achieve control of gene expression by interfering with transcription factors that bind to DNA. Therefore, the ability to screen for these molecules in a high-throughput fashion could dramatically improve the drug screening process. The assay reported here provides excellent discrimination between strong, intermediate, and weak duplex and triplex DNA binders in a high-throughput fashion. PMID:17614366
High-throughput strategies for the discovery and engineering of enzymes for biocatalysis.
Jacques, Philippe; Béchet, Max; Bigan, Muriel; Caly, Delphine; Chataigné, Gabrielle; Coutte, François; Flahaut, Christophe; Heuson, Egon; Leclère, Valérie; Lecouturier, Didier; Phalip, Vincent; Ravallec, Rozenn; Dhulster, Pascal; Froidevaux, Rénato
2017-02-01
Innovations in novel enzyme discoveries impact upon a wide range of industries for which biocatalysis and biotransformations represent a great challenge, i.e., food industry, polymers and chemical industry. Key tools and technologies, such as bioinformatics tools to guide mutant library design, molecular biology tools to create mutants library, microfluidics/microplates, parallel miniscale bioreactors and mass spectrometry technologies to create high-throughput screening methods and experimental design tools for screening and optimization, allow to evolve the discovery, development and implementation of enzymes and whole cells in (bio)processes. These technological innovations are also accompanied by the development and implementation of clean and sustainable integrated processes to meet the growing needs of chemical, pharmaceutical, environmental and biorefinery industries. This review gives an overview of the benefits of high-throughput screening approach from the discovery and engineering of biocatalysts to cell culture for optimizing their production in integrated processes and their extraction/purification.
Neto, A I; Correia, C R; Oliveira, M B; Rial-Hermida, M I; Alvarez-Lorenzo, C; Reis, R L; Mano, J F
2015-04-01
We propose a novel hanging spherical drop system for anchoring arrays of droplets of cell suspension based on the use of biomimetic superhydrophobic flat substrates, with controlled positional adhesion and minimum contact with a solid substrate. By facing down the platform, it was possible to generate independent spheroid bodies in a high throughput manner, in order to mimic in vivo tumour models on the lab-on-chip scale. To validate this system for drug screening purposes, the toxicity of the anti-cancer drug doxorubicin in cell spheroids was tested and compared to cells in 2D culture. The advantages presented by this platform, such as feasibility of the system and the ability to control the size uniformity of the spheroid, emphasize its potential to be used as a new low cost toolbox for high-throughput drug screening and in cell or tissue engineering.
Jacobs, K R; Guillemin, G J; Lovejoy, D B
2018-02-01
Kynurenine 3-monooxygenase (KMO) is a well-validated therapeutic target for the treatment of neurodegenerative diseases, including Alzheimer's disease (AD) and Huntington's disease (HD). This work reports a facile fluorescence-based KMO assay optimized for high-throughput screening (HTS) that achieves a throughput approximately 20-fold higher than the fastest KMO assay currently reported. The screen was run with excellent performance (average Z' value of 0.80) from 110,000 compounds across 341 plates and exceeded all statistical parameters used to describe a robust HTS assay. A subset of molecules was selected for validation by ultra-high-performance liquid chromatography, resulting in the confirmation of a novel hit with an IC 50 comparable to that of the well-described KMO inhibitor Ro-61-8048. A medicinal chemistry program is currently underway to further develop our novel KMO inhibitor scaffolds.
Lo Cicero, Alessandra; Jaskowiak, Anne-Laure; Egesipe, Anne-Laure; Tournois, Johana; Brinon, Benjamin; Pitrez, Patricia R.; Ferreira, Lino; de Sandre-Giovannoli, Annachiara; Levy, Nicolas; Nissan, Xavier
2016-01-01
Hutchinson-Gilford progeria syndrome (HGPS) is a rare fatal genetic disorder that causes systemic accelerated aging in children. Thanks to the pluripotency and self-renewal properties of induced pluripotent stem cells (iPSC), HGPS iPSC-based modeling opens up the possibility of access to different relevant cell types for pharmacological approaches. In this study, 2800 small molecules were explored using high-throughput screening, looking for compounds that could potentially reduce the alkaline phosphatase activity of HGPS mesenchymal stem cells (MSCs) committed into osteogenic differentiation. Results revealed seven compounds that normalized the osteogenic differentiation process and, among these, all-trans retinoic acid and 13-cis-retinoic acid, that also decreased progerin expression. This study highlights the potential of high-throughput drug screening using HGPS iPS-derived cells, in order to find therapeutic compounds for HGPS and, potentially, for other aging-related disorders. PMID:27739443
Lo Cicero, Alessandra; Jaskowiak, Anne-Laure; Egesipe, Anne-Laure; Tournois, Johana; Brinon, Benjamin; Pitrez, Patricia R; Ferreira, Lino; de Sandre-Giovannoli, Annachiara; Levy, Nicolas; Nissan, Xavier
2016-10-14
Hutchinson-Gilford progeria syndrome (HGPS) is a rare fatal genetic disorder that causes systemic accelerated aging in children. Thanks to the pluripotency and self-renewal properties of induced pluripotent stem cells (iPSC), HGPS iPSC-based modeling opens up the possibility of access to different relevant cell types for pharmacological approaches. In this study, 2800 small molecules were explored using high-throughput screening, looking for compounds that could potentially reduce the alkaline phosphatase activity of HGPS mesenchymal stem cells (MSCs) committed into osteogenic differentiation. Results revealed seven compounds that normalized the osteogenic differentiation process and, among these, all-trans retinoic acid and 13-cis-retinoic acid, that also decreased progerin expression. This study highlights the potential of high-throughput drug screening using HGPS iPS-derived cells, in order to find therapeutic compounds for HGPS and, potentially, for other aging-related disorders.
From Classical to High Throughput Screening Methods for Feruloyl Esterases: A Review.
Ramírez-Velasco, Lorena; Armendáriz-Ruiz, Mariana; Rodríguez-González, Jorge Alberto; Müller-Santos, Marcelo; Asaff-Torres, Ali; Mateos-Díaz, Juan Carlos
2016-01-01
Feruloyl esterases (FAEs) are a diverse group of hydrolases widely distributed in plants and microorganisms which catalyzes the cleavage and formation of ester bonds between plant cell wall polysaccharides and phenolic acids. FAEs have gained importance in biofuel, medicine and food industries due to their capability of acting on a large range of substrates for cleaving ester bonds and synthesizing highadded value molecules through esterification and transesterification reactions. During the past two decades extensive studies have been carried out on the production, characterization and classification of FAEs, however only a few reports of suitable High Throughput Screening assays for this kind of enzymes have been reported. This review is focused on a concise but complete revision of classical to High Throughput Screening methods for FAEs, highlighting its advantages and disadvantages, and finally suggesting future perspectives for this important research field.
Keenan, Martine; Alexander, Paul W; Chaplin, Jason H; Abbott, Michael J; Diao, Hugo; Wang, Zhisen; Best, Wayne M; Perez, Catherine J; Cornwall, Scott M J; Keatley, Sarah K; Thompson, R C Andrew; Charman, Susan A; White, Karen L; Ryan, Eileen; Chen, Gong; Ioset, Jean-Robert; von Geldern, Thomas W; Chatelain, Eric
2013-10-01
Inhibitors of Trypanosoma cruzi with novel mechanisms of action are urgently required to diversify the current clinical and preclinical pipelines. Increasing the number and diversity of hits available for assessment at the beginning of the discovery process will help to achieve this aim. We report the evaluation of multiple hits generated from a high-throughput screen to identify inhibitors of T. cruzi and from these studies the discovery of two novel series currently in lead optimization. Lead compounds from these series potently and selectively inhibit growth of T. cruzi in vitro and the most advanced compound is orally active in a subchronic mouse model of T. cruzi infection. High-throughput screening of novel compound collections has an important role to play in diversifying the trypanosomatid drug discovery portfolio. A new T. cruzi inhibitor series with good drug-like properties and promising in vivo efficacy has been identified through this process.
Hubble, Lee J; Cooper, James S; Sosa-Pintos, Andrea; Kiiveri, Harri; Chow, Edith; Webster, Melissa S; Wieczorek, Lech; Raguse, Burkhard
2015-02-09
Chemiresistor sensor arrays are a promising technology to replace current laboratory-based analysis instrumentation, with the advantage of facile integration into portable, low-cost devices for in-field use. To increase the performance of chemiresistor sensor arrays a high-throughput fabrication and screening methodology was developed to assess different organothiol-functionalized gold nanoparticle chemiresistors. This high-throughput fabrication and testing methodology was implemented to screen a library consisting of 132 different organothiol compounds as capping agents for functionalized gold nanoparticle chemiresistor sensors. The methodology utilized an automated liquid handling workstation for the in situ functionalization of gold nanoparticle films and subsequent automated analyte testing of sensor arrays using a flow-injection analysis system. To test the methodology we focused on the discrimination and quantitation of benzene, toluene, ethylbenzene, p-xylene, and naphthalene (BTEXN) mixtures in water at low microgram per liter concentration levels. The high-throughput methodology identified a sensor array configuration consisting of a subset of organothiol-functionalized chemiresistors which in combination with random forests analysis was able to predict individual analyte concentrations with overall root-mean-square errors ranging between 8-17 μg/L for mixtures of BTEXN in water at the 100 μg/L concentration. The ability to use a simple sensor array system to quantitate BTEXN mixtures in water at the low μg/L concentration range has direct and significant implications to future environmental monitoring and reporting strategies. In addition, these results demonstrate the advantages of high-throughput screening to improve the performance of gold nanoparticle based chemiresistors for both new and existing applications.
Yue, Jin-feng; Qiao, Guan-hua; Liu, Ni; Nan, Fa-jun; Gao, Zhao-bing
2016-01-01
Aim: To establish an improved, high-throughput screening techniques for identifying novel KCNQ2 channel activators. Methods: KCNQ2 channels were stably expressed in CHO cells (KCNQ2 cells). Thallium flux assay was used for primary screening, and 384-well automated patch-clamp IonWorks Barracuda was used for hit validation. Two validated activators were characterized using a conventional patch-clamp recording technique. Results: From a collection of 80 000 compounds, the primary screening revealed a total of 565 compounds that potentiated the fluorescence signals in thallium flux assay by more than 150%. When the 565 hits were examined in IonWorks Barracuda, 38 compounds significantly enhanced the outward currents recorded in KCNQ2 cells, and were confirmed as KCNQ2 activators. In the conventional patch-clamp recordings, two validated activators ZG1732 and ZG2083 enhanced KCNQ2 currents with EC50 values of 1.04±0.18 μmol/L and 1.37±0.06 μmol/L, respectively. Conclusion: The combination of thallium flux assay and IonWorks Barracuda assay is an efficient high-throughput screening (HTS) route for discovering KCNQ2 activators. PMID:26725738
Hassig, Christian A; Zeng, Fu-Yue; Kung, Paul; Kiankarimi, Mehrak; Kim, Sylvia; Diaz, Paul W; Zhai, Dayong; Welsh, Kate; Morshedian, Shana; Su, Ying; O'Keefe, Barry; Newman, David J; Rusman, Yudi; Kaur, Harneet; Salomon, Christine E; Brown, Susan G; Baire, Beeraiah; Michel, Andrew R; Hoye, Thomas R; Francis, Subhashree; Georg, Gunda I; Walters, Michael A; Divlianska, Daniela B; Roth, Gregory P; Wright, Amy E; Reed, John C
2014-09-01
Antiapoptotic Bcl-2 family proteins are validated cancer targets composed of six related proteins. From a drug discovery perspective, these are challenging targets that exert their cellular functions through protein-protein interactions (PPIs). Although several isoform-selective inhibitors have been developed using structure-based design or high-throughput screening (HTS) of synthetic chemical libraries, no large-scale screen of natural product collections has been reported. A competitive displacement fluorescence polarization (FP) screen of nearly 150,000 natural product extracts was conducted against all six antiapoptotic Bcl-2 family proteins using fluorochrome-conjugated peptide ligands that mimic functionally relevant PPIs. The screens were conducted in 1536-well format and displayed satisfactory overall HTS statistics, with Z'-factor values ranging from 0.72 to 0.83 and a hit confirmation rate between 16% and 64%. Confirmed active extracts were orthogonally tested in a luminescent assay for caspase-3/7 activation in tumor cells. Active extracts were resupplied, and effort toward the isolation of pure active components was initiated through iterative bioassay-guided fractionation. Several previously described altertoxins were isolated from a microbial source, and the pure compounds demonstrate activity in both Bcl-2 FP and caspase cellular assays. The studies demonstrate the feasibility of ultra-high-throughput screening using natural product sources and highlight some of the challenges associated with this approach. © 2014 Society for Laboratory Automation and Screening.
The Texas-Indiana Virtual STAR Center: Zebrafish Models for Developmental Toxicity Screening
The Texas-Indiana Virtual STAR Center: Zebrafish Models for Developmental Toxicity Screening (Presented by Maria Bondesson Bolin, Ph.D, University of Houston, Center for Nuclear Receptors and Cell Signaling) (3/22/2012)
Zhang, Wen; Qiu, Kai-Xiong; Yu, Fang; Xie, Xiao-Guang; Zhang, Shu-Qun; Chen, Ya-Juan; Xie, Hui-Ding
2017-10-01
B-Raf kinase has been identified as an important target in recent cancer treatment. In order to discover structurally diverse and novel B-Raf inhibitors (BRIs), a virtual screening of BRIs against ZINC database was performed by using a combination of pharmacophore modelling, molecular docking, 3D-QSAR model and binding free energy (ΔG bind ) calculation studies in this work. After the virtual screening, six promising hit compounds were obtained, which were then tested for inhibitory activities of A375 cell lines. In the result, five hit compounds show good biological activities (IC 50 <50μM). The present method of virtual screening can be applied to find structurally diverse inhibitors, and the obtained five structurally diverse compounds are expected to develop novel BRIs. Copyright © 2017. Published by Elsevier Ltd.
Exploiting PubChem for Virtual Screening
Xie, Xiang-Qun
2011-01-01
Importance of the field PubChem is a public molecular information repository, a scientific showcase of the NIH Roadmap Initiative. The PubChem database holds over 27 million records of unique chemical structures of compounds (CID) derived from nearly 70 million substance depositions (SID), and contains more than 449,000 bioassay records with over thousands of in vitro biochemical and cell-based screening bioassays established, with targeting more than 7000 proteins and genes linking to over 1.8 million of substances. Areas covered in this review This review builds on recent PubChem-related computational chemistry research reported by other authors while providing readers with an overview of the PubChem database, focusing on its increasing role in cheminformatics, virtual screening and toxicity prediction modeling. What the reader will gain These publicly available datasets in PubChem provide great opportunities for scientists to perform cheminformatics and virtual screening research for computer-aided drug design. However, the high volume and complexity of the datasets, in particular the bioassay-associated false positives/negatives and highly imbalanced datasets in PubChem, also creates major challenges. Several approaches regarding the modeling of PubChem datasets and development of virtual screening models for bioactivity and toxicity predictions are also reviewed. Take home message Novel data-mining cheminformatics tools and virtual screening algorithms are being developed and used to retrieve, annotate and analyze the large-scale and highly complex PubChem biological screening data for drug design. PMID:21691435
Discovery of novel human acrosin inhibitors by virtual screening
NASA Astrophysics Data System (ADS)
Liu, Xuefei; Dong, Guoqiang; Zhang, Jue; Qi, Jingjing; Zheng, Canhui; Zhou, Youjun; Zhu, Ju; Sheng, Chunquan; Lü, Jiaguo
2011-10-01
Human acrosin is an attractive target for the discovery of male contraceptive drugs. For the first time, structure-based drug design was applied to discover structurally diverse human acrosin inhibitors. A parallel virtual screening strategy in combination with pharmacophore-based and docking-based techniques was used to screen the SPECS database. From 16 compounds selected by virtual screening, a total of 10 compounds were found to be human acrosin inhibitors. Compound 2 was found to be the most potent hit (IC50 = 14 μM) and its binding mode was investigated by molecular dynamics simulations. The hit interacted with human acrosin mainly through hydrophobic and hydrogen-bonding interactions, which provided a good starting structure for further optimization studies.
Rational Methods for the Selection of Diverse Screening Compounds
Huggins, David J.; Venkitaraman, Ashok R.; Spring, David R.
2016-01-01
Traditionally a pursuit of large pharmaceutical companies, high-throughput screening assays are becoming increasingly common within academic and government laboratories. This shift has been instrumental in enabling projects that have not been commercially viable, such as chemical probe discovery and screening against high risk targets. Once an assay has been prepared and validated, it must be fed with screening compounds. Crafting a successful collection of small molecules for screening poses a significant challenge. An optimized collection will minimize false positives whilst maximizing hit rates of compounds that are amenable to lead generation and optimization. Without due consideration of the relevant protein targets and the downstream screening assays, compound filtering and selection can fail to explore the great extent of chemical diversity and eschew valuable novelty. Herein, we discuss the different factors to be considered and methods that may be employed when assembling a structurally diverse compound screening collection. Rational methods for selecting diverse chemical libraries are essential for their effective use in high-throughput screens. PMID:21261294
Bell, Andrew S; Bradley, Joseph; Everett, Jeremy R; Knight, Michelle; Loesel, Jens; Mathias, John; McLoughlin, David; Mills, James; Sharp, Robert E; Williams, Christine; Wood, Terence P
2013-05-01
The screening files of many large companies, including Pfizer, have grown considerably due to internal chemistry efforts, company mergers and acquisitions, external contracted synthesis, or compound purchase schemes. In order to screen the targets of interest in a cost-effective fashion, we devised an easy-to-assemble, plate-based diversity subset (PBDS) that represents almost the entire computed chemical space of the screening file whilst comprising only a fraction of the plates in the collection. In order to create this file, we developed new design principles for the quality assessment of screening plates: the Rule of 40 (Ro40) and a plate selection process that insured excellent coverage of both library chemistry and legacy chemistry space. This paper describes the rationale, design, construction, and performance of the PBDS, that has evolved into the standard paradigm for singleton (one compound per well) high-throughput screening in Pfizer since its introduction in 2006.
Optimizing multi-dimensional high throughput screening using zebrafish
Truong, Lisa; Bugel, Sean M.; Chlebowski, Anna; Usenko, Crystal Y.; Simonich, Michael T.; Massey Simonich, Staci L.; Tanguay, Robert L.
2016-01-01
The use of zebrafish for high throughput screening (HTS) for chemical bioactivity assessments is becoming routine in the fields of drug discovery and toxicology. Here we report current recommendations from our experiences in zebrafish HTS. We compared the effects of different high throughput chemical delivery methods on nominal water concentration, chemical sorption to multi-well polystyrene plates, transcription responses, and resulting whole animal responses. We demonstrate that digital dispensing consistently yields higher data quality and reproducibility compared to standard plastic tip-based liquid handling. Additionally, we illustrate the challenges in using this sensitive model for chemical assessment when test chemicals have trace impurities. Adaptation of these better practices for zebrafish HTS should increase reproducibility across laboratories. PMID:27453428
A Robotic Platform for Quantitative High-Throughput Screening
Michael, Sam; Auld, Douglas; Klumpp, Carleen; Jadhav, Ajit; Zheng, Wei; Thorne, Natasha; Austin, Christopher P.; Inglese, James
2008-01-01
Abstract High-throughput screening (HTS) is increasingly being adopted in academic institutions, where the decoupling of screening and drug development has led to unique challenges, as well as novel uses of instrumentation, assay formulations, and software tools. Advances in technology have made automated unattended screening in the 1,536-well plate format broadly accessible and have further facilitated the exploration of new technologies and approaches to screening. A case in point is our recently developed quantitative HTS (qHTS) paradigm, which tests each library compound at multiple concentrations to construct concentration-response curves (CRCs) generating a comprehensive data set for each assay. The practical implementation of qHTS for cell-based and biochemical assays across libraries of > 100,000 compounds (e.g., between 700,000 and 2,000,000 sample wells tested) requires maximal efficiency and miniaturization and the ability to easily accommodate many different assay formats and screening protocols. Here, we describe the design and utilization of a fully integrated and automated screening system for qHTS at the National Institutes of Health's Chemical Genomics Center. We report system productivity, reliability, and flexibility, as well as modifications made to increase throughput, add additional capabilities, and address limitations. The combination of this system and qHTS has led to the generation of over 6 million CRCs from > 120 assays in the last 3 years and is a technology that can be widely implemented to increase efficiency of screening and lead generation. PMID:19035846
ChemScreener: A Distributed Computing Tool for Scaffold based Virtual Screening.
Karthikeyan, Muthukumarasamy; Pandit, Deepak; Vyas, Renu
2015-01-01
In this work we present ChemScreener, a Java-based application to perform virtual library generation combined with virtual screening in a platform-independent distributed computing environment. ChemScreener comprises a scaffold identifier, a distinct scaffold extractor, an interactive virtual library generator as well as a virtual screening module for subsequently selecting putative bioactive molecules. The virtual libraries are annotated with chemophore-, pharmacophore- and toxicophore-based information for compound prioritization. The hits selected can then be further processed using QSAR, docking and other in silico approaches which can all be interfaced within the ChemScreener framework. As a sample application, in this work scaffold selectivity, diversity, connectivity and promiscuity towards six important therapeutic classes have been studied. In order to illustrate the computational power of the application, 55 scaffolds extracted from 161 anti-psychotic compounds were enumerated to produce a virtual library comprising 118 million compounds (17 GB) and annotated with chemophore, pharmacophore and toxicophore based features in a single step which would be non-trivial to perform with many standard software tools today on libraries of this size.
Diving deeper into Zebrafish development of social behavior: analyzing high resolution data.
Buske, Christine; Gerlai, Robert
2014-08-30
Vertebrate model organisms have been utilized in high throughput screening but only with substantial cost and human capital investment. The zebrafish is a vertebrate model species that is a promising and cost effective candidate for efficient high throughput screening. Larval zebrafish have already been successfully employed in this regard (Lessman, 2011), but adult zebrafish also show great promise. High throughput screening requires the use of a large number of subjects and collection of substantial amount of data. Collection of data is only one of the demanding aspects of screening. However, in most screening approaches that involve behavioral data the main bottleneck that slows throughput is the time consuming aspect of analysis of the collected data. Some automated analytical tools do exist, but often they only work for one subject at a time, eliminating the possibility of fully utilizing zebrafish as a screening tool. This is a particularly important limitation for such complex phenotypes as social behavior. Testing multiple fish at a time can reveal complex social interactions but it may also allow the identification of outliers from a group of mutagenized or pharmacologically treated fish. Here, we describe a novel method using a custom software tool developed within our laboratory, which enables tracking multiple fish, in combination with a sophisticated analytical approach for summarizing and analyzing high resolution behavioral data. This paper focuses on the latter, the analytic tool, which we have developed using the R programming language and environment for statistical computing. We argue that combining sophisticated data collection methods with appropriate analytical tools will propel zebrafish into the future of neurobehavioral genetic research. Copyright © 2014. Published by Elsevier B.V.
Nile Red Detection of Bacterial Hydrocarbons and Ketones in a High-Throughput Format
DOE Office of Scientific and Technical Information (OSTI.GOV)
Pinzon, NM; Aukema, KG; Gralnick, JA
A method for use in high-throughput screening of bacteria for the production of long-chain hydrocarbons and ketones by monitoring fluorescent light emission in the presence of Nile red is described. Nile red has previously been used to screen for polyhydroxybutyrate (PHB) and fatty acid esters, but this is the first report of screening for recombinant bacteria making hydrocarbons or ketones. The microtiter plate assay was evaluated using wild-type and recombinant strains of Shewanella oneidensis and Escherichia coli expressing the enzyme OleA, previously shown to initiate hydrocarbon biosynthesis. The strains expressing exogenous Stenotrophomonas maltophilia oleA, with increased levels of ketone productionmore » as determined by gas chromatography-mass spectrometry, were distinguished with Nile red fluorescence. Confocal microscopy images of S. oneidensis oleA-expressing strains stained with Nile red were consistent with a membrane localization of the ketones. This differed from Nile red staining of bacterial PHB or algal lipid droplets that showed intracellular inclusion bodies. These results demonstrated the applicability of Nile red in a high-throughput technique for the detection of bacterial hydrocarbons and ketones. IMPORTANCE In recent years, there has been renewed interest in advanced biofuel sources such as bacterial hydrocarbon production. Previous studies used solvent extraction of bacterial cultures followed by gas chromatography-mass spectrometry (GC-MS) to detect and quantify ketones and hydrocarbons (Beller HR, Goh EB, Keasling JD, Appl. Environ. Microbiol. 76: 1212-1223, 2010; Sukovich DJ, Seffernick JL, Richman JE, Gralnick JA, Wackett LP, Appl. Environ. Microbiol. 76: 3850-3862, 2010). While these analyses are powerful and accurate, their labor-intensive nature makes them intractable to high-throughput screening; therefore, methods for rapid identification of bacterial strains that are overproducing hydrocarbons are needed. The use of high-throughput evaluation of bacterial and algal hydrophobic molecule production via Nile red fluorescence from lipids and esters was extended in this study to include hydrocarbons and ketones. This work demonstrated accurate, high-throughput detection of high-level bacterial long-chain ketone and hydrocarbon production by screening for increased fluorescence of the hydrophobic dye Nile red.« less
Angiuoli, Samuel V; Matalka, Malcolm; Gussman, Aaron; Galens, Kevin; Vangala, Mahesh; Riley, David R; Arze, Cesar; White, James R; White, Owen; Fricke, W Florian
2011-08-30
Next-generation sequencing technologies have decentralized sequence acquisition, increasing the demand for new bioinformatics tools that are easy to use, portable across multiple platforms, and scalable for high-throughput applications. Cloud computing platforms provide on-demand access to computing infrastructure over the Internet and can be used in combination with custom built virtual machines to distribute pre-packaged with pre-configured software. We describe the Cloud Virtual Resource, CloVR, a new desktop application for push-button automated sequence analysis that can utilize cloud computing resources. CloVR is implemented as a single portable virtual machine (VM) that provides several automated analysis pipelines for microbial genomics, including 16S, whole genome and metagenome sequence analysis. The CloVR VM runs on a personal computer, utilizes local computer resources and requires minimal installation, addressing key challenges in deploying bioinformatics workflows. In addition CloVR supports use of remote cloud computing resources to improve performance for large-scale sequence processing. In a case study, we demonstrate the use of CloVR to automatically process next-generation sequencing data on multiple cloud computing platforms. The CloVR VM and associated architecture lowers the barrier of entry for utilizing complex analysis protocols on both local single- and multi-core computers and cloud systems for high throughput data processing.
Wu, Szu-Huei; Yao, Chun-Hsu; Hsieh, Chieh-Jui; Liu, Yu-Wei; Chao, Yu-Sheng; Song, Jen-Shin; Lee, Jinq-Chyi
2015-07-10
Sodium-dependent glucose co-transporter 2 (SGLT2) inhibitors are of current interest as a treatment for type 2 diabetes. Efforts have been made to discover phlorizin-related glycosides with good SGLT2 inhibitory activity. To increase structural diversity and better understand the role of non-glycoside SGLT2 inhibitors on glycemic control, we initiated a research program to identify non-glycoside hits from high-throughput screening. Here, we report the development of a novel, fluorogenic probe-based glucose uptake system based on a Cu(I)-catalyzed [3+2] cycloaddition. The safer processes and cheaper substances made the developed assay our first priority for large-scale primary screening as compared to the well-known [(14)C]-labeled α-methyl-D-glucopyranoside ([(14)C]-AMG) radioactive assay. This effort culminated in the identification of a benzimidazole, non-glycoside SGLT2 hit with an EC50 value of 0.62 μM by high-throughput screening of 41,000 compounds. Copyright © 2015 Elsevier B.V. All rights reserved.
A BSL-4 high-throughput screen identifies sulfonamide inhibitors of Nipah virus.
Tigabu, Bersabeh; Rasmussen, Lynn; White, E Lucile; Tower, Nichole; Saeed, Mohammad; Bukreyev, Alexander; Rockx, Barry; LeDuc, James W; Noah, James W
2014-04-01
Nipah virus is a biosafety level 4 (BSL-4) pathogen that causes severe respiratory illness and encephalitis in humans. To identify novel small molecules that target Nipah virus replication as potential therapeutics, Southern Research Institute and Galveston National Laboratory jointly developed an automated high-throughput screening platform that is capable of testing 10,000 compounds per day within BSL-4 biocontainment. Using this platform, we screened a 10,080-compound library using a cell-based, high-throughput screen for compounds that inhibited the virus-induced cytopathic effect. From this pilot effort, 23 compounds were identified with EC50 values ranging from 3.9 to 20.0 μM and selectivities >10. Three sulfonamide compounds with EC50 values <12 μM were further characterized for their point of intervention in the viral replication cycle and for broad antiviral efficacy. Development of HTS capability under BSL-4 containment changes the paradigm for drug discovery for highly pathogenic agents because this platform can be readily modified to identify prophylactic and postexposure therapeutic candidates against other BSL-4 pathogens, particularly Ebola, Marburg, and Lassa viruses.
Lu, Zhi-Yan; Guo, Xiao-Jue; Li, Hui; Huang, Zhong-Zi; Lin, Kuang-Fei; Liu, Yong-Di
2015-01-01
A high-throughput screening system for moderately halophilic phenol-degrading bacteria from various habitats was developed to replace the conventional strain screening owing to its high efficiency. Bacterial enrichments were cultivated in 48 deep well microplates instead of shake flasks or tubes. Measurement of phenol concentrations was performed in 96-well microplates instead of using the conventional spectrophotometric method or high-performance liquid chromatography (HPLC). The high-throughput screening system was used to cultivate forty-three bacterial enrichments and gained a halophilic bacterial community E3 with the best phenol-degrading capability. Halomonas sp. strain 4-5 was isolated from the E3 community. Strain 4-5 was able to degrade more than 94% of the phenol (500 mg·L−1 starting concentration) over a range of 3%–10% NaCl. Additionally, the strain accumulated the compatible solute, ectoine, with increasing salt concentrations. PCR detection of the functional genes suggested that the largest subunit of multicomponent phenol hydroxylase (LmPH) and catechol 1,2-dioxygenase (C12O) were active in the phenol degradation process. PMID:26020478
A BSL-4 High-Throughput Screen Identifies Sulfonamide Inhibitors of Nipah Virus
Tigabu, Bersabeh; Rasmussen, Lynn; White, E. Lucile; Tower, Nichole; Saeed, Mohammad; Bukreyev, Alexander; Rockx, Barry; LeDuc, James W.
2014-01-01
Abstract Nipah virus is a biosafety level 4 (BSL-4) pathogen that causes severe respiratory illness and encephalitis in humans. To identify novel small molecules that target Nipah virus replication as potential therapeutics, Southern Research Institute and Galveston National Laboratory jointly developed an automated high-throughput screening platform that is capable of testing 10,000 compounds per day within BSL-4 biocontainment. Using this platform, we screened a 10,080-compound library using a cell-based, high-throughput screen for compounds that inhibited the virus-induced cytopathic effect. From this pilot effort, 23 compounds were identified with EC50 values ranging from 3.9 to 20.0 μM and selectivities >10. Three sulfonamide compounds with EC50 values <12 μM were further characterized for their point of intervention in the viral replication cycle and for broad antiviral efficacy. Development of HTS capability under BSL-4 containment changes the paradigm for drug discovery for highly pathogenic agents because this platform can be readily modified to identify prophylactic and postexposure therapeutic candidates against other BSL-4 pathogens, particularly Ebola, Marburg, and Lassa viruses. PMID:24735442
How to benchmark methods for structure-based virtual screening of large compound libraries.
Christofferson, Andrew J; Huang, Niu
2012-01-01
Structure-based virtual screening is a useful computational technique for ligand discovery. To systematically evaluate different docking approaches, it is important to have a consistent benchmarking protocol that is both relevant and unbiased. Here, we describe the designing of a benchmarking data set for docking screen assessment, a standard docking screening process, and the analysis and presentation of the enrichment of annotated ligands among a background decoy database.
Evaluating Rapid Models for High-Throughput Exposure Forecasting (SOT)
High throughput exposure screening models can provide quantitative predictions for thousands of chemicals; however these predictions must be systematically evaluated for predictive ability. Without the capability to make quantitative, albeit uncertain, forecasts of exposure, the ...
McDonald, Peter R; Roy, Anuradha; Chaguturu, Rathnam
2011-01-01
The University of Kansas High-Throughput Screening (KU HTS) core is a state-of-the-art drug-discovery facility with an entrepreneurial open-service policy, which provides centralized resources supporting public- and private-sector research initiatives. The KU HTS core was established in 2002 at the University of Kansas with support from an NIH grant and the state of Kansas. It collaborates with investigators from national and international academic, nonprofit and pharmaceutical organizations in executing HTS-ready assay development and screening of chemical libraries for target validation, probe selection, hit identification and lead optimization. This is part two of a contribution from the KU HTS laboratory. PMID:21806374
Microelectroporation device for genomic screening
Perroud, Thomas D.; Renzi, Ronald F.; Negrete, Oscar; Claudnic, Mark R.
2014-09-09
We have developed an microelectroporation device that combines microarrays of oligonucleotides, microfluidic channels, and electroporation for cell transfection and high-throughput screening applications (e.g. RNA interference screens). Microarrays allow the deposition of thousands of different oligonucleotides in microscopic spots. Microfluidic channels and microwells enable efficient loading of cells into the device and prevent cross-contamination between different oligonucleotides spots. Electroporation allows optimal transfection of nucleic acids into cells (especially hard-to-transfect cells such as primary cells) by minimizing cell death while maximizing transfection efficiency. This invention has the advantage of a higher throughput and lower cost, while preventing cross-contamination compared to conventional screening technologies. Moreover, this device does not require bulky robotic liquid handling equipment and is inherently safer given that it is a closed system.
Nesaratnam, N; Thomas, P; Vivian, A
2017-10-01
IntroductionDissociated tests of strabismus provide valuable information for diagnosis and monitoring of ocular misalignment in patients with normal retinal correspondence. However, they are vulnerable to operator error and rely on a fixed head position. Virtual reality headsets obviate the need for head fixation, while providing other clear theoretical advantages, including complete control over the illumination and targets presented for the patient's interaction.PurposeWe compared the performance of a virtual reality-based test of ocular misalignment to that of the traditional Lees screen, to establish the feasibility of using virtual reality technology in ophthalmic settings in the future.MethodsThree patients underwent a traditional Lees screen test, and a virtual reality headset-based test of ocular motility. The virtual reality headset-based programme consisted of an initial test to measure horizontal and vertical deviation, followed by a test for torsion.ResultsThe pattern of deviation obtained using the virtual reality-based test showed agreement with that obtained from the Lees screen for patients with a fourth nerve palsy, comitant esotropia, and restrictive thyroid eye disease.ConclusionsThis study reports the first use of a virtual reality headset in assessing ocular misalignment, and demonstrates that it is a feasible dissociative test of strabismus.
Akeroyd, Michiel; Olsthoorn, Maurien; Gerritsma, Jort; Gutker-Vermaas, Diana; Ekkelkamp, Laurens; van Rij, Tjeerd; Klaassen, Paul; Plugge, Wim; Smit, Ed; Strupat, Kerstin; Wenzel, Thibaut; van Tilborg, Marcel; van der Hoeven, Rob
2013-03-10
In the discovery of new enzymes genomic and cDNA expression libraries containing thousands of differential clones are generated to obtain biodiversity. These libraries need to be screened for the activity of interest. Removing so-called empty and redundant clones significantly reduces the size of these expression libraries and therefore speeds up new enzyme discovery. Here, we present a sensitive, generic workflow for high throughput screening of successful microbial protein over-expression in microtiter plates containing a complex matrix based on mass spectrometry techniques. MALDI-LTQ-Orbitrap screening followed by principal component analysis and peptide mass fingerprinting was developed to obtain a throughput of ∼12,000 samples per week. Alternatively, a UHPLC-MS(2) approach including MS(2) protein identification was developed for microorganisms with a complex protein secretome with a throughput of ∼2000 samples per week. TCA-induced protein precipitation enhanced by addition of bovine serum albumin is used for protein purification prior to MS detection. We show that this generic workflow can effectively reduce large expression libraries from fungi and bacteria to their minimal size by detection of successful protein over-expression using MS. Copyright © 2012 Elsevier B.V. All rights reserved.
De Diego, Nuria; Fürst, Tomáš; Humplík, Jan F; Ugena, Lydia; Podlešáková, Kateřina; Spíchal, Lukáš
2017-01-01
High-throughput plant phenotyping platforms provide new possibilities for automated, fast scoring of several plant growth and development traits, followed over time using non-invasive sensors. Using Arabidops is as a model offers important advantages for high-throughput screening with the opportunity to extrapolate the results obtained to other crops of commercial interest. In this study we describe the development of a highly reproducible high-throughput Arabidopsis in vitro bioassay established using our OloPhen platform, suitable for analysis of rosette growth in multi-well plates. This method was successfully validated on example of multivariate analysis of Arabidopsis rosette growth in different salt concentrations and the interaction with varying nutritional composition of the growth medium. Several traits such as changes in the rosette area, relative growth rate, survival rate and homogeneity of the population are scored using fully automated RGB imaging and subsequent image analysis. The assay can be used for fast screening of the biological activity of chemical libraries, phenotypes of transgenic or recombinant inbred lines, or to search for potential quantitative trait loci. It is especially valuable for selecting genotypes or growth conditions that improve plant stress tolerance.
Sharda, Saphy; Sarmandal, Palash; Cherukommu, Shirisha; Dindhoria, Kiran; Yadav, Manisha; Bandaru, Srinivas; Sharma, Anudeep; Sakhi, Aditi; Vyas, Tanmay; Hussain, Tajamul; Nayarisseri, Anuraj; Singh, Sanjeev Kumar
2017-01-01
CML originates due to reciprocal translocation in Philadelphia chromosome leading to the formation of fusion product BCR-ABL which constitutively activates tyrosine kinase signaling pathways eventually leading to abnormal proliferation of granulocytic cells. As a therapeutic strategy, BCR-ABL inhibitors have been clinically approved which terminates its phosphorylation activity and retards cancer progression. However, a number of patients develop resistance to inhibitors which demand for the discovery of new inhibitors. Given the drawbacks of present inhibitors, by high throughput virtual screening approaches, present study pursues to identify high affinity compounds targeting BCR-ABL1 anticipated to have safer pharmacological profiles. Five established BCR-ABL inhibitors formed the query compounds for identification of structurally similar compounds by Tanimoto coefficient based linear fingerprint search with a threshold of 95% against PubChemdatabase. Assisted by MolDock algorithm all compounds were docked against BCR-ABL protein in order to retrieve high affinity compounds. The parents and similars were further tested for their ADMET propertiesand bioactivity. Rebastinib formed higher affinity inhibitor than rest of the four established compound investigated in the study. Interestingly, Rebastinib similar compound with Pubchem ID: 67254402 was also shown to have highest affinity than other similars including the similars of respective five parents. In terms of ADMET properties Pubchem ID: 67254402 had appreciable ADMET profile and bioactivity. However, Rebastinib still stood as the best inhibitor in terms of binding affinity and ADMET properties than Pubchem ID: 67254402. Nevertheless, owing to the similar pharmacological properties with Rebastinib, Pubchem ID: 67254402 can be expected to form potential BCR-ABL inhibitor. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.
Maréchal, Eric
2008-09-01
Chemogenomics is the study of the interaction of functional biological systems with exogenous small molecules, or in broader sense the study of the intersection of biological and chemical spaces. Chemogenomics requires expertises in biology, chemistry and computational sciences (bioinformatics, cheminformatics, large scale statistics and machine learning methods) but it is more than the simple apposition of each of these disciplines. Biological entities interacting with small molecules can be isolated proteins or more elaborate systems, from single cells to complete organisms. The biological space is therefore analyzed at various postgenomic levels (genomic, transcriptomic, proteomic or any phenotypic level). The space of small molecules is partially real, corresponding to commercial and academic collections of compounds, and partially virtual, corresponding to the chemical space possibly synthesizable. Synthetic chemistry has developed novel strategies allowing a physical exploration of this universe of possibilities. A major challenge of cheminformatics is to charter the virtual space of small molecules using realistic biological constraints (bioavailability, druggability, structural biological information). Chemogenomics is a descendent of conventional pharmaceutical approaches, since it involves the screening of chemolibraries for their effect on biological targets, and benefits from the advances in the corresponding enabling technologies and the introduction of new biological markers. Screening was originally motivated by the rigorous discovery of new drugs, neglecting and throwing away any molecule that would fail to meet the standards required for a therapeutic treatment. It is now the basis for the discovery of small molecules that might or might not be directly used as drugs, but which have an immense potential for basic research, as probes to explore an increasing number of biological phenomena. Concerns about the environmental impact of chemical industry open new fields of research for chemogenomics.
Lu, Pinyi; Hontecillas, Raquel; Horne, William T; Carbo, Adria; Viladomiu, Monica; Pedragosa, Mireia; Bevan, David R; Lewis, Stephanie N; Bassaganya-Riera, Josep
2012-01-01
Lanthionine synthetase component C-like protein 2 (LANCL2) is a member of the eukaryotic lanthionine synthetase component C-Like protein family involved in signal transduction and insulin sensitization. Recently, LANCL2 is a target for the binding and signaling of abscisic acid (ABA), a plant hormone with anti-diabetic and anti-inflammatory effects. The goal of this study was to determine the role of LANCL2 as a potential therapeutic target for developing novel drugs and nutraceuticals against inflammatory diseases. Previously, we performed homology modeling to construct a three-dimensional structure of LANCL2 using the crystal structure of lanthionine synthetase component C-like protein 1 (LANCL1) as a template. Using this model, structure-based virtual screening was performed using compounds from NCI (National Cancer Institute) Diversity Set II, ChemBridge, ZINC natural products, and FDA-approved drugs databases. Several potential ligands were identified using molecular docking. In order to validate the anti-inflammatory efficacy of the top ranked compound (NSC61610) in the NCI Diversity Set II, a series of in vitro and pre-clinical efficacy studies were performed using a mouse model of dextran sodium sulfate (DSS)-induced colitis. Our findings showed that the lead compound, NSC61610, activated peroxisome proliferator-activated receptor gamma in a LANCL2- and adenylate cyclase/cAMP dependent manner in vitro and ameliorated experimental colitis by down-modulating colonic inflammatory gene expression and favoring regulatory T cell responses. LANCL2 is a novel therapeutic target for inflammatory diseases. High-throughput, structure-based virtual screening is an effective computational-based drug design method for discovering anti-inflammatory LANCL2-based drug candidates.
Lu, Pinyi; Hontecillas, Raquel; Horne, William T.; Carbo, Adria; Viladomiu, Monica; Pedragosa, Mireia; Bevan, David R.; Lewis, Stephanie N.; Bassaganya-Riera, Josep
2012-01-01
Background Lanthionine synthetase component C-like protein 2 (LANCL2) is a member of the eukaryotic lanthionine synthetase component C-Like protein family involved in signal transduction and insulin sensitization. Recently, LANCL2 is a target for the binding and signaling of abscisic acid (ABA), a plant hormone with anti-diabetic and anti-inflammatory effects. Methodology/Principal Findings The goal of this study was to determine the role of LANCL2 as a potential therapeutic target for developing novel drugs and nutraceuticals against inflammatory diseases. Previously, we performed homology modeling to construct a three-dimensional structure of LANCL2 using the crystal structure of lanthionine synthetase component C-like protein 1 (LANCL1) as a template. Using this model, structure-based virtual screening was performed using compounds from NCI (National Cancer Institute) Diversity Set II, ChemBridge, ZINC natural products, and FDA-approved drugs databases. Several potential ligands were identified using molecular docking. In order to validate the anti-inflammatory efficacy of the top ranked compound (NSC61610) in the NCI Diversity Set II, a series of in vitro and pre-clinical efficacy studies were performed using a mouse model of dextran sodium sulfate (DSS)-induced colitis. Our findings showed that the lead compound, NSC61610, activated peroxisome proliferator-activated receptor gamma in a LANCL2- and adenylate cyclase/cAMP dependent manner in vitro and ameliorated experimental colitis by down-modulating colonic inflammatory gene expression and favoring regulatory T cell responses. Conclusions/Significance LANCL2 is a novel therapeutic target for inflammatory diseases. High-throughput, structure-based virtual screening is an effective computational-based drug design method for discovering anti-inflammatory LANCL2-based drug candidates. PMID:22509338
Development and evaluation of human AP endonuclease inhibitors in melanoma and glioma cell lines.
Mohammed, M Z; Vyjayanti, V N; Laughton, C A; Dekker, L V; Fischer, P M; Wilson, D M; Abbotts, R; Shah, S; Patel, P M; Hickson, I D; Madhusudan, S
2011-02-15
Modulation of DNA base excision repair (BER) has the potential to enhance response to chemotherapy and improve outcomes in tumours such as melanoma and glioma. APE1, a critical protein in BER that processes potentially cytotoxic abasic sites (AP sites), is a promising new target in cancer. In the current study, we aimed to develop small molecule inhibitors of APE1 for cancer therapy. An industry-standard high throughput virtual screening strategy was adopted. The Sybyl8.0 (Tripos, St Louis, MO, USA) molecular modelling software suite was used to build inhibitor templates. Similarity searching strategies were then applied using ROCS 2.3 (Open Eye Scientific, Santa Fe, NM, USA) to extract pharmacophorically related subsets of compounds from a chemically diverse database of 2.6 million compounds. The compounds in these subsets were subjected to docking against the active site of the APE1 model, using the genetic algorithm-based programme GOLD2.7 (CCDC, Cambridge, UK). Predicted ligand poses were ranked on the basis of several scoring functions. The top virtual hits with promising pharmaceutical properties underwent detailed in vitro analyses using fluorescence-based APE1 cleavage assays and counter screened using endonuclease IV cleavage assays, fluorescence quenching assays and radiolabelled oligonucleotide assays. Biochemical APE1 inhibitors were then subjected to detailed cytotoxicity analyses. Several specific APE1 inhibitors were isolated by this approach. The IC(50) for APE1 inhibition ranged between 30 nM and 50 μM. We demonstrated that APE1 inhibitors lead to accumulation of AP sites in genomic DNA and potentiated the cytotoxicity of alkylating agents in melanoma and glioma cell lines. Our study provides evidence that APE1 is an emerging drug target and could have therapeutic application in patients with melanoma and glioma.
Noise Reduction in High-Throughput Gene Perturbation Screens
USDA-ARS?s Scientific Manuscript database
Motivation: Accurate interpretation of perturbation screens is essential for a successful functional investigation. However, the screened phenotypes are often distorted by noise, and their analysis requires specialized statistical analysis tools. The number and scope of statistical methods available...
DOE Office of Scientific and Technical Information (OSTI.GOV)
Heusinkveld, Harm J.; Westerink, Remco H.S., E-mail: R.Westerink@uu.nl
Calcium plays a crucial role in virtually all cellular processes, including neurotransmission. The intracellular Ca{sup 2+} concentration ([Ca{sup 2+}]{sub i}) is therefore an important readout in neurotoxicological and neuropharmacological studies. Consequently, there is an increasing demand for high-throughput measurements of [Ca{sup 2+}]{sub i}, e.g. using multi-well microplate readers, in hazard characterization, human risk assessment and drug development. However, changes in [Ca{sup 2+}]{sub i} are highly dynamic, thereby creating challenges for high-throughput measurements. Nonetheless, several protocols are now available for real-time kinetic measurement of [Ca{sup 2+}]{sub i} in plate reader systems, though the results of such plate reader-based measurements have beenmore » questioned. In view of the increasing use of plate reader systems for measurements of [Ca{sup 2+}]{sub i} a careful evaluation of current technologies is warranted. We therefore performed an extensive set of experiments, using two cell lines (PC12 and B35) and two fluorescent calcium-sensitive dyes (Fluo-4 and Fura-2), for comparison of a linear plate reader system with single cell fluorescence microscopy. Our data demonstrate that the use of plate reader systems for high-throughput real-time kinetic measurements of [Ca{sup 2+}]{sub i} is associated with many pitfalls and limitations, including erroneous sustained increases in fluorescence, limited sensitivity and lack of single cell resolution. Additionally, our data demonstrate that probenecid, which is often used to prevent dye leakage, effectively inhibits the depolarization-evoked increase in [Ca{sup 2+}]{sub i}. Overall, the data indicate that the use of current plate reader-based strategies for high-throughput real-time kinetic measurements of [Ca{sup 2+}]{sub i} is associated with caveats and limitations that require further investigation. - Research Highlights: > The use of plate readers for high-throughput screening of intracellular Ca{sup 2+} is associated with many pitfalls and limitations. > Single cell fluorescent microscopy is recommended for measurements of intracellular Ca{sup 2+}. > Dual-wavelength dyes (Fura-2) are preferred over single-wavelength dyes (Fluo-4) for measurements of intracellular Ca{sup 2+}. > Probenecid prevents dye leakage but abolishes depolarization-evoked Ca{sup 2+} influx, severely hampering measurements of Ca{sup 2+}. > In general, care should be taken when interpreting data from high-throughput kinetic measurements.« less
Virtual Screening Approaches towards the Discovery of Toll-Like Receptor Modulators
Pérez-Regidor, Lucía; Zarioh, Malik; Ortega, Laura; Martín-Santamaría, Sonsoles
2016-01-01
This review aims to summarize the latest efforts performed in the search for novel chemical entities such as Toll-like receptor (TLR) modulators by means of virtual screening techniques. This is an emergent research field with only very recent (and successful) contributions. Identification of drug-like molecules with potential therapeutic applications for the treatment of a variety of TLR-regulated diseases has attracted considerable interest due to the clinical potential. Additionally, the virtual screening databases and computational tools employed have been overviewed in a descriptive way, widening the scope for researchers interested in the field. PMID:27618029
I describe research on high throughput exposure and toxicokinetics. These tools provide context for data generated by high throughput toxicity screening to allow risk-based prioritization of thousands of chemicals.
MIPHENO: Data normalization for high throughput metabolic analysis.
High throughput methodologies such as microarrays, mass spectrometry and plate-based small molecule screens are increasingly used to facilitate discoveries from gene function to drug candidate identification. These large-scale experiments are typically carried out over the course...
High-Throughput Pharmacokinetics for Environmental Chemicals (SOT)
High throughput screening (HTS) promises to allow prioritization of thousands of environmental chemicals with little or no in vivo information. For bioactivity identified by HTS, toxicokinetic (TK) models are essential to predict exposure thresholds below which no significant bio...
Pei, Fen; Jin, Hongwei; Zhou, Xin; Xia, Jie; Sun, Lidan; Liu, Zhenming; Zhang, Liangren
2015-11-01
Toll-like receptor 8 agonists, which activate adaptive immune responses by inducing robust production of T-helper 1-polarizing cytokines, are promising candidates for vaccine adjuvants. As the binding site of toll-like receptor 8 is large and highly flexible, virtual screening by individual method has inevitable limitations; thus, a comprehensive comparison of different methods may provide insights into seeking effective strategy for the discovery of novel toll-like receptor 8 agonists. In this study, the performance of knowledge-based pharmacophore, shape-based 3D screening, and combined strategies was assessed against a maximum unbiased benchmarking data set containing 13 actives and 1302 decoys specialized for toll-like receptor 8 agonists. Prior structure-activity relationship knowledge was involved in knowledge-based pharmacophore generation, and a set of antagonists was innovatively used to verify the selectivity of the selected knowledge-based pharmacophore. The benchmarking data set was generated from our recently developed 'mubd-decoymaker' protocol. The enrichment assessment demonstrated a considerable performance through our selected three-layer virtual screening strategy: knowledge-based pharmacophore (Phar1) screening, shape-based 3D similarity search (Q4_combo), and then a Gold docking screening. This virtual screening strategy could be further employed to perform large-scale database screening and to discover novel toll-like receptor 8 agonists. © 2015 John Wiley & Sons A/S.
Teplitsky, Ella; Joshi, Karan; Ericson, Daniel L.; ...
2015-07-01
We describe a high throughput method for screening up to 1728 distinct chemicals with protein crystals on a single microplate. Acoustic droplet ejection (ADE) was used to co-position 2.5 nL of protein, precipitant, and chemicals on a MiTeGen in situ-1 crystallization plate™ for screening by co-crystallization or soaking. ADE-transferred droplets follow a precise trajectory which allows all components to be transferred through small apertures in the microplate lid. The apertures were large enough for 2.5 nL droplets to pass through them, but small enough so that they did not disrupt the internal environment created by the mother liquor. Using thismore » system, thermolysin and trypsin crystals were efficiently screened for binding to a heavy-metal mini-library. Fluorescence and X-ray diffraction were used to confirm that each chemical in the heavy-metal library was correctly paired with the intended protein crystal. Moreover, a fragment mini-library was screened to observe two known lysozyme We describe a high throughput method for screening up to 1728 distinct chemicals with protein crystals on a single microplate. Acoustic droplet ejection (ADE) was used to co-position 2.5 nL of protein, precipitant, and chemicals on a MiTeGen in situ-1 crystallization plate™ for screening by co-crystallization or soaking. ADE-transferred droplets follow a precise trajectory which allows all components to be transferred through small apertures in the microplate lid. The apertures were large enough for 2.5 nL droplets to pass through them, but small enough so that they did not disrupt the internal environment created by the mother liquor. Using this system, thermolysin and trypsin crystals were efficiently screened for binding to a heavy-metal mini-library. Fluorescence and X-ray diffraction were used to confirm that each chemical in the heavy-metal library was correctly paired with the intended protein crystal. A fragment mini-library was screened to observe two known lysozyme ligands using both co-crystallization and soaking. A similar approach was used to identify multiple, novel thaumatin binding sites for ascorbic acid. This technology pushes towards a faster, automated, and more flexible strategy for high throughput screening of chemical libraries (such as fragment libraries) using as little as 2.5 nL of each component.ds using both co-crystallization and soaking. We used a A similar approach to identify multiple, novel thaumatin binding sites for ascorbic acid. This technology pushes towards a faster, automated, and more flexible strategy for high throughput screening of chemical libraries (such as fragment libraries) using as little as 2.5 nL of each component.« less
Ibrahim, Tamer M; Bauer, Matthias R; Boeckler, Frank M
2015-01-01
Structure-based virtual screening techniques can help to identify new lead structures and complement other screening approaches in drug discovery. Prior to docking, the data (protein crystal structures and ligands) should be prepared with great attention to molecular and chemical details. Using a subset of 18 diverse targets from the recently introduced DEKOIS 2.0 benchmark set library, we found differences in the virtual screening performance of two popular docking tools (GOLD and Glide) when employing two different commercial packages (e.g. MOE and Maestro) for preparing input data. We systematically investigated the possible factors that can be responsible for the found differences in selected sets. For the Angiotensin-I-converting enzyme dataset, preparation of the bioactive molecules clearly exerted the highest influence on VS performance compared to preparation of the decoys or the target structure. The major contributing factors were different protonation states, molecular flexibility, and differences in the input conformation (particularly for cyclic moieties) of bioactives. In addition, score normalization strategies eliminated the biased docking scores shown by GOLD (ChemPLP) for the larger bioactives and produced a better performance. Generalizing these normalization strategies on the 18 DEKOIS 2.0 sets, improved the performances for the majority of GOLD (ChemPLP) docking, while it showed detrimental performances for the majority of Glide (SP) docking. In conclusion, we exemplify herein possible issues particularly during the preparation stage of molecular data and demonstrate to which extent these issues can cause perturbations in the virtual screening performance. We provide insights into what problems can occur and should be avoided, when generating benchmarks to characterize the virtual screening performance. Particularly, careful selection of an appropriate molecular preparation setup for the bioactive set and the use of score normalization for docking with GOLD (ChemPLP) appear to have a great importance for the screening performance. For virtual screening campaigns, we recommend to invest time and effort into including alternative preparation workflows into the generation of the master library, even at the cost of including multiple representations of each molecule. Graphical AbstractUsing DEKOIS 2.0 benchmark sets in structure-based virtual screening to probe the impact of molecular preparation and score normalization.
Screening_mgmt: a Python module for managing screening data.
Helfenstein, Andreas; Tammela, Päivi
2015-02-01
High-throughput screening is an established technique in drug discovery and, as such, has also found its way into academia. High-throughput screening generates a considerable amount of data, which is why specific software is used for its analysis and management. The commercially available software packages are often beyond the financial limits of small-scale academic laboratories and, furthermore, lack the flexibility to fulfill certain user-specific requirements. We have developed a Python module, screening_mgmt, which is a lightweight tool for flexible data retrieval, analysis, and storage for different screening assays in one central database. The module reads custom-made analysis scripts and plotting instructions, and it offers a graphical user interface to import, modify, and display the data in a uniform manner. During the test phase, we used this module for the management of 10,000 data points of various origins. It has provided a practical, user-friendly tool for sharing and exchanging information between researchers. © 2014 Society for Laboratory Automation and Screening.
Xiao, Xiaodong; Douthwaite, Julie A; Chen, Yan; Kemp, Ben; Kidd, Sara; Percival-Alwyn, Jennifer; Smith, Alison; Goode, Kate; Swerdlow, Bonnie; Lowe, David; Wu, Herren; Dall'Acqua, William F; Chowdhury, Partha S
Phage display antibody libraries are a rich resource for discovery of potential therapeutic antibodies. Single-chain variable fragment (scFv) libraries are the most common format due to the efficient display of scFv by phage particles and the ease by which soluble scFv antibodies can be expressed for high-throughput screening. Typically, a cascade of screening and triaging activities are performed, beginning with the assessment of large numbers of E. coli-expressed scFv, and progressing through additional assays with individual reformatting of the most promising scFv to full-length IgG. However, use of high-throughput screening of scFv for the discovery of full-length IgG is not ideal because of the differences between these molecules. Furthermore, the reformatting step represents a bottle neck in the process because each antibody has to be handled individually to preserve the unique VH and VL pairing. These problems could be resolved if populations of scFv could be reformatted to full-length IgG before screening without disrupting the variable region pairing. Here, we describe a novel strategy that allows the reformatting of diverse populations of scFv from phage selections to full-length IgG in a batch format. The reformatting process maintains the diversity and variable region pairing with high fidelity, and the resulted IgG pool enables high-throughput expression of IgG in mammalian cells and cell-based functional screening. The improved process led to the discovery of potent candidates that are comparable or better than those obtained by traditional methods. This strategy should also be readily applicable to Fab-based phage libraries. Our approach, Screening in Product Format (SiPF), represents a substantial improvement in the field of antibody discovery using phage display.
Auerbach, Scott; Filer, Dayne; Reif, David; Walker, Vickie; Holloway, Alison C.; Schlezinger, Jennifer; Srinivasan, Supriya; Svoboda, Daniel; Judson, Richard; Bucher, John R.; Thayer, Kristina A.
2016-01-01
Background: Diabetes and obesity are major threats to public health in the United States and abroad. Understanding the role that chemicals in our environment play in the development of these conditions is an emerging issue in environmental health, although identifying and prioritizing chemicals for testing beyond those already implicated in the literature is challenging. This review is intended to help researchers generate hypotheses about chemicals that may contribute to diabetes and to obesity-related health outcomes by summarizing relevant findings from the U.S. Environmental Protection Agency (EPA) ToxCast™ high-throughput screening (HTS) program. Objectives: Our aim was to develop new hypotheses around environmental chemicals of potential interest for diabetes- or obesity-related outcomes using high-throughput screening data. Methods: We identified ToxCast™ assay targets relevant to several biological processes related to diabetes and obesity (insulin sensitivity in peripheral tissue, pancreatic islet and β cell function, adipocyte differentiation, and feeding behavior) and presented chemical screening data against those assay targets to identify chemicals of potential interest. Discussion: The results of this screening-level analysis suggest that the spectrum of environmental chemicals to consider in research related to diabetes and obesity is much broader than indicated by research papers and reviews published in the peer-reviewed literature. Testing hypotheses based on ToxCast™ data will also help assess the predictive utility of this HTS platform. Conclusions: More research is required to put these screening-level analyses into context, but the information presented in this review should facilitate the development of new hypotheses. Citation: Auerbach S, Filer D, Reif D, Walker V, Holloway AC, Schlezinger J, Srinivasan S, Svoboda D, Judson R, Bucher JR, Thayer KA. 2016. Prioritizing environmental chemicals for obesity and diabetes outcomes research: a screening approach using ToxCast™ high-throughput data. Environ Health Perspect 124:1141–1154; http://dx.doi.org/10.1289/ehp.1510456 PMID:26978842
Auerbach, Scott; Filer, Dayne; Reif, David; Walker, Vickie; Holloway, Alison C; Schlezinger, Jennifer; Srinivasan, Supriya; Svoboda, Daniel; Judson, Richard; Bucher, John R; Thayer, Kristina A
2016-08-01
Diabetes and obesity are major threats to public health in the United States and abroad. Understanding the role that chemicals in our environment play in the development of these conditions is an emerging issue in environmental health, although identifying and prioritizing chemicals for testing beyond those already implicated in the literature is challenging. This review is intended to help researchers generate hypotheses about chemicals that may contribute to diabetes and to obesity-related health outcomes by summarizing relevant findings from the U.S. Environmental Protection Agency (EPA) ToxCast™ high-throughput screening (HTS) program. Our aim was to develop new hypotheses around environmental chemicals of potential interest for diabetes- or obesity-related outcomes using high-throughput screening data. We identified ToxCast™ assay targets relevant to several biological processes related to diabetes and obesity (insulin sensitivity in peripheral tissue, pancreatic islet and β cell function, adipocyte differentiation, and feeding behavior) and presented chemical screening data against those assay targets to identify chemicals of potential interest. The results of this screening-level analysis suggest that the spectrum of environmental chemicals to consider in research related to diabetes and obesity is much broader than indicated by research papers and reviews published in the peer-reviewed literature. Testing hypotheses based on ToxCast™ data will also help assess the predictive utility of this HTS platform. More research is required to put these screening-level analyses into context, but the information presented in this review should facilitate the development of new hypotheses. Auerbach S, Filer D, Reif D, Walker V, Holloway AC, Schlezinger J, Srinivasan S, Svoboda D, Judson R, Bucher JR, Thayer KA. 2016. Prioritizing environmental chemicals for obesity and diabetes outcomes research: a screening approach using ToxCast™ high-throughput data. Environ Health Perspect 124:1141-1154; http://dx.doi.org/10.1289/ehp.1510456.
Ufarté, Lisa; Bozonnet, Sophie; Laville, Elisabeth; Cecchini, Davide A; Pizzut-Serin, Sandra; Jacquiod, Samuel; Demanèche, Sandrine; Simonet, Pascal; Franqueville, Laure; Veronese, Gabrielle Potocki
2016-01-01
Activity-based metagenomics is one of the most efficient approaches to boost the discovery of novel biocatalysts from the huge reservoir of uncultivated bacteria. In this chapter, we describe a highly generic procedure of metagenomic library construction and high-throughput screening for carbohydrate-active enzymes. Applicable to any bacterial ecosystem, it enables the swift identification of functional enzymes that are highly efficient, alone or acting in synergy, to break down polysaccharides and oligosaccharides.
Campos-Gomez, Javier; Benitez, Jorge A
2018-07-01
RNA polymerase containing the stress response regulator σ S subunit (RpoS) plays a key role in bacterial survival in hostile environments in nature and during infection. Here we devise and validate a simple cell-based high throughput luminescence assay for this holoenzyme suitable for screening large chemical libraries in a robotic platform. Copyright © 2018 Elsevier B.V. All rights reserved.
2014-12-24
toxlet.2011.04.007 Rogers JV, Choi YW, Kiser RC et al (2004) Microarray analysis of gene expression in murine skin exposed to sulfur mustard. J Bio...Chemotactic factors released in culture by intact developing and healing skin lesions produced in rabbits by the irritant sulfur mustard. Inflam- mation 21(2...Project ID Number CBM.CUTOC.04.10. RC 00114. ABSTRACT See reprint. 15. SUBJECT TERMS sulfur mustard, cutaneous injury, siRNA, high-throughput screening
Islam, Md Koushikul; Baudin, Maria; Eriksson, Jonas; Öberg, Christopher; Habjan, Matthias; Weber, Friedemann; Överby, Anna K; Ahlm, Clas; Evander, Magnus
2016-04-01
Rift Valley fever virus (RVFV) is an emerging virus that causes serious illness in humans and livestock. There are no approved vaccines or treatments for humans. The purpose of the study was to identify inhibitory compounds of RVFV infection without any preconceived idea of the mechanism of action. A whole-cell-based high-throughput drug screening assay was developed to screen 28,437 small chemical compounds targeting RVFV infection. To accomplish both speed and robustness, a replication-competent NSs-deleted RVFV expressing a fluorescent reporter gene was developed. Inhibition of fluorescence intensity was quantified by spectrophotometry and related to virus infection in human lung epithelial cells (A549). Cell toxicity was assessed by the Resazurin cell viability assay. After primary screening, 641 compounds were identified that inhibited RVFV infection by ≥80%, with ≥50% cell viability at 50 µM concentration. These compounds were subjected to a second screening regarding dose-response profiles, and 63 compounds with ≥60% inhibition of RVFV infection at 3.12 µM compound concentration and ≥50% cell viability at 25 µM were considered hits. Of these, six compounds with high inhibitory activity were identified. In conclusion, the high-throughput assay could efficiently and safely identify several promising compounds that inhibited RVFV infection. © 2016 Society for Laboratory Automation and Screening.
Two High Throughput Screen Assays for Measurement of TNF-α in THP-1 Cells
Leister, Kristin P; Huang, Ruili; Goodwin, Bonnie L; Chen, Andrew; Austin, Christopher P; Xia, Menghang
2011-01-01
Tumor Necrosis Factor-α (TNF-α), a secreted cytokine, plays an important role in inflammatory diseases and immune disorders, and is a potential target for drug development. The traditional assays for detecting TNF-α, enzyme linked immunosorbent assay (ELISA) and radioimmunoassay, are not suitable for the large size compound screens. Both assays suffer from a complicated protocol, multiple plate wash steps and/or excessive radioactive waste. A simple and quick measurement of TNF-α production in a cell based assay is needed for high throughput screening to identify the lead compounds from the compound library. We have developed and optimized two homogeneous TNF-α assays using the HTRF (homogeneous time resolved fluorescence) and AlphaLISA assay formats. We have validated the HTRF based TNF-α assay in a 1536-well plate format by screening a library of 1280 pharmacologically active compounds. The active compounds identified from the screen were confirmed in the AlphaLISA TNF-α assay using a bead-based technology. These compounds were also confirmed in a traditional ELISA assay. From this study, several beta adrenergic agonists have been identified as TNF-α inhibitors. We also identified several novel inhibitors of TNF-α, such as BTO-1, CCG-2046, ellipticine, and PD 169316. The results demonstrated that both homogeneous TNF-α assays are robust and suitable for high throughput screening. PMID:21643507
Hassig, Christian A.; Zeng, Fu-Yue; Kung, Paul; Kiankarimi, Mehrak; Kim, Sylvia; Diaz, Paul W.; Zhai, Dayong; Welsh, Kate; Morshedian, Shana; Su, Ying; O'Keefe, Barry; Newman, David J.; Rusman, Yudi; Kaur, Harneet; Salomon, Christine E.; Brown, Susan G.; Baire, Beeraiah; Michel, Andrew R.; Hoye, Thomas R.; Francis, Subhashree; Georg, Gunda I.; Walters, Michael A.; Divlianska, Daniela B.; Roth, Gregory P.; Wright, Amy E.; Reed, John C.
2015-01-01
Anti-apoptotic Bcl-2 family proteins are validated cancer targets comprised of six related proteins. From a drug discovery perspective, these are challenging targets that exert their cellular functions through protein-protein interactions (PPIs). While several isoform-selective inhibitors have been developed using structure-based design or high throughput screening (HTS) of synthetic chemical libraries, no large scale screen of natural product collections has been reported. A competitive displacement fluorescence polarization (FP) screen of nearly 150,000 natural product extracts was conducted against all six anti-apoptotic Bcl-2 family proteins using fluorochrome-conjugated peptide ligands that mimic functionally-relevant PPIs. The screens were conducted in 1,536-well format and displayed satisfactory overall HTS statistics, with Z’-factor values ranging from 0.72 to 0.83, and a hit confirmation rate between 16-64%. Confirmed active extracts were orthogonally tested in a luminescent assay for caspase-3/7 activation in tumor cells. Active extracts were resupplied and effort toward the isolation of pure active components was initiated through iterative bioassay-guided fractionation. Several previously described altertoxins were isolated from a microbial source and the pure compounds demonstrate activity in both Bcl-2 FP and caspase cellular assays. The studies demonstrate the feasibility of ultra high throughput screening using natural product sources and highlight some of the challenges associated with this approach. PMID:24870016
Adissu, Hibret A.; Estabel, Jeanne; Sunter, David; Tuck, Elizabeth; Hooks, Yvette; Carragher, Damian M.; Clarke, Kay; Karp, Natasha A.; Project, Sanger Mouse Genetics; Newbigging, Susan; Jones, Nora; Morikawa, Lily; White, Jacqueline K.; McKerlie, Colin
2014-01-01
The Mouse Genetics Project (MGP) at the Wellcome Trust Sanger Institute aims to generate and phenotype over 800 genetically modified mouse lines over the next 5 years to gain a better understanding of mammalian gene function and provide an invaluable resource to the scientific community for follow-up studies. Phenotyping includes the generation of a standardized biobank of paraffin-embedded tissues for each mouse line, but histopathology is not routinely performed. In collaboration with the Pathology Core of the Centre for Modeling Human Disease (CMHD) we report the utility of histopathology in a high-throughput primary phenotyping screen. Histopathology was assessed in an unbiased selection of 50 mouse lines with (n=30) or without (n=20) clinical phenotypes detected by the standard MGP primary phenotyping screen. Our findings revealed that histopathology added correlating morphological data in 19 of 30 lines (63.3%) in which the primary screen detected a phenotype. In addition, seven of the 50 lines (14%) presented significant histopathology findings that were not associated with or predicted by the standard primary screen. Three of these seven lines had no clinical phenotype detected by the standard primary screen. Incidental and strain-associated background lesions were present in all mutant lines with good concordance to wild-type controls. These findings demonstrate the complementary and unique contribution of histopathology to high-throughput primary phenotyping of mutant mice. PMID:24652767
Goldberg, Deborah S; Lewus, Rachael A; Esfandiary, Reza; Farkas, David C; Mody, Neil; Day, Katrina J; Mallik, Priyanka; Tracka, Malgorzata B; Sealey, Smita K; Samra, Hardeep S
2017-08-01
Selecting optimal formulation conditions for monoclonal antibodies for first time in human clinical trials is challenging due to short timelines and reliance on predictive assays to ensure product quality and adequate long-term stability. Accelerated stability studies are considered to be the gold standard for excipient screening, but they are relatively low throughput and time consuming. High throughput screening (HTS) techniques allow for large amounts of data to be collected quickly and easily, and can be used to screen solution conditions for early formulation development. The utility of using accelerated stability compared to HTS techniques (differential scanning light scattering and differential scanning fluorescence) for early formulation screening was evaluated along with the impact of excipients of various types on aggregation of monoclonal antibodies from multiple IgG subtypes. The excipient rank order using quantitative HTS measures was found to correlate with accelerated stability aggregation rate ranking for only 33% (by differential scanning fluorescence) to 42% (by differential scanning light scattering) of the antibodies tested, due to the high intrinsic stability and minimal impact of excipients on aggregation rates and HTS data. Also explored was a case study of employing a platform formulation instead of broader formulation screening for early formulation development. Copyright © 2017 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.
Wang, Xixian; Ren, Lihui; Su, Yetian; Ji, Yuetong; Liu, Yaoping; Li, Chunyu; Li, Xunrong; Zhang, Yi; Wang, Wei; Hu, Qiang; Han, Danxiang; Xu, Jian; Ma, Bo
2017-11-21
Raman-activated cell sorting (RACS) has attracted increasing interest, yet throughput remains one major factor limiting its broader application. Here we present an integrated Raman-activated droplet sorting (RADS) microfluidic system for functional screening of live cells in a label-free and high-throughput manner, by employing AXT-synthetic industrial microalga Haematococcus pluvialis (H. pluvialis) as a model. Raman microspectroscopy analysis of individual cells is carried out prior to their microdroplet encapsulation, which is then directly coupled to DEP-based droplet sorting. To validate the system, H. pluvialis cells containing different levels of AXT were mixed and underwent RADS. Those AXT-hyperproducing cells were sorted with an accuracy of 98.3%, an enrichment ratio of eight folds, and a throughput of ∼260 cells/min. Of the RADS-sorted cells, 92.7% remained alive and able to proliferate, which is equivalent to the unsorted cells. Thus, the RADS achieves a much higher throughput than existing RACS systems, preserves the vitality of cells, and facilitates seamless coupling with downstream manipulations such as single-cell sequencing and cultivation.
Mayo, Johnathan; Baur, Kilian; Wittmann, Frieder; Riener, Robert; Wolf, Peter
2018-01-01
Background Goal-directed reaching for real-world objects by humans is enabled through visual depth cues. In virtual environments, the number and quality of available visual depth cues is limited, which may affect reaching performance and quality of reaching movements. Methods We assessed three-dimensional reaching movements in five experimental groups each with ten healthy volunteers. Three groups used a two-dimensional computer screen and two groups used a head-mounted display. The first screen group received the typically recreated visual depth cues, such as aerial and linear perspective, occlusion, shadows, and texture gradients. The second screen group received an abstract minimal rendering lacking those. The third screen group received the cues of the first screen group and absolute depth cues enabled by retinal image size of a known object, which realized with visual renderings of the handheld device and a ghost handheld at the target location. The two head-mounted display groups received the same virtually recreated visual depth cues as the second or the third screen group respectively. Additionally, they could rely on stereopsis and motion parallax due to head-movements. Results and conclusion All groups using the screen performed significantly worse than both groups using the head-mounted display in terms of completion time normalized by the straight-line distance to the target. Both groups using the head-mounted display achieved the optimal minimum in number of speed peaks and in hand path ratio, indicating that our subjects performed natural movements when using a head-mounted display. Virtually recreated visual depth cues had a minor impact on reaching performance. Only the screen group with rendered handhelds could outperform the other screen groups. Thus, if reaching performance in virtual environments is in the main scope of a study, we suggest applying a head-mounted display. Otherwise, when two-dimensional screens are used, achievable performance is likely limited by the reduced depth perception and not just by subjects’ motor skills. PMID:29293512
Gerrard, Gareth; Valgañón, Mikel; Foong, Hui En; Kasperaviciute, Dalia; Iskander, Deena; Game, Laurence; Müller, Michael; Aitman, Timothy J; Roberts, Irene; de la Fuente, Josu; Foroni, Letizia; Karadimitris, Anastasios
2013-08-01
Diamond-Blackfan anaemia (DBA) is caused by inactivating mutations in ribosomal protein (RP) genes, with mutations in 13 of the 80 RP genes accounting for 50-60% of cases. The remaining 40-50% cases may harbour mutations in one of the remaining RP genes, but the very low frequencies render conventional genetic screening as challenging. We, therefore, applied custom enrichment technology combined with high-throughput sequencing to screen all 80 RP genes. Using this approach, we identified and validated inactivating mutations in 15/17 (88%) DBA patients. Target enrichment combined with high-throughput sequencing is a robust and improved methodology for the genetic diagnosis of DBA. © 2013 John Wiley & Sons Ltd.
Optimizing multi-dimensional high throughput screening using zebrafish.
Truong, Lisa; Bugel, Sean M; Chlebowski, Anna; Usenko, Crystal Y; Simonich, Michael T; Simonich, Staci L Massey; Tanguay, Robert L
2016-10-01
The use of zebrafish for high throughput screening (HTS) for chemical bioactivity assessments is becoming routine in the fields of drug discovery and toxicology. Here we report current recommendations from our experiences in zebrafish HTS. We compared the effects of different high throughput chemical delivery methods on nominal water concentration, chemical sorption to multi-well polystyrene plates, transcription responses, and resulting whole animal responses. We demonstrate that digital dispensing consistently yields higher data quality and reproducibility compared to standard plastic tip-based liquid handling. Additionally, we illustrate the challenges in using this sensitive model for chemical assessment when test chemicals have trace impurities. Adaptation of these better practices for zebrafish HTS should increase reproducibility across laboratories. Copyright © 2016 Elsevier Inc. All rights reserved.
Microengineering methods for cell-based microarrays and high-throughput drug-screening applications.
Xu, Feng; Wu, JinHui; Wang, ShuQi; Durmus, Naside Gozde; Gurkan, Umut Atakan; Demirci, Utkan
2011-09-01
Screening for effective therapeutic agents from millions of drug candidates is costly, time consuming, and often faces concerns due to the extensive use of animals. To improve cost effectiveness, and to minimize animal testing in pharmaceutical research, in vitro monolayer cell microarrays with multiwell plate assays have been developed. Integration of cell microarrays with microfluidic systems has facilitated automated and controlled component loading, significantly reducing the consumption of the candidate compounds and the target cells. Even though these methods significantly increased the throughput compared to conventional in vitro testing systems and in vivo animal models, the cost associated with these platforms remains prohibitively high. Besides, there is a need for three-dimensional (3D) cell-based drug-screening models which can mimic the in vivo microenvironment and the functionality of the native tissues. Here, we present the state-of-the-art microengineering approaches that can be used to develop 3D cell-based drug-screening assays. We highlight the 3D in vitro cell culture systems with live cell-based arrays, microfluidic cell culture systems, and their application to high-throughput drug screening. We conclude that among the emerging microengineering approaches, bioprinting holds great potential to provide repeatable 3D cell-based constructs with high temporal, spatial control and versatility.
Efthymiou, Anastasia; Shaltouki, Atossa; Steiner, Joseph P; Jha, Balendu; Heman-Ackah, Sabrina M; Swistowski, Andrzej; Zeng, Xianmin; Rao, Mahendra S; Malik, Nasir
2014-01-01
Rapid and effective drug discovery for neurodegenerative disease is currently impeded by an inability to source primary neural cells for high-throughput and phenotypic screens. This limitation can be addressed through the use of pluripotent stem cells (PSCs), which can be derived from patient-specific samples and differentiated to neural cells for use in identifying novel compounds for the treatment of neurodegenerative diseases. We have developed an efficient protocol to culture pure populations of neurons, as confirmed by gene expression analysis, in the 96-well format necessary for screens. These differentiated neurons were subjected to viability assays to illustrate their potential in future high-throughput screens. We have also shown that organelles such as nuclei and mitochondria could be live-labeled and visualized through fluorescence, suggesting that we should be able to monitor subcellular phenotypic changes. Neurons derived from a green fluorescent protein-expressing reporter line of PSCs were live-imaged to assess markers of neuronal maturation such as neurite length and co-cultured with astrocytes to demonstrate further maturation. These studies confirm that PSC-derived neurons can be used effectively in viability and functional assays and pave the way for high-throughput screens on neurons derived from patients with neurodegenerative disorders.
Kusters, Ilja; van Oijen, Antoine M; Driessen, Arnold J M
2014-04-22
Screening of transport processes across biological membranes is hindered by the challenge to establish fragile supported lipid bilayers and the difficulty to determine at which side of the membrane reactants reside. Here, we present a method for the generation of suspended lipid bilayers with physiological relevant lipid compositions on microstructured Si/SiO2 chips that allow for high-throughput screening of both membrane transport and viral membrane fusion. Simultaneous observation of hundreds of single-membrane channels yields statistical information revealing population heterogeneities of the pore assembly and conductance of the bacterial toxin α-hemolysin (αHL). The influence of lipid composition and ionic strength on αHL pore formation was investigated at the single-channel level, resolving features of the pore-assembly pathway. Pore formation is inhibited by a specific antibody, demonstrating the applicability of the platform for drug screening of bacterial toxins and cell-penetrating agents. Furthermore, fusion of H3N2 influenza viruses with suspended lipid bilayers can be observed directly using a specialized chip architecture. The presented micropore arrays are compatible with fluorescence readout from below using an air objective, thus allowing high-throughput screening of membrane transport in multiwell formats in analogy to plate readers.
Microengineering Methods for Cell Based Microarrays and High-Throughput Drug Screening Applications
Xu, Feng; Wu, JinHui; Wang, ShuQi; Durmus, Naside Gozde; Gurkan, Umut Atakan; Demirci, Utkan
2011-01-01
Screening for effective therapeutic agents from millions of drug candidates is costly, time-consuming and often face ethical concerns due to extensive use of animals. To improve cost-effectiveness, and to minimize animal testing in pharmaceutical research, in vitro monolayer cell microarrays with multiwell plate assays have been developed. Integration of cell microarrays with microfluidic systems have facilitated automated and controlled component loading, significantly reducing the consumption of the candidate compounds and the target cells. Even though these methods significantly increased the throughput compared to conventional in vitro testing systems and in vivo animal models, the cost associated with these platforms remains prohibitively high. Besides, there is a need for three-dimensional (3D) cell based drug-screening models, which can mimic the in vivo microenvironment and the functionality of the native tissues. Here, we present the state-of-the-art microengineering approaches that can be used to develop 3D cell based drug screening assays. We highlight the 3D in vitro cell culture systems with live cell-based arrays, microfluidic cell culture systems, and their application to high-throughput drug screening. We conclude that among the emerging microengineering approaches, bioprinting holds a great potential to provide repeatable 3D cell based constructs with high temporal, spatial control and versatility. PMID:21725152
Screening Chemicals for Estrogen Receptor Bioactivity Using a Computational Model.
Browne, Patience; Judson, Richard S; Casey, Warren M; Kleinstreuer, Nicole C; Thomas, Russell S
2015-07-21
The U.S. Environmental Protection Agency (EPA) is considering high-throughput and computational methods to evaluate the endocrine bioactivity of environmental chemicals. Here we describe a multistep, performance-based validation of new methods and demonstrate that these new tools are sufficiently robust to be used in the Endocrine Disruptor Screening Program (EDSP). Results from 18 estrogen receptor (ER) ToxCast high-throughput screening assays were integrated into a computational model that can discriminate bioactivity from assay-specific interference and cytotoxicity. Model scores range from 0 (no activity) to 1 (bioactivity of 17β-estradiol). ToxCast ER model performance was evaluated for reference chemicals, as well as results of EDSP Tier 1 screening assays in current practice. The ToxCast ER model accuracy was 86% to 93% when compared to reference chemicals and predicted results of EDSP Tier 1 guideline and other uterotrophic studies with 84% to 100% accuracy. The performance of high-throughput assays and ToxCast ER model predictions demonstrates that these methods correctly identify active and inactive reference chemicals, provide a measure of relative ER bioactivity, and rapidly identify chemicals with potential endocrine bioactivities for additional screening and testing. EPA is accepting ToxCast ER model data for 1812 chemicals as alternatives for EDSP Tier 1 ER binding, ER transactivation, and uterotrophic assays.
Staged anticonvulsant screening for chronic epilepsy.
Berdichevsky, Yevgeny; Saponjian, Yero; Park, Kyung-Il; Roach, Bonnie; Pouliot, Wendy; Lu, Kimberly; Swiercz, Waldemar; Dudek, F Edward; Staley, Kevin J
2016-12-01
Current anticonvulsant screening programs are based on seizures evoked in normal animals. One-third of epileptic patients do not respond to the anticonvulsants discovered with these models. We evaluated a tiered program based on chronic epilepsy and spontaneous seizures, with compounds advancing from high-throughput in vitro models to low-throughput in vivo models. Epileptogenesis in organotypic hippocampal slice cultures was quantified by lactate production and lactate dehydrogenase release into culture media as rapid assays for seizure-like activity and cell death, respectively. Compounds that reduced these biochemical measures were retested with in vitro electrophysiological confirmation (i.e., second stage). The third stage involved crossover testing in the kainate model of chronic epilepsy, with blinded analysis of spontaneous seizures after continuous electrographic recordings. We screened 407 compound-concentration combinations. The cyclooxygenase inhibitor, celecoxib, had no effect on seizures evoked in normal brain tissue but demonstrated robust antiseizure activity in all tested models of chronic epilepsy. The use of organotypic hippocampal cultures, where epileptogenesis occurs on a compressed time scale, and where seizure-like activity and seizure-induced cell death can be easily quantified with biomarker assays, allowed us to circumvent the throughput limitations of in vivo chronic epilepsy models. Ability to rapidly screen compounds in a chronic model of epilepsy allowed us to find an anticonvulsant that would be missed by screening in acute models.
Fully Bayesian Analysis of High-throughput Targeted Metabolomics Assays
High-throughput metabolomic assays that allow simultaneous targeted screening of hundreds of metabolites have recently become available in kit form. Such assays provide a window into understanding changes to biochemical pathways due to chemical exposure or disease, and are usefu...
Zebrafish Development: High-throughput Test Systems to Assess Developmental Toxicity
Abstract Because of its developmental concordance, ease of handling and rapid development, the small teleost, zebrafish (Danio rerio), is frequently promoted as a vertebrate model for medium-throughput developmental screens. This present chapter discusses zebrafish as an altern...
Noeske, Tobias; Trifanova, Dina; Kauss, Valerjans; Renner, Steffen; Parsons, Christopher G; Schneider, Gisbert; Weil, Tanja
2009-08-01
We report the identification of novel potent and selective metabotropic glutamate receptor 1 (mGluR1) antagonists by virtual screening and subsequent hit optimization. For ligand-based virtual screening, molecules were represented by a topological pharmacophore descriptor (CATS-2D) and clustered by a self-organizing map (SOM). The most promising compounds were tested in mGluR1 functional and binding assays. We identified a potent chemotype exhibiting selective antagonistic activity at mGluR1 (functional IC(50)=0.74+/-0.29 microM). Hit optimization yielded lead structure 16 with an affinity of K(i)=0.024+/-0.001 microM and greater than 1000-fold selectivity for mGluR1 versus mGluR5. Homology-based receptor modelling suggests a binding site compatible with previously reported mutation studies. Our study demonstrates the usefulness of ligand-based virtual screening for scaffold-hopping and rapid lead structure identification in early drug discovery projects.
Melagraki, G; Afantitis, A
2011-01-01
Virtual Screening (VS) has experienced increased attention into the recent years due to the large datasets made available, the development of advanced VS techniques and the encouraging fact that VS has contributed to the discovery of several compounds that have either reached the market or entered clinical trials. Hepatitis C Virus (HCV) nonstructural protein 5B (NS5B) has become an attractive target for the development of antiviral drugs and many small molecules have been explored as possible HCV NS5B inhibitors. In parallel with experimental practices, VS can serve as a valuable tool in the identification of novel effective inhibitors. Different techniques and workflows have been reported in literature with the goal to prioritize possible potent hits. In this context, different virtual screening strategies have been deployed for the identification of novel Hepatitis C Virus (HCV) inhibitors. This work reviews recent applications of virtual screening in an effort to identify novel potent HCV inhibitors.
Maximum unbiased validation (MUV) data sets for virtual screening based on PubChem bioactivity data.
Rohrer, Sebastian G; Baumann, Knut
2009-02-01
Refined nearest neighbor analysis was recently introduced for the analysis of virtual screening benchmark data sets. It constitutes a technique from the field of spatial statistics and provides a mathematical framework for the nonparametric analysis of mapped point patterns. Here, refined nearest neighbor analysis is used to design benchmark data sets for virtual screening based on PubChem bioactivity data. A workflow is devised that purges data sets of compounds active against pharmaceutically relevant targets from unselective hits. Topological optimization using experimental design strategies monitored by refined nearest neighbor analysis functions is applied to generate corresponding data sets of actives and decoys that are unbiased with regard to analogue bias and artificial enrichment. These data sets provide a tool for Maximum Unbiased Validation (MUV) of virtual screening methods. The data sets and a software package implementing the MUV design workflow are freely available at http://www.pharmchem.tu-bs.de/lehre/baumann/MUV.html.
Dreyer, Florian S; Cantone, Martina; Eberhardt, Martin; Jaitly, Tanushree; Walter, Lisa; Wittmann, Jürgen; Gupta, Shailendra K; Khan, Faiz M; Wolkenhauer, Olaf; Pützer, Brigitte M; Jäck, Hans-Martin; Heinzerling, Lucie; Vera, Julio
2018-06-01
Cellular phenotypes are established and controlled by complex and precisely orchestrated molecular networks. In cancer, mutations and dysregulations of multiple molecular factors perturb the regulation of these networks and lead to malignant transformation. High-throughput technologies are a valuable source of information to establish the complex molecular relationships behind the emergence of malignancy, but full exploitation of this massive amount of data requires bioinformatics tools that rely on network-based analyses. In this report we present the Virtual Melanoma Cell, an online tool developed to facilitate the mining and interpretation of high-throughput data on melanoma by biomedical researches. The platform is based on a comprehensive, manually generated and expert-validated regulatory map composed of signaling pathways important in malignant melanoma. The Virtual Melanoma Cell is a tool designed to accept, visualize and analyze user-generated datasets. It is available at: https://www.vcells.net/melanoma. To illustrate the utilization of the web platform and the regulatory map, we have analyzed a large publicly available dataset accounting for anti-PD1 immunotherapy treatment of malignant melanoma patients. Copyright © 2018 Elsevier B.V. All rights reserved.
Li, Guoliang; Yuan, Hui; Zhang, Hongchao; Li, Yanjun; Xie, Xixian; Chen, Ning
2017-01-01
In the present study, a novel breeding strategy of atmospheric and room temperature plasma (ARTP) mutagenesis was used to improve the uridine production of engineered Bacillus subtilis TD12np. A high-throughput screening method was established using both resistant plates and 96-well microplates to select the ideal mutants with diverse phenotypes. Mutant F126 accumulated 5.7 and 30.3 g/L uridine after 30 h in shake-flask and 48 h in fed-batch fermentation, respectively, which represented a 4.4- and 8.7-fold increase over the parent strain. Sequence analysis of the pyrimidine nucleotide biosynthetic operon in the representative mutants showed that proline 1016 and glutamate 949 in the large subunit of B. subtilis carbamoyl phosphate synthetase were of importance for the allosteric regulation caused by uridine 5′-monophosphate. The proposed mutation method with efficient high-throughput screening assay was proved to be an appropriate strategy to obtain uridine-overproducing strain. PMID:28472077
Fan, Xiaoguang; Wu, Heyun; Li, Guoliang; Yuan, Hui; Zhang, Hongchao; Li, Yanjun; Xie, Xixian; Chen, Ning
2017-01-01
In the present study, a novel breeding strategy of atmospheric and room temperature plasma (ARTP) mutagenesis was used to improve the uridine production of engineered Bacillus subtilis TD12np. A high-throughput screening method was established using both resistant plates and 96-well microplates to select the ideal mutants with diverse phenotypes. Mutant F126 accumulated 5.7 and 30.3 g/L uridine after 30 h in shake-flask and 48 h in fed-batch fermentation, respectively, which represented a 4.4- and 8.7-fold increase over the parent strain. Sequence analysis of the pyrimidine nucleotide biosynthetic operon in the representative mutants showed that proline 1016 and glutamate 949 in the large subunit of B. subtilis carbamoyl phosphate synthetase were of importance for the allosteric regulation caused by uridine 5'-monophosphate. The proposed mutation method with efficient high-throughput screening assay was proved to be an appropriate strategy to obtain uridine-overproducing strain.
Ngo, Tony; Coleman, James L J; Smith, Nicola J
2015-01-01
Orphan G protein-coupled receptors represent an underexploited resource for drug discovery but pose a considerable challenge for assay development because their cognate G protein signaling pathways are often unknown. In this methodological chapter, we describe the use of constitutive activity, that is, the inherent ability of receptors to couple to their cognate G proteins in the absence of ligand, to inform the development of high-throughput screening assays for a particular orphan receptor. We specifically focus on a two-step process, whereby constitutive G protein coupling is first determined using yeast Gpa1/human G protein chimeras linked to growth and β-galactosidase generation. Coupling selectivity is then confirmed in mammalian cells expressing endogenous G proteins and driving accumulation of transcription factor-fused luciferase reporters specific to each of the classes of G protein. Based on these findings, high-throughput screening campaigns can be performed on the already miniaturized mammalian reporter system.
Novel method for high-throughput colony PCR screening in nanoliter-reactors
Walser, Marcel; Pellaux, Rene; Meyer, Andreas; Bechtold, Matthias; Vanderschuren, Herve; Reinhardt, Richard; Magyar, Joseph; Panke, Sven; Held, Martin
2009-01-01
We introduce a technology for the rapid identification and sequencing of conserved DNA elements employing a novel suspension array based on nanoliter (nl)-reactors made from alginate. The reactors have a volume of 35 nl and serve as reaction compartments during monoseptic growth of microbial library clones, colony lysis, thermocycling and screening for sequence motifs via semi-quantitative fluorescence analyses. nl-Reactors were kept in suspension during all high-throughput steps which allowed performing the protocol in a highly space-effective fashion and at negligible expenses of consumables and reagents. As a first application, 11 high-quality microsatellites for polymorphism studies in cassava were isolated and sequenced out of a library of 20 000 clones in 2 days. The technology is widely scalable and we envision that throughputs for nl-reactor based screenings can be increased up to 100 000 and more samples per day thereby efficiently complementing protocols based on established deep-sequencing technologies. PMID:19282448
Mordwinkin, Nicholas M; Burridge, Paul W; Wu, Joseph C
2013-02-01
Drug attrition rates have increased in past years, resulting in growing costs for the pharmaceutical industry and consumers. The reasons for this include the lack of in vitro models that correlate with clinical results and poor preclinical toxicity screening assays. The in vitro production of human cardiac progenitor cells and cardiomyocytes from human pluripotent stem cells provides an amenable source of cells for applications in drug discovery, disease modeling, regenerative medicine, and cardiotoxicity screening. In addition, the ability to derive human-induced pluripotent stem cells from somatic tissues, combined with current high-throughput screening and pharmacogenomics, may help realize the use of these cells to fulfill the potential of personalized medicine. In this review, we discuss the use of pluripotent stem cell-derived cardiomyocytes for drug discovery and cardiotoxicity screening, as well as current hurdles that must be overcome for wider clinical applications of this promising approach.
Stewart, Eugene L; Brown, Peter J; Bentley, James A; Willson, Timothy M
2004-08-01
A methodology for the selection and validation of nuclear receptor ligand chemical descriptors is described. After descriptors for a targeted chemical space were selected, a virtual screening methodology utilizing this space was formulated for the identification of potential NR ligands from our corporate collection. Using simple descriptors and our virtual screening method, we are able to quickly identify potential NR ligands from a large collection of compounds. As validation of the virtual screening procedure, an 8, 000-membered NR targeted set and a 24, 000-membered diverse control set of compounds were selected from our in-house general screening collection and screened in parallel across a number of orphan NR FRET assays. For the two assays that provided at least one hit per set by the established minimum pEC(50) for activity, the results showed a 2-fold increase in the hit-rate of the targeted compound set over the diverse set.
New approaches are vital for efficiently evaluating human health risk of thousands of chemicals in commerce. In vitro models offer a high-throughput approach for assaying chemical-induced molecular and cellular changes; however, bridging these perturbations to in vivo effects acr...
A large scale virtual screen of DprE1.
Wilsey, Claire; Gurka, Jessica; Toth, David; Franco, Jimmy
2013-12-01
Tuberculosis continues to plague the world with the World Health Organization estimating that about one third of the world's population is infected. Due to the emergence of MDR and XDR strains of TB, the need for novel therapeutics has become increasing urgent. Herein we report the results of a virtual screen of 4.1 million compounds against a promising drug target, DrpE1. The virtual compounds were obtained from the Zinc docking site and screened using the molecular docking program, AutoDock Vina. The computational hits have led to the identification of several promising lead compounds. Copyright © 2013 Elsevier Ltd. All rights reserved.
USDA-ARS?s Scientific Manuscript database
The field of high-content screening (HCS) typically uses measures of screen quality conceived for fairly straightforward high-throughput screening (HTS) scenarios. However, in contrast to HTS, image-based HCS systems rely on multidimensional readouts reporting biological responses associated with co...
Watt, Eric D.; Hornung, Michael W.; Hedge, Joan M.; Judson, Richard S.; Crofton, Kevin M.; Houck, Keith A.; Simmons, Steven O.
2016-01-01
High-throughput screening for potential thyroid-disrupting chemicals requires a system of assays to capture multiple molecular-initiating events (MIEs) that converge on perturbed thyroid hormone (TH) homeostasis. Screening for MIEs specific to TH-disrupting pathways is limited in the U.S. Environmental Protection Agency ToxCast screening assay portfolio. To fill 1 critical screening gap, the Amplex UltraRed-thyroperoxidase (AUR-TPO) assay was developed to identify chemicals that inhibit TPO, as decreased TPO activity reduces TH synthesis. The ToxCast phase I and II chemical libraries, comprised of 1074 unique chemicals, were initially screened using a single, high concentration to identify potential TPO inhibitors. Chemicals positive in the single-concentration screen were retested in concentration-response. Due to high false-positive rates typically observed with loss-of-signal assays such as AUR-TPO, we also employed 2 additional assays in parallel to identify possible sources of nonspecific assay signal loss, enabling stratification of roughly 300 putative TPO inhibitors based upon selective AUR-TPO activity. A cell-free luciferase inhibition assay was used to identify nonspecific enzyme inhibition among the putative TPO inhibitors, and a cytotoxicity assay using a human cell line was used to estimate the cellular tolerance limit. Additionally, the TPO inhibition activities of 150 chemicals were compared between the AUR-TPO and an orthogonal peroxidase oxidation assay using guaiacol as a substrate to confirm the activity profiles of putative TPO inhibitors. This effort represents the most extensive TPO inhibition screening campaign to date and illustrates a tiered screening approach that focuses resources, maximizes assay throughput, and reduces animal use. PMID:26884060
Targeted post-mortem computed tomography cardiac angiography: proof of concept.
Saunders, Sarah L; Morgan, Bruno; Raj, Vimal; Robinson, Claire E; Rutty, Guy N
2011-07-01
With the increasing use and availability of multi-detector computed tomography and magnetic resonance imaging in autopsy practice, there has been an international push towards the development of the so-called near virtual autopsy. However, currently, a significant obstacle to the consideration as to whether or not near virtual autopsies could one day replace the conventional invasive autopsy is the failure of post-mortem imaging to yield detailed information concerning the coronary arteries. To date, a cost-effective, practical solution to allow high throughput imaging has not been presented within the forensic literature. We present a proof of concept paper describing a simple, quick, cost-effective, manual, targeted in situ post-mortem cardiac angiography method using a minimally invasive approach, to be used with multi-detector computed tomography for high throughput cadaveric imaging which can be used in permanent or temporary mortuaries.
Beeman, Katrin; Baumgärtner, Jens; Laubenheimer, Manuel; Hergesell, Karlheinz; Hoffmann, Martin; Pehl, Ulrich; Fischer, Frank; Pieck, Jan-Carsten
2017-12-01
Mass spectrometry (MS) is known for its label-free detection of substrates and products from a variety of enzyme reactions. Recent hardware improvements have increased interest in the use of matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) MS for high-throughput drug discovery. Despite interest in this technology, several challenges remain and must be overcome before MALDI-MS can be integrated as an automated "in-line reader" for high-throughput drug discovery. Two such hurdles include in situ sample processing and deposition, as well as integration of MALDI-MS for enzymatic screening assays that usually contain high levels of MS-incompatible components. Here we adapt our c-MET kinase assay to optimize for MALDI-MS compatibility and test its feasibility for compound screening. The pros and cons of the Echo (Labcyte) as a transfer system for in situ MALDI-MS sample preparation are discussed. We demonstrate that this method generates robust data in a 1536-grid format. We use the MALDI-MS to directly measure the ratio of c-MET substrate and phosphorylated product to acquire IC50 curves and demonstrate that the pharmacology is unaffected. The resulting IC50 values correlate well between the common label-based capillary electrophoresis and the label-free MALDI-MS detection method. We predict that label-free MALDI-MS-based high-throughput screening will become increasingly important and more widely used for drug discovery.
Okagbare, Paul I.; Soper, Steven A.
2011-01-01
Microfluidics represents a viable platform for performing High Throughput Screening (HTS) due to its ability to automate fluid handling and generate fluidic networks with high number densities over small footprints appropriate for the simultaneous optical interrogation of many screening assays. While most HTS campaigns depend on fluorescence, readers typically use point detection and serially address the assay results significantly lowering throughput or detection sensitivity due to a low duty cycle. To address this challenge, we present here the fabrication of a high density microfluidic network packed into the imaging area of a large field-of-view (FoV) ultrasensitive fluorescence detection system. The fluidic channels were 1, 5 or 10 μm (width), 1 μm (depth) with a pitch of 1–10 μm and each fluidic processor was individually addressable. The fluidic chip was produced from a molding tool using hot embossing and thermal fusion bonding to enclose the fluidic channels. A 40X microscope objective (numerical aperture = 0.75) created a FoV of 200 μm, providing the ability to interrogate ~25 channels using the current fluidic configuration. An ultrasensitive fluorescence detection system with a large FoV was used to transduce fluorescence signals simultaneously from each fluidic processor onto the active area of an electron multiplying charge-coupled device (EMCCD). The utility of these multichannel networks for HTS was demonstrated by carrying out the high throughput monitoring of the activity of an enzyme, APE1, used as a model screening assay. PMID:20872611
High Throughput Assays and Exposure Science (ISES annual meeting)
High throughput screening (HTS) data characterizing chemical-induced biological activity has been generated for thousands of environmentally-relevant chemicals by the US inter-agency Tox21 and the US EPA ToxCast programs. For a limited set of chemicals, bioactive concentrations r...
High Throughput Exposure Estimation Using NHANES Data (SOT)
In the ExpoCast project, high throughput (HT) exposure models enable rapid screening of large numbers of chemicals for exposure potential. Evaluation of these models requires empirical exposure data and due to the paucity of human metabolism/exposure data such evaluations includ...
Embryonic vascular disruption is an important adverse outcome pathway (AOP) given the knowledge that chemical disruption of early cardiovascular system development leads to broad prenatal defects. High throughput screening (HTS) assays provide potential building blocks for AOP d...
Accounting For Uncertainty in The Application Of High Throughput Datasets
The use of high throughput screening (HTS) datasets will need to adequately account for uncertainties in the data generation process and propagate these uncertainties through to ultimate use. Uncertainty arises at multiple levels in the construction of predictors using in vitro ...
Streamlined approaches that use in vitro experimental data to predict chemical toxicokinetics (TK) are increasingly being used to perform risk-based prioritization based upon dosimetric adjustment of high-throughput screening (HTS) data across thousands of chemicals. However, ass...
Optimization and high-throughput screening of antimicrobial peptides.
Blondelle, Sylvie E; Lohner, Karl
2010-01-01
While a well-established process for lead compound discovery in for-profit companies, high-throughput screening is becoming more popular in basic and applied research settings in academia. The development of combinatorial libraries combined with easy and less expensive access to new technologies have greatly contributed to the implementation of high-throughput screening in academic laboratories. While such techniques were earlier applied to simple assays involving single targets or based on binding affinity, they have now been extended to more complex systems such as whole cell-based assays. In particular, the urgent need for new antimicrobial compounds that would overcome the rapid rise of drug-resistant microorganisms, where multiple target assays or cell-based assays are often required, has forced scientists to focus onto high-throughput technologies. Based on their existence in natural host defense systems and their different mode of action relative to commercial antibiotics, antimicrobial peptides represent a new hope in discovering novel antibiotics against multi-resistant bacteria. The ease of generating peptide libraries in different formats has allowed a rapid adaptation of high-throughput assays to the search for novel antimicrobial peptides. Similarly, the availability nowadays of high-quantity and high-quality antimicrobial peptide data has permitted the development of predictive algorithms to facilitate the optimization process. This review summarizes the various library formats that lead to de novo antimicrobial peptide sequences as well as the latest structural knowledge and optimization processes aimed at improving the peptides selectivity.
High-Throughput Screening and Hit Validation of Extracellular-Related Kinase 5 (ERK5) Inhibitors.
Myers, Stephanie M; Bawn, Ruth H; Bisset, Louise C; Blackburn, Timothy J; Cottyn, Betty; Molyneux, Lauren; Wong, Ai-Ching; Cano, Celine; Clegg, William; Harrington, Ross W; Leung, Hing; Rigoreau, Laurent; Vidot, Sandrine; Golding, Bernard T; Griffin, Roger J; Hammonds, Tim; Newell, David R; Hardcastle, Ian R
2016-08-08
The extracellular-related kinase 5 (ERK5) is a promising target for cancer therapy. A high-throughput screen was developed for ERK5, based on the IMAP FP progressive binding system, and used to identify hits from a library of 57 617 compounds. Four distinct chemical series were evident within the screening hits. Resynthesis and reassay of the hits demonstrated that one series did not return active compounds, whereas three series returned active hits. Structure-activity studies demonstrated that the 4-benzoylpyrrole-2-carboxamide pharmacophore had excellent potential for further development. The minimum kinase binding pharmacophore was identified, and key examples demonstrated good selectivity for ERK5 over p38α kinase.
Sensitive high-throughput screening for the detection of reducing sugars.
Mellitzer, Andrea; Glieder, Anton; Weis, Roland; Reisinger, Christoph; Flicker, Karlheinz
2012-01-01
The exploitation of renewable resources for the production of biofuels relies on efficient processes for the enzymatic hydrolysis of lignocellulosic materials. The development of enzymes and strains for these processes requires reliable and fast activity-based screening assays. Additionally, these assays are also required to operate on the microscale and on the high-throughput level. Herein, we report the development of a highly sensitive reducing-sugar assay in a 96-well microplate screening format. The assay is based on the formation of osazones from reducing sugars and para-hydroxybenzoic acid hydrazide. By using this sensitive assay, the enzyme loads and conversion times during lignocellulose hydrolysis can be reduced, thus allowing higher throughput. The assay is about five times more sensitive than the widely applied dinitrosalicylic acid based assay and can reliably detect reducing sugars down to 10 μM. The assay-specific variation over one microplate was determined for three different lignocellulolytic enzymes and ranges from 2 to 8%. Furthermore, the assay was combined with a microscale cultivation procedure for the activity-based screening of Pichia pastoris strains expressing functional Thermomyces lanuginosus xylanase A, Trichoderma reesei β-mannanase, or T. reesei cellobiohydrolase 2. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Candidiasis and the impact of flow cytometry on antifungal drug discovery.
Ku, Tsun Sheng N; Bernardo, Stella; Walraven, Carla J; Lee, Samuel A
2017-11-01
Invasive candidiasis continues to be associated with significant morbidity and mortality as well as substantial health care costs nationally and globally. One of the contributing factors is the development of resistance to antifungal agents that are already in clinical use. Moreover, there are known treatment limitations with all of the available antifungal agents. Since traditional techniques in novel drug discovery are time consuming, high-throughput screening using flow cytometry presents as a potential tool to identify new antifungal agents that would be useful in the management of these patients. Areas covered: In this review, the authors discuss the use of automated high-throughput screening assays based upon flow cytometry to identify potential antifungals from a library comprised of a large number of bioactive compounds. They also review studies that employed the use of this research methodology that has identified compounds with antifungal activity. Expert opinion: High-throughput screening using flow cytometry has substantially decreased the processing time necessary for screening thousands of compounds, and has helped enhance our understanding of fungal pathogenesis. Indeed, the authors see this technology as a powerful tool to help scientists identify new antifungal agents that can be added to the clinician's arsenal in their fight against invasive candidiasis.
The Stanford Automated Mounter: Enabling High-Throughput Protein Crystal Screening at SSRL
DOE Office of Scientific and Technical Information (OSTI.GOV)
Smith, C.A.; Cohen, A.E.
2009-05-26
The macromolecular crystallography experiment lends itself perfectly to high-throughput technologies. The initial steps including the expression, purification, and crystallization of protein crystals, along with some of the later steps involving data processing and structure determination have all been automated to the point where some of the last remaining bottlenecks in the process have been crystal mounting, crystal screening, and data collection. At the Stanford Synchrotron Radiation Laboratory, a National User Facility that provides extremely brilliant X-ray photon beams for use in materials science, environmental science, and structural biology research, the incorporation of advanced robotics has enabled crystals to be screenedmore » in a true high-throughput fashion, thus dramatically accelerating the final steps. Up to 288 frozen crystals can be mounted by the beamline robot (the Stanford Auto-Mounting System) and screened for diffraction quality in a matter of hours without intervention. The best quality crystals can then be remounted for the collection of complete X-ray diffraction data sets. Furthermore, the entire screening and data collection experiment can be controlled from the experimenter's home laboratory by means of advanced software tools that enable network-based control of the highly automated beamlines.« less
Fernandez Montenegro, Juan Manuel; Argyriou, Vasileios
2017-05-01
Alzheimer's screening tests are commonly used by doctors to diagnose the patient's condition and stage as early as possible. Most of these tests are based on pen-paper interaction and do not embrace the advantages provided by new technologies. This paper proposes novel Alzheimer's screening tests based on virtual environments and game principles using new immersive technologies combined with advanced Human Computer Interaction (HCI) systems. These new tests are focused on the immersion of the patient in a virtual room, in order to mislead and deceive the patient's mind. In addition, we propose two novel variations of Turing Test proposed by Alan Turing as a method to detect dementia. As a result, four tests are introduced demonstrating the wide range of screening mechanisms that could be designed using virtual environments and game concepts. The proposed tests are focused on the evaluation of memory loss related to common objects, recent conversations and events; the diagnosis of problems in expressing and understanding language; the ability to recognize abnormalities; and to differentiate between virtual worlds and reality, or humans and machines. The proposed screening tests were evaluated and tested using both patients and healthy adults in a comparative study with state-of-the-art Alzheimer's screening tests. The results show the capacity of the new tests to distinguish healthy people from Alzheimer's patients. Copyright © 2017. Published by Elsevier Inc.
Introducing Bayesian thinking to high-throughput screening for false-negative rate estimation.
Wei, Xin; Gao, Lin; Zhang, Xiaolei; Qian, Hong; Rowan, Karen; Mark, David; Peng, Zhengwei; Huang, Kuo-Sen
2013-10-01
High-throughput screening (HTS) has been widely used to identify active compounds (hits) that bind to biological targets. Because of cost concerns, the comprehensive screening of millions of compounds is typically conducted without replication. Real hits that fail to exhibit measurable activity in the primary screen due to random experimental errors will be lost as false-negatives. Conceivably, the projected false-negative rate is a parameter that reflects screening quality. Furthermore, it can be used to guide the selection of optimal numbers of compounds for hit confirmation. Therefore, a method that predicts false-negative rates from the primary screening data is extremely valuable. In this article, we describe the implementation of a pilot screen on a representative fraction (1%) of the screening library in order to obtain information about assay variability as well as a preliminary hit activity distribution profile. Using this training data set, we then developed an algorithm based on Bayesian logic and Monte Carlo simulation to estimate the number of true active compounds and potential missed hits from the full library screen. We have applied this strategy to five screening projects. The results demonstrate that this method produces useful predictions on the numbers of false negatives.
High-throughput screening of dye-ligands for chromatography.
Kumar, Sunil; Punekar, Narayan S
2014-01-01
Dye-ligand-based chromatography has become popular after Cibacron Blue, the first reactive textile dye, found application for protein purification. Many other textile dyes have since been successfully used to purify a number of proteins and enzymes. While the exact nature of their interaction with target proteins is often unclear, dye-ligands are thought to mimic the structural features of their corresponding substrates, cofactors, etc. The dye-ligand affinity matrices are therefore considered pseudo-affinity matrices. In addition, dye-ligands may simply bind with proteins due to electrostatic, hydrophobic, and hydrogen-bonding interactions. Because of their low cost, ready availability, and structural stability, dye-ligand affinity matrices have gained much popularity. Choice of a large number of dye structures offers a range of matrices to be prepared and tested. When presented in the high-throughput screening mode, these dye-ligand matrices provide a formidable tool for protein purification. One could pick from the list of dye-ligands already available or build a systematic library of such structures for use. A high-throughput screen may be set up to choose best dye-ligand matrix as well as ideal conditions for binding and elution, for a given protein. The mode of operation could be either manual or automated. The technology is available to test the performance of dye-ligand matrices in small volumes in an automated liquid-handling workstation. Screening a systematic library of dye-ligand structures can help establish a structure-activity relationship. While the origins of dye-ligand chromatography lay in exploiting pseudo-affinity, it is now possible to design very specific biomimetic dye structures. High-throughput screening will be of value in this endeavor as well.
Gong, Chenyuan; Ni, Zhongya; Yao, Chao; Zhu, Xiaowen; Ni, Lulu; Wang, Lixin; Zhu, Shiguo
2015-01-01
Recently, immunotherapy has shown a lot of promise in cancer treatment and different immune cell types are involved in this endeavor. Among different immune cell populations, NK cells are also an important component in unleashing the therapeutic activity of immune cells. Therefore, in order to enhance the tumoricidal activity of NK cells, identification of new small-molecule natural products is important. Despite the availability of different screening methods for identification of natural products, a simple, economic and high-throughput method is lacking. Hence, in this study, we have developed a high-throughput assay for screening and indentifying natural products that can enhance NK cell-mediated killing of cancer cells. We expanded human NK cell population from human peripheral blood mononuclear cells (PBMCs) by culturing these PBMCs with membrane-bound IL-21 and CD137L engineered K562 cells. Next, expanded NK cells were co-cultured with non-small cell lung cancer (NSCLC) cells with or without natural products and after 24 h of co-culturing, harvested supernatants were analyzed for IFN-γ secretions by ELISA method. We screened 502 natural products and identified that 28 candidates has the potential to induce IFN-γ secretion by NK cells to varying degrees. Among the 28 natural product candidates, we further confirmed and analyzed the potential of one molecule, andrographolide. It actually increased IFN-γ secretion by NK cells and enhanced NK cell-mediated killing of NSCLC cells. Our results demonstrated that this IFN-γ based high-throughput assay for screening of natural products for NK cell tumoricidal activity is a simple, economic and reliable method.
A high throughput screen for biomining cellulase activity from metagenomic libraries.
Mewis, Keith; Taupp, Marcus; Hallam, Steven J
2011-02-01
Cellulose, the most abundant source of organic carbon on the planet, has wide-ranging industrial applications with increasing emphasis on biofuel production (1). Chemical methods to modify or degrade cellulose typically require strong acids and high temperatures. As such, enzymatic methods have become prominent in the bioconversion process. While the identification of active cellulases from bacterial and fungal isolates has been somewhat effective, the vast majority of microbes in nature resist laboratory cultivation. Environmental genomic, also known as metagenomic, screening approaches have great promise in bridging the cultivation gap in the search for novel bioconversion enzymes. Metagenomic screening approaches have successfully recovered novel cellulases from environments as varied as soils (2), buffalo rumen (3) and the termite hind-gut (4) using carboxymethylcellulose (CMC) agar plates stained with congo red dye (based on the method of Teather and Wood (5)). However, the CMC method is limited in throughput, is not quantitative and manifests a low signal to noise ratio (6). Other methods have been reported (7,8) but each use an agar plate-based assay, which is undesirable for high-throughput screening of large insert genomic libraries. Here we present a solution-based screen for cellulase activity using a chromogenic dinitrophenol (DNP)-cellobioside substrate (9). Our library was cloned into the pCC1 copy control fosmid to increase assay sensitivity through copy number induction (10). The method uses one-pot chemistry in 384-well microplates with the final readout provided as an absorbance measurement. This readout is quantitative, sensitive and automated with a throughput of up to 100X 384-well plates per day using a liquid handler and plate reader with attached stacking system.
Liu, Yang; Cao, Fei; Xiong, Hui; Shen, Yanbing; Wang, Min
2016-01-01
To develop a quick method for the preliminarily screening of mutant strains that can accumulate 9α-hydroxyandrost-4-ene-3,17-dione (9α-OH-AD), a high-throughput screening method was presented by applying the principle that 2,4-dinitrophenylhydrazine (DNPH) can react with ketones to produce precipitation. The optimal color assay conditions were the substrate androst-4-ene-3,17-dione (AD) concentration at 2.0 g/L, the ratio of AD to DNPH solution at 1:4, and the sulfuric acid and ethanol solution percentages in DNPH solution at 2% and 35%, respectively. This method was used to preliminarily screen the mutants of Rhodococcus rhodochrous DSM43269, from which the three ones obtained could produce more 9α-OH-AD. This DNPH color assay method not only broadens screening methods and increases screening efficiency in microbial mutation breeding but also establishes a good foundation for obtaining strains for industrial application. PMID:27706217
Liu, Yang; Cao, Fei; Xiong, Hui; Shen, Yanbing; Wang, Min
2016-01-01
To develop a quick method for the preliminarily screening of mutant strains that can accumulate 9α-hydroxyandrost-4-ene-3,17-dione (9α-OH-AD), a high-throughput screening method was presented by applying the principle that 2,4-dinitrophenylhydrazine (DNPH) can react with ketones to produce precipitation. The optimal color assay conditions were the substrate androst-4-ene-3,17-dione (AD) concentration at 2.0 g/L, the ratio of AD to DNPH solution at 1:4, and the sulfuric acid and ethanol solution percentages in DNPH solution at 2% and 35%, respectively. This method was used to preliminarily screen the mutants of Rhodococcus rhodochrous DSM43269, from which the three ones obtained could produce more 9α-OH-AD. This DNPH color assay method not only broadens screening methods and increases screening efficiency in microbial mutation breeding but also establishes a good foundation for obtaining strains for industrial application.
iScreen: Image-Based High-Content RNAi Screening Analysis Tools.
Zhong, Rui; Dong, Xiaonan; Levine, Beth; Xie, Yang; Xiao, Guanghua
2015-09-01
High-throughput RNA interference (RNAi) screening has opened up a path to investigating functional genomics in a genome-wide pattern. However, such studies are often restricted to assays that have a single readout format. Recently, advanced image technologies have been coupled with high-throughput RNAi screening to develop high-content screening, in which one or more cell image(s), instead of a single readout, were generated from each well. This image-based high-content screening technology has led to genome-wide functional annotation in a wider spectrum of biological research studies, as well as in drug and target discovery, so that complex cellular phenotypes can be measured in a multiparametric format. Despite these advances, data analysis and visualization tools are still largely lacking for these types of experiments. Therefore, we developed iScreen (image-Based High-content RNAi Screening Analysis Tool), an R package for the statistical modeling and visualization of image-based high-content RNAi screening. Two case studies were used to demonstrate the capability and efficiency of the iScreen package. iScreen is available for download on CRAN (http://cran.cnr.berkeley.edu/web/packages/iScreen/index.html). The user manual is also available as a supplementary document. © 2014 Society for Laboratory Automation and Screening.
2011-01-01
Background Next-generation sequencing technologies have decentralized sequence acquisition, increasing the demand for new bioinformatics tools that are easy to use, portable across multiple platforms, and scalable for high-throughput applications. Cloud computing platforms provide on-demand access to computing infrastructure over the Internet and can be used in combination with custom built virtual machines to distribute pre-packaged with pre-configured software. Results We describe the Cloud Virtual Resource, CloVR, a new desktop application for push-button automated sequence analysis that can utilize cloud computing resources. CloVR is implemented as a single portable virtual machine (VM) that provides several automated analysis pipelines for microbial genomics, including 16S, whole genome and metagenome sequence analysis. The CloVR VM runs on a personal computer, utilizes local computer resources and requires minimal installation, addressing key challenges in deploying bioinformatics workflows. In addition CloVR supports use of remote cloud computing resources to improve performance for large-scale sequence processing. In a case study, we demonstrate the use of CloVR to automatically process next-generation sequencing data on multiple cloud computing platforms. Conclusion The CloVR VM and associated architecture lowers the barrier of entry for utilizing complex analysis protocols on both local single- and multi-core computers and cloud systems for high throughput data processing. PMID:21878105
High Throughput, Polymeric Aqueous Two-Phase Printing of Tumor Spheroids
Atefi, Ehsan; Lemmo, Stephanie; Fyffe, Darcy; Luker, Gary D.; Tavana, Hossein
2014-01-01
This paper presents a new 3D culture microtechnology for high throughput production of tumor spheroids and validates its utility for screening anti-cancer drugs. We use two immiscible polymeric aqueous solutions and microprint a submicroliter drop of the “patterning” phase containing cells into a bath of the “immersion” phase. Selecting proper formulations of biphasic systems using a panel of biocompatible polymers results in the formation of a round drop that confines cells to facilitate spontaneous formation of a spheroid without any external stimuli. Adapting this approach to robotic tools enables straightforward generation and maintenance of spheroids of well-defined size in standard microwell plates and biochemical analysis of spheroids in situ, which is not possible with existing techniques for spheroid culture. To enable high throughput screening, we establish a phase diagram to identify minimum cell densities within specific volumes of the patterning drop to result in a single spheroid. Spheroids show normal growth over long-term incubation and dose-dependent decrease in cellular viability when treated with drug compounds, but present significant resistance compared to monolayer cultures. The unprecedented ease of implementing this microtechnology and its robust performance will benefit high throughput studies of drug screening against cancer cells with physiologically-relevant 3D tumor models. PMID:25411577
Improving the quality of physician communication with rapid-throughput analysis and report cards.
Farrell, Michael H; Christopher, Stephanie A; La Pean Kirschner, Alison; Roedl, Sara J; O'Tool, Faith O; Ahmad, Nadia Y; Farrell, Philip M
2014-11-01
Problems with clinician-patient communication negatively impact newborn screening, genetics, and all of healthcare. Training programs teach communication, but educational methods are not feasible for entire populations of clinicians. To address this healthcare quality gap, we developed a Communication Quality Assurance intervention. Child health providers volunteered for a randomized controlled trial of assessment and a report card. Participants provided telephone counseling to a standardized parent regarding a newborn screening result showing heterozygous status for cystic fibrosis or sickle cell disease. Our rapid-throughput timeline allows individualized feedback within a week. Two encounters were recorded (baseline and after a random sample received the report card) and abstracted for four groups of communication quality indicators. 92 participants finished both counseling encounters within our rapid-throughput time limits. Participants randomized to receive the report card improved communication behaviors more than controls, including request for teach-back (p<0.01), opening behaviors (p=0.01), anticipate/validate emotion (p<0.001) and the ratio of explained to unexplained jargon words (p<0.03). The rapid-throughput report card is effective at improving specific communication behaviors. Communication can be taught, but this project shows how healthcare organizations can assure communication quality everywhere. Further implementation could improve newborn screening, genetics, and healthcare in general. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.
Identifying Novel Molecular Structures for Advanced Melanoma by Ligand-Based Virtual Screening
Wang, Zhao; Lu, Yan; Seibel, William; Miller, Duane D.; Li, Wei
2009-01-01
We recently discovered a new class of thiazole analogs that are highly potent against melanoma cells. To expand the structure-activity relationship study and to explore potential new molecular scaffolds, we performed extensive ligand-based virtual screening against a compound library containing 342,910 small molecules. Two different approaches of virtual screening were carried out using the structure of our lead molecule: 1) connectivity-based search using Scitegic Pipeline Pilot from Accelerys and 2) molecular shape similarity search using Schrodinger software. Using a testing compound library, both approaches can rank similar compounds very high and rank dissimilar compounds very low, thus validating our screening methods. Structures identified from these searches were analyzed, and selected compounds were tested in vitro to assess their activity against melanoma cancer cell lines. Several molecules showed good anticancer activity. While none of the identified compounds showed better activity than our lead compound, they provided important insight into structural modifications for our lead compound and also provided novel platforms on which we can optimize new classes of anticancer compounds. One of the newly synthesized analogs based on this virtual screening has improved potency and selectivity against melanoma. PMID:19445498
Quantum probability ranking principle for ligand-based virtual screening.
Al-Dabbagh, Mohammed Mumtaz; Salim, Naomie; Himmat, Mubarak; Ahmed, Ali; Saeed, Faisal
2017-04-01
Chemical libraries contain thousands of compounds that need screening, which increases the need for computational methods that can rank or prioritize compounds. The tools of virtual screening are widely exploited to enhance the cost effectiveness of lead drug discovery programs by ranking chemical compounds databases in decreasing probability of biological activity based upon probability ranking principle (PRP). In this paper, we developed a novel ranking approach for molecular compounds inspired by quantum mechanics, called quantum probability ranking principle (QPRP). The QPRP ranking criteria would make an attempt to draw an analogy between the physical experiment and molecular structure ranking process for 2D fingerprints in ligand based virtual screening (LBVS). The development of QPRP criteria in LBVS has employed the concepts of quantum at three different levels, firstly at representation level, this model makes an effort to develop a new framework of molecular representation by connecting the molecular compounds with mathematical quantum space. Secondly, estimate the similarity between chemical libraries and references based on quantum-based similarity searching method. Finally, rank the molecules using QPRP approach. Simulated virtual screening experiments with MDL drug data report (MDDR) data sets showed that QPRP outperformed the classical ranking principle (PRP) for molecular chemical compounds.
Quantum probability ranking principle for ligand-based virtual screening
NASA Astrophysics Data System (ADS)
Al-Dabbagh, Mohammed Mumtaz; Salim, Naomie; Himmat, Mubarak; Ahmed, Ali; Saeed, Faisal
2017-04-01
Chemical libraries contain thousands of compounds that need screening, which increases the need for computational methods that can rank or prioritize compounds. The tools of virtual screening are widely exploited to enhance the cost effectiveness of lead drug discovery programs by ranking chemical compounds databases in decreasing probability of biological activity based upon probability ranking principle (PRP). In this paper, we developed a novel ranking approach for molecular compounds inspired by quantum mechanics, called quantum probability ranking principle (QPRP). The QPRP ranking criteria would make an attempt to draw an analogy between the physical experiment and molecular structure ranking process for 2D fingerprints in ligand based virtual screening (LBVS). The development of QPRP criteria in LBVS has employed the concepts of quantum at three different levels, firstly at representation level, this model makes an effort to develop a new framework of molecular representation by connecting the molecular compounds with mathematical quantum space. Secondly, estimate the similarity between chemical libraries and references based on quantum-based similarity searching method. Finally, rank the molecules using QPRP approach. Simulated virtual screening experiments with MDL drug data report (MDDR) data sets showed that QPRP outperformed the classical ranking principle (PRP) for molecular chemical compounds.
Fun with High Throughput Toxicokinetics (CalEPA webinar)
Thousands of chemicals have been profiled by high-throughput screening (HTS) programs such as ToxCast and Tox21. These chemicals are tested in part because there are limited or no data on hazard, exposure, or toxicokinetics (TK). TK models aid in predicting tissue concentrations ...
HTTK: R Package for High-Throughput Toxicokinetics
Thousands of chemicals have been profiled by high-throughput screening programs such as ToxCast and Tox21; these chemicals are tested in part because most of them have limited or no data on hazard, exposure, or toxicokinetics. Toxicokinetic models aid in predicting tissue concent...
Duffy, Fergal J; Verniere, Mélanie; Devocelle, Marc; Bernard, Elise; Shields, Denis C; Chubb, Anthony J
2011-04-25
We introduce CycloPs, software for the generation of virtual libraries of constrained peptides including natural and nonnatural commercially available amino acids. The software is written in the cross-platform Python programming language, and features include generating virtual libraries in one-dimensional SMILES and three-dimensional SDF formats, suitable for virtual screening. The stand-alone software is capable of filtering the virtual libraries using empirical measurements, including peptide synthesizability by standard peptide synthesis techniques, stability, and the druglike properties of the peptide. The software and accompanying Web interface is designed to enable the rapid generation of large, structurally diverse, synthesizable virtual libraries of constrained peptides quickly and conveniently, for use in virtual screening experiments. The stand-alone software, and the Web interface for evaluating these empirical properties of a single peptide, are available at http://bioware.ucd.ie .
High-throughput screening for combinatorial thin-film library of thermoelectric materials.
Watanabe, Masaki; Kita, Takuji; Fukumura, Tomoteru; Ohtomo, Akira; Ueno, Kazunori; Kawasaki, Masashi
2008-01-01
A high-throughput method has been developed to evaluate the Seebeck coefficient and electrical resistivity of combinatorial thin-film libraries of thermoelectric materials from room temperature to 673 K. Thin-film samples several millimeters in size were deposited on an integrated Al2O3 substrate with embedded lead wires and local heaters for measurement of the thermopower under a controlled temperature gradient. An infrared camera was used for real-time observation of the temperature difference Delta T between two electrical contacts on the sample to obtain the Seebeck coefficient. The Seebeck coefficient and electrical resistivity of constantan thin films were shown to be almost identical to standard data for bulk constantan. High-throughput screening was demonstrated for a thermoelectric Mg-Si-Ge combinatorial library.
Rao, Hanbing; Huangfu, Changxin; Wang, Yanying; Wang, Xianxiang; Tang, Tiansheng; Zeng, Xianyin; Li, Zerong; Chen, Yuzong
2015-05-01
Combinatorial chemistry, high-throughput and virtual screening technologies have been extensively used for discovering agrochemical leads from chemical libraries. The knowledge of the physicochemical properties of the marketed agrochemicals is useful for guiding the design and selection of such libraries. Since the earlier profiling of marketed agrochemicals, the number and types of marketed agrochemicals have significantly increased. Recent studies have shown the change of some physicochemical properties of oral drugs with time. There is a need to also profile the physicochemical properties of the marketed agrochemicals. In this work, we analyzed the key physicochemical properties of 1751 marketed agrochemicals in comparison with the previously-analyzed herbicides and insecticides, 106 391 natural products and 57 548 diverse synthetic libraries compounds. Our study revealed the distribution profiles and evolution trend of different types of agrochemicals that in many respects are broadly similar to the reported profiles for oral drugs, with the most marked difference being that agrochemicals have a lower number of hydrogen bond donors. The derived distribution patterns provided the rule of thumb guidelines for selecting potential agrochemical leads and also provided clues for further improving the libraries for agrochemical lead discovery. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Small molecule inhibitors of mesotrypsin from a structure-based docking screen
Kayode, Olumide; Huang, Zunnan; Soares, Alexei S.; ...
2017-05-02
PRSS3/mesotrypsin is an atypical isoform of trypsin, the upregulation of which has been implicated in promoting tumor progression. To date there are no mesotrypsin-selective pharmacological inhibitors which could serve as tools for deciphering the pathological role of this enzyme, and could potentially form the basis for novel therapeutic strategies targeting mesotrypsin. A virtual screen of the Natural Product Database (NPD) and Food and Drug Administration (FDA) approved Drug Database was conducted by high-throughput molecular docking utilizing crystal structures of mesotrypsin. Twelve high-scoring compounds were selected for testing based on lowest free energy docking scores, interaction with key mesotrypsin active sitemore » residues, and commercial availability. Diminazene (C1D22956468), along with two similar compounds presenting the bis-benzamidine substructure, was validated as a competitive inhibitor of mesotrypsin and other human trypsin isoforms. Diminazene is the most potent small molecule inhibitor of mesotrypsin reported to date with an inhibitory constant (K i) of 3.6±0.3 pM. Diminazene was subsequently co-crystalized with mesotrypsin and the crystal structure was solved and refined to 1.25 Å resolution. This high resolution crystal structure can now offer a foundation for structure-guided efforts to develop novel and potentially more selective mesotrypsin inhibitors based on similar molecular substructures.« less
Small molecule inhibitors of mesotrypsin from a structure-based docking screen
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kayode, Olumide; Huang, Zunnan; Soares, Alexei S.
PRSS3/mesotrypsin is an atypical isoform of trypsin, the upregulation of which has been implicated in promoting tumor progression. To date there are no mesotrypsin-selective pharmacological inhibitors which could serve as tools for deciphering the pathological role of this enzyme, and could potentially form the basis for novel therapeutic strategies targeting mesotrypsin. A virtual screen of the Natural Product Database (NPD) and Food and Drug Administration (FDA) approved Drug Database was conducted by high-throughput molecular docking utilizing crystal structures of mesotrypsin. Twelve high-scoring compounds were selected for testing based on lowest free energy docking scores, interaction with key mesotrypsin active sitemore » residues, and commercial availability. Diminazene (C1D22956468), along with two similar compounds presenting the bis-benzamidine substructure, was validated as a competitive inhibitor of mesotrypsin and other human trypsin isoforms. Diminazene is the most potent small molecule inhibitor of mesotrypsin reported to date with an inhibitory constant (K i) of 3.6±0.3 pM. Diminazene was subsequently co-crystalized with mesotrypsin and the crystal structure was solved and refined to 1.25 Å resolution. This high resolution crystal structure can now offer a foundation for structure-guided efforts to develop novel and potentially more selective mesotrypsin inhibitors based on similar molecular substructures.« less
Correction of Microplate Data from High-Throughput Screening.
Wang, Yuhong; Huang, Ruili
2016-01-01
High-throughput screening (HTS) makes it possible to collect cellular response data from a large number of cell lines and small molecules in a timely and cost-effective manner. The errors and noises in the microplate-formatted data from HTS have unique characteristics, and they can be generally grouped into three categories: run-wise (temporal, multiple plates), plate-wise (background pattern, single plate), and well-wise (single well). In this chapter, we describe a systematic solution for identifying and correcting such errors and noises, mainly basing on pattern recognition and digital signal processing technologies.
Machine learning of molecular electronic properties in chemical compound space
NASA Astrophysics Data System (ADS)
Montavon, Grégoire; Rupp, Matthias; Gobre, Vivekanand; Vazquez-Mayagoitia, Alvaro; Hansen, Katja; Tkatchenko, Alexandre; Müller, Klaus-Robert; Anatole von Lilienfeld, O.
2013-09-01
The combination of modern scientific computing with electronic structure theory can lead to an unprecedented amount of data amenable to intelligent data analysis for the identification of meaningful, novel and predictive structure-property relationships. Such relationships enable high-throughput screening for relevant properties in an exponentially growing pool of virtual compounds that are synthetically accessible. Here, we present a machine learning model, trained on a database of ab initio calculation results for thousands of organic molecules, that simultaneously predicts multiple electronic ground- and excited-state properties. The properties include atomization energy, polarizability, frontier orbital eigenvalues, ionization potential, electron affinity and excitation energies. The machine learning model is based on a deep multi-task artificial neural network, exploiting the underlying correlations between various molecular properties. The input is identical to ab initio methods, i.e. nuclear charges and Cartesian coordinates of all atoms. For small organic molecules, the accuracy of such a ‘quantum machine’ is similar, and sometimes superior, to modern quantum-chemical methods—at negligible computational cost.
Detecting and removing multiplicative spatial bias in high-throughput screening technologies.
Caraus, Iurie; Mazoure, Bogdan; Nadon, Robert; Makarenkov, Vladimir
2017-10-15
Considerable attention has been paid recently to improve data quality in high-throughput screening (HTS) and high-content screening (HCS) technologies widely used in drug development and chemical toxicity research. However, several environmentally- and procedurally-induced spatial biases in experimental HTS and HCS screens decrease measurement accuracy, leading to increased numbers of false positives and false negatives in hit selection. Although effective bias correction methods and software have been developed over the past decades, almost all of these tools have been designed to reduce the effect of additive bias only. Here, we address the case of multiplicative spatial bias. We introduce three new statistical methods meant to reduce multiplicative spatial bias in screening technologies. We assess the performance of the methods with synthetic and real data affected by multiplicative spatial bias, including comparisons with current bias correction methods. We also describe a wider data correction protocol that integrates methods for removing both assay and plate-specific spatial biases, which can be either additive or multiplicative. The methods for removing multiplicative spatial bias and the data correction protocol are effective in detecting and cleaning experimental data generated by screening technologies. As our protocol is of a general nature, it can be used by researchers analyzing current or next-generation high-throughput screens. The AssayCorrector program, implemented in R, is available on CRAN. makarenkov.vladimir@uqam.ca. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com
A high-throughput screen for single gene activities: isolation of apoptosis inducers.
Albayrak, Timur; Grimm, Stefan
2003-05-16
We describe a novel genetic screen that is performed by transfecting every individual clone of an expression library into a separate population of cells in a high-throughput mode. The screen allows one to achieve a hitherto unattained sensitivity in expression cloning which was exploited in a first read-out to clone apoptosis-inducing genes. This led to the isolation of several genes whose proteins induce distinct phenotypes of apoptosis in 293T cells. One of the isolated genes is the tumor suppressor cytochrome b(L) (cybL), a component of the respiratory chain complex II, that diminishes the activity of this complex for apoptosis induction. This gene is more efficient and specific for causing cell death than a drug with the same activity. These results suggest further applications, both of the isolated genes and the screen.
Liu, Ju; Li, Ruihua; Liu, Kun; Li, Liangliang; Zai, Xiaodong; Chi, Xiangyang; Fu, Ling; Xu, Junjie; Chen, Wei
2016-04-22
High-throughput sequencing of the antibody repertoire provides a large number of antibody variable region sequences that can be used to generate human monoclonal antibodies. However, current screening methods for identifying antigen-specific antibodies are inefficient. In the present study, we developed an antibody clone screening strategy based on clone dynamics and relative frequency, and used it to identify antigen-specific human monoclonal antibodies. Enzyme-linked immunosorbent assay showed that at least 52% of putative positive immunoglobulin heavy chains composed antigen-specific antibodies. Combining information on dynamics and relative frequency improved identification of positive clones and elimination of negative clones. and increase the credibility of putative positive clones. Therefore the screening strategy could simplify the subsequent experimental screening and may facilitate the generation of antigen-specific antibodies. Copyright © 2016 Elsevier Inc. All rights reserved.
Recent advances in quantitative high throughput and high content data analysis.
Moutsatsos, Ioannis K; Parker, Christian N
2016-01-01
High throughput screening has become a basic technique with which to explore biological systems. Advances in technology, including increased screening capacity, as well as methods that generate multiparametric readouts, are driving the need for improvements in the analysis of data sets derived from such screens. This article covers the recent advances in the analysis of high throughput screening data sets from arrayed samples, as well as the recent advances in the analysis of cell-by-cell data sets derived from image or flow cytometry application. Screening multiple genomic reagents targeting any given gene creates additional challenges and so methods that prioritize individual gene targets have been developed. The article reviews many of the open source data analysis methods that are now available and which are helping to define a consensus on the best practices to use when analyzing screening data. As data sets become larger, and more complex, the need for easily accessible data analysis tools will continue to grow. The presentation of such complex data sets, to facilitate quality control monitoring and interpretation of the results will require the development of novel visualizations. In addition, advanced statistical and machine learning algorithms that can help identify patterns, correlations and the best features in massive data sets will be required. The ease of use for these tools will be important, as they will need to be used iteratively by laboratory scientists to improve the outcomes of complex analyses.
2014-01-01
Background Identification of ligand-protein binding interactions is a critical step in drug discovery. Experimental screening of large chemical libraries, in spite of their specific role and importance in drug discovery, suffer from the disadvantages of being random, time-consuming and expensive. To accelerate the process, traditional structure- or ligand-based VLS approaches are combined with experimental high-throughput screening, HTS. Often a single protein or, at most, a protein family is considered. Large scale VLS benchmarking across diverse protein families is rarely done, and the reported success rate is very low. Here, we demonstrate the experimental HTS validation of a novel VLS approach, FINDSITEcomb, across a diverse set of medically-relevant proteins. Results For eight different proteins belonging to different fold-classes and from diverse organisms, the top 1% of FINDSITEcomb’s VLS predictions were tested, and depending on the protein target, 4%-47% of the predicted ligands were shown to bind with μM or better affinities. In total, 47 small molecule binders were identified. Low nanomolar (nM) binders for dihydrofolate reductase and protein tyrosine phosphatases (PTPs) and micromolar binders for the other proteins were identified. Six novel molecules had cytotoxic activity (<10 μg/ml) against the HCT-116 colon carcinoma cell line and one novel molecule had potent antibacterial activity. Conclusions We show that FINDSITEcomb is a promising new VLS approach that can assist drug discovery. PMID:24936211
Cai, Yingying; Xia, Miaomiao; Dong, Huina; Qian, Yuan; Zhang, Tongcun; Zhu, Beiwei; Wu, Jinchuan; Zhang, Dawei
2018-05-11
As a very important coenzyme in the cell metabolism, Vitamin B 12 (cobalamin, VB 12 ) has been widely used in food and medicine fields. The complete biosynthesis of VB 12 requires approximately 30 genes, but overexpression of these genes did not result in expected increase of VB 12 production. High-yield VB 12 -producing strains are usually obtained by mutagenesis treatments, thus developing an efficient screening approach is urgently needed. By the help of engineered strains with varied capacities of VB 12 production, a riboswitch library was constructed and screened, and the btuB element from Salmonella typhimurium was identified as the best regulatory device. A flow cytometry high-throughput screening system was developed based on the btuB riboswitch with high efficiency to identify positive mutants. Mutation of Sinorhizobium meliloti (S. meliloti) was optimized using the novel mutation technique of atmospheric and room temperature plasma (ARTP). Finally, the mutant S. meliloti MC5-2 was obtained and considered as a candidate for industrial applications. After 7 d's cultivation on a rotary shaker at 30 °C, the VB 12 titer of S. meliloti MC5-2 reached 156 ± 4.2 mg/L, which was 21.9% higher than that of the wild type strain S. meliloti 320 (128 ± 3.2 mg/L). The genome of S. meliloti MC5-2 was sequenced, and gene mutations were identified and analyzed. To our knowledge, it is the first time that a riboswitch element was used in S. meliloti. The flow cytometry high-throughput screening system was successfully developed and a high-yield VB 12 producing strain was obtained. The identified and analyzed gene mutations gave useful information for developing high-yield strains by metabolic engineering. Overall, this work provides a useful high-throughput screening method for developing high VB 12 -yield strains.
Babaoglu, Kerim; Simeonov, Anton; Irwin, John J.; Nelson, Michael E.; Feng, Brian; Thomas, Craig J.; Cancian, Laura; Costi, M. Paola; Maltby, David A.; Jadhav, Ajit; Inglese, James; Austin, Christopher P.; Shoichet, Brian K.
2009-01-01
High-throughput screening (HTS) is widely used in drug discovery. Especially for screens of unbiased libraries, false positives can dominate “hit lists”; their origins are much debated. Here we determine the mechanism of every active hit from a screen of 70,563 unbiased molecules against β-lactamase using quantitative HTS (qHTS). Of the 1274 initial inhibitors, 95% were detergent-sensitive and were classified as aggregators. Among the 70 remaining were 25 potent, covalent-acting β-lactams. Mass spectra, counter-screens, and crystallography identified 12 as promiscuous covalent inhibitors. The remaining 33 were either aggregators or irreproducible. No specific reversible inhibitors were found. We turned to molecular docking to prioritize molecules from the same library for testing at higher concentrations. Of 16 tested, 2 were modest inhibitors. Subsequent X-ray structures corresponded to the docking prediction. Analog synthesis improved affinity to 8 µM. These results suggest that it may be the physical behavior of organic molecules, not their reactivity, that accounts for most screening artifacts. Structure-based methods may prioritize weak-but-novel chemotypes in unbiased library screens. PMID:18333608
Niu, Chenqi; Xu, Yuancong; Zhang, Chao; Zhu, Pengyu; Huang, Kunlun; Luo, Yunbo; Xu, Wentao
2018-05-01
As genetically modified (GM) technology develops and genetically modified organisms (GMOs) become more available, GMOs face increasing regulations and pressure to adhere to strict labeling guidelines. A singleplex detection method cannot perform the high-throughput analysis necessary for optimal GMO detection. Combining the advantages of multiplex detection and droplet digital polymerase chain reaction (ddPCR), a single universal primer-multiplex-ddPCR (SUP-M-ddPCR) strategy was proposed for accurate broad-spectrum screening and quantification. The SUP increases efficiency of the primers in PCR and plays an important role in establishing a high-throughput, multiplex detection method. Emerging ddPCR technology has been used for accurate quantification of nucleic acid molecules without a standard curve. Using maize as a reference point, four heterologous sequences ( 35S, NOS, NPTII, and PAT) were selected to evaluate the feasibility and applicability of this strategy. Surprisingly, these four genes cover more than 93% of the transgenic maize lines and serve as preliminary screening sequences. All screening probes were labeled with FAM fluorescence, which allows the signals from the samples with GMO content and those without to be easily differentiated. This fiveplex screening method is a new development in GMO screening. Utilizing an optimal amplification assay, the specificity, limit of detection (LOD), and limit of quantitation (LOQ) were validated. The LOD and LOQ of this GMO screening method were 0.1% and 0.01%, respectively, with a relative standard deviation (RSD) < 25%. This method could serve as an important tool for the detection of GM maize from different processed, commercially available products. Further, this screening method could be applied to other fields that require reliable and sensitive detection of DNA targets.
Cell-Based High-Throughput Screening for Aromatase Inhibitors in the Tox21 10K Library.
Chen, Shiuan; Hsieh, Jui-Hua; Huang, Ruili; Sakamuru, Srilatha; Hsin, Li-Yu; Xia, Menghang; Shockley, Keith R; Auerbach, Scott; Kanaya, Noriko; Lu, Hannah; Svoboda, Daniel; Witt, Kristine L; Merrick, B Alex; Teng, Christina T; Tice, Raymond R
2015-10-01
Multiple mechanisms exist for endocrine disruption; one nonreceptor-mediated mechanism is via effects on aromatase, an enzyme critical for maintaining the normal in vivo balance of androgens and estrogens. We adapted the AroER tri-screen 96-well assay to 1536-well format to identify potential aromatase inhibitors (AIs) in the U.S. Tox21 10K compound library. In this assay, screening with compound alone identifies estrogen receptor alpha (ERα) agonists, screening in the presence of testosterone (T) identifies AIs and/or ERα antagonists, and screening in the presence of 17β-estradiol (E2) identifies ERα antagonists. Screening the Tox-21 library in the presence of T resulted in finding 302 potential AIs. These compounds, along with 31 known AI actives and inactives, were rescreened using all 3 assay formats. Of the 333 compounds tested, 113 (34%; 63 actives, 50 marginal actives) were considered to be potential AIs independent of cytotoxicity and ER antagonism activity. Structure-activity analysis suggested the presence of both conventional (eg, 1, 2, 4, - triazole class) and novel AI structures. Due to their novel structures, 14 of the 63 potential AI actives, including both drugs and fungicides, were selected for confirmation in the biochemical tritiated water-release aromatase assay. Ten compounds were active in the assay; the remaining 4 were only active in high-throughput screen assay, but with low efficacy. To further characterize these 10 novel AIs, we investigated their binding characteristics. The AroER tri-screen, in high-throughput format, accurately and efficiently identified chemicals in a large and diverse chemical library that selectively interact with aromatase. © The Author 2015. Published by Oxford University Press on behalf of the Society of Toxicology. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
Cell-Based High-Throughput Screening for Aromatase Inhibitors in the Tox21 10K Library
Chen, Shiuan; Hsieh, Jui-Hua; Huang, Ruili; Sakamuru, Srilatha; Hsin, Li-Yu; Xia, Menghang; Shockley, Keith R.; Auerbach, Scott; Kanaya, Noriko; Lu, Hannah; Svoboda, Daniel; Witt, Kristine L.; Merrick, B. Alex; Teng, Christina T.; Tice, Raymond R.
2015-01-01
Multiple mechanisms exist for endocrine disruption; one nonreceptor-mediated mechanism is via effects on aromatase, an enzyme critical for maintaining the normal in vivo balance of androgens and estrogens. We adapted the AroER tri-screen 96-well assay to 1536-well format to identify potential aromatase inhibitors (AIs) in the U.S. Tox21 10K compound library. In this assay, screening with compound alone identifies estrogen receptor alpha (ERα) agonists, screening in the presence of testosterone (T) identifies AIs and/or ERα antagonists, and screening in the presence of 17β-estradiol (E2) identifies ERα antagonists. Screening the Tox-21 library in the presence of T resulted in finding 302 potential AIs. These compounds, along with 31 known AI actives and inactives, were rescreened using all 3 assay formats. Of the 333 compounds tested, 113 (34%; 63 actives, 50 marginal actives) were considered to be potential AIs independent of cytotoxicity and ER antagonism activity. Structure-activity analysis suggested the presence of both conventional (eg, 1, 2, 4, - triazole class) and novel AI structures. Due to their novel structures, 14 of the 63 potential AI actives, including both drugs and fungicides, were selected for confirmation in the biochemical tritiated water-release aromatase assay. Ten compounds were active in the assay; the remaining 4 were only active in high-throughput screen assay, but with low efficacy. To further characterize these 10 novel AIs, we investigated their binding characteristics. The AroER tri-screen, in high-throughput format, accurately and efficiently identified chemicals in a large and diverse chemical library that selectively interact with aromatase. PMID:26141389
High-Throughput Models for Exposure-Based Chemical Prioritization in the ExpoCast Project
The United States Environmental Protection Agency (U.S. EPA) must characterize potential risks to human health and the environment associated with manufacture and use of thousands of chemicals. High-throughput screening (HTS) for biological activity allows the ToxCast research pr...
Use of High-Throughput Testing and Approaches for Evaluating Chemical Risk-Relevance to Humans
ToxCast is profiling the bioactivity of thousands of chemicals based on high-throughput screening (HTS) and computational models that integrate knowledge of biological systems and in vivo toxicities. Many of these assays probe signaling pathways and cellular processes critical to...
High-Throughput Simulation of Environmental Chemical Fate for Exposure Prioritization
The U.S. EPA must consider lists of hundreds to thousands of chemicals when allocating resources to identify risk in human populations and the environment. High-throughput screening assays to characterize biological activity in vitro have allowed the ToxCastTM program to identify...
High Throughput Genotoxicity Profiling of the US EPA ToxCast Chemical Library
A key aim of the ToxCast project is to investigate modern molecular and genetic high content and high throughput screening (HTS) assays, along with various computational tools to supplement and perhaps replace traditional assays for evaluating chemical toxicity. Genotoxicity is a...
Momentum is growing worldwide to use in vitro high-throughput screening (HTS) to evaluate human health effects of chemicals. However, the integration of dosimetry into HTS assays and incorporation of population variability will be essential before its application in a risk assess...
Determining mechanism-based biomarkers that distinguish adaptive and adverse cellular processes is critical to understanding the health effects of environmental exposures. Shifting from in vivo, low-throughput toxicity studies to high-throughput screening (HTS) paradigms and risk...
Virtual screening of cocrystal formers for CL-20
NASA Astrophysics Data System (ADS)
Zhou, Jun-Hong; Chen, Min-Bo; Chen, Wei-Ming; Shi, Liang-Wei; Zhang, Chao-Yang; Li, Hong-Zhen
2014-08-01
According to the structure characteristics of 2,4,6,8,10,12-hexanitrohexaazaisowurtzitane (CL-20) and the kinetic mechanism of the cocrystal formation, the method of virtual screening CL-20 cocrystal formers by the criterion of the strongest intermolecular site pairing energy (ISPE) was proposed. In this method the strongest ISPE was thought to determine the first step of the cocrystal formation. The prediction results for four sets of common drug molecule cocrystals by this method were compared with those by the total ISPE method from the reference (Musumeci et al., 2011), and the experimental results. This method was then applied to virtually screen the CL-20 cocrystal formers, and the prediction results were compared with the experimental results.
Virtual Screening of Receptor Sites for Molecularly Imprinted Polymers.
Bates, Ferdia; Cela-Pérez, María Concepción; Karim, Kal; Piletsky, Sergey; López-Vilariño, José Manuel
2016-08-01
Molecularly Imprinted Polymers (MIPs) are highly advantageous in the field of analytical chemistry. However, interference from secondary molecules can also impede capture of a target by a MIP receptor. This greatly complicates the design process and often requires extensive laboratory screening which is time consuming, costly, and creates substantial waste products. Herein, is presented a new technique for screening of "virtually imprinted receptors" for rebinding of the molecular template as well as secondary structures, correlating the virtual predictions with experimentally acquired data in three case studies. This novel technique is particularly applicable to the evaluation and prediction of MIP receptor specificity and efficiency in complex aqueous systems. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Novel screening techniques for ion channel targeting drugs
Obergrussberger, Alison; Stölzle-Feix, Sonja; Becker, Nadine; Brüggemann, Andrea; Fertig, Niels; Möller, Clemens
2015-01-01
Ion channels are integral membrane proteins that regulate the flux of ions across the cell membrane. They are involved in nearly all physiological processes, and malfunction of ion channels has been linked to many diseases. Until recently, high-throughput screening of ion channels was limited to indirect, e.g. fluorescence-based, readout technologies. In the past years, direct label-free biophysical readout technologies by means of electrophysiology have been developed. Planar patch-clamp electrophysiology provides a direct functional label-free readout of ion channel function in medium to high throughput. Further electrophysiology features, including temperature control and higher-throughput instruments, are continually being developed. Electrophysiological screening in a 384-well format has recently become possible. Advances in chip and microfluidic design, as well as in cell preparation and handling, have allowed challenging cell types to be studied by automated patch clamp. Assays measuring action potentials in stem cell-derived cardiomyocytes, relevant for cardiac safety screening, and neuronal cells, as well as a large number of different ion channels, including fast ligand-gated ion channels, have successfully been established by automated patch clamp. Impedance and multi-electrode array measurements are particularly suitable for studying cardiomyocytes and neuronal cells within their physiological network, and to address more complex physiological questions. This article discusses recent advances in electrophysiological technologies available for screening ion channel function and regulation. PMID:26556400
Novel screening techniques for ion channel targeting drugs.
Obergrussberger, Alison; Stölzle-Feix, Sonja; Becker, Nadine; Brüggemann, Andrea; Fertig, Niels; Möller, Clemens
2015-01-01
Ion channels are integral membrane proteins that regulate the flux of ions across the cell membrane. They are involved in nearly all physiological processes, and malfunction of ion channels has been linked to many diseases. Until recently, high-throughput screening of ion channels was limited to indirect, e.g. fluorescence-based, readout technologies. In the past years, direct label-free biophysical readout technologies by means of electrophysiology have been developed. Planar patch-clamp electrophysiology provides a direct functional label-free readout of ion channel function in medium to high throughput. Further electrophysiology features, including temperature control and higher-throughput instruments, are continually being developed. Electrophysiological screening in a 384-well format has recently become possible. Advances in chip and microfluidic design, as well as in cell preparation and handling, have allowed challenging cell types to be studied by automated patch clamp. Assays measuring action potentials in stem cell-derived cardiomyocytes, relevant for cardiac safety screening, and neuronal cells, as well as a large number of different ion channels, including fast ligand-gated ion channels, have successfully been established by automated patch clamp. Impedance and multi-electrode array measurements are particularly suitable for studying cardiomyocytes and neuronal cells within their physiological network, and to address more complex physiological questions. This article discusses recent advances in electrophysiological technologies available for screening ion channel function and regulation.
Meng, Juncai; Lai, Ming-Tain; Munshi, Vandna; Grobler, Jay; McCauley, John; Zuck, Paul; Johnson, Eric N; Uebele, Victor N; Hermes, Jeffrey D; Adam, Gregory C
2015-06-01
HIV-1 protease (PR) represents one of the primary targets for developing antiviral agents for the treatment of HIV-infected patients. To identify novel PR inhibitors, a label-free, high-throughput mass spectrometry (HTMS) assay was developed using the RapidFire platform and applied as an orthogonal assay to confirm hits identified in a fluorescence resonance energy transfer (FRET)-based primary screen of > 1 million compounds. For substrate selection, a panel of peptide substrates derived from natural processing sites for PR was evaluated on the RapidFire platform. As a result, KVSLNFPIL, a new substrate measured to have a ~ 20- and 60-fold improvement in k cat/K m over the frequently used sequences SQNYPIVQ and SQNYPIV, respectively, was identified for the HTMS screen. About 17% of hits from the FRET-based primary screen were confirmed in the HTMS confirmatory assay including all 304 known PR inhibitors in the set, demonstrating that the HTMS assay is effective at triaging false-positives while capturing true hits. Hence, with a sampling rate of ~7 s per well, the RapidFire HTMS assay enables the high-throughput evaluation of peptide substrates and functions as an efficient tool for hits triage in the discovery of novel PR inhibitors. © 2015 Society for Laboratory Automation and Screening.
Zhu, Tian; Cao, Shuyi; Su, Pin-Chih; Patel, Ram; Shah, Darshan; Chokshi, Heta B; Szukala, Richard; Johnson, Michael E; Hevener, Kirk E
2013-09-12
A critical analysis of virtual screening results published between 2007 and 2011 was performed. The activity of reported hit compounds from over 400 studies was compared to their hit identification criteria. Hit rates and ligand efficiencies were calculated to assist in these analyses, and the results were compared with factors such as the size of the virtual library and the number of compounds tested. A series of promiscuity, druglike, and ADMET filters were applied to the reported hits to assess the quality of compounds reported, and a careful analysis of a subset of the studies that presented hit optimization was performed. These data allowed us to make several practical recommendations with respect to selection of compounds for experimental testing, definition of hit identification criteria, and general virtual screening hit criteria to allow for realistic hit optimization. A key recommendation is the use of size-targeted ligand efficiency values as hit identification criteria.
Design and Development of ChemInfoCloud: An Integrated Cloud Enabled Platform for Virtual Screening.
Karthikeyan, Muthukumarasamy; Pandit, Deepak; Bhavasar, Arvind; Vyas, Renu
2015-01-01
The power of cloud computing and distributed computing has been harnessed to handle vast and heterogeneous data required to be processed in any virtual screening protocol. A cloud computing platorm ChemInfoCloud was built and integrated with several chemoinformatics and bioinformatics tools. The robust engine performs the core chemoinformatics tasks of lead generation, lead optimisation and property prediction in a fast and efficient manner. It has also been provided with some of the bioinformatics functionalities including sequence alignment, active site pose prediction and protein ligand docking. Text mining, NMR chemical shift (1H, 13C) prediction and reaction fingerprint generation modules for efficient lead discovery are also implemented in this platform. We have developed an integrated problem solving cloud environment for virtual screening studies that also provides workflow management, better usability and interaction with end users using container based virtualization, OpenVz.
2010-01-01
Background Shared-usage high throughput screening (HTS) facilities are becoming more common in academe as large-scale small molecule and genome-scale RNAi screening strategies are adopted for basic research purposes. These shared facilities require a unique informatics infrastructure that must not only provide access to and analysis of screening data, but must also manage the administrative and technical challenges associated with conducting numerous, interleaved screening efforts run by multiple independent research groups. Results We have developed Screensaver, a free, open source, web-based lab information management system (LIMS), to address the informatics needs of our small molecule and RNAi screening facility. Screensaver supports the storage and comparison of screening data sets, as well as the management of information about screens, screeners, libraries, and laboratory work requests. To our knowledge, Screensaver is one of the first applications to support the storage and analysis of data from both genome-scale RNAi screening projects and small molecule screening projects. Conclusions The informatics and administrative needs of an HTS facility may be best managed by a single, integrated, web-accessible application such as Screensaver. Screensaver has proven useful in meeting the requirements of the ICCB-Longwood/NSRB Screening Facility at Harvard Medical School, and has provided similar benefits to other HTS facilities. PMID:20482787
Tolopko, Andrew N; Sullivan, John P; Erickson, Sean D; Wrobel, David; Chiang, Su L; Rudnicki, Katrina; Rudnicki, Stewart; Nale, Jennifer; Selfors, Laura M; Greenhouse, Dara; Muhlich, Jeremy L; Shamu, Caroline E
2010-05-18
Shared-usage high throughput screening (HTS) facilities are becoming more common in academe as large-scale small molecule and genome-scale RNAi screening strategies are adopted for basic research purposes. These shared facilities require a unique informatics infrastructure that must not only provide access to and analysis of screening data, but must also manage the administrative and technical challenges associated with conducting numerous, interleaved screening efforts run by multiple independent research groups. We have developed Screensaver, a free, open source, web-based lab information management system (LIMS), to address the informatics needs of our small molecule and RNAi screening facility. Screensaver supports the storage and comparison of screening data sets, as well as the management of information about screens, screeners, libraries, and laboratory work requests. To our knowledge, Screensaver is one of the first applications to support the storage and analysis of data from both genome-scale RNAi screening projects and small molecule screening projects. The informatics and administrative needs of an HTS facility may be best managed by a single, integrated, web-accessible application such as Screensaver. Screensaver has proven useful in meeting the requirements of the ICCB-Longwood/NSRB Screening Facility at Harvard Medical School, and has provided similar benefits to other HTS facilities.
Alternative toxicity assessment methods to characterize the hazards of chemical substances have been proposed to reduce animal testing and screen thousands of chemicals in an efficient manner. Resources to accomplish these goals include utilizing large in vitro chemical screening...
The U.S. EPA's ToxCast Chemical Screening Program and Predictive Modeling of Toxicity
The ToxCast program was developed by the U.S. EPA's National Center for Computational Toxicology to provide cost-effective high-throughput screening for the potential toxicity of thousands of chemicals. Phase I screened 309 compounds in over 500 assays to evaluate concentration-...
A High-Throughput Screening Assay to Detect Thyroperoxidase Inhibitors (Teratology Society)
In support of the Endocrine Disruption Screening Program (EDSP21), the US EPA ToxCast program is developing assays to enable screening for chemicals that may disrupt thyroid hormone synthesis. Thyroperoxidase (TPO) is critical for TH synthesis and is a known target of thyroid-dis...
The U.S. Environmental Protection Agency (EPA), through its ToxCast program, is developing predictive toxicity approaches that will use in vitro high-throughput screening (HTS), high-content screening (HCS) and toxicogenomic data to predict in vivo toxicity phenotypes. There are ...
DOE Office of Scientific and Technical Information (OSTI.GOV)
McLean, Larry R.; Zhang, Ying; Li, Hua
Biochemical and X-ray crystallographic studies confirmed that hydroxyquinoline derivatives identified by virtual screening were actually covalent inhibitors of the MIF tautomerase. Adducts were formed by N-alkylation of the Pro-1 at the catalytic site with a loss of an amino group of the inhibitor.
Torktaz, Ibrahim; Mohamadhashem, Faezeh; Esmaeili, Abolghasem; Behjati, Mohaddeseh; Sharifzadeh, Sara
2013-01-01
Metastasis is a crucial aspect of cancer. Macrophage stimulating protein (MSP) is a single chain protein and can be cleaved by serum proteases. MSP has several roles in metastasis. In this in silico study, MSP as a metastatic agent was considered as a drug target. Crystallographic structure of MSP was retrieved from protein data bank. To find a chemical inhibitor of MSP, a library of KEGG compounds was screened and 1000 shape complemented ligands were retrieved with FindSite algorithm. Molegro Virtual Docker (MVD) software was used for docking simulation of shape complemented ligands against MSP. Moldock score was used as scoring function for virtual screening and potential inhibitors with more negative binding energy were obtained. PLANS scoring function was used for revaluation of virtual screening data. The top found chemical had binding affinity of -183.55 based on MolDock score and equal to -66.733 PLANTs score to MSP structure. Based on pharmacophore model of potential inhibitor, this study suggests that the chemical which was found in this research and its derivate can be used for subsequent laboratory studies.
Shin, Woong-Hee; Kihara, Daisuke
2018-01-01
Virtual screening is a computational technique for predicting a potent binding compound for a receptor protein from a ligand library. It has been a widely used in the drug discovery field to reduce the efforts of medicinal chemists to find hit compounds by experiments.Here, we introduce our novel structure-based virtual screening program, PL-PatchSurfer, which uses molecular surface representation with the three-dimensional Zernike descriptors, which is an effective mathematical representation for identifying physicochemical complementarities between local surfaces of a target protein and a ligand. The advantage of the surface-patch description is its tolerance on a receptor and compound structure variation. PL-PatchSurfer2 achieves higher accuracy on apo form and computationally modeled receptor structures than conventional structure-based virtual screening programs. Thus, PL-PatchSurfer2 opens up an opportunity for targets that do not have their crystal structures. The program is provided as a stand-alone program at http://kiharalab.org/plps2 . We also provide files for two ligand libraries, ChEMBL and ZINC Drug-like.
RAS - Screens & Assays - Drug Discovery
The RAS Drug Discovery group aims to develop assays that will reveal aspects of RAS biology upon which cancer cells depend. Successful assay formats are made available for high-throughput screening programs to yield potentially effective drug compounds.
Soulard, Patricia; McLaughlin, Meg; Stevens, Jessica; Connolly, Brendan; Coli, Rocco; Wang, Leyu; Moore, Jennifer; Kuo, Ming-Shang T; LaMarr, William A; Ozbal, Can C; Bhat, B Ganesh
2008-10-03
Several recent reports suggest that stearoyl-CoA desaturase 1 (SCD1), the rate-limiting enzyme in monounsaturated fatty acid synthesis, plays an important role in regulating lipid homeostasis and lipid oxidation in metabolically active tissues. As several manifestations of type 2 diabetes and related metabolic disorders are associated with alterations in intracellular lipid partitioning, pharmacological manipulation of SCD1 activity might be of benefit in the treatment of these disease states. In an effort to identify small molecule inhibitors of SCD1, we have developed a mass spectrometry based high-throughput screening (HTS) assay using deuterium labeled stearoyl-CoA substrate and induced rat liver microsomes. The methodology developed allows the use of a nonradioactive substrate which avoids interference by the endogenous SCD1 substrate and/or product that exist in the non-purified enzyme source. Throughput of the assay was up to twenty 384-well assay plates per day. The assay was linear with protein concentration and time, and was saturable for stearoyl-CoA substrate (K(m)=10.5 microM). The assay was highly reproducible with an average Z' value=0.6. Conjugated linoleic acid and sterculic acid, known inhibitors of SCD1, exhibited IC(50) values of 0.88 and 0.12 microM, respectively. High-throughput mass spectrometry screening of over 1.7 million compounds in compressed format demonstrated that the enzyme target is druggable. A total of 2515 hits were identified (0.1% hit rate), and 346 were confirmed active (>40% inhibition of total SCD activity at 20 microM--14% conformation rate). Of the confirmed hits 172 had IC(50) values of <10 microM, including 111 <1 microM and 48 <100 nM. A large number of potent drug-like (MW<450) hits representing six different chemical series were identified. The application of mass spectrometry to high-throughput screening permitted the development of a high-quality screening protocol for an otherwise intractable target, SCD1. Further medicinal chemistry and characterization of SCD inhibitors should lead to the development of reagents to treat metabolic disorders.
Camattari, Andrea; Weinhandl, Katrin; Gudiminchi, Rama K
2014-01-01
The methylotrophic yeast Pichia pastoris is becoming one of the favorite industrial workhorses for protein expression. Due to the widespread use of integration vectors, which generates significant clonal variability, screening methods allowing assaying hundreds of individual clones are of particular importance. Here we describe methods to detect and analyze protein expression, developed in a 96-well format for high-throughput screening of recombinant P. pastoris strains. The chapter covers essentially three common scenarios: (1) an enzymatic assay for proteins expressed in the cell cytoplasm, requiring cell lysis; (2) a whole-cell assay for a fungal cytochrome P450; and (3) a nonenzymatic assay for detection and quantification of tagged protein secreted into the supernatant.
Large-scale virtual screening on public cloud resources with Apache Spark.
Capuccini, Marco; Ahmed, Laeeq; Schaal, Wesley; Laure, Erwin; Spjuth, Ola
2017-01-01
Structure-based virtual screening is an in-silico method to screen a target receptor against a virtual molecular library. Applying docking-based screening to large molecular libraries can be computationally expensive, however it constitutes a trivially parallelizable task. Most of the available parallel implementations are based on message passing interface, relying on low failure rate hardware and fast network connection. Google's MapReduce revolutionized large-scale analysis, enabling the processing of massive datasets on commodity hardware and cloud resources, providing transparent scalability and fault tolerance at the software level. Open source implementations of MapReduce include Apache Hadoop and the more recent Apache Spark. We developed a method to run existing docking-based screening software on distributed cloud resources, utilizing the MapReduce approach. We benchmarked our method, which is implemented in Apache Spark, docking a publicly available target receptor against [Formula: see text]2.2 M compounds. The performance experiments show a good parallel efficiency (87%) when running in a public cloud environment. Our method enables parallel Structure-based virtual screening on public cloud resources or commodity computer clusters. The degree of scalability that we achieve allows for trying out our method on relatively small libraries first and then to scale to larger libraries. Our implementation is named Spark-VS and it is freely available as open source from GitHub (https://github.com/mcapuccini/spark-vs).Graphical abstract.
In response to a proposed vision and strategy for toxicity testing in the 21st century nascent high throughput toxicology (HTT) programs have tested thousands of chemicals in hundreds of pathway-based biological assays. Although, to date, use of HTT data for safety assessment of ...
Increasing efficiency and declining cost of generating whole transcriptome profiles has made high-throughput transcriptomics a practical option for chemical bioactivity screening. The resulting data output provides information on the expression of thousands of genes and is amenab...
Disruption of steroidogenesis by environmental chemicals can result in altered hormone levels causing adverse reproductive and developmental effects. A high-throughput assay using H295R human adrenocortical carcinoma cells was used to evaluate the effect of 2,060 chemical samples...
The U.S. EPA must consider thousands of chemicals when allocating resources to assess risk in human populations and the environment. High-throughput screening assays to characterize biological activity in vitro are being implemented in the ToxCastTM program to rapidly characteri...
We previously integrated dosimetry and exposure with high-throughput screening (HTS) to enhance the utility of ToxCast™ HTS data by translating in vitro bioactivity concentrations to oral equivalent doses (OEDs) required to achieve these levels internally. These OEDs were compare...
High Throughput Assays for Exposure Science (NIEHS OHAT Staff Meeting presentation)
High throughput screening (HTS) data that characterize chemically induced biological activity have been generated for thousands of chemicals by the US interagency Tox21 and the US EPA ToxCast programs. In many cases there are no data available for comparing bioactivity from HTS w...
Increasing efficiency and declining cost of generating whole transcriptome profiles has made high-throughput transcriptomics a practical option for chemical bioactivity screening. The resulting data output provides information on the expression of thousands of genes and is amenab...
The U.S. Environmental Protection Agency’s ToxCast program has screened thousands of chemicals for biological activity, primarily using high-throughput in vitro bioassays. Adverse outcome pathways (AOPs) offer a means to link pathway-specific biological activities with potential ...
“httk”: EPA’s Tool for High Throughput Toxicokinetics (CompTox CoP)
Thousands of chemicals have been pro?led by high-throughput screening programs such as ToxCast and Tox21; these chemicals are tested in part because most of them have limited or no data on hazard, exposure, or toxicokinetics. Toxicokinetic models aid in predicting tissue concentr...
Perspectives on Validation of High-Throughput Assays Supporting 21st Century Toxicity Testing
In vitro high-throughput screening (HTS) assays are seeing increasing use in toxicity testing. HTS assays can simultaneously test many chemicals but have seen limited use in the regulatory arena, in part because of the need to undergo rigorous, time-consuming formal validation. ...
Traditional toxicity testing involves a large investment in resources, often using low-throughput in vivo animal studies for limited numbers of chemicals. An alternative strategy is the emergence of high-throughput (HT) in vitro assays as a rapid, cost-efficient means to screen t...
One use of alternative methods is to target animal use at only those chemicals and tests that are absolutely necessary. We discuss prioritization of testing based on high-throughput screening assays (HTS), QSAR modeling, high-throughput toxicokinetics (HTTK), and exposure modelin...
Over the past ten years, the US government has invested in high-throughput (HT) methods to screen chemicals for biological activity. Under the interagency Tox21 consortium and the US Environmental Protection Agency’s (EPA) ToxCast™ program, thousands of chemicals have...
Shi, Zheng; Yu, Tian; Sun, Rong; Wang, Shan; Chen, Xiao-Qian; Cheng, Li-Jia; Liu, Rong
2016-01-01
Human epidermal growth factor receptor-2 (HER2) is a trans-membrane receptor like protein, and aberrant signaling of HER2 is implicated in many human cancers, such as ovarian cancer, gastric cancer, and prostate cancer, most notably breast cancer. Moreover, it has been in the spotlight in the recent years as a promising new target for therapy of breast cancer. Since virtual screening has become an integral part of the drug discovery process, it is of great significant to identify novel HER2 inhibitors by structure-based virtual screening. In this study, we carried out a series of elegant bioinformatics approaches, such as virtual screening and molecular dynamics (MD) simulations to identify HER2 inhibitors from Food and Drug Administration-approved small molecule drug as potential "new use" drugs. Molecular docking identified top 10 potential drugs which showed spectrum affinity to HER2. Moreover, MD simulations suggested that ZINC08214629 (Nonoxynol-9) and ZINC03830276 (Benzonatate) might exert potential inhibitory effects against HER2-targeted anti-breast cancer therapeutics. Together, our findings may provide successful application of virtual screening studies in the lead discovery process, and suggest that our discovered small molecules could be effective HER2 inhibitor candidates for further study. A series of elegant bioinformatics approaches, including virtual screening and molecular dynamics (MD) simulations were took advantage to identify human epidermal growth factor receptor-2 (HER2) inhibitors. Molecular docking recognized top 10 candidate compounds, which showed spectrum affinity to HER2. Further, MD simulations suggested that ZINC08214629 (Nonoxynol-9) and ZINC03830276 (Benzonatate) in candidate compounds were identified as potential "new use" drugs against HER2-targeted anti-breast cancer therapeutics. Abbreviations used: HER2: Human epidermal growth factor receptor-2, FDA: Food and Drug Administration, PDB: Protein Database Bank, RMSDs: Root mean square deviations, SPC: Single point charge, PME: Particle mesh Ewald, NVT: Constant volume, NPT: Constant pressure, RMSF: Root-mean-square fluctuation.
Islam, Md Ataul; Pillay, Tahir S
2017-08-01
In this study, we searched for potential DNA GyrB inhibitors using pharmacophore-based virtual screening followed by molecular docking and molecular dynamics simulation approaches. For this purpose, a set of 248 DNA GyrB inhibitors was collected from the literature and a well-validated pharmacophore model was generated. The best pharmacophore model explained that two each of hydrogen bond acceptors and hydrophobicity regions were critical for inhibition of DNA GyrB. Good statistical results of the pharmacophore model indicated that the model was robust in nature. Virtual screening of molecular databases revealed three molecules as potential antimycobacterial agents. The final screened promising compounds were evaluated in molecular docking and molecular dynamics simulation studies. In the molecular dynamics studies, RMSD and RMSF values undoubtedly explained that the screened compounds formed stable complexes with DNA GyrB. Therefore, it can be concluded that the compounds identified may have potential for the treatment of TB. © 2017 John Wiley & Sons A/S.
Extended length microchannels for high density high throughput electrophoresis systems
Davidson, James C.; Balch, Joseph W.
2000-01-01
High throughput electrophoresis systems which provide extended well-to-read distances on smaller substrates, thus compacting the overall systems. The electrophoresis systems utilize a high density array of microchannels for electrophoresis analysis with extended read lengths. The microchannel geometry can be used individually or in conjunction to increase the effective length of a separation channel while minimally impacting the packing density of channels. One embodiment uses sinusoidal microchannels, while another embodiment uses plural microchannels interconnected by a via. The extended channel systems can be applied to virtually any type of channel confined chromatography.
Cheng, Han; Koning, Katie; O'Hearn, Aileen; Wang, Minxiu; Rumschlag-Booms, Emily; Varhegyi, Elizabeth; Rong, Lijun
2015-11-24
Genome-wide RNAi screening has been widely used to identify host proteins involved in replication and infection of different viruses, and numerous host factors are implicated in the replication cycles of these viruses, demonstrating the power of this approach. However, discrepancies on target identification of the same viruses by different groups suggest that high throughput RNAi screening strategies need to be carefully designed, developed and optimized prior to the large scale screening. Two genome-wide RNAi screens were performed in parallel against the entry of pseudotyped Marburg viruses and avian influenza virus H5N1 utilizing an HIV-1 based surrogate system, to identify host factors which are important for virus entry. A comparative analysis approach was employed in data analysis, which alleviated systematic positional effects and reduced the false positive number of virus-specific hits. The parallel nature of the strategy allows us to easily identify the host factors for a specific virus with a greatly reduced number of false positives in the initial screen, which is one of the major problems with high throughput screening. The power of this strategy is illustrated by a genome-wide RNAi screen for identifying the host factors important for Marburg virus and/or avian influenza virus H5N1 as described in this study. This strategy is particularly useful for highly pathogenic viruses since pseudotyping allows us to perform high throughput screens in the biosafety level 2 (BSL-2) containment instead of the BSL-3 or BSL-4 for the infectious viruses, with alleviated safety concerns. The screening strategy together with the unique comparative analysis approach makes the data more suitable for hit selection and enables us to identify virus-specific hits with a much lower false positive rate.
A Versatile Cell Death Screening Assay Using Dye-Stained Cells and Multivariate Image Analysis.
Collins, Tony J; Ylanko, Jarkko; Geng, Fei; Andrews, David W
2015-11-01
A novel dye-based method for measuring cell death in image-based screens is presented. Unlike conventional high- and medium-throughput cell death assays that measure only one form of cell death accurately, using multivariate analysis of micrographs of cells stained with the inexpensive mix, red dye nonyl acridine orange, and a nuclear stain, it was possible to quantify cell death induced by a variety of different agonists even without a positive control. Surprisingly, using a single known cytotoxic agent as a positive control for training a multivariate classifier allowed accurate quantification of cytotoxicity for mechanistically unrelated compounds enabling generation of dose-response curves. Comparison with low throughput biochemical methods suggested that cell death was accurately distinguished from cell stress induced by low concentrations of the bioactive compounds Tunicamycin and Brefeldin A. High-throughput image-based format analyses of more than 300 kinase inhibitors correctly identified 11 as cytotoxic with only 1 false positive. The simplicity and robustness of this dye-based assay makes it particularly suited to live cell screening for toxic compounds.
A Versatile Cell Death Screening Assay Using Dye-Stained Cells and Multivariate Image Analysis
Collins, Tony J.; Ylanko, Jarkko; Geng, Fei
2015-01-01
Abstract A novel dye-based method for measuring cell death in image-based screens is presented. Unlike conventional high- and medium-throughput cell death assays that measure only one form of cell death accurately, using multivariate analysis of micrographs of cells stained with the inexpensive mix, red dye nonyl acridine orange, and a nuclear stain, it was possible to quantify cell death induced by a variety of different agonists even without a positive control. Surprisingly, using a single known cytotoxic agent as a positive control for training a multivariate classifier allowed accurate quantification of cytotoxicity for mechanistically unrelated compounds enabling generation of dose–response curves. Comparison with low throughput biochemical methods suggested that cell death was accurately distinguished from cell stress induced by low concentrations of the bioactive compounds Tunicamycin and Brefeldin A. High-throughput image-based format analyses of more than 300 kinase inhibitors correctly identified 11 as cytotoxic with only 1 false positive. The simplicity and robustness of this dye-based assay makes it particularly suited to live cell screening for toxic compounds. PMID:26422066
Ehrenworth, Amy M; Claiborne, Tauris; Peralta-Yahya, Pamela
2017-10-17
Chemical biosensors, for which chemical detection triggers a fluorescent signal, have the potential to accelerate the screening of noncolorimetric chemicals produced by microbes, enabling the high-throughput engineering of enzymes and metabolic pathways. Here, we engineer a G-protein-coupled receptor (GPCR)-based sensor to detect serotonin produced by a producer microbe in the producer microbe's supernatant. Detecting a chemical in the producer microbe's supernatant is nontrivial because of the number of other metabolites and proteins present that could interfere with sensor performance. We validate the two-cell screening system for medium-throughput applications, opening the door to the rapid engineering of microbes for the increased production of serotonin. We focus on serotonin detection as serotonin levels limit the microbial production of hydroxystrictosidine, a modified alkaloid that could accelerate the semisynthesis of camptothecin-derived anticancer pharmaceuticals. This work shows the ease of generating GPCR-based chemical sensors and their ability to detect specific chemicals in complex aqueous solutions, such as microbial spent medium. In addition, this work sets the stage for the rapid engineering of serotonin-producing microbes.
High-throughput screening of metal-porphyrin-like graphenes for selective capture of carbon dioxide
Bae, Hyeonhu; Park, Minwoo; Jang, Byungryul; Kang, Yura; Park, Jinwoo; Lee, Hosik; Chung, Haegeun; Chung, ChiHye; Hong, Suklyun; Kwon, Yongkyung; Yakobson, Boris I.; Lee, Hoonkyung
2016-01-01
Nanostructured materials, such as zeolites and metal-organic frameworks, have been considered to capture CO2. However, their application has been limited largely because they exhibit poor selectivity for flue gases and low capture capacity under low pressures. We perform a high-throughput screening for selective CO2 capture from flue gases by using first principles thermodynamics. We find that elements with empty d orbitals selectively attract CO2 from gaseous mixtures under low CO2 pressures (~10−3 bar) at 300 K and release it at ~450 K. CO2 binding to elements involves hybridization of the metal d orbitals with the CO2 π orbitals and CO2-transition metal complexes were observed in experiments. This result allows us to perform high-throughput screening to discover novel promising CO2 capture materials with empty d orbitals (e.g., Sc– or V–porphyrin-like graphene) and predict their capture performance under various conditions. Moreover, these findings provide physical insights into selective CO2 capture and open a new path to explore CO2 capture materials. PMID:26902156
High-throughput screening of metal-porphyrin-like graphenes for selective capture of carbon dioxide.
Bae, Hyeonhu; Park, Minwoo; Jang, Byungryul; Kang, Yura; Park, Jinwoo; Lee, Hosik; Chung, Haegeun; Chung, ChiHye; Hong, Suklyun; Kwon, Yongkyung; Yakobson, Boris I; Lee, Hoonkyung
2016-02-23
Nanostructured materials, such as zeolites and metal-organic frameworks, have been considered to capture CO2. However, their application has been limited largely because they exhibit poor selectivity for flue gases and low capture capacity under low pressures. We perform a high-throughput screening for selective CO2 capture from flue gases by using first principles thermodynamics. We find that elements with empty d orbitals selectively attract CO2 from gaseous mixtures under low CO2 pressures (~10(-3) bar) at 300 K and release it at ~450 K. CO2 binding to elements involves hybridization of the metal d orbitals with the CO2 π orbitals and CO2-transition metal complexes were observed in experiments. This result allows us to perform high-throughput screening to discover novel promising CO2 capture materials with empty d orbitals (e.g., Sc- or V-porphyrin-like graphene) and predict their capture performance under various conditions. Moreover, these findings provide physical insights into selective CO2 capture and open a new path to explore CO2 capture materials.
High-throughput screening of metal-porphyrin-like graphenes for selective capture of carbon dioxide
NASA Astrophysics Data System (ADS)
Bae, Hyeonhu; Park, Minwoo; Jang, Byungryul; Kang, Yura; Park, Jinwoo; Lee, Hosik; Chung, Haegeun; Chung, Chihye; Hong, Suklyun; Kwon, Yongkyung; Yakobson, Boris I.; Lee, Hoonkyung
2016-02-01
Nanostructured materials, such as zeolites and metal-organic frameworks, have been considered to capture CO2. However, their application has been limited largely because they exhibit poor selectivity for flue gases and low capture capacity under low pressures. We perform a high-throughput screening for selective CO2 capture from flue gases by using first principles thermodynamics. We find that elements with empty d orbitals selectively attract CO2 from gaseous mixtures under low CO2 pressures (~10-3 bar) at 300 K and release it at ~450 K. CO2 binding to elements involves hybridization of the metal d orbitals with the CO2 π orbitals and CO2-transition metal complexes were observed in experiments. This result allows us to perform high-throughput screening to discover novel promising CO2 capture materials with empty d orbitals (e.g., Sc- or V-porphyrin-like graphene) and predict their capture performance under various conditions. Moreover, these findings provide physical insights into selective CO2 capture and open a new path to explore CO2 capture materials.
Genome-scale measurement of off-target activity using Cas9 toxicity in high-throughput screens.
Morgens, David W; Wainberg, Michael; Boyle, Evan A; Ursu, Oana; Araya, Carlos L; Tsui, C Kimberly; Haney, Michael S; Hess, Gaelen T; Han, Kyuho; Jeng, Edwin E; Li, Amy; Snyder, Michael P; Greenleaf, William J; Kundaje, Anshul; Bassik, Michael C
2017-05-05
CRISPR-Cas9 screens are powerful tools for high-throughput interrogation of genome function, but can be confounded by nuclease-induced toxicity at both on- and off-target sites, likely due to DNA damage. Here, to test potential solutions to this issue, we design and analyse a CRISPR-Cas9 library with 10 variable-length guides per gene and thousands of negative controls targeting non-functional, non-genic regions (termed safe-targeting guides), in addition to non-targeting controls. We find this library has excellent performance in identifying genes affecting growth and sensitivity to the ricin toxin. The safe-targeting guides allow for proper control of toxicity from on-target DNA damage. Using this toxicity as a proxy to measure off-target cutting, we demonstrate with tens of thousands of guides both the nucleotide position-dependent sensitivity to single mismatches and the reduction of off-target cutting using truncated guides. Our results demonstrate a simple strategy for high-throughput evaluation of target specificity and nuclease toxicity in Cas9 screens.