GalaxyDock BP2 score: a hybrid scoring function for accurate protein-ligand docking

Science.gov (United States)

Baek, Minkyung; Shin, Woong-Hee; Chung, Hwan Won; Seok, Chaok

2017-07-01

Protein-ligand docking is a useful tool for providing atomic-level understanding of protein functions in nature and design principles for artificial ligands or proteins with desired properties. The ability to identify the true binding pose of a ligand to a target protein among numerous possible candidate poses is an essential requirement for successful protein-ligand docking. Many previously developed docking scoring functions were trained to reproduce experimental binding affinities and were also used for scoring binding poses. However, in this study, we developed a new docking scoring function, called GalaxyDock BP2 Score, by directly training the scoring power of binding poses. This function is a hybrid of physics-based, empirical, and knowledge-based score terms that are balanced to strengthen the advantages of each component. The performance of the new scoring function exhibits significant improvement over existing scoring functions in decoy pose discrimination tests. In addition, when the score is used with the GalaxyDock2 protein-ligand docking program, it outperformed other state-of-the-art docking programs in docking tests on the Astex diverse set, the Cross2009 benchmark set, and the Astex non-native set. GalaxyDock BP2 Score and GalaxyDock2 with this score are freely available at http://galaxy.seoklab.org/softwares/galaxydock.html.

Machine learning in computational biology to accelerate high-throughput protein expression.

Science.gov (United States)

Sastry, Anand; Monk, Jonathan; Tegel, Hanna; Uhlen, Mathias; Palsson, Bernhard O; Rockberg, Johan; Brunk, Elizabeth

2017-08-15

The Human Protein Atlas (HPA) enables the simultaneous characterization of thousands of proteins across various tissues to pinpoint their spatial location in the human body. This has been achieved through transcriptomics and high-throughput immunohistochemistry-based approaches, where over 40 000 unique human protein fragments have been expressed in E. coli. These datasets enable quantitative tracking of entire cellular proteomes and present new avenues for understanding molecular-level properties influencing expression and solubility. Combining computational biology and machine learning identifies protein properties that hinder the HPA high-throughput antibody production pipeline. We predict protein expression and solubility with accuracies of 70% and 80%, respectively, based on a subset of key properties (aromaticity, hydropathy and isoelectric point). We guide the selection of protein fragments based on these characteristics to optimize high-throughput experimentation. We present the machine learning workflow as a series of IPython notebooks hosted on GitHub (https://github.com/SBRG/Protein_ML). The workflow can be used as a template for analysis of further expression and solubility datasets. ebrunk@ucsd.edu or johanr@biotech.kth.se. 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

High-throughput purification of recombinant proteins using self-cleaving intein tags.

Science.gov (United States)

Coolbaugh, M J; Shakalli Tang, M J; Wood, D W

2017-01-01

High throughput methods for recombinant protein production using E. coli typically involve the use of affinity tags for simple purification of the protein of interest. One drawback of these techniques is the occasional need for tag removal before study, which can be hard to predict. In this work, we demonstrate two high throughput purification methods for untagged protein targets based on simple and cost-effective self-cleaving intein tags. Two model proteins, E. coli beta-galactosidase (βGal) and superfolder green fluorescent protein (sfGFP), were purified using self-cleaving versions of the conventional chitin-binding domain (CBD) affinity tag and the nonchromatographic elastin-like-polypeptide (ELP) precipitation tag in a 96-well filter plate format. Initial tests with shake flask cultures confirmed that the intein purification scheme could be scaled down, with >90% pure product generated in a single step using both methods. The scheme was then validated in a high throughput expression platform using 24-well plate cultures followed by purification in 96-well plates. For both tags and with both target proteins, the purified product was consistently obtained in a single-step, with low well-to-well and plate-to-plate variability. This simple method thus allows the reproducible production of highly pure untagged recombinant proteins in a convenient microtiter plate format. Copyright © 2016 Elsevier Inc. All rights reserved.

Protein-protein docking using region-based 3D Zernike descriptors.

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Venkatraman, Vishwesh; Yang, Yifeng D; Sael, Lee; Kihara, Daisuke

2009-12-09

Protein-protein interactions are a pivotal component of many biological processes and mediate a variety of functions. Knowing the tertiary structure of a protein complex is therefore essential for understanding the interaction mechanism. However, experimental techniques to solve the structure of the complex are often found to be difficult. To this end, computational protein-protein docking approaches can provide a useful alternative to address this issue. Prediction of docking conformations relies on methods that effectively capture shape features of the participating proteins while giving due consideration to conformational changes that may occur. We present a novel protein docking algorithm based on the use of 3D Zernike descriptors as regional features of molecular shape. The key motivation of using these descriptors is their invariance to transformation, in addition to a compact representation of local surface shape characteristics. Docking decoys are generated using geometric hashing, which are then ranked by a scoring function that incorporates a buried surface area and a novel geometric complementarity term based on normals associated with the 3D Zernike shape description. Our docking algorithm was tested on both bound and unbound cases in the ZDOCK benchmark 2.0 dataset. In 74% of the bound docking predictions, our method was able to find a near-native solution (interface C-alphaRMSD 3D Zernike descriptors are adept in capturing shape complementarity at the protein-protein interface and useful for protein docking prediction. Rigorous benchmark studies show that our docking approach has a superior performance compared to existing methods.

Printing Proteins as Microarrays for High-Throughput Function Determination

Science.gov (United States)

MacBeath, Gavin; Schreiber, Stuart L.

2000-09-01

Systematic efforts are currently under way to construct defined sets of cloned genes for high-throughput expression and purification of recombinant proteins. To facilitate subsequent studies of protein function, we have developed miniaturized assays that accommodate extremely low sample volumes and enable the rapid, simultaneous processing of thousands of proteins. A high-precision robot designed to manufacture complementary DNA microarrays was used to spot proteins onto chemically derivatized glass slides at extremely high spatial densities. The proteins attached covalently to the slide surface yet retained their ability to interact specifically with other proteins, or with small molecules, in solution. Three applications for protein microarrays were demonstrated: screening for protein-protein interactions, identifying the substrates of protein kinases, and identifying the protein targets of small molecules.

High-throughput assessment of context-dependent effects of chromatin proteins

NARCIS (Netherlands)

Brueckner, L. (Laura); Van Arensbergen, J. (Joris); Akhtar, W. (Waseem); L. Pagie (Ludo); B. van Steensel (Bas)

2016-01-01

textabstractBackground: Chromatin proteins control gene activity in a concerted manner. We developed a high-throughput assay to study the effects of the local chromatin environment on the regulatory activity of a protein of interest. The assay combines a previously reported multiplexing strategy

Development of Control Applications for High-Throughput Protein Crystallography Experiments

International Nuclear Information System (INIS)

Gaponov, Yurii A.; Matsugaki, Naohiro; Honda, Nobuo; Sasajima, Kumiko; Igarashi, Noriyuki; Hiraki, Masahiko; Yamada, Yusuke; Wakatsuki, Soichi

2007-01-01

An integrated client-server control system (PCCS) with a unified relational database (PCDB) has been developed for high-throughput protein crystallography experiments on synchrotron beamlines. The major steps in protein crystallographic experiments (purification, crystallization, crystal harvesting, data collection, and data processing) are integrated into the software. All information necessary for performing protein crystallography experiments is stored in the PCDB database (except raw X-ray diffraction data, which is stored in the Network File Server). To allow all members of a protein crystallography group to participate in experiments, the system was developed as a multi-user system with secure network access based on TCP/IP secure UNIX sockets. Secure remote access to the system is possible from any operating system with X-terminal and SSH/X11 (Secure Shell with graphical user interface) support. Currently, the system covers the high-throughput X-ray data collection stages and is being commissioned at BL5A and NW12A (PF, PF-AR, KEK, Tsukuba, Japan)

Integrated Automation of High-Throughput Screening and Reverse Phase Protein Array Sample Preparation

DEFF Research Database (Denmark)

Pedersen, Marlene Lemvig; Block, Ines; List, Markus

into automated robotic high-throughput screens, which allows subsequent protein quantification. In this integrated solution, samples are directly forwarded to automated cell lysate preparation and preparation of dilution series, including reformatting to a protein spotter-compatible format after the high......-throughput screening. Tracking of huge sample numbers and data analysis from a high-content screen to RPPAs is accomplished via MIRACLE, a custom made software suite developed by us. To this end, we demonstrate that the RPPAs generated in this manner deliver reliable protein readouts and that GAPDH and TFR levels can...

Arbitrary protein−protein docking targets biologically relevant interfaces

International Nuclear Information System (INIS)

Martin, Juliette; Lavery, Richard

2012-01-01

Protein-protein recognition is of fundamental importance in the vast majority of biological processes. However, it has already been demonstrated that it is very hard to distinguish true complexes from false complexes in so-called cross-docking experiments, where binary protein complexes are separated and the isolated proteins are all docked against each other and scored. Does this result, at least in part, reflect a physical reality? False complexes could reflect possible nonspecific or weak associations. In this paper, we investigate the twilight zone of protein-protein interactions, building on an interesting outcome of cross-docking experiments: false complexes seem to favor residues from the true interaction site, suggesting that randomly chosen partners dock in a non-random fashion on protein surfaces. Here, we carry out arbitrary docking of a non-redundant data set of 198 proteins, with more than 300 randomly chosen "probe" proteins. We investigate the tendency of arbitrary partners to aggregate at localized regions of the protein surfaces, the shape and compositional bias of the generated interfaces, and the potential of this property to predict biologically relevant binding sites. We show that the non-random localization of arbitrary partners after protein-protein docking is a generic feature of protein structures. The interfaces generated in this way are not systematically planar or curved, but tend to be closer than average to the center of the proteins. These results can be used to predict biological interfaces with an AUC value up to 0.69 alone, and 0.72 when used in combination with evolutionary information. An appropriate choice of random partners and number of docking models make this method computationally practical. It is also noted that nonspecific interfaces can point to alternate interaction sites in the case of proteins with multiple interfaces. We illustrate the usefulness of arbitrary docking using PEBP (Phosphatidylethanolamine binding

Arbitrary protein−protein docking targets biologically relevant interfaces

Directory of Open Access Journals (Sweden)

Martin Juliette

2012-05-01

Full Text Available Abstract Background Protein-protein recognition is of fundamental importance in the vast majority of biological processes. However, it has already been demonstrated that it is very hard to distinguish true complexes from false complexes in so-called cross-docking experiments, where binary protein complexes are separated and the isolated proteins are all docked against each other and scored. Does this result, at least in part, reflect a physical reality? False complexes could reflect possible nonspecific or weak associations. Results In this paper, we investigate the twilight zone of protein-protein interactions, building on an interesting outcome of cross-docking experiments: false complexes seem to favor residues from the true interaction site, suggesting that randomly chosen partners dock in a non-random fashion on protein surfaces. Here, we carry out arbitrary docking of a non-redundant data set of 198 proteins, with more than 300 randomly chosen "probe" proteins. We investigate the tendency of arbitrary partners to aggregate at localized regions of the protein surfaces, the shape and compositional bias of the generated interfaces, and the potential of this property to predict biologically relevant binding sites. We show that the non-random localization of arbitrary partners after protein-protein docking is a generic feature of protein structures. The interfaces generated in this way are not systematically planar or curved, but tend to be closer than average to the center of the proteins. These results can be used to predict biological interfaces with an AUC value up to 0.69 alone, and 0.72 when used in combination with evolutionary information. An appropriate choice of random partners and number of docking models make this method computationally practical. It is also noted that nonspecific interfaces can point to alternate interaction sites in the case of proteins with multiple interfaces. We illustrate the usefulness of arbitrary docking

MEGADOCK 4.0: an ultra-high-performance protein-protein docking software for heterogeneous supercomputers.

Science.gov (United States)

Ohue, Masahito; Shimoda, Takehiro; Suzuki, Shuji; Matsuzaki, Yuri; Ishida, Takashi; Akiyama, Yutaka

2014-11-15

The application of protein-protein docking in large-scale interactome analysis is a major challenge in structural bioinformatics and requires huge computing resources. In this work, we present MEGADOCK 4.0, an FFT-based docking software that makes extensive use of recent heterogeneous supercomputers and shows powerful, scalable performance of >97% strong scaling. MEGADOCK 4.0 is written in C++ with OpenMPI and NVIDIA CUDA 5.0 (or later) and is freely available to all academic and non-profit users at: http://www.bi.cs.titech.ac.jp/megadock. akiyama@cs.titech.ac.jp Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press.

Surfing the Protein-Protein Interaction Surface Using Docking Methods: Application to the Design of PPI Inhibitors.

Science.gov (United States)

Sable, Rushikesh; Jois, Seetharama

2015-06-23

Blocking protein-protein interactions (PPI) using small molecules or peptides modulates biochemical pathways and has therapeutic significance. PPI inhibition for designing drug-like molecules is a new area that has been explored extensively during the last decade. Considering the number of available PPI inhibitor databases and the limited number of 3D structures available for proteins, docking and scoring methods play a major role in designing PPI inhibitors as well as stabilizers. Docking methods are used in the design of PPI inhibitors at several stages of finding a lead compound, including modeling the protein complex, screening for hot spots on the protein-protein interaction interface and screening small molecules or peptides that bind to the PPI interface. There are three major challenges to the use of docking on the relatively flat surfaces of PPI. In this review we will provide some examples of the use of docking in PPI inhibitor design as well as its limitations. The combination of experimental and docking methods with improved scoring function has thus far resulted in few success stories of PPI inhibitors for therapeutic purposes. Docking algorithms used for PPI are in the early stages, however, and as more data are available docking will become a highly promising area in the design of PPI inhibitors or stabilizers.

HDOCK: a web server for protein-protein and protein-DNA/RNA docking based on a hybrid strategy.

Science.gov (United States)

Yan, Yumeng; Zhang, Di; Zhou, Pei; Li, Botong; Huang, Sheng-You

2017-07-03

Protein-protein and protein-DNA/RNA interactions play a fundamental role in a variety of biological processes. Determining the complex structures of these interactions is valuable, in which molecular docking has played an important role. To automatically make use of the binding information from the PDB in docking, here we have presented HDOCK, a novel web server of our hybrid docking algorithm of template-based modeling and free docking, in which cases with misleading templates can be rescued by the free docking protocol. The server supports protein-protein and protein-DNA/RNA docking and accepts both sequence and structure inputs for proteins. The docking process is fast and consumes about 10-20 min for a docking run. Tested on the cases with weakly homologous complexes of server. The HDOCK web server is available at http://hdock.phys.hust.edu.cn/. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

High-throughput fractionation of human plasma for fast enrichment of low- and high-abundance proteins.

Science.gov (United States)

Breen, Lucas; Cao, Lulu; Eom, Kirsten; Srajer Gajdosik, Martina; Camara, Lila; Giacometti, Jasminka; Dupuy, Damian E; Josic, Djuro

2012-05-01

Fast, cost-effective and reproducible isolation of IgM from plasma is invaluable to the study of IgM and subsequent understanding of the human immune system. Additionally, vast amounts of information regarding human physiology and disease can be derived from analysis of the low abundance proteome of the plasma. In this study, methods were optimized for both the high-throughput isolation of IgM from human plasma, and the high-throughput isolation and fractionation of low abundance plasma proteins. To optimize the chromatographic isolation of IgM from human plasma, many variables were examined including chromatography resin, mobile phases, and order of chromatographic separations. Purification of IgM was achieved most successfully through isolation of immunoglobulin from human plasma using Protein A chromatography with a specific resin followed by subsequent fractionation using QA strong anion exchange chromatography. Through these optimization experiments, an additional method was established to prepare plasma for analysis of low abundance proteins. This method involved chromatographic depletion of high-abundance plasma proteins and reduction of plasma proteome complexity through further chromatographic fractionation. Purification of IgM was achieved with high purity as confirmed by SDS-PAGE and IgM-specific immunoblot. Isolation and fractionation of low abundance protein was also performed successfully, as confirmed by SDS-PAGE and mass spectrometry analysis followed by label-free quantitative spectral analysis. The level of purity of the isolated IgM allows for further IgM-specific analysis of plasma samples. The developed fractionation scheme can be used for high throughput screening of human plasma in order to identify low and high abundance proteins as potential prognostic and diagnostic disease biomarkers.

Surfing the Protein-Protein Interaction Surface Using Docking Methods: Application to the Design of PPI Inhibitors

Directory of Open Access Journals (Sweden)

Rushikesh Sable

2015-06-01

Full Text Available Blocking protein-protein interactions (PPI using small molecules or peptides modulates biochemical pathways and has therapeutic significance. PPI inhibition for designing drug-like molecules is a new area that has been explored extensively during the last decade. Considering the number of available PPI inhibitor databases and the limited number of 3D structures available for proteins, docking and scoring methods play a major role in designing PPI inhibitors as well as stabilizers. Docking methods are used in the design of PPI inhibitors at several stages of finding a lead compound, including modeling the protein complex, screening for hot spots on the protein-protein interaction interface and screening small molecules or peptides that bind to the PPI interface. There are three major challenges to the use of docking on the relatively flat surfaces of PPI. In this review we will provide some examples of the use of docking in PPI inhibitor design as well as its limitations. The combination of experimental and docking methods with improved scoring function has thus far resulted in few success stories of PPI inhibitors for therapeutic purposes. Docking algorithms used for PPI are in the early stages, however, and as more data are available docking will become a highly promising area in the design of PPI inhibitors or stabilizers.

The Protein Maker: an automated system for high-throughput parallel purification

International Nuclear Information System (INIS)

Smith, Eric R.; Begley, Darren W.; Anderson, Vanessa; Raymond, Amy C.; Haffner, Taryn E.; Robinson, John I.; Edwards, Thomas E.; Duncan, Natalie; Gerdts, Cory J.; Mixon, Mark B.; Nollert, Peter; Staker, Bart L.; Stewart, Lance J.

2011-01-01

The Protein Maker instrument addresses a critical bottleneck in structural genomics by allowing automated purification and buffer testing of multiple protein targets in parallel with a single instrument. Here, the use of this instrument to (i) purify multiple influenza-virus proteins in parallel for crystallization trials and (ii) identify optimal lysis-buffer conditions prior to large-scale protein purification is described. The Protein Maker is an automated purification system developed by Emerald BioSystems for high-throughput parallel purification of proteins and antibodies. This instrument allows multiple load, wash and elution buffers to be used in parallel along independent lines for up to 24 individual samples. To demonstrate its utility, its use in the purification of five recombinant PB2 C-terminal domains from various subtypes of the influenza A virus is described. Three of these constructs crystallized and one diffracted X-rays to sufficient resolution for structure determination and deposition in the Protein Data Bank. Methods for screening lysis buffers for a cytochrome P450 from a pathogenic fungus prior to upscaling expression and purification are also described. The Protein Maker has become a valuable asset within the Seattle Structural Genomics Center for Infectious Disease (SSGCID) and hence is a potentially valuable tool for a variety of high-throughput protein-purification applications

High-throughput kinase assays with protein substrates using fluorescent polymer superquenching

Directory of Open Access Journals (Sweden)

Weatherford Wendy

2005-05-01

Full Text Available Abstract Background High-throughput screening is used by the pharmaceutical industry for identifying lead compounds that interact with targets of pharmacological interest. Because of the key role that aberrant regulation of protein phosphorylation plays in diseases such as cancer, diabetes and hypertension, kinases have become one of the main drug targets. With the exception of antibody-based assays, methods to screen for specific kinase activity are generally restricted to the use of small synthetic peptides as substrates. However, the use of natural protein substrates has the advantage that potential inhibitors can be detected that affect enzyme activity by binding to a site other than the catalytic site. We have previously reported a non-radioactive and non-antibody-based fluorescence quench assay for detection of phosphorylation or dephosphorylation using synthetic peptide substrates. The aim of this work is to develop an assay for detection of phosphorylation of chemically unmodified proteins based on this polymer superquenching platform. Results Using a modified QTL Lightspeed™ assay, phosphorylation of native protein was quantified by the interaction of the phosphorylated proteins with metal-ion coordinating groups co-located with fluorescent polymer deposited onto microspheres. The binding of phospho-protein inhibits a dye-labeled "tracer" peptide from associating to the phosphate-binding sites present on the fluorescent microspheres. The resulting inhibition of quench generates a "turn on" assay, in which the signal correlates with the phosphorylation of the substrate. The assay was tested on three different proteins: Myelin Basic Protein (MBP, Histone H1 and Phosphorylated heat- and acid-stable protein (PHAS-1. Phosphorylation of the proteins was detected by Protein Kinase Cα (PKCα and by the Interleukin -1 Receptor-associated Kinase 4 (IRAK4. Enzyme inhibition yielded IC50 values that were comparable to those obtained using

High-throughput kinase assays with protein substrates using fluorescent polymer superquenching.

Science.gov (United States)

Rininsland, Frauke; Stankewicz, Casey; Weatherford, Wendy; McBranch, Duncan

2005-05-31

High-throughput screening is used by the pharmaceutical industry for identifying lead compounds that interact with targets of pharmacological interest. Because of the key role that aberrant regulation of protein phosphorylation plays in diseases such as cancer, diabetes and hypertension, kinases have become one of the main drug targets. With the exception of antibody-based assays, methods to screen for specific kinase activity are generally restricted to the use of small synthetic peptides as substrates. However, the use of natural protein substrates has the advantage that potential inhibitors can be detected that affect enzyme activity by binding to a site other than the catalytic site. We have previously reported a non-radioactive and non-antibody-based fluorescence quench assay for detection of phosphorylation or dephosphorylation using synthetic peptide substrates. The aim of this work is to develop an assay for detection of phosphorylation of chemically unmodified proteins based on this polymer superquenching platform. Using a modified QTL Lightspeed assay, phosphorylation of native protein was quantified by the interaction of the phosphorylated proteins with metal-ion coordinating groups co-located with fluorescent polymer deposited onto microspheres. The binding of phospho-protein inhibits a dye-labeled "tracer" peptide from associating to the phosphate-binding sites present on the fluorescent microspheres. The resulting inhibition of quench generates a "turn on" assay, in which the signal correlates with the phosphorylation of the substrate. The assay was tested on three different proteins: Myelin Basic Protein (MBP), Histone H1 and Phosphorylated heat- and acid-stable protein (PHAS-1). Phosphorylation of the proteins was detected by Protein Kinase Calpha (PKCalpha) and by the Interleukin -1 Receptor-associated Kinase 4 (IRAK4). Enzyme inhibition yielded IC50 values that were comparable to those obtained using peptide substrates. Statistical parameters that

Sequence alignment reveals possible MAPK docking motifs on HIV proteins.

Directory of Open Access Journals (Sweden)

Perry Evans

Full Text Available Over the course of HIV infection, virus replication is facilitated by the phosphorylation of HIV proteins by human ERK1 and ERK2 mitogen-activated protein kinases (MAPKs. MAPKs are known to phosphorylate their substrates by first binding with them at a docking site. Docking site interactions could be viable drug targets because the sequences guiding them are more specific than phosphorylation consensus sites. In this study we use multiple bioinformatics tools to discover candidate MAPK docking site motifs on HIV proteins known to be phosphorylated by MAPKs, and we discuss the possibility of targeting docking sites with drugs. Using sequence alignments of HIV proteins of different subtypes, we show that MAPK docking patterns previously described for human proteins appear on the HIV matrix, Tat, and Vif proteins in a strain dependent manner, but are absent from HIV Rev and appear on all HIV Nef strains. We revise the regular expressions of previously annotated MAPK docking patterns in order to provide a subtype independent motif that annotates all HIV proteins. One revision is based on a documented human variant of one of the substrate docking motifs, and the other reduces the number of required basic amino acids in the standard docking motifs from two to one. The proposed patterns are shown to be consistent with in silico docking between ERK1 and the HIV matrix protein. The motif usage on HIV proteins is sufficiently different from human proteins in amino acid sequence similarity to allow for HIV specific targeting using small-molecule drugs.

High-throughput Cloning and Expression of Integral Membrane Proteins in Escherichia coli

Science.gov (United States)

Bruni, Renato

2014-01-01

Recently, several structural genomics centers have been established and a remarkable number of three-dimensional structures of soluble proteins have been solved. For membrane proteins, the number of structures solved has been significantly trailing those for their soluble counterparts, not least because over-expression and purification of membrane proteins is a much more arduous process. By using high throughput technologies, a large number of membrane protein targets can be screened simultaneously and a greater number of expression and purification conditions can be employed, leading to a higher probability of successfully determining the structure of membrane proteins. This unit describes the cloning, expression and screening of membrane proteins using high throughput methodologies developed in our laboratory. Basic Protocol 1 deals with the cloning of inserts into expression vectors by ligation-independent cloning. Basic Protocol 2 describes the expression and purification of the target proteins on a miniscale. Lastly, for the targets that express at the miniscale, basic protocols 3 and 4 outline the methods employed for the expression and purification of targets at the midi-scale, as well as a procedure for detergent screening and identification of detergent(s) in which the target protein is stable. PMID:24510647

Assessing the utility and limitations of high throughput virtual screening

Directory of Open Access Journals (Sweden)

Paul Daniel Phillips

2016-05-01

Full Text Available Due to low cost, speed, and unmatched ability to explore large numbers of compounds, high throughput virtual screening and molecular docking engines have become widely utilized by computational scientists. It is generally accepted that docking engines, such as AutoDock, produce reliable qualitative results for ligand-macromolecular receptor binding, and molecular docking results are commonly reported in literature in the absence of complementary wet lab experimental data. In this investigation, three variants of the sixteen amino acid peptide, α-conotoxin MII, were docked to a homology model of the a3β2-nicotinic acetylcholine receptor. DockoMatic version 2.0 was used to perform a virtual screen of each peptide ligand to the receptor for ten docking trials consisting of 100 AutoDock cycles per trial. The results were analyzed for both variation in the calculated binding energy obtained from AutoDock, and the orientation of bound peptide within the receptor. The results show that, while no clear correlation exists between consistent ligand binding pose and the calculated binding energy, AutoDock is able to determine a consistent positioning of bound peptide in the majority of trials when at least ten trials were evaluated.

istar: a web platform for large-scale protein-ligand docking.

Directory of Open Access Journals (Sweden)

Hongjian Li

Full Text Available Protein-ligand docking is a key computational method in the design of starting points for the drug discovery process. We are motivated by the desire to automate large-scale docking using our popular docking engine idock and thus have developed a publicly-accessible web platform called istar. Without tedious software installation, users can submit jobs using our website. Our istar website supports 1 filtering ligands by desired molecular properties and previewing the number of ligands to dock, 2 monitoring job progress in real time, and 3 visualizing ligand conformations and outputting free energy and ligand efficiency predicted by idock, binding affinity predicted by RF-Score, putative hydrogen bonds, and supplier information for easy purchase, three useful features commonly lacked on other online docking platforms like DOCK Blaster or iScreen. We have collected 17,224,424 ligands from the All Clean subset of the ZINC database, and revamped our docking engine idock to version 2.0, further improving docking speed and accuracy, and integrating RF-Score as an alternative rescoring function. To compare idock 2.0 with the state-of-the-art AutoDock Vina 1.1.2, we have carried out a rescoring benchmark and a redocking benchmark on the 2,897 and 343 protein-ligand complexes of PDBbind v2012 refined set and CSAR NRC HiQ Set 24Sept2010 respectively, and an execution time benchmark on 12 diverse proteins and 3,000 ligands of different molecular weight. Results show that, under various scenarios, idock achieves comparable success rates while outperforming AutoDock Vina in terms of docking speed by at least 8.69 times and at most 37.51 times. When evaluated on the PDBbind v2012 core set, our istar platform combining with RF-Score manages to reproduce Pearson's correlation coefficient and Spearman's correlation coefficient of as high as 0.855 and 0.859 respectively between the experimental binding affinity and the predicted binding affinity of the docked

istar: a web platform for large-scale protein-ligand docking.

Science.gov (United States)

Li, Hongjian; Leung, Kwong-Sak; Ballester, Pedro J; Wong, Man-Hon

2014-01-01

Protein-ligand docking is a key computational method in the design of starting points for the drug discovery process. We are motivated by the desire to automate large-scale docking using our popular docking engine idock and thus have developed a publicly-accessible web platform called istar. Without tedious software installation, users can submit jobs using our website. Our istar website supports 1) filtering ligands by desired molecular properties and previewing the number of ligands to dock, 2) monitoring job progress in real time, and 3) visualizing ligand conformations and outputting free energy and ligand efficiency predicted by idock, binding affinity predicted by RF-Score, putative hydrogen bonds, and supplier information for easy purchase, three useful features commonly lacked on other online docking platforms like DOCK Blaster or iScreen. We have collected 17,224,424 ligands from the All Clean subset of the ZINC database, and revamped our docking engine idock to version 2.0, further improving docking speed and accuracy, and integrating RF-Score as an alternative rescoring function. To compare idock 2.0 with the state-of-the-art AutoDock Vina 1.1.2, we have carried out a rescoring benchmark and a redocking benchmark on the 2,897 and 343 protein-ligand complexes of PDBbind v2012 refined set and CSAR NRC HiQ Set 24Sept2010 respectively, and an execution time benchmark on 12 diverse proteins and 3,000 ligands of different molecular weight. Results show that, under various scenarios, idock achieves comparable success rates while outperforming AutoDock Vina in terms of docking speed by at least 8.69 times and at most 37.51 times. When evaluated on the PDBbind v2012 core set, our istar platform combining with RF-Score manages to reproduce Pearson's correlation coefficient and Spearman's correlation coefficient of as high as 0.855 and 0.859 respectively between the experimental binding affinity and the predicted binding affinity of the docked conformation. istar

DECK: Distance and environment-dependent, coarse-grained, knowledge-based potentials for protein-protein docking

Directory of Open Access Journals (Sweden)

Vakser Ilya A

2011-07-01

Full Text Available Abstract Background Computational approaches to protein-protein docking typically include scoring aimed at improving the rank of the near-native structure relative to the false-positive matches. Knowledge-based potentials improve modeling of protein complexes by taking advantage of the rapidly increasing amount of experimentally derived information on protein-protein association. An essential element of knowledge-based potentials is defining the reference state for an optimal description of the residue-residue (or atom-atom pairs in the non-interaction state. Results The study presents a new Distance- and Environment-dependent, Coarse-grained, Knowledge-based (DECK potential for scoring of protein-protein docking predictions. Training sets of protein-protein matches were generated based on bound and unbound forms of proteins taken from the DOCKGROUND resource. Each residue was represented by a pseudo-atom in the geometric center of the side chain. To capture the long-range and the multi-body interactions, residues in different secondary structure elements at protein-protein interfaces were considered as different residue types. Five reference states for the potentials were defined and tested. The optimal reference state was selected and the cutoff effect on the distance-dependent potentials investigated. The potentials were validated on the docking decoys sets, showing better performance than the existing potentials used in scoring of protein-protein docking results. Conclusions A novel residue-based statistical potential for protein-protein docking was developed and validated on docking decoy sets. The results show that the scoring function DECK can successfully identify near-native protein-protein matches and thus is useful in protein docking. In addition to the practical application of the potentials, the study provides insights into the relative utility of the reference states, the scope of the distance dependence, and the coarse-graining of

Molecular classification of fatty liver by high-throughput profiling of protein post-translational modifications.

Science.gov (United States)

Urasaki, Yasuyo; Fiscus, Ronald R; Le, Thuc T

2016-04-01

We describe an alternative approach to classifying fatty liver by profiling protein post-translational modifications (PTMs) with high-throughput capillary isoelectric focusing (cIEF) immunoassays. Four strains of mice were studied, with fatty livers induced by different causes, such as ageing, genetic mutation, acute drug usage, and high-fat diet. Nutrient-sensitive PTMs of a panel of 12 liver metabolic and signalling proteins were simultaneously evaluated with cIEF immunoassays, using nanograms of total cellular protein per assay. Changes to liver protein acetylation, phosphorylation, and O-N-acetylglucosamine glycosylation were quantified and compared between normal and diseased states. Fatty liver tissues could be distinguished from one another by distinctive protein PTM profiles. Fatty liver is currently classified by morphological assessment of lipid droplets, without identifying the underlying molecular causes. In contrast, high-throughput profiling of protein PTMs has the potential to provide molecular classification of fatty liver. Copyright © 2016 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

High throughput platforms for structural genomics of integral membrane proteins.

Science.gov (United States)

Mancia, Filippo; Love, James

2011-08-01

Structural genomics approaches on integral membrane proteins have been postulated for over a decade, yet specific efforts are lagging years behind their soluble counterparts. Indeed, high throughput methodologies for production and characterization of prokaryotic integral membrane proteins are only now emerging, while large-scale efforts for eukaryotic ones are still in their infancy. Presented here is a review of recent literature on actively ongoing structural genomics of membrane protein initiatives, with a focus on those aimed at implementing interesting techniques aimed at increasing our rate of success for this class of macromolecules. Copyright © 2011 Elsevier Ltd. All rights reserved.

Robotic high-throughput purification of affinity-tagged recombinant proteins.

Science.gov (United States)

Wiesler, Simone C; Weinzierl, Robert O J

2015-01-01

Affinity purification of recombinant proteins has become the method of choice to obtain good quantities and qualities of proteins for a variety of downstream biochemical applications. While manual or FPLC-assisted purification techniques are generally time-consuming and labor-intensive, the advent of high-throughput technologies and liquid handling robotics has simplified and accelerated this process significantly. Additionally, without the human factor as a potential source of error, automated purification protocols allow for the generation of large numbers of proteins simultaneously and under directly comparable conditions. The delivered material is ideal for activity comparisons of different variants of the same protein. Here, we present our strategy for the simultaneous purification of up to 24 affinity-tagged proteins for activity measurements in biochemical assays. The protocol described is suitable for the scale typically required in individual research laboratories.

A unified conformational selection and induced fit approach to protein-peptide docking.

Directory of Open Access Journals (Sweden)

Mikael Trellet

Full Text Available Protein-peptide interactions are vital for the cell. They mediate, inhibit or serve as structural components in nearly 40% of all macromolecular interactions, and are often associated with diseases, making them interesting leads for protein drug design. In recent years, large-scale technologies have enabled exhaustive studies on the peptide recognition preferences for a number of peptide-binding domain families. Yet, the paucity of data regarding their molecular binding mechanisms together with their inherent flexibility makes the structural prediction of protein-peptide interactions very challenging. This leaves flexible docking as one of the few amenable computational techniques to model these complexes. We present here an ensemble, flexible protein-peptide docking protocol that combines conformational selection and induced fit mechanisms. Starting from an ensemble of three peptide conformations (extended, a-helix, polyproline-II, flexible docking with HADDOCK generates 79.4% of high quality models for bound/unbound and 69.4% for unbound/unbound docking when tested against the largest protein-peptide complexes benchmark dataset available to date. Conformational selection at the rigid-body docking stage successfully recovers the most relevant conformation for a given protein-peptide complex and the subsequent flexible refinement further improves the interface by up to 4.5 Å interface RMSD. Cluster-based scoring of the models results in a selection of near-native solutions in the top three for ∼75% of the successfully predicted cases. This unified conformational selection and induced fit approach to protein-peptide docking should open the route to the modeling of challenging systems such as disorder-order transitions taking place upon binding, significantly expanding the applicability limit of biomolecular interaction modeling by docking.

DockoMatic 2.0: high throughput inverse virtual screening and homology modeling.

Science.gov (United States)

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.

On the analysis of protein-protein interactions via knowledge-based potentials for the prediction of protein-protein docking

DEFF Research Database (Denmark)

Feliu, Elisenda; Aloy, Patrick; Oliva, Baldo

2011-01-01

Development of effective methods to screen binary interactions obtained by rigid-body protein-protein docking is key for structure prediction of complexes and for elucidating physicochemical principles of protein-protein binding. We have derived empirical knowledge-based potential functions for s...... and with independence of the partner. This information is encoded at the residue level and could be easily incorporated in the initial grid scoring for Fast Fourier Transform rigid-body docking methods.......Development of effective methods to screen binary interactions obtained by rigid-body protein-protein docking is key for structure prediction of complexes and for elucidating physicochemical principles of protein-protein binding. We have derived empirical knowledge-based potential functions...... for selecting rigid-body docking poses. These potentials include the energetic component that provides the residues with a particular secondary structure and surface accessibility. These scoring functions have been tested on a state-of-art benchmark dataset and on a decoy dataset of permanent interactions. Our...

MEGADOCK-Web: an integrated database of high-throughput structure-based protein-protein interaction predictions.

Science.gov (United States)

Hayashi, Takanori; Matsuzaki, Yuri; Yanagisawa, Keisuke; Ohue, Masahito; Akiyama, Yutaka

2018-05-08

Protein-protein interactions (PPIs) play several roles in living cells, and computational PPI prediction is a major focus of many researchers. The three-dimensional (3D) structure and binding surface are important for the design of PPI inhibitors. Therefore, rigid body protein-protein docking calculations for two protein structures are expected to allow elucidation of PPIs different from known complexes in terms of 3D structures because known PPI information is not explicitly required. We have developed rapid PPI prediction software based on protein-protein docking, called MEGADOCK. In order to fully utilize the benefits of computational PPI predictions, it is necessary to construct a comprehensive database to gather prediction results and their predicted 3D complex structures and to make them easily accessible. Although several databases exist that provide predicted PPIs, the previous databases do not contain a sufficient number of entries for the purpose of discovering novel PPIs. In this study, we constructed an integrated database of MEGADOCK PPI predictions, named MEGADOCK-Web. MEGADOCK-Web provides more than 10 times the number of PPI predictions than previous databases and enables users to conduct PPI predictions that cannot be found in conventional PPI prediction databases. In MEGADOCK-Web, there are 7528 protein chains and 28,331,628 predicted PPIs from all possible combinations of those proteins. Each protein structure is annotated with PDB ID, chain ID, UniProt AC, related KEGG pathway IDs, and known PPI pairs. Additionally, MEGADOCK-Web provides four powerful functions: 1) searching precalculated PPI predictions, 2) providing annotations for each predicted protein pair with an experimentally known PPI, 3) visualizing candidates that may interact with the query protein on biochemical pathways, and 4) visualizing predicted complex structures through a 3D molecular viewer. MEGADOCK-Web provides a huge amount of comprehensive PPI predictions based on

Applications of the NRGsuite and the Molecular Docking Software FlexAID in Computational Drug Discovery and Design.

Science.gov (United States)

Morency, Louis-Philippe; Gaudreault, Francis; Najmanovich, Rafael

2018-01-01

Docking simulations help us understand molecular interactions. Here we present a hands-on tutorial to utilize FlexAID (Flexible Artificial Intelligence Docking), an open source molecular docking software between ligands such as small molecules or peptides and macromolecules such as proteins and nucleic acids. The tutorial uses the NRGsuite PyMOL plugin graphical user interface to set up and visualize docking simulations in real time as well as detect and refine target cavities. The ease of use of FlexAID and the NRGsuite combined with its superior performance relative to widely used docking software provides nonexperts with an important tool to understand molecular interactions with direct applications in structure-based drug design and virtual high-throughput screening.

Accurate Classification of Protein Subcellular Localization from High-Throughput Microscopy Images Using Deep Learning

Directory of Open Access Journals (Sweden)

Tanel Pärnamaa

2017-05-01

Full Text Available High-throughput microscopy of many single cells generates high-dimensional data that are far from straightforward to analyze. One important problem is automatically detecting the cellular compartment where a fluorescently-tagged protein resides, a task relatively simple for an experienced human, but difficult to automate on a computer. Here, we train an 11-layer neural network on data from mapping thousands of yeast proteins, achieving per cell localization classification accuracy of 91%, and per protein accuracy of 99% on held-out images. We confirm that low-level network features correspond to basic image characteristics, while deeper layers separate localization classes. Using this network as a feature calculator, we train standard classifiers that assign proteins to previously unseen compartments after observing only a small number of training examples. Our results are the most accurate subcellular localization classifications to date, and demonstrate the usefulness of deep learning for high-throughput microscopy.

Accurate Classification of Protein Subcellular Localization from High-Throughput Microscopy Images Using Deep Learning.

Science.gov (United States)

Pärnamaa, Tanel; Parts, Leopold

2017-05-05

High-throughput microscopy of many single cells generates high-dimensional data that are far from straightforward to analyze. One important problem is automatically detecting the cellular compartment where a fluorescently-tagged protein resides, a task relatively simple for an experienced human, but difficult to automate on a computer. Here, we train an 11-layer neural network on data from mapping thousands of yeast proteins, achieving per cell localization classification accuracy of 91%, and per protein accuracy of 99% on held-out images. We confirm that low-level network features correspond to basic image characteristics, while deeper layers separate localization classes. Using this network as a feature calculator, we train standard classifiers that assign proteins to previously unseen compartments after observing only a small number of training examples. Our results are the most accurate subcellular localization classifications to date, and demonstrate the usefulness of deep learning for high-throughput microscopy. Copyright © 2017 Parnamaa and Parts.

Molecular docking.

Science.gov (United States)

Morris, Garrett M; Lim-Wilby, Marguerita

2008-01-01

Molecular docking is a key tool in structural molecular biology and computer-assisted drug design. The goal of ligand-protein docking is to predict the predominant binding mode(s) of a ligand with a protein of known three-dimensional structure. Successful docking methods search high-dimensional spaces effectively and use a scoring function that correctly ranks candidate dockings. Docking can be used to perform virtual screening on large libraries of compounds, rank the results, and propose structural hypotheses of how the ligands inhibit the target, which is invaluable in lead optimization. The setting up of the input structures for the docking is just as important as the docking itself, and analyzing the results of stochastic search methods can sometimes be unclear. This chapter discusses the background and theory of molecular docking software, and covers the usage of some of the most-cited docking software.

High-throughput method for optimum solubility screening for homogeneity and crystallization of proteins

Science.gov (United States)

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.

PSOVina: The hybrid particle swarm optimization algorithm for protein-ligand docking.

Science.gov (United States)

Ng, Marcus C K; Fong, Simon; Siu, Shirley W I

2015-06-01

Protein-ligand docking is an essential step in modern drug discovery process. The challenge here is to accurately predict and efficiently optimize the position and orientation of ligands in the binding pocket of a target protein. In this paper, we present a new method called PSOVina which combined the particle swarm optimization (PSO) algorithm with the efficient Broyden-Fletcher-Goldfarb-Shannon (BFGS) local search method adopted in AutoDock Vina to tackle the conformational search problem in docking. Using a diverse data set of 201 protein-ligand complexes from the PDBbind database and a full set of ligands and decoys for four representative targets from the directory of useful decoys (DUD) virtual screening data set, we assessed the docking performance of PSOVina in comparison to the original Vina program. Our results showed that PSOVina achieves a remarkable execution time reduction of 51-60% without compromising the prediction accuracies in the docking and virtual screening experiments. This improvement in time efficiency makes PSOVina a better choice of a docking tool in large-scale protein-ligand docking applications. Our work lays the foundation for the future development of swarm-based algorithms in molecular docking programs. PSOVina is freely available to non-commercial users at http://cbbio.cis.umac.mo .

Development of Microfluidic Systems Enabling High-Throughput Single-Cell Protein Characterization

OpenAIRE

Fan, Beiyuan; Li, Xiufeng; Chen, Deyong; Peng, Hongshang; Wang, Junbo; Chen, Jian

2016-01-01

This article reviews recent developments in microfluidic systems enabling high-throughput characterization of single-cell proteins. Four key perspectives of microfluidic platforms are included in this review: (1) microfluidic fluorescent flow cytometry; (2) droplet based microfluidic flow cytometry; (3) large-array micro wells (microengraving); and (4) large-array micro chambers (barcode microchips). We examine the advantages and limitations of each technique and discuss future research oppor...

Using constitutive activity to define appropriate high-throughput screening assays for orphan g protein-coupled receptors.

Science.gov (United States)

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.

An NMR-based scoring function improves the accuracy of binding pose predictions by docking by two orders of magnitude

Energy Technology Data Exchange (ETDEWEB)

Orts, Julien [EMBL, Structure and Computational Biology Unit (Germany); Bartoschek, Stefan [Industriepark Hoechst, Sanofi-Aventis Deutschland GmbH, R and D LGCR/Parallel Synthesis and Natural Products (Germany); Griesinger, Christian [Max Planck Institute for Biophysical Chemistry (Germany); Monecke, Peter [Industriepark Hoechst, Sanofi-Aventis Deutschland GmbH, R and D LGCR/Structure, Design and Informatics (Germany); Carlomagno, Teresa, E-mail: teresa.carlomagno@embl.de [EMBL, Structure and Computational Biology Unit (Germany)

2012-01-15

Low-affinity ligands can be efficiently optimized into high-affinity drug leads by structure based drug design when atomic-resolution structural information on the protein/ligand complexes is available. In this work we show that the use of a few, easily obtainable, experimental restraints improves the accuracy of the docking experiments by two orders of magnitude. The experimental data are measured in nuclear magnetic resonance spectra and consist of protein-mediated NOEs between two competitively binding ligands. The methodology can be widely applied as the data are readily obtained for low-affinity ligands in the presence of non-labelled receptor at low concentration. The experimental inter-ligand NOEs are efficiently used to filter and rank complex model structures that have been pre-selected by docking protocols. This approach dramatically reduces the degeneracy and inaccuracy of the chosen model in docking experiments, is robust with respect to inaccuracy of the structural model used to represent the free receptor and is suitable for high-throughput docking campaigns.

Analysis and Ranking of Protein-Protein Docking Models Using Inter-Residue Contacts and Inter-Molecular Contact Maps

KAUST Repository

Oliva, Romina; Chermak, Edrisse; Cavallo, Luigi

2015-01-01

In view of the increasing interest both in inhibitors of protein-protein interactions and in protein drugs themselves, analysis of the three-dimensional structure of protein-protein complexes is assuming greater relevance in drug design. In the many cases where an experimental structure is not available, protein-protein docking becomes the method of choice for predicting the arrangement of the complex. However, reliably scoring protein-protein docking poses is still an unsolved problem. As a consequence, the screening of many docking models is usually required in the analysis step, to possibly single out the correct ones. Here, making use of exemplary cases, we review our recently introduced methods for the analysis of protein complex structures and for the scoring of protein docking poses, based on the use of inter-residue contacts and their visualization in inter-molecular contact maps. We also show that the ensemble of tools we developed can be used in the context of rational drug design targeting protein-protein interactions.

Analysis and Ranking of Protein-Protein Docking Models Using Inter-Residue Contacts and Inter-Molecular Contact Maps

KAUST Repository

Oliva, Romina

2015-07-01

In view of the increasing interest both in inhibitors of protein-protein interactions and in protein drugs themselves, analysis of the three-dimensional structure of protein-protein complexes is assuming greater relevance in drug design. In the many cases where an experimental structure is not available, protein-protein docking becomes the method of choice for predicting the arrangement of the complex. However, reliably scoring protein-protein docking poses is still an unsolved problem. As a consequence, the screening of many docking models is usually required in the analysis step, to possibly single out the correct ones. Here, making use of exemplary cases, we review our recently introduced methods for the analysis of protein complex structures and for the scoring of protein docking poses, based on the use of inter-residue contacts and their visualization in inter-molecular contact maps. We also show that the ensemble of tools we developed can be used in the context of rational drug design targeting protein-protein interactions.

PEPSI-Dock: a detailed data-driven protein-protein interaction potential accelerated by polar Fourier correlation.

Science.gov (United States)

Neveu, Emilie; Ritchie, David W; Popov, Petr; Grudinin, Sergei

2016-09-01

Docking prediction algorithms aim to find the native conformation of a complex of proteins from knowledge of their unbound structures. They rely on a combination of sampling and scoring methods, adapted to different scales. Polynomial Expansion of Protein Structures and Interactions for Docking (PEPSI-Dock) improves the accuracy of the first stage of the docking pipeline, which will sharpen up the final predictions. Indeed, PEPSI-Dock benefits from the precision of a very detailed data-driven model of the binding free energy used with a global and exhaustive rigid-body search space. As well as being accurate, our computations are among the fastest by virtue of the sparse representation of the pre-computed potentials and FFT-accelerated sampling techniques. Overall, this is the first demonstration of a FFT-accelerated docking method coupled with an arbitrary-shaped distance-dependent interaction potential. First, we present a novel learning process to compute data-driven distant-dependent pairwise potentials, adapted from our previous method used for rescoring of putative protein-protein binding poses. The potential coefficients are learned by combining machine-learning techniques with physically interpretable descriptors. Then, we describe the integration of the deduced potentials into a FFT-accelerated spherical sampling provided by the Hex library. Overall, on a training set of 163 heterodimers, PEPSI-Dock achieves a success rate of 91% mid-quality predictions in the top-10 solutions. On a subset of the protein docking benchmark v5, it achieves 44.4% mid-quality predictions in the top-10 solutions when starting from bound structures and 20.5% when starting from unbound structures. The method runs in 5-15 min on a modern laptop and can easily be extended to other types of interactions. https://team.inria.fr/nano-d/software/PEPSI-Dock sergei.grudinin@inria.fr. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e

Detection of dysregulated protein-association networks by high-throughput proteomics predicts cancer vulnerabilities.

Science.gov (United States)

Lapek, John D; Greninger, Patricia; Morris, Robert; Amzallag, Arnaud; Pruteanu-Malinici, Iulian; Benes, Cyril H; Haas, Wilhelm

2017-10-01

The formation of protein complexes and the co-regulation of the cellular concentrations of proteins are essential mechanisms for cellular signaling and for maintaining homeostasis. Here we use isobaric-labeling multiplexed proteomics to analyze protein co-regulation and show that this allows the identification of protein-protein associations with high accuracy. We apply this 'interactome mapping by high-throughput quantitative proteome analysis' (IMAHP) method to a panel of 41 breast cancer cell lines and show that deviations of the observed protein co-regulations in specific cell lines from the consensus network affects cellular fitness. Furthermore, these aberrant interactions serve as biomarkers that predict the drug sensitivity of cell lines in screens across 195 drugs. We expect that IMAHP can be broadly used to gain insight into how changing landscapes of protein-protein associations affect the phenotype of biological systems.

HPEPDOCK: a web server for blind peptide-protein docking based on a hierarchical algorithm.

Science.gov (United States)

Zhou, Pei; Jin, Bowen; Li, Hao; Huang, Sheng-You

2018-05-09

Protein-peptide interactions are crucial in many cellular functions. Therefore, determining the structure of protein-peptide complexes is important for understanding the molecular mechanism of related biological processes and developing peptide drugs. HPEPDOCK is a novel web server for blind protein-peptide docking through a hierarchical algorithm. Instead of running lengthy simulations to refine peptide conformations, HPEPDOCK considers the peptide flexibility through an ensemble of peptide conformations generated by our MODPEP program. For blind global peptide docking, HPEPDOCK obtained a success rate of 33.3% in binding mode prediction on a benchmark of 57 unbound cases when the top 10 models were considered, compared to 21.1% for pepATTRACT server. HPEPDOCK also performed well in docking against homology models and obtained a success rate of 29.8% within top 10 predictions. For local peptide docking, HPEPDOCK achieved a high success rate of 72.6% on a benchmark of 62 unbound cases within top 10 predictions, compared to 45.2% for HADDOCK peptide protocol. Our HPEPDOCK server is computationally efficient and consumed an average of 29.8 mins for a global peptide docking job and 14.2 mins for a local peptide docking job. The HPEPDOCK web server is available at http://huanglab.phys.hust.edu.cn/hpepdock/.

Re-docking scheme for generating near-native protein complexes by assembling residue interaction fingerprints.

Directory of Open Access Journals (Sweden)

Nobuyuki Uchikoga

Full Text Available Interaction profile method is a useful method for processing rigid-body docking. After the docking process, the resulting set of docking poses could be classified by calculating similarities among them using these interaction profiles to search for near-native poses. However, there are some cases where the near-native poses are not included in this set of docking poses even when the bound-state structures are used. Therefore, we have developed a method for generating near-native docking poses by introducing a re-docking process. We devised a method for calculating the profile of interaction fingerprints by assembling protein complexes after determining certain core-protein complexes. For our analysis, we used 44 bound-state protein complexes selected from the ZDOCK benchmark dataset ver. 2.0, including some protein pairs none of which generated near-native poses in the docking process. Consequently, after the re-docking process we obtained profiles of interaction fingerprints, some of which yielded near-native poses. The re-docking process involved searching for possible docking poses in a restricted area using the profile of interaction fingerprints. If the profile includes interactions identical to those in the native complex, we obtained near-native docking poses. Accordingly, near-native poses were obtained for all bound-state protein complexes examined here. Application of interaction fingerprints to the re-docking process yielded structures with more native interactions, even when a docking pose, obtained following the initial docking process, contained only a small number of native amino acid interactions. Thus, utilization of the profile of interaction fingerprints in the re-docking process yielded more near-native poses.

Re-docking scheme for generating near-native protein complexes by assembling residue interaction fingerprints.

Science.gov (United States)

Uchikoga, Nobuyuki; Matsuzaki, Yuri; Ohue, Masahito; Hirokawa, Takatsugu; Akiyama, Yutaka

2013-01-01

Interaction profile method is a useful method for processing rigid-body docking. After the docking process, the resulting set of docking poses could be classified by calculating similarities among them using these interaction profiles to search for near-native poses. However, there are some cases where the near-native poses are not included in this set of docking poses even when the bound-state structures are used. Therefore, we have developed a method for generating near-native docking poses by introducing a re-docking process. We devised a method for calculating the profile of interaction fingerprints by assembling protein complexes after determining certain core-protein complexes. For our analysis, we used 44 bound-state protein complexes selected from the ZDOCK benchmark dataset ver. 2.0, including some protein pairs none of which generated near-native poses in the docking process. Consequently, after the re-docking process we obtained profiles of interaction fingerprints, some of which yielded near-native poses. The re-docking process involved searching for possible docking poses in a restricted area using the profile of interaction fingerprints. If the profile includes interactions identical to those in the native complex, we obtained near-native docking poses. Accordingly, near-native poses were obtained for all bound-state protein complexes examined here. Application of interaction fingerprints to the re-docking process yielded structures with more native interactions, even when a docking pose, obtained following the initial docking process, contained only a small number of native amino acid interactions. Thus, utilization of the profile of interaction fingerprints in the re-docking process yielded more near-native poses.

CPdock: the complementarity plot for docking of proteins: implementing multi-dielectric continuum electrostatics.

Science.gov (United States)

Basu, Sankar

2017-12-07

The complementarity plot (CP) is an established validation tool for protein structures, applicable to both globular proteins (folding) as well as protein-protein complexes (binding). It computes the shape and electrostatic complementarities (S m , E m ) for amino acid side-chains buried within the protein interior or interface and plots them in a two-dimensional plot having knowledge-based probabilistic quality estimates for the residues as well as for the whole structure. The current report essentially presents an upgraded version of the plot with the implementation of the advanced multi-dielectric functionality (as in Delphi version 6.2 or higher) in the computation of electrostatic complementarity to make the validation tool physico-chemically more realistic. The two methods (single- and multi-dielectric) agree decently in their resultant E m values, and hence, provisions for both methods have been kept in the software suite. So to speak, the global electrostatic balance within a well-folded protein and/or a well-packed interface seems only marginally perturbed by the choice of different internal dielectric values. However, both from theoretical as well as practical grounds, the more advanced multi-dielectric version of the plot is certainly recommended for potentially producing more reliable results. The report also presents a new methodology and a variant plot, namely CP dock , based on the same principles of complementarity specifically designed to be used in the docking of proteins. The efficacy of the method to discriminate between good and bad docked protein complexes has been tested on a recent state-of-the-art docking benchmark. The results unambiguously indicate that CP dock can indeed be effective in the initial screening phase of a docking scoring pipeline before going into more sophisticated and computationally expensive scoring functions. CP dock has been made available at https://github.com/nemo8130/CPdock . Graphical Abstract An example showing

Domain requirements for the Dock adapter protein in growth- cone signaling.

Science.gov (United States)

Rao, Y; Zipursky, S L

1998-03-03

Tyrosine phosphorylation has been implicated in growth-cone guidance through genetic, biochemical, and pharmacological studies. Adapter proteins containing src homology 2 (SH2) domains and src homology 3 (SH3) domains provide a means of linking guidance signaling through phosphotyrosine to downstream effectors regulating growth-cone motility. The Drosophila adapter, Dreadlocks (Dock), the homolog of mammalian Nck containing three N-terminal SH3 domains and a single SH2 domain, is highly specialized for growth-cone guidance. In this paper, we demonstrate that Dock can couple signals in either an SH2-dependent or an SH2-independent fashion in photoreceptor (R cell) growth cones, and that Dock displays different domain requirements in different neurons.

Evaluation of the novel algorithm of flexible ligand docking with moveable target-protein atoms.

Science.gov (United States)

Sulimov, Alexey V; Zheltkov, Dmitry A; Oferkin, Igor V; Kutov, Danil C; Katkova, Ekaterina V; Tyrtyshnikov, Eugene E; Sulimov, Vladimir B

2017-01-01

We present the novel docking algorithm based on the Tensor Train decomposition and the TT-Cross global optimization. The algorithm is applied to the docking problem with flexible ligand and moveable protein atoms. The energy of the protein-ligand complex is calculated in the frame of the MMFF94 force field in vacuum. The grid of precalculated energy potentials of probe ligand atoms in the field of the target protein atoms is not used. The energy of the protein-ligand complex for any given configuration is computed directly with the MMFF94 force field without any fitting parameters. The conformation space of the system coordinates is formed by translations and rotations of the ligand as a whole, by the ligand torsions and also by Cartesian coordinates of the selected target protein atoms. Mobility of protein and ligand atoms is taken into account in the docking process simultaneously and equally. The algorithm is realized in the novel parallel docking SOL-P program and results of its performance for a set of 30 protein-ligand complexes are presented. Dependence of the docking positioning accuracy is investigated as a function of parameters of the docking algorithm and the number of protein moveable atoms. It is shown that mobility of the protein atoms improves docking positioning accuracy. The SOL-P program is able to perform docking of a flexible ligand into the active site of the target protein with several dozens of protein moveable atoms: the native crystallized ligand pose is correctly found as the global energy minimum in the search space with 157 dimensions using 4700 CPU ∗ h at the Lomonosov supercomputer.

An Improved Methodology for Multidimensional High-Throughput Preformulation Characterization of Protein Conformational Stability

Science.gov (United States)

Maddux, Nathaniel R.; Rosen, Ilan T.; Hu, Lei; Olsen, Christopher M.; Volkin, David B.; Middaugh, C. Russell

2013-01-01

The Empirical Phase Diagram (EPD) technique is a vector-based multidimensional analysis method for summarizing large data sets from a variety of biophysical techniques. It can be used to provide comprehensive preformulation characterization of a macromolecule’s higher-order structural integrity and conformational stability. In its most common mode, it represents a type of stimulus-response diagram using environmental variables such as temperature, pH, and ionic strength as the stimulus, with alterations in macromolecular structure being the response. Until now EPD analysis has not been available in a high throughput mode because of the large number of experimental techniques and environmental stressor/stabilizer variables typically employed. A new instrument has been developed that combines circular dichroism, UV-absorbance, fluorescence spectroscopy and light scattering in a single unit with a 6-position temperature controlled cuvette turret. Using this multifunctional instrument and a new software system we have generated EPDs for four model proteins. Results confirm the reproducibility of the apparent phase boundaries and protein behavior within the boundaries. This new approach permits two EPDs to be generated per day using only 0.5 mg of protein per EPD. Thus, the new methodology generates reproducible EPDs in high-throughput mode, and represents the next step in making such determinations more routine. PMID:22447621

Solvated protein-DNA docking using HADDOCK

NARCIS (Netherlands)

van Dijk, Marc; Visscher, Koen M; Bonvin, Alexandre M.J.J; Kastritis, Panagiotis L.

2013-01-01

Interfacial water molecules play an important role in many aspects of protein-DNA specificity and recognition. Yet they have been mostly neglected in the computational modeling of these complexes. We present here a solvated docking protocol that allows explicit inclusion of water molecules in the

Homologous high-throughput expression and purification of highly conserved E coli proteins

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Duchmann Rainer

2007-06-01

Full Text Available Abstract Background Genetic factors and a dysregulated immune response towards commensal bacteria contribute to the pathogenesis of Inflammatory Bowel Disease (IBD. Animal models demonstrated that the normal intestinal flora is crucial for the development of intestinal inflammation. However, due to the complexity of the intestinal flora, it has been difficult to design experiments for detection of proinflammatory bacterial antigen(s involved in the pathogenesis of the disease. Several studies indicated a potential association of E. coli with IBD. In addition, T cell clones of IBD patients were shown to cross react towards antigens from different enteric bacterial species and thus likely responded to conserved bacterial antigens. We therefore chose highly conserved E. coli proteins as candidate antigens for abnormal T cell responses in IBD and used high-throughput techniques for cloning, expression and purification under native conditions of a set of 271 conserved E. coli proteins for downstream immunologic studies. Results As a standardized procedure, genes were PCR amplified and cloned into the expression vector pQTEV2 in order to express proteins N-terminally fused to a seven-histidine-tag. Initial small-scale expression and purification under native conditions by metal chelate affinity chromatography indicated that the vast majority of target proteins were purified in high yields. Targets that revealed low yields after purification probably due to weak solubility were shuttled into Gateway (Invitrogen destination vectors in order to enhance solubility by N-terminal fusion of maltose binding protein (MBP, N-utilizing substance A (NusA, or glutathione S-transferase (GST to the target protein. In addition, recombinant proteins were treated with polymyxin B coated magnetic beads in order to remove lipopolysaccharide (LPS. Thus, 73% of the targeted proteins could be expressed and purified in large-scale to give soluble proteins in the range of 500

Analysis of protein-protein docking decoys using interaction fingerprints: application to the reconstruction of CaM-ligand complexes

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Uchikoga Nobuyuki

2010-05-01

Full Text Available Abstract Background Protein-protein docking for proteins with large conformational changes was analyzed by using interaction fingerprints, one of the scales for measuring similarities among complex structures, utilized especially for searching near-native protein-ligand or protein-protein complex structures. Here, we have proposed a combined method for analyzing protein-protein docking by taking large conformational changes into consideration. This combined method consists of ensemble soft docking with multiple protein structures, refinement of complexes, and cluster analysis using interaction fingerprints and energy profiles. Results To test for the applicability of this combined method, various CaM-ligand complexes were reconstructed from the NMR structures of unbound CaM. For the purpose of reconstruction, we used three known CaM-ligands, namely, the CaM-binding peptides of cyclic nucleotide gateway (CNG, CaM kinase kinase (CaMKK and the plasma membrane Ca2+ ATPase pump (PMCA, and thirty-one structurally diverse CaM conformations. For each ligand, 62000 CaM-ligand complexes were generated in the docking step and the relationship between their energy profiles and structural similarities to the native complex were analyzed using interaction fingerprint and RMSD. Near-native clusters were obtained in the case of CNG and CaMKK. Conclusions The interaction fingerprint method discriminated near-native structures better than the RMSD method in cluster analysis. We showed that a combined method that includes the interaction fingerprint is very useful for protein-protein docking analysis of certain cases.

3D-SURFER: software for high-throughput protein surface comparison and analysis.

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La, David; Esquivel-Rodríguez, Juan; Venkatraman, Vishwesh; Li, Bin; Sael, Lee; Ueng, Stephen; Ahrendt, Steven; Kihara, Daisuke

2009-11-01

We present 3D-SURFER, a web-based tool designed to facilitate high-throughput comparison and characterization of proteins based on their surface shape. As each protein is effectively represented by a vector of 3D Zernike descriptors, comparison times for a query protein against the entire PDB take, on an average, only a couple of seconds. The web interface has been designed to be as interactive as possible with displays showing animated protein rotations, CATH codes and structural alignments using the CE program. In addition, geometrically interesting local features of the protein surface, such as pockets that often correspond to ligand binding sites as well as protrusions and flat regions can also be identified and visualized. 3D-SURFER is a web application that can be freely accessed from: http://dragon.bio.purdue.edu/3d-surfer dkihara@purdue.edu Supplementary data are available at Bioinformatics online.

PEPSI-Dock: a detailed data-driven protein–protein interaction potential accelerated by polar Fourier correlation

OpenAIRE

Neveu , Emilie; Ritchie , David; Popov , Petr; Grudinin , Sergei

2016-01-01

International audience; Motivation: Docking prediction algorithms aim to find the native conformation of a complex of proteins from knowledge of their unbound structures. They rely on a combination of sampling and scoring methods, adapted to different scales. Polynomial Expansion of Protein Structures and Interactions for Docking (PEPSI-Dock) improves the accuracy of the first stage of the docking pipeline , which will sharpen up the final predictions. Indeed, PEPSI-Dock benefits from the pre...

Novel strategy for protein exploration: high-throughput screening assisted with fuzzy neural network.

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Kato, Ryuji; Nakano, Hideo; Konishi, Hiroyuki; Kato, Katsuya; Koga, Yuchi; Yamane, Tsuneo; Kobayashi, Takeshi; Honda, Hiroyuki

2005-08-19

To engineer proteins with desirable characteristics from a naturally occurring protein, high-throughput screening (HTS) combined with directed evolutional approach is the essential technology. However, most HTS techniques are simple positive screenings. The information obtained from the positive candidates is used only as results but rarely as clues for understanding the structural rules, which may explain the protein activity. In here, we have attempted to establish a novel strategy for exploring functional proteins associated with computational analysis. As a model case, we explored lipases with inverted enantioselectivity for a substrate p-nitrophenyl 3-phenylbutyrate from the wild-type lipase of Burkhorderia cepacia KWI-56, which is originally selective for (S)-configuration of the substrate. Data from our previous work on (R)-enantioselective lipase screening were applied to fuzzy neural network (FNN), bioinformatic algorithm, to extract guidelines for screening and engineering processes to be followed. FNN has an advantageous feature of extracting hidden rules that lie between sequences of variants and their enzyme activity to gain high prediction accuracy. Without any prior knowledge, FNN predicted a rule indicating that "size at position L167," among four positions (L17, F119, L167, and L266) in the substrate binding core region, is the most influential factor for obtaining lipase with inverted (R)-enantioselectivity. Based on the guidelines obtained, newly engineered novel variants, which were not found in the actual screening, were experimentally proven to gain high (R)-enantioselectivity by engineering the size at position L167. We also designed and assayed two novel variants, namely FIGV (L17F, F119I, L167G, and L266V) and FFGI (L17F, L167G, and L266I), which were compatible with the guideline obtained from FNN analysis, and confirmed that these designed lipases could acquire high inverted enantioselectivity. The results have shown that with the aid of

Post processing of protein-compound docking for fragment-based drug discovery (FBDD): in-silico structure-based drug screening and ligand-binding pose prediction.

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Fukunishi, Yoshifumi

2010-01-01

For fragment-based drug development, both hit (active) compound prediction and docking-pose (protein-ligand complex structure) prediction of the hit compound are important, since chemical modification (fragment linking, fragment evolution) subsequent to the hit discovery must be performed based on the protein-ligand complex structure. However, the naïve protein-compound docking calculation shows poor accuracy in terms of docking-pose prediction. Thus, post-processing of the protein-compound docking is necessary. Recently, several methods for the post-processing of protein-compound docking have been proposed. In FBDD, the compounds are smaller than those for conventional drug screening. This makes it difficult to perform the protein-compound docking calculation. A method to avoid this problem has been reported. Protein-ligand binding free energy estimation is useful to reduce the procedures involved in the chemical modification of the hit fragment. Several prediction methods have been proposed for high-accuracy estimation of protein-ligand binding free energy. This paper summarizes the various computational methods proposed for docking-pose prediction and their usefulness in FBDD.

DockoMatic: automated peptide analog creation for high throughput virtual screening.

Science.gov (United States)

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.

DockingShop: A Tool for Interactive Molecular Docking

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Lu, Ting-Cheng; Max, Nelson L.; Ding, Jinhui; Bethel, E. Wes; Crivelli, Silvia N.

2005-04-24

Given two independently determined molecular structures, the molecular docking problem predicts the bound association, or best fit between them, while allowing for conformational changes of the individual molecules during construction of a molecular complex. Docking Shop is an integrated environment that permits interactive molecular docking by navigating a ligand or protein to an estimated binding site of a receptor with real-time graphical feedback of scoring factors as visual guides. Our program can be used to create initial configurations for a protein docking prediction process. Its output--the structure of aprotein-ligand or protein-protein complex--may serve as an input for aprotein docking algorithm, or an optimization process. This tool provides molecular graphics interfaces for structure modeling, interactive manipulation, navigation, optimization, and dynamic visualization to aid users steer the prediction process using their biological knowledge.

Evaluation of multiple protein docking structures using correctly predicted pairwise subunits

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Esquivel-Rodríguez Juan

2012-03-01

Full Text Available Abstract Background Many functionally important proteins in a cell form complexes with multiple chains. Therefore, computational prediction of multiple protein complexes is an important task in bioinformatics. In the development of multiple protein docking methods, it is important to establish a metric for evaluating prediction results in a reasonable and practical fashion. However, since there are only few works done in developing methods for multiple protein docking, there is no study that investigates how accurate structural models of multiple protein complexes should be to allow scientists to gain biological insights. Methods We generated a series of predicted models (decoys of various accuracies by our multiple protein docking pipeline, Multi-LZerD, for three multi-chain complexes with 3, 4, and 6 chains. We analyzed the decoys in terms of the number of correctly predicted pair conformations in the decoys. Results and conclusion We found that pairs of chains with the correct mutual orientation exist even in the decoys with a large overall root mean square deviation (RMSD to the native. Therefore, in addition to a global structure similarity measure, such as the global RMSD, the quality of models for multiple chain complexes can be better evaluated by using the local measurement, the number of chain pairs with correct mutual orientation. We termed the fraction of correctly predicted pairs (RMSD at the interface of less than 4.0Å as fpair and propose to use it for evaluation of the accuracy of multiple protein docking.

High-throughput single-molecule force spectroscopy for membrane proteins

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Bosshart, Patrick D.; Casagrande, Fabio; Frederix, Patrick L. T. M.; Ratera, Merce; Bippes, Christian A.; Müller, Daniel J.; Palacin, Manuel; Engel, Andreas; Fotiadis, Dimitrios

2008-09-01

Atomic force microscopy-based single-molecule force spectroscopy (SMFS) is a powerful tool for studying the mechanical properties, intermolecular and intramolecular interactions, unfolding pathways, and energy landscapes of membrane proteins. One limiting factor for the large-scale applicability of SMFS on membrane proteins is its low efficiency in data acquisition. We have developed a semi-automated high-throughput SMFS (HT-SMFS) procedure for efficient data acquisition. In addition, we present a coarse filter to efficiently extract protein unfolding events from large data sets. The HT-SMFS procedure and the coarse filter were validated using the proton pump bacteriorhodopsin (BR) from Halobacterium salinarum and the L-arginine/agmatine antiporter AdiC from the bacterium Escherichia coli. To screen for molecular interactions between AdiC and its substrates, we recorded data sets in the absence and in the presence of L-arginine, D-arginine, and agmatine. Altogether ~400 000 force-distance curves were recorded. Application of coarse filtering to this wealth of data yielded six data sets with ~200 (AdiC) and ~400 (BR) force-distance spectra in each. Importantly, the raw data for most of these data sets were acquired in one to two days, opening new perspectives for HT-SMFS applications.

High-throughput single-molecule force spectroscopy for membrane proteins

International Nuclear Information System (INIS)

Bosshart, Patrick D; Casagrande, Fabio; Frederix, Patrick L T M; Engel, Andreas; Fotiadis, Dimitrios; Ratera, Merce; Palacin, Manuel; Bippes, Christian A; Mueller, Daniel J

2008-01-01

Atomic force microscopy-based single-molecule force spectroscopy (SMFS) is a powerful tool for studying the mechanical properties, intermolecular and intramolecular interactions, unfolding pathways, and energy landscapes of membrane proteins. One limiting factor for the large-scale applicability of SMFS on membrane proteins is its low efficiency in data acquisition. We have developed a semi-automated high-throughput SMFS (HT-SMFS) procedure for efficient data acquisition. In addition, we present a coarse filter to efficiently extract protein unfolding events from large data sets. The HT-SMFS procedure and the coarse filter were validated using the proton pump bacteriorhodopsin (BR) from Halobacterium salinarum and the L-arginine/agmatine antiporter AdiC from the bacterium Escherichia coli. To screen for molecular interactions between AdiC and its substrates, we recorded data sets in the absence and in the presence of L-arginine, D-arginine, and agmatine. Altogether ∼400 000 force-distance curves were recorded. Application of coarse filtering to this wealth of data yielded six data sets with ∼200 (AdiC) and ∼400 (BR) force-distance spectra in each. Importantly, the raw data for most of these data sets were acquired in one to two days, opening new perspectives for HT-SMFS applications

High-throughput single-molecule force spectroscopy for membrane proteins

Energy Technology Data Exchange (ETDEWEB)

Bosshart, Patrick D; Casagrande, Fabio; Frederix, Patrick L T M; Engel, Andreas; Fotiadis, Dimitrios [M E Mueller Institute for Structural Biology, Biozentrum of the University of Basel, CH-4056 Basel (Switzerland); Ratera, Merce; Palacin, Manuel [Institute for Research in Biomedicine, Barcelona Science Park, Department of Biochemistry and Molecular Biology, Faculty of Biology, University of Barcelona and Centro de Investigacion Biomedica en Red de Enfermedades Raras, E-08028 Barcelona (Spain); Bippes, Christian A; Mueller, Daniel J [BioTechnology Center, Technical University, Tatzberg 47, D-01307 Dresden (Germany)], E-mail: andreas.engel@unibas.ch, E-mail: dimitrios.fotiadis@mci.unibe.ch

2008-09-24

Atomic force microscopy-based single-molecule force spectroscopy (SMFS) is a powerful tool for studying the mechanical properties, intermolecular and intramolecular interactions, unfolding pathways, and energy landscapes of membrane proteins. One limiting factor for the large-scale applicability of SMFS on membrane proteins is its low efficiency in data acquisition. We have developed a semi-automated high-throughput SMFS (HT-SMFS) procedure for efficient data acquisition. In addition, we present a coarse filter to efficiently extract protein unfolding events from large data sets. The HT-SMFS procedure and the coarse filter were validated using the proton pump bacteriorhodopsin (BR) from Halobacterium salinarum and the L-arginine/agmatine antiporter AdiC from the bacterium Escherichia coli. To screen for molecular interactions between AdiC and its substrates, we recorded data sets in the absence and in the presence of L-arginine, D-arginine, and agmatine. Altogether {approx}400 000 force-distance curves were recorded. Application of coarse filtering to this wealth of data yielded six data sets with {approx}200 (AdiC) and {approx}400 (BR) force-distance spectra in each. Importantly, the raw data for most of these data sets were acquired in one to two days, opening new perspectives for HT-SMFS applications.

Small-molecule inhibitors of phosphatidylcholine transfer protein/StarD2 identified by high-throughput screening.

Science.gov (United States)

Wagle, Neil; Xian, Jun; Shishova, Ekaterina Y; Wei, Jie; Glicksman, Marcie A; Cuny, Gregory D; Stein, Ross L; Cohen, David E

2008-12-01

Phosphatidylcholine transfer protein (PC-TP, also referred to as StarD2) is a highly specific intracellular lipid-binding protein that catalyzes the transfer of phosphatidylcholines between membranes in vitro. Recent studies have suggested that PC-TP in vivo functions to regulate fatty acid and glucose metabolism, possibly via interactions with selected other proteins. To begin to address the relationship between activity in vitro and biological function, we undertook a high-throughput screen to identify small-molecule inhibitors of the phosphatidylcholine transfer activity of PC-TP. After adapting a fluorescence quench assay to measure phosphatidylcholine transfer activity, we screened 114,752 compounds of a small-molecule library. The high-throughput screen identified 14 potential PC-TP inhibitors. Of these, 6 compounds exhibited characteristics consistent with specific inhibition of PC-TP activity, with IC(50) values that ranged from 4.1 to 95.0muM under conditions of the in vitro assay. These compounds should serve as valuable reagents to elucidate the biological function of PC-TP. Because mice with homozygous disruption of the PC-TP gene (Pctp) are sensitized to insulin action and relatively resistant to the development of atherosclerosis, these inhibitors may also prove to be of value in the management of diabetes and atherosclerotic cardiovascular diseases.

GPCR-Bench: A Benchmarking Set and Practitioners' Guide for G Protein-Coupled Receptor Docking.

Science.gov (United States)

Weiss, Dahlia R; Bortolato, Andrea; Tehan, Benjamin; Mason, Jonathan S

2016-04-25

Virtual screening is routinely used to discover new ligands and in particular new ligand chemotypes for G protein-coupled receptors (GPCRs). To prepare for a virtual screen, we often tailor a docking protocol that will enable us to select the best candidates for further screening. To aid this, we created GPCR-Bench, a publically available docking benchmarking set in the spirit of the DUD and DUD-E reference data sets for validation studies, containing 25 nonredundant high-resolution GPCR costructures with an accompanying set of diverse ligands and computational decoy molecules for each target. Benchmarking sets are often used to compare docking protocols; however, it is important to evaluate docking methods not by "retrospective" hit rates but by the actual likelihood that they will produce novel prospective hits. Therefore, docking protocols must not only rank active molecules highly but also produce good poses that a chemist will select for purchase and screening. Currently, no simple objective machine-scriptable function exists that can do this; instead, docking hit lists must be subjectively examined in a consistent way to compare between docking methods. We present here a case study highlighting considerations we feel are of importance when evaluating a method, intended to be useful as a practitioners' guide.

Dockomatic - automated ligand creation and docking.

Science.gov (United States)

Bullock, Casey W; Jacob, Reed B; McDougal, Owen M; Hampikian, Greg; Andersen, Tim

2010-11-08

The application of computational modeling to rationally design drugs and characterize macro biomolecular receptors has proven increasingly useful due to the accessibility of computing clusters and clouds. AutoDock is a well-known and powerful software program used to model ligand to receptor binding interactions. In its current version, AutoDock requires significant amounts of user time to setup and run jobs, and collect results. This paper presents DockoMatic, a user friendly Graphical User Interface (GUI) application that eases and automates the creation and management of AutoDock jobs for high throughput screening of ligand to receptor interactions. DockoMatic allows the user to invoke and manage AutoDock jobs on a single computer or cluster, including jobs for evaluating secondary ligand interactions. It also automates the process of collecting, summarizing, and viewing results. In addition, DockoMatic automates creation of peptide ligand .pdb files from strings of single-letter amino acid abbreviations. DockoMatic significantly reduces the complexity of managing multiple AutoDock jobs by facilitating ligand and AutoDock job creation and management.

Dockomatic - automated ligand creation and docking

Directory of Open Access Journals (Sweden)

Hampikian Greg

2010-11-01

Full Text Available Abstract Background The application of computational modeling to rationally design drugs and characterize macro biomolecular receptors has proven increasingly useful due to the accessibility of computing clusters and clouds. AutoDock is a well-known and powerful software program used to model ligand to receptor binding interactions. In its current version, AutoDock requires significant amounts of user time to setup and run jobs, and collect results. This paper presents DockoMatic, a user friendly Graphical User Interface (GUI application that eases and automates the creation and management of AutoDock jobs for high throughput screening of ligand to receptor interactions. Results DockoMatic allows the user to invoke and manage AutoDock jobs on a single computer or cluster, including jobs for evaluating secondary ligand interactions. It also automates the process of collecting, summarizing, and viewing results. In addition, DockoMatic automates creation of peptide ligand .pdb files from strings of single-letter amino acid abbreviations. Conclusions DockoMatic significantly reduces the complexity of managing multiple AutoDock jobs by facilitating ligand and AutoDock job creation and management.

The Stanford Automated Mounter: Enabling High-Throughput Protein Crystal Screening at SSRL

International Nuclear Information System (INIS)

Smith, C.A.; Cohen, A.E.

2009-01-01

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 screened 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.

Methods for efficient high-throughput screening of protein expression in recombinant Pichia pastoris strains.

Science.gov (United States)

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.

The protein crystallography beamline BW6 at DORIS - automatic operation and high-throughput data collection

CERN Document Server

Blume, H; Bourenkov, G P; Kosciesza, D; Bartunik, H D

2001-01-01

The wiggler beamline BW6 at DORIS has been optimized for de-novo solution of protein structures on the basis of MAD phasing. Facilities for automatic data collection, rapid data transfer and storage, and online processing have been developed which provide adequate conditions for high-throughput applications, e.g., in structural genomics.

Structure and Sequence Search on Aptamer-Protein Docking

Science.gov (United States)

Xiao, Jiajie; Bonin, Keith; Guthold, Martin; Salsbury, Freddie

2015-03-01

Interactions between proteins and deoxyribonucleic acid (DNA) play a significant role in the living systems, especially through gene regulation. However, short nucleic acids sequences (aptamers) with specific binding affinity to specific proteins exhibit clinical potential as therapeutics. Our capillary and gel electrophoresis selection experiments show that specific sequences of aptamers can be selected that bind specific proteins. Computationally, given the experimentally-determined structure and sequence of a thrombin-binding aptamer, we can successfully dock the aptamer onto thrombin in agreement with experimental structures of the complex. In order to further study the conformational flexibility of this thrombin-binding aptamer and to potentially develop a predictive computational model of aptamer-binding, we use GPU-enabled molecular dynamics simulations to both examine the conformational flexibility of the aptamer in the absence of binding to thrombin, and to determine our ability to fold an aptamer. This study should help further de-novo predictions of aptamer sequences by enabling the study of structural and sequence-dependent effects on aptamer-protein docking specificity.

MM-ISMSA: An Ultrafast and Accurate Scoring Function for Protein-Protein Docking.

Science.gov (United States)

Klett, Javier; Núñez-Salgado, Alfonso; Dos Santos, Helena G; Cortés-Cabrera, Álvaro; Perona, Almudena; Gil-Redondo, Rubén; Abia, David; Gago, Federico; Morreale, Antonio

2012-09-11

An ultrafast and accurate scoring function for protein-protein docking is presented. It includes (1) a molecular mechanics (MM) part based on a 12-6 Lennard-Jones potential; (2) an electrostatic component based on an implicit solvent model (ISM) with individual desolvation penalties for each partner in the protein-protein complex plus a hydrogen bonding term; and (3) a surface area (SA) contribution to account for the loss of water contacts upon protein-protein complex formation. The accuracy and performance of the scoring function, termed MM-ISMSA, have been assessed by (1) comparing the total binding energies, the electrostatic term, and its components (charge-charge and individual desolvation energies), as well as the per residue contributions, to results obtained with well-established methods such as APBSA or MM-PB(GB)SA for a set of 1242 decoy protein-protein complexes and (2) testing its ability to recognize the docking solution closest to the experimental structure as that providing the most favorable total binding energy. For this purpose, a test set consisting of 15 protein-protein complexes with known 3D structure mixed with 10 decoys for each complex was used. The correlation between the values afforded by MM-ISMSA and those from the other methods is quite remarkable (r(2) ∼ 0.9), and only 0.2-5.0 s (depending on the number of residues) are spent on a single calculation including an all vs all pairwise energy decomposition. On the other hand, MM-ISMSA correctly identifies the best docking solution as that closest to the experimental structure in 80% of the cases. Finally, MM-ISMSA can process molecular dynamics trajectories and reports the results as averaged values with their standard deviations. MM-ISMSA has been implemented as a plugin to the widely used molecular graphics program PyMOL, although it can also be executed in command-line mode. MM-ISMSA is distributed free of charge to nonprofit organizations.

Parallel Evolutionary Optimization Algorithms for Peptide-Protein Docking

Science.gov (United States)

Poluyan, Sergey; Ershov, Nikolay

2018-02-01

In this study we examine the possibility of using evolutionary optimization algorithms in protein-peptide docking. We present the main assumptions that reduce the docking problem to a continuous global optimization problem and provide a way of using evolutionary optimization algorithms. The Rosetta all-atom force field was used for structural representation and energy scoring. We describe the parallelization scheme and MPI/OpenMP realization of the considered algorithms. We demonstrate the efficiency and the performance for some algorithms which were applied to a set of benchmark tests.

A modified FASP protocol for high-throughput preparation of protein samples for mass spectrometry.

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Jeremy Potriquet

Full Text Available To facilitate high-throughput proteomic analyses we have developed a modified FASP protocol which improves the rate at which protein samples can be processed prior to mass spectrometry. Adapting the original FASP protocol to a 96-well format necessitates extended spin times for buffer exchange due to the low centrifugation speeds tolerated by these devices. However, by using 96-well plates with a more robust polyethersulfone molecular weight cutoff membrane, instead of the cellulose membranes typically used in these devices, we could use isopropanol as a wetting agent, decreasing spin times required for buffer exchange from an hour to 30 minutes. In a typical work flow used in our laboratory this equates to a reduction of 3 hours per plate, providing processing times similar to FASP for the processing of up to 96 samples per plate. To test whether our modified protocol produced similar results to FASP and other FASP-like protocols we compared the performance of our modified protocol to the original FASP and the more recently described eFASP and MStern-blot. We show that all FASP-like methods, including our modified protocol, display similar performance in terms of proteins identified and reproducibility. Our results show that our modified FASP protocol is an efficient method for the high-throughput processing of protein samples for mass spectral analysis.

Enabling systematic interrogation of protein-protein interactions in live cells with a versatile ultra-high-throughput biosensor platform | Office of Cancer Genomics

Science.gov (United States)

The vast datasets generated by next generation gene sequencing and expression profiling have transformed biological and translational research. However, technologies to produce large-scale functional genomics datasets, such as high-throughput detection of protein-protein interactions (PPIs), are still in early development. While a number of powerful technologies have been employed to detect PPIs, a singular PPI biosensor platform featured with both high sensitivity and robustness in a mammalian cell environment remains to be established.

Screening and Crystallization Plates for Manual and High-throughput Protein Crystal Growth

Science.gov (United States)

Thorne, Robert E. (Inventor); Berejnov, Viatcheslav (Inventor); Kalinin, Yevgeniy (Inventor)

2010-01-01

In one embodiment, a crystallization and screening plate comprises a plurality of cells open at a top and a bottom, a frame that defines the cells in the plate, and at least two films. The first film seals a top of the plate and the second film seals a bottom of the plate. At least one of the films is patterned to strongly pin the contact lines of drops dispensed onto it, fixing their position and shape. The present invention also includes methods and other devices for manual and high-throughput protein crystal growth.

High-throughput identification of off-targets for the mechanistic study of severe adverse drug reactions induced by analgesics

Energy Technology Data Exchange (ETDEWEB)

Pan, Jian-Bo [Department of Chemical Biology, College of Chemistry and Chemical Engineering, The Key Laboratory for Chemical Biology of Fujian Province, Xiamen University, Xiamen, Fujian 361005 (China); Ji, Nan; Pan, Wen; Hong, Ru [State Key Laboratory of Stress Cell Biology, School of Life Sciences, Xiamen University, Xiamen, Fujian 361102 (China); Wang, Hao [Department of Chemical Biology, College of Chemistry and Chemical Engineering, The Key Laboratory for Chemical Biology of Fujian Province, Xiamen University, Xiamen, Fujian 361005 (China); Ji, Zhi-Liang, E-mail: appo@xmu.edu.cn [State Key Laboratory of Stress Cell Biology, School of Life Sciences, Xiamen University, Xiamen, Fujian 361102 (China); Department of Chemical Biology, College of Chemistry and Chemical Engineering, The Key Laboratory for Chemical Biology of Fujian Province, Xiamen University, Xiamen, Fujian 361005 (China)

2014-01-01

Drugs may induce adverse drug reactions (ADRs) when they unexpectedly bind to proteins other than their therapeutic targets. Identification of these undesired protein binding partners, called off-targets, can facilitate toxicity assessment in the early stages of drug development. In this study, a computational framework was introduced for the exploration of idiosyncratic mechanisms underlying analgesic-induced severe adverse drug reactions (SADRs). The putative analgesic-target interactions were predicted by performing reverse docking of analgesics or their active metabolites against human/mammal protein structures in a high-throughput manner. Subsequently, bioinformatics analyses were undertaken to identify ADR-associated proteins (ADRAPs) and pathways. Using the pathways and ADRAPs that this analysis identified, the mechanisms of SADRs such as cardiac disorders were explored. For instance, 53 putative ADRAPs and 24 pathways were linked with cardiac disorders, of which 10 ADRAPs were confirmed by previous experiments. Moreover, it was inferred that pathways such as base excision repair, glycolysis/glyconeogenesis, ErbB signaling, calcium signaling, and phosphatidyl inositol signaling likely play pivotal roles in drug-induced cardiac disorders. In conclusion, our framework offers an opportunity to globally understand SADRs at the molecular level, which has been difficult to realize through experiments. It also provides some valuable clues for drug repurposing. - Highlights: • A novel computational framework was developed for mechanistic study of SADRs. • Off-targets of drugs were identified in large scale and in a high-throughput manner. • SADRs like cardiac disorders were systematically explored in molecular networks. • A number of ADR-associated proteins were identified.

High-throughput identification of off-targets for the mechanistic study of severe adverse drug reactions induced by analgesics

International Nuclear Information System (INIS)

Pan, Jian-Bo; Ji, Nan; Pan, Wen; Hong, Ru; Wang, Hao; Ji, Zhi-Liang

2014-01-01

Drugs may induce adverse drug reactions (ADRs) when they unexpectedly bind to proteins other than their therapeutic targets. Identification of these undesired protein binding partners, called off-targets, can facilitate toxicity assessment in the early stages of drug development. In this study, a computational framework was introduced for the exploration of idiosyncratic mechanisms underlying analgesic-induced severe adverse drug reactions (SADRs). The putative analgesic-target interactions were predicted by performing reverse docking of analgesics or their active metabolites against human/mammal protein structures in a high-throughput manner. Subsequently, bioinformatics analyses were undertaken to identify ADR-associated proteins (ADRAPs) and pathways. Using the pathways and ADRAPs that this analysis identified, the mechanisms of SADRs such as cardiac disorders were explored. For instance, 53 putative ADRAPs and 24 pathways were linked with cardiac disorders, of which 10 ADRAPs were confirmed by previous experiments. Moreover, it was inferred that pathways such as base excision repair, glycolysis/glyconeogenesis, ErbB signaling, calcium signaling, and phosphatidyl inositol signaling likely play pivotal roles in drug-induced cardiac disorders. In conclusion, our framework offers an opportunity to globally understand SADRs at the molecular level, which has been difficult to realize through experiments. It also provides some valuable clues for drug repurposing. - Highlights: • A novel computational framework was developed for mechanistic study of SADRs. • Off-targets of drugs were identified in large scale and in a high-throughput manner. • SADRs like cardiac disorders were systematically explored in molecular networks. • A number of ADR-associated proteins were identified

Evaluation of Docking Target Functions by the Comprehensive Investigation of Protein-Ligand Energy Minima.

Science.gov (United States)

Oferkin, Igor V; Katkova, Ekaterina V; Sulimov, Alexey V; Kutov, Danil C; Sobolev, Sergey I; Voevodin, Vladimir V; Sulimov, Vladimir B

2015-01-01

The adequate choice of the docking target function impacts the accuracy of the ligand positioning as well as the accuracy of the protein-ligand binding energy calculation. To evaluate a docking target function we compared positions of its minima with the experimentally known pose of the ligand in the protein active site. We evaluated five docking target functions based on either the MMFF94 force field or the PM7 quantum-chemical method with or without implicit solvent models: PCM, COSMO, and SGB. Each function was tested on the same set of 16 protein-ligand complexes. For exhaustive low-energy minima search the novel MPI parallelized docking program FLM and large supercomputer resources were used. Protein-ligand binding energies calculated using low-energy minima were compared with experimental values. It was demonstrated that the docking target function on the base of the MMFF94 force field in vacuo can be used for discovery of native or near native ligand positions by finding the low-energy local minima spectrum of the target function. The importance of solute-solvent interaction for the correct ligand positioning is demonstrated. It is shown that docking accuracy can be improved by replacement of the MMFF94 force field by the new semiempirical quantum-chemical PM7 method.

Evaluation of Docking Target Functions by the Comprehensive Investigation of Protein-Ligand Energy Minima

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Igor V. Oferkin

2015-01-01

Full Text Available The adequate choice of the docking target function impacts the accuracy of the ligand positioning as well as the accuracy of the protein-ligand binding energy calculation. To evaluate a docking target function we compared positions of its minima with the experimentally known pose of the ligand in the protein active site. We evaluated five docking target functions based on either the MMFF94 force field or the PM7 quantum-chemical method with or without implicit solvent models: PCM, COSMO, and SGB. Each function was tested on the same set of 16 protein-ligand complexes. For exhaustive low-energy minima search the novel MPI parallelized docking program FLM and large supercomputer resources were used. Protein-ligand binding energies calculated using low-energy minima were compared with experimental values. It was demonstrated that the docking target function on the base of the MMFF94 force field in vacuo can be used for discovery of native or near native ligand positions by finding the low-energy local minima spectrum of the target function. The importance of solute-solvent interaction for the correct ligand positioning is demonstrated. It is shown that docking accuracy can be improved by replacement of the MMFF94 force field by the new semiempirical quantum-chemical PM7 method.

Affinity selection-mass spectrometry and its emerging application to the high throughput screening of G protein-coupled receptors.

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Whitehurst, Charles E; Annis, D Allen

2008-07-01

Advances in combinatorial chemistry and genomics have inspired the development of novel affinity selection-based screening techniques that rely on mass spectrometry to identify compounds that preferentially bind to a protein target. Of the many affinity selection-mass spectrometry techniques so far documented, only a few solution-based implementations that separate target-ligand complexes away from unbound ligands persist today as routine high throughput screening platforms. Because affinity selection-mass spectrometry techniques do not rely on radioactive or fluorescent reporters or enzyme activities, they can complement traditional biochemical and cell-based screening assays and enable scientists to screen targets that may not be easily amenable to other methods. In addition, by employing mass spectrometry for ligand detection, these techniques enable high throughput screening of massive library collections of pooled compound mixtures, vastly increasing the chemical space that a target can encounter during screening. Of all drug targets, G protein coupled receptors yield the highest percentage of therapeutically effective drugs. In this manuscript, we present the emerging application of affinity selection-mass spectrometry to the high throughput screening of G protein coupled receptors. We also review how affinity selection-mass spectrometry can be used as an analytical tool to guide receptor purification, and further used after screening to characterize target-ligand binding interactions, enabling the classification of orthosteric and allosteric binders.

High-throughput Screening for Protein-based Inheritance in S. cerevisiae.

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Byers, James S; Jarosz, Daniel F

2017-08-08

The encoding of biological information that is accessible to future generations is generally achieved via changes to the DNA sequence. Long-lived inheritance encoded in protein conformation (rather than sequence) has long been viewed as paradigm-shifting but rare. The best characterized examples of such epigenetic elements are prions, which possess a self-assembling behavior that can drive the heritable manifestation of new phenotypes. Many archetypal prions display a striking N/Q-rich sequence bias and assemble into an amyloid fold. These unusual features have informed most screening efforts to identify new prion proteins. However, at least three known prions (including the founding prion, PrP Sc ) do not harbor these biochemical characteristics. We therefore developed an alternative method to probe the scope of protein-based inheritance based on a property of mass action: the transient overexpression of prion proteins increases the frequency at which they acquire a self-templating conformation. This paper describes a method for analyzing the capacity of the yeast ORFeome to elicit protein-based inheritance. Using this strategy, we previously found that >1% of yeast proteins could fuel the emergence of biological traits that were long-lived, stable, and arose more frequently than genetic mutation. This approach can be employed in high throughput across entire ORFeomes or as a targeted screening paradigm for specific genetic networks or environmental stimuli. Just as forward genetic screens define numerous developmental and signaling pathways, these techniques provide a methodology to investigate the influence of protein-based inheritance in biological processes.

IFACEwat: the interfacial water-implemented re-ranking algorithm to improve the discrimination of near native structures for protein rigid docking.

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Su, Chinh; Nguyen, Thuy-Diem; Zheng, Jie; Kwoh, Chee-Keong

2014-01-01

Protein-protein docking is an in silico method to predict the formation of protein complexes. Due to limited computational resources, the protein-protein docking approach has been developed under the assumption of rigid docking, in which one of the two protein partners remains rigid during the protein associations and water contribution is ignored or implicitly presented. Despite obtaining a number of acceptable complex predictions, it seems to-date that most initial rigid docking algorithms still find it difficult or even fail to discriminate successfully the correct predictions from the other incorrect or false positive ones. To improve the rigid docking results, re-ranking is one of the effective methods that help re-locate the correct predictions in top high ranks, discriminating them from the other incorrect ones. Our results showed that the IFACEwat increased both the numbers of the near-native structures and improved their ranks as compared to the initial rigid docking ZDOCK3.0.2. In fact, the IFACEwat achieved a success rate of 83.8% for Antigen/Antibody complexes, which is 10% better than ZDOCK3.0.2. As compared to another re-ranking technique ZRANK, the IFACEwat obtains success rates of 92.3% (8% better) and 90% (5% better) respectively for medium and difficult cases. When comparing with the latest published re-ranking method F2Dock, the IFACEwat performed equivalently well or even better for several Antigen/Antibody complexes. With the inclusion of interfacial water, the IFACEwat improves mostly results of the initial rigid docking, especially for Antigen/Antibody complexes. The improvement is achieved by explicitly taking into account the contribution of water during the protein interactions, which was ignored or not fully presented by the initial rigid docking and other re-ranking techniques. In addition, the IFACEwat maintains sufficient computational efficiency of the initial docking algorithm, yet improves the ranks as well as the number of the near

Designing coarse grained-and atom based-potentials for protein-protein docking

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Tobi Dror

2010-11-01

Full Text Available Abstract Background Protein-protein docking is a challenging computational problem in functional genomics, particularly when one or both proteins undergo conformational change(s upon binding. The major challenge is to define a scoring function soft enough to tolerate these changes and specific enough to distinguish between near-native and "misdocked" conformations. Results Using a linear programming (LP technique, we developed two types of potentials: (i Side chain-based and (ii Heavy atom-based. To achieve this we considered a set of 161 transient complexes and generated a large set of putative docked structures (decoys, based on a shape complementarity criterion, for each complex. The demand on the potentials was to yield, for the native (correctly docked structure, a potential energy lower than those of any of the non-native (misdocked structures. We show that the heavy atom-based potentials were able to comply with this requirement but not the side chain-based one. Thus, despite the smaller number of parameters, the capability of heavy atom-based potentials to discriminate between native and "misdocked" conformations is improved relative to those of the side chain-based potentials. The performance of the atom-based potentials was evaluated by a jackknife test on a set of 50 complexes taken from the Zdock2.3 decoys set. Conclusions Our results show that, using the LP approach, we were able to train our potentials using a dataset of transient complexes only the newly developed potentials outperform three other known potentials in this test.

HDOCK: a web server for protein–protein and protein–DNA/RNA docking based on a hybrid strategy

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Yan, Yumeng; Zhang, Di; Zhou, Pei; Li, Botong

2017-01-01

Abstract Protein–protein and protein–DNA/RNA interactions play a fundamental role in a variety of biological processes. Determining the complex structures of these interactions is valuable, in which molecular docking has played an important role. To automatically make use of the binding information from the PDB in docking, here we have presented HDOCK, a novel web server of our hybrid docking algorithm of template-based modeling and free docking, in which cases with misleading templates can be rescued by the free docking protocol. The server supports protein–protein and protein–DNA/RNA docking and accepts both sequence and structure inputs for proteins. The docking process is fast and consumes about 10–20 min for a docking run. Tested on the cases with weakly homologous complexes of server. The HDOCK web server is available at http://hdock.phys.hust.edu.cn/. PMID:28521030

A family of E. coli expression vectors for laboratory scale and high throughput soluble protein production

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Bottomley Stephen P

2006-03-01

Full Text Available Abstract Background In the past few years, both automated and manual high-throughput protein expression and purification has become an accessible means to rapidly screen and produce soluble proteins for structural and functional studies. However, many of the commercial vectors encoding different solubility tags require different cloning and purification steps for each vector, considerably slowing down expression screening. We have developed a set of E. coli expression vectors with different solubility tags that allow for parallel cloning from a single PCR product and can be purified using the same protocol. Results The set of E. coli expression vectors, encode for either a hexa-histidine tag or the three most commonly used solubility tags (GST, MBP, NusA and all with an N-terminal hexa-histidine sequence. The result is two-fold: the His-tag facilitates purification by immobilised metal affinity chromatography, whilst the fusion domains act primarily as solubility aids during expression, in addition to providing an optional purification step. We have also incorporated a TEV recognition sequence following the solubility tag domain, which allows for highly specific cleavage (using TEV protease of the fusion protein to yield native protein. These vectors are also designed for ligation-independent cloning and they possess a high-level expressing T7 promoter, which is suitable for auto-induction. To validate our vector system, we have cloned four different genes and also one gene into all four vectors and used small-scale expression and purification techniques. We demonstrate that the vectors are capable of high levels of expression and that efficient screening of new proteins can be readily achieved at the laboratory level. Conclusion The result is a set of four rationally designed vectors, which can be used for streamlined cloning, expression and purification of target proteins in the laboratory and have the potential for being adaptable to a high-throughput

Annotating Protein Functional Residues by Coupling High-Throughput Fitness Profile and Homologous-Structure Analysis.

Science.gov (United States)

Du, Yushen; Wu, Nicholas C; Jiang, Lin; Zhang, Tianhao; Gong, Danyang; Shu, Sara; Wu, Ting-Ting; Sun, Ren

2016-11-01

Identification and annotation of functional residues are fundamental questions in protein sequence analysis. Sequence and structure conservation provides valuable information to tackle these questions. It is, however, limited by the incomplete sampling of sequence space in natural evolution. Moreover, proteins often have multiple functions, with overlapping sequences that present challenges to accurate annotation of the exact functions of individual residues by conservation-based methods. Using the influenza A virus PB1 protein as an example, we developed a method to systematically identify and annotate functional residues. We used saturation mutagenesis and high-throughput sequencing to measure the replication capacity of single nucleotide mutations across the entire PB1 protein. After predicting protein stability upon mutations, we identified functional PB1 residues that are essential for viral replication. To further annotate the functional residues important to the canonical or noncanonical functions of viral RNA-dependent RNA polymerase (vRdRp), we performed a homologous-structure analysis with 16 different vRdRp structures. We achieved high sensitivity in annotating the known canonical polymerase functional residues. Moreover, we identified a cluster of noncanonical functional residues located in the loop region of the PB1 β-ribbon. We further demonstrated that these residues were important for PB1 protein nuclear import through the interaction with Ran-binding protein 5. In summary, we developed a systematic and sensitive method to identify and annotate functional residues that are not restrained by sequence conservation. Importantly, this method is generally applicable to other proteins about which homologous-structure information is available. To fully comprehend the diverse functions of a protein, it is essential to understand the functionality of individual residues. Current methods are highly dependent on evolutionary sequence conservation, which is

Gab Docking Proteins in Cardiovascular Disease, Cancer, and Inflammation

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Yoshikazu Nakaoka

2013-01-01

Full Text Available The docking proteins of the Grb2-associated binder (Gab family have emerged as crucial signaling compartments in metazoans. In mammals, the Gab proteins, consisting of Gab1, Gab2, and Gab3, are involved in the amplification and integration of signal transduction evoked by a variety of extracellular stimuli, including growth factors, cytokines, antigens, and other molecules. Gab proteins lack the enzymatic activity themselves; however, when phosphorylated on tyrosine residues, they provide binding sites for multiple Src homology-2 (SH2 domain-containing proteins, such as SH2-containing protein tyrosine phosphatase 2 (SHP2, phosphatidylinositol 3-kinase regulatory subunit p85, phospholipase Cγ, Crk, and GC-GAP. Through these interactions, the Gab proteins transduce signals from activated receptors into pathways with distinct biological functions, thereby contributing to signal diversification. They are known to play crucial roles in numerous physiological processes through their associations with SHP2 and p85. In addition, abnormal Gab protein signaling has been linked to human diseases including cancer, cardiovascular disease, and inflammatory disorders. In this paper, we provide an overview of the structure, effector functions, and regulation of the Gab docking proteins, with a special focus on their associations with cardiovascular disease, cancer, and inflammation.

High-Throughput Cloning and Expression Library Creation for Functional Proteomics

Science.gov (United States)

Festa, Fernanda; Steel, Jason; Bian, Xiaofang; Labaer, Joshua

2013-01-01

The study of protein function usually requires the use of a cloned version of the gene for protein expression and functional assays. This strategy is particular important when the information available regarding function is limited. The functional characterization of the thousands of newly identified proteins revealed by genomics requires faster methods than traditional single gene experiments, creating the need for fast, flexible and reliable cloning systems. These collections of open reading frame (ORF) clones can be coupled with high-throughput proteomics platforms, such as protein microarrays and cell-based assays, to answer biological questions. In this tutorial we provide the background for DNA cloning, discuss the major high-throughput cloning systems (Gateway® Technology, Flexi® Vector Systems, and Creator™ DNA Cloning System) and compare them side-by-side. We also report an example of high-throughput cloning study and its application in functional proteomics. This Tutorial is part of the International Proteomics Tutorial Programme (IPTP12). Details can be found at http://www.proteomicstutorials.org. PMID:23457047

Adverse drug reaction prediction using scores produced by large-scale drug-protein target docking on high-performance computing machines.

Science.gov (United States)

LaBute, Montiago X; Zhang, Xiaohua; Lenderman, Jason; Bennion, Brian J; Wong, Sergio E; Lightstone, Felice C

2014-01-01

Late-stage or post-market identification of adverse drug reactions (ADRs) is a significant public health issue and a source of major economic liability for drug development. Thus, reliable in silico screening of drug candidates for possible ADRs would be advantageous. In this work, we introduce a computational approach that predicts ADRs by combining the results of molecular docking and leverages known ADR information from DrugBank and SIDER. We employed a recently parallelized version of AutoDock Vina (VinaLC) to dock 906 small molecule drugs to a virtual panel of 409 DrugBank protein targets. L1-regularized logistic regression models were trained on the resulting docking scores of a 560 compound subset from the initial 906 compounds to predict 85 side effects, grouped into 10 ADR phenotype groups. Only 21% (87 out of 409) of the drug-protein binding features involve known targets of the drug subset, providing a significant probe of off-target effects. As a control, associations of this drug subset with the 555 annotated targets of these compounds, as reported in DrugBank, were used as features to train a separate group of models. The Vina off-target models and the DrugBank on-target models yielded comparable median area-under-the-receiver-operating-characteristic-curves (AUCs) during 10-fold cross-validation (0.60-0.69 and 0.61-0.74, respectively). Evidence was found in the PubMed literature to support several putative ADR-protein associations identified by our analysis. Among them, several associations between neoplasm-related ADRs and known tumor suppressor and tumor invasiveness marker proteins were found. A dual role for interstitial collagenase in both neoplasms and aneurysm formation was also identified. These associations all involve off-target proteins and could not have been found using available drug/on-target interaction data. This study illustrates a path forward to comprehensive ADR virtual screening that can potentially scale with increasing number

Adverse drug reaction prediction using scores produced by large-scale drug-protein target docking on high-performance computing machines.

Directory of Open Access Journals (Sweden)

Montiago X LaBute

Full Text Available Late-stage or post-market identification of adverse drug reactions (ADRs is a significant public health issue and a source of major economic liability for drug development. Thus, reliable in silico screening of drug candidates for possible ADRs would be advantageous. In this work, we introduce a computational approach that predicts ADRs by combining the results of molecular docking and leverages known ADR information from DrugBank and SIDER. We employed a recently parallelized version of AutoDock Vina (VinaLC to dock 906 small molecule drugs to a virtual panel of 409 DrugBank protein targets. L1-regularized logistic regression models were trained on the resulting docking scores of a 560 compound subset from the initial 906 compounds to predict 85 side effects, grouped into 10 ADR phenotype groups. Only 21% (87 out of 409 of the drug-protein binding features involve known targets of the drug subset, providing a significant probe of off-target effects. As a control, associations of this drug subset with the 555 annotated targets of these compounds, as reported in DrugBank, were used as features to train a separate group of models. The Vina off-target models and the DrugBank on-target models yielded comparable median area-under-the-receiver-operating-characteristic-curves (AUCs during 10-fold cross-validation (0.60-0.69 and 0.61-0.74, respectively. Evidence was found in the PubMed literature to support several putative ADR-protein associations identified by our analysis. Among them, several associations between neoplasm-related ADRs and known tumor suppressor and tumor invasiveness marker proteins were found. A dual role for interstitial collagenase in both neoplasms and aneurysm formation was also identified. These associations all involve off-target proteins and could not have been found using available drug/on-target interaction data. This study illustrates a path forward to comprehensive ADR virtual screening that can potentially scale with

Multiplexed homogeneous proximity ligation assays for high throughput protein biomarker research in serological material

DEFF Research Database (Denmark)

Lundberg, Martin; Thorsen, Stine Buch; Assarsson, Erika

2011-01-01

A high throughput protein biomarker discovery tool has been developed based on multiplexed proximity ligation assays (PLA) in a homogeneous format in the sense of no washing steps. The platform consists of four 24-plex panels profiling 74 putative biomarkers with sub pM sensitivity each consuming...... sequences are united by DNA ligation upon simultaneous target binding forming a PCR amplicon. Multiplex PLA thereby converts multiple target analytes into real-time PCR amplicons that are individually quantificatied using microfluidic high capacity qPCR in nano liter volumes. The assay shows excellent...

Acoustic transfer of protein crystals from agarose pedestals to micromeshes for high-throughput screening

International Nuclear Information System (INIS)

Cuttitta, Christina M.; Ericson, Daniel L.; Scalia, Alexander; Roessler, Christian G.; Teplitsky, Ella; Joshi, Karan; Campos, Olven; Agarwal, Rakhi; Allaire, Marc; Orville, Allen M.; Sweet, Robert M.; Soares, Alexei S.

2015-01-01

An acoustic high-throughput screening method is described for harvesting protein crystals and combining the protein crystals with chemicals such as a fragment library. Acoustic droplet ejection (ADE) is an emerging technology with broad applications in serial crystallography such as growing, improving and manipulating protein crystals. One application of this technology is to gently transfer crystals onto MiTeGen micromeshes with minimal solvent. Once mounted on a micromesh, each crystal can be combined with different chemicals such as crystal-improving additives or a fragment library. Acoustic crystal mounting is fast (2.33 transfers s −1 ) and all transfers occur in a sealed environment that is in vapor equilibrium with the mother liquor. Here, a system is presented to retain crystals near the ejection point and away from the inaccessible dead volume at the bottom of the well by placing the crystals on a concave agarose pedestal (CAP) with the same chemical composition as the crystal mother liquor. The bowl-shaped CAP is impenetrable to crystals. Consequently, gravity will gently move the crystals into the optimal location for acoustic ejection. It is demonstrated that an agarose pedestal of this type is compatible with most commercially available crystallization conditions and that protein crystals are readily transferred from the agarose pedestal onto micromeshes with no loss in diffraction quality. It is also shown that crystals can be grown directly on CAPs, which avoids the need to transfer the crystals from the hanging drop to a CAP. This technology has been used to combine thermolysin and lysozyme crystals with an assortment of anomalously scattering heavy atoms. The results point towards a fast nanolitre method for crystal mounting and high-throughput screening

AnchorDock: Blind and Flexible Anchor-Driven Peptide Docking.

Science.gov (United States)

Ben-Shimon, Avraham; Niv, Masha Y

2015-05-05

The huge conformational space stemming from the inherent flexibility of peptides is among the main obstacles to successful and efficient computational modeling of protein-peptide interactions. Current peptide docking methods typically overcome this challenge using prior knowledge from the structure of the complex. Here we introduce AnchorDock, a peptide docking approach, which automatically targets the docking search to the most relevant parts of the conformational space. This is done by precomputing the free peptide's structure and by computationally identifying anchoring spots on the protein surface. Next, a free peptide conformation undergoes anchor-driven simulated annealing molecular dynamics simulations around the predicted anchoring spots. In the challenging task of a completely blind docking test, AnchorDock produced exceptionally good results (backbone root-mean-square deviation ≤ 2.2Å, rank ≤15) for 10 of 13 unbound cases tested. The impressive performance of AnchorDock supports a molecular recognition pathway that is driven via pre-existing local structural elements. Copyright © 2015 Elsevier Ltd. All rights reserved.

Complete cDNA sequence coding for human docking protein

Energy Technology Data Exchange (ETDEWEB)

Hortsch, M; Labeit, S; Meyer, D I

1988-01-11

Docking protein (DP, or SRP receptor) is a rough endoplasmic reticulum (ER)-associated protein essential for the targeting and translocation of nascent polypeptides across this membrane. It specifically interacts with a cytoplasmic ribonucleoprotein complex, the signal recognition particle (SRP). The nucleotide sequence of cDNA encoding the entire human DP and its deduced amino acid sequence are given.

Computational and statistical methods for high-throughput analysis of post-translational modifications of proteins

DEFF Research Database (Denmark)

Schwämmle, Veit; Braga, Thiago Verano; Roepstorff, Peter

2015-01-01

The investigation of post-translational modifications (PTMs) represents one of the main research focuses for the study of protein function and cell signaling. Mass spectrometry instrumentation with increasing sensitivity improved protocols for PTM enrichment and recently established pipelines...... for high-throughput experiments allow large-scale identification and quantification of several PTM types. This review addresses the concurrently emerging challenges for the computational analysis of the resulting data and presents PTM-centered approaches for spectra identification, statistical analysis...

Ultra-High-Throughput Screening of Natural Product Extracts to Identify Proapoptotic Inhibitors of Bcl-2 Family Proteins.

Science.gov (United States)

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.

Fluorescent foci quantitation for high-throughput analysis

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Elena Ledesma-Fernández

2015-06-01

Full Text Available A number of cellular proteins localize to discrete foci within cells, for example DNA repair proteins, microtubule organizing centers, P bodies or kinetochores. It is often possible to measure the fluorescence emission from tagged proteins within these foci as a surrogate for the concentration of that specific protein. We wished to develop tools that would allow quantitation of fluorescence foci intensities in high-throughput studies. As proof of principle we have examined the kinetochore, a large multi-subunit complex that is critical for the accurate segregation of chromosomes during cell division. Kinetochore perturbations lead to aneuploidy, which is a hallmark of cancer cells. Hence, understanding kinetochore homeostasis and regulation are important for a global understanding of cell division and genome integrity. The 16 budding yeast kinetochores colocalize within the nucleus to form a single focus. Here we have created a set of freely-available tools to allow high-throughput quantitation of kinetochore foci fluorescence. We use this ‘FociQuant’ tool to compare methods of kinetochore quantitation and we show proof of principle that FociQuant can be used to identify changes in kinetochore protein levels in a mutant that affects kinetochore function. This analysis can be applied to any protein that forms discrete foci in cells.

DARC 2.0: Improved Docking and Virtual Screening at Protein Interaction Sites.

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Ragul Gowthaman

Full Text Available Over the past decade, protein-protein interactions have emerged as attractive but challenging targets for therapeutic intervention using small molecules. Due to the relatively flat surfaces that typify protein interaction sites, modern virtual screening tools developed for optimal performance against "traditional" protein targets perform less well when applied instead at protein interaction sites. Previously, we described a docking method specifically catered to the shallow binding modes characteristic of small-molecule inhibitors of protein interaction sites. This method, called DARC (Docking Approach using Ray Casting, operates by comparing the topography of the protein surface when "viewed" from a vantage point inside the protein against the topography of a bound ligand when "viewed" from the same vantage point. Here, we present five key enhancements to DARC. First, we use multiple vantage points to more accurately determine protein-ligand surface complementarity. Second, we describe a new scheme for rapidly determining optimal weights in the DARC scoring function. Third, we incorporate sampling of ligand conformers "on-the-fly" during docking. Fourth, we move beyond simple shape complementarity and introduce a term in the scoring function to capture electrostatic complementarity. Finally, we adjust the control flow in our GPU implementation of DARC to achieve greater speedup of these calculations. At each step of this study, we evaluate the performance of DARC in a "pose recapitulation" experiment: predicting the binding mode of 25 inhibitors each solved in complex with its distinct target protein (a protein interaction site. Whereas the previous version of DARC docked only one of these inhibitors to within 2 Å RMSD of its position in the crystal structure, the newer version achieves this level of accuracy for 12 of the 25 complexes, corresponding to a statistically significant performance improvement (p < 0.001. Collectively then, we find

Acoustic transfer of protein crystals from agarose pedestals to micromeshes for high-throughput screening

Energy Technology Data Exchange (ETDEWEB)

Cuttitta, Christina M. [Brookhaven National Laboratory, Upton, NY 11973-5000 (United States); The City University of New York, 2800 Victory Boulevard, Staten Island, NY 10314 (United States); Ericson, Daniel L. [Brookhaven National Laboratory, Upton, NY 11973-5000 (United States); University at Buffalo, SUNY, 12 Capen Hall, Buffalo, NY 14260 (United States); Scalia, Alexander [Brookhaven National Laboratory, Upton, NY 11973-5000 (United States); Binghamton University, 4400 Vestal Parkway East, Binghamton, NY 11973-5000 (United States); Roessler, Christian G. [Brookhaven National Laboratory, Upton, NY 11973-5000 (United States); Teplitsky, Ella [Brookhaven National Laboratory, Upton, NY 11973-5000 (United States); Stony Brook University, Stony Brook, NY 11794-5215 (United States); Joshi, Karan [Brookhaven National Laboratory, Upton, NY 11973-5000 (United States); PEC University of Technology, Chandigarh (India); Campos, Olven [Brookhaven National Laboratory, Upton, NY 11973-5000 (United States); Florida Atlantic University, 777 Glades Road, Boca Raton, FL 33414 (United States); Agarwal, Rakhi; Allaire, Marc [Brookhaven National Laboratory, Upton, NY 11973-5000 (United States); Orville, Allen M. [Brookhaven National Laboratory, Upton, NY 11973-5000 (United States); Brookhaven National Laboratory, Upton, NY 11973-5000 (United States); Sweet, Robert M.; Soares, Alexei S., E-mail: soares@bnl.gov [Brookhaven National Laboratory, Upton, NY 11973-5000 (United States)

2015-01-01

An acoustic high-throughput screening method is described for harvesting protein crystals and combining the protein crystals with chemicals such as a fragment library. Acoustic droplet ejection (ADE) is an emerging technology with broad applications in serial crystallography such as growing, improving and manipulating protein crystals. One application of this technology is to gently transfer crystals onto MiTeGen micromeshes with minimal solvent. Once mounted on a micromesh, each crystal can be combined with different chemicals such as crystal-improving additives or a fragment library. Acoustic crystal mounting is fast (2.33 transfers s{sup −1}) and all transfers occur in a sealed environment that is in vapor equilibrium with the mother liquor. Here, a system is presented to retain crystals near the ejection point and away from the inaccessible dead volume at the bottom of the well by placing the crystals on a concave agarose pedestal (CAP) with the same chemical composition as the crystal mother liquor. The bowl-shaped CAP is impenetrable to crystals. Consequently, gravity will gently move the crystals into the optimal location for acoustic ejection. It is demonstrated that an agarose pedestal of this type is compatible with most commercially available crystallization conditions and that protein crystals are readily transferred from the agarose pedestal onto micromeshes with no loss in diffraction quality. It is also shown that crystals can be grown directly on CAPs, which avoids the need to transfer the crystals from the hanging drop to a CAP. This technology has been used to combine thermolysin and lysozyme crystals with an assortment of anomalously scattering heavy atoms. The results point towards a fast nanolitre method for crystal mounting and high-throughput screening.

Non-invasive high throughput approach for protein hydrophobicity determination based on surface tension.

Science.gov (United States)

Amrhein, Sven; Bauer, Katharina Christin; Galm, Lara; Hubbuch, Jürgen

2015-12-01

The surface hydrophobicity of a protein is an important factor for its interactions in solution and thus the outcome of its production process. Yet most of the methods are not able to evaluate the influence of these hydrophobic interactions under natural conditions. In the present work we have established a high resolution stalagmometric method for surface tension determination on a liquid handling station, which can cope with accuracy as well as high throughput requirements. Surface tensions could be derived with a low sample consumption (800 μL) and a high reproducibility (content. The protein influence on the solutions' surface tension was correlated to the hydrophobicity of lysozyme, human lysozyme, BSA, and α-lactalbumin. Differences in proteins' hydrophobic character depending on pH and species could be resolved. Within this work we have developed a pH dependent hydrophobicity ranking, which was found to be in good agreement with literature. For the studied pH range of 3-9 lysozyme from chicken egg white was identified to be the most hydrophilic. α-lactalbumin at pH 3 exhibited the most pronounced hydrophobic character. The stalagmometric method occurred to outclass the widely used spectrophotometric method with bromophenol blue sodium salt as it gave reasonable results without restrictions on pH and protein species. © 2015 Wiley Periodicals, Inc.

Domain requirements for the Dock adapter protein in growth- cone signaling

OpenAIRE

Rao, Yong; Zipursky, S. Lawrence

1998-01-01

Tyrosine phosphorylation has been implicated in growth-cone guidance through genetic, biochemical, and pharmacological studies. Adapter proteins containing src homology 2 (SH2) domains and src homology 3 (SH3) domains provide a means of linking guidance signaling through phosphotyrosine to downstream effectors regulating growth-cone motility. The Drosophila adapter, Dreadlocks (Dock), the homolog of mammalian Nck containing three N-terminal SH3 domains and a single SH2 domain, is highly speci...

Prediction of homoprotein and heteroprotein complexes by protein docking and template-based modeling: A CASP-CAPRI experiment

KAUST Repository

Lensink, Marc F.; Velankar, Sameer; Kryshtafovych, Andriy; Huang, Shen-You; Schneidman-Duhovny, Dina; Sali, Andrej; Segura, Joan; Fernandez-Fuentes, Narcis; Viswanath, Shruthi; Elber, Ron; Grudinin, Sergei; Popov, Petr; Neveu, Emilie; Lee, Hasup; Baek, Minkyung; Park, Sangwoo; Heo, Lim; Rie Lee, Gyu; Seok, Chaok; Qin, Sanbo; Zhou, Huan-Xiang; Ritchie, David W.; Maigret, Bernard; Devignes, Marie-Dominique; Ghoorah, Anisah; Torchala, Mieczyslaw; Chaleil, Raphaë l A.G.; Bates, Paul A.; Ben-Zeev, Efrat; Eisenstein, Miriam; Negi, Surendra S.; Weng, Zhiping; Vreven, Thom; Pierce, Brian G.; Borrman, Tyler M.; Yu, Jinchao; Ochsenbein, Franç oise; Guerois, Raphaë l; Vangone, Anna; Rodrigues, Joã o P.G.L.M.; van Zundert, Gydo; Nellen, Mehdi; Xue, Li; Karaca, Ezgi; Melquiond, Adrien S.J.; Visscher, Koen; Kastritis, Panagiotis L.; Bonvin, Alexandre M.J.J.; Xu, Xianjin; Qiu, Liming; Yan, Chengfei; Li, Jilong; Ma, Zhiwei; Cheng, Jianlin; Zou, Xiaoqin; Shen, Yang; Peterson, Lenna X.; Kim, Hyung-Rae; Roy, Amit; Han, Xusi; Esquivel-Rodriguez, Juan; Kihara, Daisuke; Yu, Xiaofeng; Bruce, Neil J.; Fuller, Jonathan C.; Wade, Rebecca C.; Anishchenko, Ivan; Kundrotas, Petras J.; Vakser, Ilya A.; Imai, Kenichiro; Yamada, Kazunori; Oda, Toshiyuki; Nakamura, Tsukasa; Tomii, Kentaro; Pallara, Chiara; Romero-Durana, Miguel; Jimé nez-Garcí a, Brian; Moal, Iain H.; Fé rnandez-Recio, Juan; Joung, Jong Young; Kim, Jong Yun; Joo, Keehyoung; Lee, Jooyoung; Kozakov, Dima; Vajda, Sandor; Mottarella, Scott; Hall, David R.; Beglov, Dmitri; Mamonov, Artem; Xia, Bing; Bohnuud, Tanggis; Del Carpio, Carlos A.; Ichiishi, Eichiro; Marze, Nicholas; Kuroda, Daisuke; Roy Burman, Shourya S.; Gray, Jeffrey J.; Chermak, Edrisse; Cavallo, Luigi; Oliva, Romina; Tovchigrechko, Andrey; Wodak, Shoshana J.

2016-01-01

We present the results for CAPRI Round 30, the first joint CASP-CAPRI experiment, which brought together experts from the protein structure prediction and protein-protein docking communities. The Round comprised 25 targets from amongst those submitted for the CASP11 prediction experiment of 2014. The targets included mostly homodimers, a few homotetramers, and two heterodimers, and comprised protein chains that could readily be modeled using templates from the Protein Data Bank. On average 24 CAPRI groups and 7 CASP groups submitted docking predictions for each target, and 12 CAPRI groups per target participated in the CAPRI scoring experiment. In total more than 9500 models were assessed against the 3D structures of the corresponding target complexes. Results show that the prediction of homodimer assemblies by homology modeling techniques and docking calculations is quite successful for targets featuring large enough subunit interfaces to represent stable associations. Targets with ambiguous or inaccurate oligomeric state assignments, often featuring crystal contact-sized interfaces, represented a confounding factor. For those, a much poorer prediction performance was achieved, while nonetheless often providing helpful clues on the correct oligomeric state of the protein. The prediction performance was very poor for genuine tetrameric targets, where the inaccuracy of the homology-built subunit models and the smaller pair-wise interfaces severely limited the ability to derive the correct assembly mode. Our analysis also shows that docking procedures tend to perform better than standard homology modeling techniques and that highly accurate models of the protein components are not always required to identify their association modes with acceptable accuracy. © 2016 Wiley Periodicals, Inc.

Prediction of homoprotein and heteroprotein complexes by protein docking and template-based modeling: A CASP-CAPRI experiment

KAUST Repository

Lensink, Marc F.

2016-04-28

We present the results for CAPRI Round 30, the first joint CASP-CAPRI experiment, which brought together experts from the protein structure prediction and protein-protein docking communities. The Round comprised 25 targets from amongst those submitted for the CASP11 prediction experiment of 2014. The targets included mostly homodimers, a few homotetramers, and two heterodimers, and comprised protein chains that could readily be modeled using templates from the Protein Data Bank. On average 24 CAPRI groups and 7 CASP groups submitted docking predictions for each target, and 12 CAPRI groups per target participated in the CAPRI scoring experiment. In total more than 9500 models were assessed against the 3D structures of the corresponding target complexes. Results show that the prediction of homodimer assemblies by homology modeling techniques and docking calculations is quite successful for targets featuring large enough subunit interfaces to represent stable associations. Targets with ambiguous or inaccurate oligomeric state assignments, often featuring crystal contact-sized interfaces, represented a confounding factor. For those, a much poorer prediction performance was achieved, while nonetheless often providing helpful clues on the correct oligomeric state of the protein. The prediction performance was very poor for genuine tetrameric targets, where the inaccuracy of the homology-built subunit models and the smaller pair-wise interfaces severely limited the ability to derive the correct assembly mode. Our analysis also shows that docking procedures tend to perform better than standard homology modeling techniques and that highly accurate models of the protein components are not always required to identify their association modes with acceptable accuracy. © 2016 Wiley Periodicals, Inc.

The pepATTRACT web server for blind, large-scale peptide-protein docking.

Science.gov (United States)

de Vries, Sjoerd J; Rey, Julien; Schindler, Christina E M; Zacharias, Martin; Tuffery, Pierre

2017-07-03

Peptide-protein interactions are ubiquitous in the cell and form an important part of the interactome. Computational docking methods can complement experimental characterization of these complexes, but current protocols are not applicable on the proteome scale. pepATTRACT is a novel docking protocol that is fully blind, i.e. it does not require any information about the binding site. In various stages of its development, pepATTRACT has participated in CAPRI, making successful predictions for five out of seven protein-peptide targets. Its performance is similar or better than state-of-the-art local docking protocols that do require binding site information. Here we present a novel web server that carries out the rigid-body stage of pepATTRACT. On the peptiDB benchmark, the web server generates a correct model in the top 50 in 34% of the cases. Compared to the full pepATTRACT protocol, this leads to some loss of performance, but the computation time is reduced from ∼18 h to ∼10 min. Combined with the fact that it is fully blind, this makes the web server well-suited for large-scale in silico protein-peptide docking experiments. The rigid-body pepATTRACT server is freely available at http://bioserv.rpbs.univ-paris-diderot.fr/services/pepATTRACT. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Spatial Mapping of Protein Abundances in the Mouse Brain by Voxelation Integrated with High-Throughput Liquid Chromatography ? Mass Spectrometry

International Nuclear Information System (INIS)

Petyuk, Vladislav A.; Qian, Weijun; Chin, Mark H.; Wang, Haixing H.; Livesay, Eric A.; Monroe, Matthew E.; Adkins, Joshua N.; Jaitly, Navdeep; Anderson, David J.; Camp, David G.; Smith, Desmond J.; Smith, Richard D.

2007-01-01

Temporally and spatially resolved mapping of protein abundance patterns within the mammalian brain is of significant interest for understanding brain function and molecular etiologies of neurodegenerative diseases; however, such imaging efforts have been greatly challenged by complexity of the proteome, throughput and sensitivity of applied analytical methodologies, and accurate quantitation of protein abundances across the brain. Here, we describe a methodology for comprehensive spatial proteome mapping that addresses these challenges by employing voxelation integrated with automated microscale sample processing, high-throughput LC system coupled with high resolution Fourier transform ion cyclotron mass spectrometer and a ''universal'' stable isotope labeled reference sample approach for robust quantitation. We applied this methodology as a proof-of-concept trial for the analysis of protein distribution within a single coronal slice of a C57BL/6J mouse brain. For relative quantitation of the protein abundances across the slice, an 18O-isotopically labeled reference sample, derived from a whole control coronal slice from another mouse, was spiked into each voxel sample and stable isotopic intensity ratios were used to obtain measures of relative protein abundances. In total, we generated maps of protein abundance patterns for 1,028 proteins. The significant agreement of the protein distributions with previously reported data supports the validity of this methodology, which opens new opportunities for studying the spatial brain proteome and its dynamics during the course of disease progression and other important biological and associated health aspects in a discovery-driven fashion

Systematic Protein-Protein Docking and Molecular Dynamics Studies of HIV-1 gp120 and CD4: Insights for New Drug Development

Directory of Open Access Journals (Sweden)

M. Rizman-Idid

2011-12-01

Full Text Available Background and the purpose of the study: The interactions between HIV-1 gp120 and mutated CD4 proteins were investigated in order to identify a lead structure for therapy based on competitive blocking of the HIV binding receptor for human T-cells. Crystal structures of HIV gp120-CD4 complexes reveal a close interaction of the virus receptor with CD4 Phe43, which is embedded in a pocket of the virus protein.Methods: This study applies computer simulations to determine the best binding of amino acid 43 CD4 mutants to HIV gp120. Besides natural CD4, three mutants carrying alternate aromatic residues His, Trp and Tyr at position 43 were investigated. Several docking programs were applied on isolated proteins based on selected crystal structures of gp120-CD4 complexes, as well as a 5 ns molecular dynamics study on the protein complexes. The initial structures were minimized in Gromacs to avoid crystal packing effects, and then subjected to docking experiments using AutoDock4, FireDock, ClusPro and ZDock. In molecular dynamics, the Gibbs free binding energy was calculated for the gp120-CD4 complexes. The docking outputs were analyzed on energy within the respective docking software.Results and conclusion: Visualization and hydrogen bonding analysis were performed using the Swiss-PdbViewer. Strong binding to HIV gp120 can be achieved with an extended aromatic group (Trp. However, the sterical demand of the interaction affects the binding kinetics. In conclusion, a ligand for an efficient blocking of HIV gp120 should involve an extended but conformational flexible aromatic group, i.e. a biphenyl. A docking study on biphenylalanine-43 confirms this expectation

Salvage and storage of infectious disease protein targets in the SSGCID high-throughput crystallization pathway using microfluidics

International Nuclear Information System (INIS)

Christensen, Jeff; Gerdts, Cory J.; Clifton, Mathew C.; Stewart, Lance

2011-01-01

SSGCID protein crystals were salvaged and stored using the MPCS Plug Maker and CrystalCards when high-throughput traditional sitting-drop vapor diffusion initially failed. The MPCS Plug Maker is a microcapillary-based protein-crystallization system for generating diffraction-ready crystals from nanovolumes of protein. Crystallization screening using the Plug Maker was used as a salvage pathway for proteins that failed to crystallize during the initial observation period using the traditional sitting-drop vapor-diffusion method. Furthermore, the CrystalCards used to store the crystallization experiments set up by the Plug Maker are shown be a viable container for long-term storage of protein crystals without a discernable loss of diffraction quality with time. Use of the Plug Maker with SSGCID proteins is demonstrated to be an effective crystal-salvage and storage method

Towards ligand docking including explicit interface water molecules.

Directory of Open Access Journals (Sweden)

Gordon Lemmon

Full Text Available Small molecule docking predicts the interaction of a small molecule ligand with a protein at atomic-detail accuracy including position and conformation the ligand but also conformational changes of the protein upon ligand binding. While successful in the majority of cases, docking algorithms including RosettaLigand fail in some cases to predict the correct protein/ligand complex structure. In this study we show that simultaneous docking of explicit interface water molecules greatly improves Rosetta's ability to distinguish correct from incorrect ligand poses. This result holds true for both protein-centric water docking wherein waters are located relative to the protein binding site and ligand-centric water docking wherein waters move with the ligand during docking. Protein-centric docking is used to model 99 HIV-1 protease/protease inhibitor structures. We find protease inhibitor placement improving at a ratio of 9:1 when one critical interface water molecule is included in the docking simulation. Ligand-centric docking is applied to 341 structures from the CSAR benchmark of diverse protein/ligand complexes [1]. Across this diverse dataset we see up to 56% recovery of failed docking studies, when waters are included in the docking simulation.

DOVIS: A Tool for High-throughput Virtual Screening

National Research Council Canada - National Science Library

Jiang, Xiaohui; Kumar, Kamal; Wallqvist, Anders; Reifman, Jaques

2007-01-01

We developed a DOcking-based Virtual Screening (DO DOVIS) pipeline to predict how small molecules may interact with a given protein, so that we can rank a large database of molecules based on their predicted affinities to the protein...

Plasticity of the Binding Site of Renin: Optimized Selection of Protein Structures for Ensemble Docking.

Science.gov (United States)

Strecker, Claas; Meyer, Bernd

2018-05-02

Protein flexibility poses a major challenge to docking of potential ligands in that the binding site can adopt different shapes. Docking algorithms usually keep the protein rigid and only allow the ligand to be treated as flexible. However, a wrong assessment of the shape of the binding pocket can prevent a ligand from adapting a correct pose. Ensemble docking is a simple yet promising method to solve this problem: Ligands are docked into multiple structures, and the results are subsequently merged. Selection of protein structures is a significant factor for this approach. In this work we perform a comprehensive and comparative study evaluating the impact of structure selection on ensemble docking. We perform ensemble docking with several crystal structures and with structures derived from molecular dynamics simulations of renin, an attractive target for antihypertensive drugs. Here, 500 ns of MD simulations revealed binding site shapes not found in any available crystal structure. We evaluate the importance of structure selection for ensemble docking by comparing binding pose prediction, ability to rank actives above nonactives (screening utility), and scoring accuracy. As a result, for ensemble definition k-means clustering appears to be better suited than hierarchical clustering with average linkage. The best performing ensemble consists of four crystal structures and is able to reproduce the native ligand poses better than any individual crystal structure. Moreover this ensemble outperforms 88% of all individual crystal structures in terms of screening utility as well as scoring accuracy. Similarly, ensembles of MD-derived structures perform on average better than 75% of any individual crystal structure in terms of scoring accuracy at all inspected ensembles sizes.

Integrated Controlling System and Unified Database for High Throughput Protein Crystallography Experiments

International Nuclear Information System (INIS)

Gaponov, Yu.A.; Igarashi, N.; Hiraki, M.; Sasajima, K.; Matsugaki, N.; Suzuki, M.; Kosuge, T.; Wakatsuki, S.

2004-01-01

An integrated controlling system and a unified database for high throughput protein crystallography experiments have been developed. Main features of protein crystallography experiments (purification, crystallization, crystal harvesting, data collection, data processing) were integrated into the software under development. All information necessary to perform protein crystallography experiments is stored (except raw X-ray data that are stored in a central data server) in a MySQL relational database. The database contains four mutually linked hierarchical trees describing protein crystals, data collection of protein crystal and experimental data processing. A database editor was designed and developed. The editor supports basic database functions to view, create, modify and delete user records in the database. Two search engines were realized: direct search of necessary information in the database and object oriented search. The system is based on TCP/IP secure UNIX sockets with four predefined sending and receiving behaviors, which support communications between all connected servers and clients with remote control functions (creating and modifying data for experimental conditions, data acquisition, viewing experimental data, and performing data processing). Two secure login schemes were designed and developed: a direct method (using the developed Linux clients with secure connection) and an indirect method (using the secure SSL connection using secure X11 support from any operating system with X-terminal and SSH support). A part of the system has been implemented on a new MAD beam line, NW12, at the Photon Factory Advanced Ring for general user experiments

High-throughput peptide mass fingerprinting and protein macroarray analysis using chemical printing strategies

International Nuclear Information System (INIS)

Sloane, A.J.; Duff, J.L.; Hopwood, F.G.; Wilson, N.L.; Smith, P.E.; Hill, C.J.; Packer, N.H.; Williams, K.L.; Gooley, A.A.; Cole, R.A.; Cooley, P.W.; Wallace, D.B.

2001-01-01

We describe a 'chemical printer' that uses piezoelectric pulsing for rapid and accurate microdispensing of picolitre volumes of fluid for proteomic analysis of 'protein macroarrays'. Unlike positive transfer and pin transfer systems, our printer dispenses fluid in a non-contact process that ensures that the fluid source cannot be contaminated by substrate during a printing event. We demonstrate automated delivery of enzyme and matrix solutions for on-membrane protein digestion and subsequent peptide mass fingerprinting (pmf) analysis directly from the membrane surface using matrix-assisted laser-desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry (MS). This approach bypasses the more commonly used multi-step procedures, thereby permitting a more rapid procedure for protein identification. We also highlight the advantage of printing different chemistries onto an individual protein spot for multiple microscale analyses. This ability is particularly useful when detailed characterisation of rare and valuable sample is required. Using a combination of PNGase F and trypsin we have mapped sites of N-glycosylation using on-membrane digestion strategies. We also demonstrate the ability to print multiple serum samples in a micro-ELISA format and rapidly screen a protein macroarray of human blood plasma for pathogen-derived antigens. We anticipate that the 'chemical printer' will be a major component of proteomic platforms for high-throughput protein identification and characterisation with widespread applications in biomedical and diagnostic discovery

CT-docking patient stretcher

International Nuclear Information System (INIS)

Mirvis, S.E.; Owens, E.; Maslyn, J.; Rizutto, M.

1990-01-01

This paper assesses the use of a patient stretcher that directly docks to a CT scanner for acutely injured and/or critically ill patients. The stretcher permits performance of radiography and acts as a platform for critical care monitoring and patient support devices. During a 1-year period, the prototype CT-docking stretcher was used for 35 patients sustaining acute trauma and 25 patients from critical care units. Observations were elicited from physicians, nurses and technologists concerning the advantages or disadvantages of the docking stretcher. Advantages of the CT-docking stretcher included time saved in moving patients to the CT table from the admitting/emergency ward, transfer of critically ill patients onto the stretcher in the controlled environment of the intensive care unit rather than the CT suite, increasing CT throughput by direct docking of the patient stretcher to the CT scanner rather than manual transfer of complex support and monitoring devices with the patient, decreased risk associated with physical movement of patients with potentially unstable spinal injuries or unstable physiologic status, and decrease in potential for injury to medical personnel performing patient transfer

Rapid directed evolution of stabilized proteins with cellular high-throughput encapsulation solubilization and screening (CHESS).

Science.gov (United States)

Yong, K J; Scott, D J

2015-03-01

Directed evolution is a powerful method for engineering proteins towards user-defined goals and has been used to generate novel proteins for industrial processes, biological research and drug discovery. Typical directed evolution techniques include cellular display, phage display, ribosome display and water-in-oil compartmentalization, all of which physically link individual members of diverse gene libraries to their translated proteins. This allows the screening or selection for a desired protein function and subsequent isolation of the encoding gene from diverse populations. For biotechnological and industrial applications there is a need to engineer proteins that are functional under conditions that are not compatible with these techniques, such as high temperatures and harsh detergents. Cellular High-throughput Encapsulation Solubilization and Screening (CHESS), is a directed evolution method originally developed to engineer detergent-stable G proteins-coupled receptors (GPCRs) for structural biology. With CHESS, library-transformed bacterial cells are encapsulated in detergent-resistant polymers to form capsules, which serve to contain mutant genes and their encoded proteins upon detergent mediated solubilization of cell membranes. Populations of capsules can be screened like single cells to enable rapid isolation of genes encoding detergent-stable protein mutants. To demonstrate the general applicability of CHESS to other proteins, we have characterized the stability and permeability of CHESS microcapsules and employed CHESS to generate thermostable, sodium dodecyl sulfate (SDS) resistant green fluorescent protein (GFP) mutants, the first soluble proteins to be engineered using CHESS. © 2014 Wiley Periodicals, Inc.

The JCSG high-throughput structural biology pipeline

International Nuclear Information System (INIS)

Elsliger, Marc-André; Deacon, Ashley M.; Godzik, Adam; Lesley, Scott A.; Wooley, John; Wüthrich, Kurt; Wilson, Ian A.

2010-01-01

The Joint Center for Structural Genomics high-throughput structural biology pipeline has delivered more than 1000 structures to the community over the past ten years and has made a significant contribution to the overall goal of the NIH Protein Structure Initiative (PSI) of expanding structural coverage of the protein universe. The Joint Center for Structural Genomics high-throughput structural biology pipeline has delivered more than 1000 structures to the community over the past ten years. The JCSG has made a significant contribution to the overall goal of the NIH Protein Structure Initiative (PSI) of expanding structural coverage of the protein universe, as well as making substantial inroads into structural coverage of an entire organism. Targets are processed through an extensive combination of bioinformatics and biophysical analyses to efficiently characterize and optimize each target prior to selection for structure determination. The pipeline uses parallel processing methods at almost every step in the process and can adapt to a wide range of protein targets from bacterial to human. The construction, expansion and optimization of the JCSG gene-to-structure pipeline over the years have resulted in many technological and methodological advances and developments. The vast number of targets and the enormous amounts of associated data processed through the multiple stages of the experimental pipeline required the development of variety of valuable resources that, wherever feasible, have been converted to free-access web-based tools and applications

NPPD: A Protein-Protein Docking Scoring Function Based on Dyadic Differences in Networks of Hydrophobic and Hydrophilic Amino Acid Residues

Directory of Open Access Journals (Sweden)

Edward S. C. Shih

2015-03-01

Full Text Available Protein-protein docking (PPD predictions usually rely on the use of a scoring function to rank docking models generated by exhaustive sampling. To rank good models higher than bad ones, a large number of scoring functions have been developed and evaluated, but the methods used for the computation of PPD predictions remain largely unsatisfactory. Here, we report a network-based PPD scoring function, the NPPD, in which the network consists of two types of network nodes, one for hydrophobic and the other for hydrophilic amino acid residues, and the nodes are connected when the residues they represent are within a certain contact distance. We showed that network parameters that compute dyadic interactions and those that compute heterophilic interactions of the amino acid networks thus constructed allowed NPPD to perform well in a benchmark evaluation of 115 PPD scoring functions, most of which, unlike NPPD, are based on some sort of protein-protein interaction energy. We also showed that NPPD was highly complementary to these energy-based scoring functions, suggesting that the combined use of conventional scoring functions and NPPD might significantly improve the accuracy of current PPD predictions.

Annotating Protein Functional Residues by Coupling High-Throughput Fitness Profile and Homologous-Structure Analysis

Directory of Open Access Journals (Sweden)

Yushen Du

2016-11-01

Full Text Available Identification and annotation of functional residues are fundamental questions in protein sequence analysis. Sequence and structure conservation provides valuable information to tackle these questions. It is, however, limited by the incomplete sampling of sequence space in natural evolution. Moreover, proteins often have multiple functions, with overlapping sequences that present challenges to accurate annotation of the exact functions of individual residues by conservation-based methods. Using the influenza A virus PB1 protein as an example, we developed a method to systematically identify and annotate functional residues. We used saturation mutagenesis and high-throughput sequencing to measure the replication capacity of single nucleotide mutations across the entire PB1 protein. After predicting protein stability upon mutations, we identified functional PB1 residues that are essential for viral replication. To further annotate the functional residues important to the canonical or noncanonical functions of viral RNA-dependent RNA polymerase (vRdRp, we performed a homologous-structure analysis with 16 different vRdRp structures. We achieved high sensitivity in annotating the known canonical polymerase functional residues. Moreover, we identified a cluster of noncanonical functional residues located in the loop region of the PB1 β-ribbon. We further demonstrated that these residues were important for PB1 protein nuclear import through the interaction with Ran-binding protein 5. In summary, we developed a systematic and sensitive method to identify and annotate functional residues that are not restrained by sequence conservation. Importantly, this method is generally applicable to other proteins about which homologous-structure information is available.

Identification of new 2,5-diketopiperazine derivatives as simultaneous effective inhibitors of αβ-tubulin and BCRP proteins: Molecular docking, Structure-Activity Relationships and virtual consensus docking studies

Science.gov (United States)

Fani, Najmeh; Sattarinezhad, Elham; Bordbar, Abdol-Khalegh

2017-06-01

In the first part of this paper, docking method was employed in order to study the binding mechanism of breast cancer resistance protein (BCRP) with a group of previously synthesized TPS-A derivatives which known as potent inhibitors of this protein to get insight into drug binding site of BCRP and to explore structure-activity relationship of these compounds. Molecular docking results showed that most of these compounds bind in the binding site of BCRP at the interface between the membrane and outer environment. In the second part, a group of designed TPS-A derivatives which showed good binding energies in the binding site of αβ-tubulin in the previous study were chosen to study their binding energies in the binding site of BCRP to investigate their simultaneous inhibitory effect on both αβ-tubulin and BCRP. The results showed that all of these compounds bind to the binding site of BCRP with relatively suitable binding energies and therefore could be potential inhibitors of both αβ-tubulin and BCRP proteins. Finally, virtual consensus docking method was utilized with the aim of design of new 2,5-diketopiperazine derivatives with significant inhibitory effect on both αβ-tubulin and BCRP proteins. For this purpose binding energies of a library of 2,5-diketopiperazine derivatives in the binding sites of αβ-tubulin and BCRP was investigated by using AutoDock and AutoDock vina tools. Molecular docking results revealed that a group of 36 compounds among them exhibit strong anti-tubulin and anti-BCRP activity.

Scoring functions for protein-protein interactions.

Science.gov (United States)

Moal, Iain H; Moretti, Rocco; Baker, David; Fernández-Recio, Juan

2013-12-01

The computational evaluation of protein-protein interactions will play an important role in organising the wealth of data being generated by high-throughput initiatives. Here we discuss future applications, report recent developments and identify areas requiring further investigation. Many functions have been developed to quantify the structural and energetic properties of interacting proteins, finding use in interrelated challenges revolving around the relationship between sequence, structure and binding free energy. These include loop modelling, side-chain refinement, docking, multimer assembly, affinity prediction, affinity change upon mutation, hotspots location and interface design. Information derived from models optimised for one of these challenges can be used to benefit the others, and can be unified within the theoretical frameworks of multi-task learning and Pareto-optimal multi-objective learning. Copyright © 2013 Elsevier Ltd. All rights reserved.

Solvated protein-protein docking using Kyte-Doolittle-based water preferences

NARCIS (Netherlands)

Kastritis, P.; Visscher, K.M.; van Dijk, A.D.J.; Bonvin, A.M.J.J.

2013-01-01

HADDOCK is one of the few docking programs that can explicitly account for water molecules in the docking process. Its solvated docking protocol starts from hydrated molecules and a fraction of the resulting interfacial waters is subsequently removed in a biased Monte Carlo procedure based on

Solvated protein-protein docking using Kyte-Doolittle-based water preferences

NARCIS (Netherlands)

Kastritis, Panagiotis L.; Visscher, Koen M.; van Dijk, Aalt D.J.; Bonvin, Alexandre M.J.J.

HADDOCK is one of the few docking programs that can explicitly account for water molecules in the docking process. Its solvated docking protocol starts from hydrated molecules and a fraction of the resulting interfacial waters is subsequently removed in a biased Monte Carlo procedure based on

An Automated High Throughput Proteolysis and Desalting Platform for Quantitative Proteomic Analysis

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Albert-Baskar Arul

2013-06-01

Full Text Available Proteomics for biomarker validation needs high throughput instrumentation to analyze huge set of clinical samples for quantitative and reproducible analysis at a minimum time without manual experimental errors. Sample preparation, a vital step in proteomics plays a major role in identification and quantification of proteins from biological samples. Tryptic digestion a major check point in sample preparation for mass spectrometry based proteomics needs to be more accurate with rapid processing time. The present study focuses on establishing a high throughput automated online system for proteolytic digestion and desalting of proteins from biological samples quantitatively and qualitatively in a reproducible manner. The present study compares online protein digestion and desalting of BSA with conventional off-line (in-solution method and validated for real time sample for reproducibility. Proteins were identified using SEQUEST data base search engine and the data were quantified using IDEALQ software. The present study shows that the online system capable of handling high throughput samples in 96 well formats carries out protein digestion and peptide desalting efficiently in a reproducible and quantitative manner. Label free quantification showed clear increase of peptide quantities with increase in concentration with much linearity compared to off line method. Hence we would like to suggest that inclusion of this online system in proteomic pipeline will be effective in quantification of proteins in comparative proteomics were the quantification is really very crucial.

Reduced dimensionality (3,2)D NMR experiments and their automated analysis: implications to high-throughput structural studies on proteins.

Science.gov (United States)

Reddy, Jithender G; Kumar, Dinesh; Hosur, Ramakrishna V

2015-02-01

Protein NMR spectroscopy has expanded dramatically over the last decade into a powerful tool for the study of their structure, dynamics, and interactions. The primary requirement for all such investigations is sequence-specific resonance assignment. The demand now is to obtain this information as rapidly as possible and in all types of protein systems, stable/unstable, soluble/insoluble, small/big, structured/unstructured, and so on. In this context, we introduce here two reduced dimensionality experiments – (3,2)D-hNCOcanH and (3,2)D-hNcoCAnH – which enhance the previously described 2D NMR-based assignment methods quite significantly. Both the experiments can be recorded in just about 2-3 h each and hence would be of immense value for high-throughput structural proteomics and drug discovery research. The applicability of the method has been demonstrated using alpha-helical bovine apo calbindin-D9k P43M mutant (75 aa) protein. Automated assignment of this data using AUTOBA has been presented, which enhances the utility of these experiments. The backbone resonance assignments so derived are utilized to estimate secondary structures and the backbone fold using Web-based algorithms. Taken together, we believe that the method and the protocol proposed here can be used for routine high-throughput structural studies of proteins. Copyright © 2014 John Wiley & Sons, Ltd.

DOCLASP - Docking ligands to target proteins using spatial and electrostatic congruence extracted from a known holoenzyme and applying simple geometrical transformations.

Science.gov (United States)

Chakraborty, Sandeep

2014-01-01

The ability to accurately and effectively predict the interaction between proteins and small drug-like compounds has long intrigued researchers for pedagogic, humanitarian and economic reasons. Protein docking methods (AutoDock, GOLD, DOCK, FlexX and Glide to name a few) rank a large number of possible conformations of protein-ligand complexes using fast algorithms. Previously, it has been shown that structural congruence leading to the same enzymatic function necessitates the congruence of electrostatic properties (CLASP). The current work presents a methodology for docking a ligand into a target protein, provided that there is at least one known holoenzyme with ligand bound - DOCLASP (Docking using CLASP). The contact points of the ligand in the holoenzyme defines a motif, which is used to query the target enzyme using CLASP. If there are significant matches, the holoenzyme and the target protein are superimposed based on congruent atoms. The same linear and rotational transformations are also applied to the ligand, thus creating a unified coordinate framework having the holoenzyme, the ligand and the target enzyme. In the current work, the dipeptidyl peptidase-IV inhibitor vildagliptin was docked to the PI-PLC structure complexed with myo-inositol using DOCLASP. Also, corroboration of the docking of phenylthiourea to the modelled structure of polyphenol oxidase (JrPPO1) from walnut is provided based on the subsequently solved structure of JrPPO1 (PDBid:5CE9). Analysis of the binding of the antitrypanosomial drug suramin to nine non-homologous proteins in the PDB database shows a diverse set of binding motifs, and multiple binding sites in the phospholipase A2-likeproteins from the Bothrops genus of pitvipers. The conformational changes in the suramin molecule on binding highlights the challenges in docking flexible ligands into an already 'plastic' binding site. Thus, DOCLASP presents a method for 'soft docking' ligands to proteins with low computational

Mining Chemical Activity Status from High-Throughput Screening Assays

KAUST Repository

Soufan, Othman; Ba Alawi, Wail; Afeef, Moataz A.; Essack, Magbubah; Rodionov, Valentin; Kalnis, Panos; Bajic, Vladimir B.

2015-01-01

High-throughput screening (HTS) experiments provide a valuable resource that reports biological activity of numerous chemical compounds relative to their molecular targets. Building computational models that accurately predict such activity status (active vs. inactive) in specific assays is a challenging task given the large volume of data and frequently small proportion of active compounds relative to the inactive ones. We developed a method, DRAMOTE, to predict activity status of chemical compounds in HTP activity assays. For a class of HTP assays, our method achieves considerably better results than the current state-of-the-art-solutions. We achieved this by modification of a minority oversampling technique. To demonstrate that DRAMOTE is performing better than the other methods, we performed a comprehensive comparison analysis with several other methods and evaluated them on data from 11 PubChem assays through 1,350 experiments that involved approximately 500,000 interactions between chemicals and their target proteins. As an example of potential use, we applied DRAMOTE to develop robust models for predicting FDA approved drugs that have high probability to interact with the thyroid stimulating hormone receptor (TSHR) in humans. Our findings are further partially and indirectly supported by 3D docking results and literature information. The results based on approximately 500,000 interactions suggest that DRAMOTE has performed the best and that it can be used for developing robust virtual screening models. The datasets and implementation of all solutions are available as a MATLAB toolbox online at www.cbrc.kaust.edu.sa/dramote and can be found on Figshare.

Mining Chemical Activity Status from High-Throughput Screening Assays

KAUST Repository

Soufan, Othman

2015-12-14

High-throughput screening (HTS) experiments provide a valuable resource that reports biological activity of numerous chemical compounds relative to their molecular targets. Building computational models that accurately predict such activity status (active vs. inactive) in specific assays is a challenging task given the large volume of data and frequently small proportion of active compounds relative to the inactive ones. We developed a method, DRAMOTE, to predict activity status of chemical compounds in HTP activity assays. For a class of HTP assays, our method achieves considerably better results than the current state-of-the-art-solutions. We achieved this by modification of a minority oversampling technique. To demonstrate that DRAMOTE is performing better than the other methods, we performed a comprehensive comparison analysis with several other methods and evaluated them on data from 11 PubChem assays through 1,350 experiments that involved approximately 500,000 interactions between chemicals and their target proteins. As an example of potential use, we applied DRAMOTE to develop robust models for predicting FDA approved drugs that have high probability to interact with the thyroid stimulating hormone receptor (TSHR) in humans. Our findings are further partially and indirectly supported by 3D docking results and literature information. The results based on approximately 500,000 interactions suggest that DRAMOTE has performed the best and that it can be used for developing robust virtual screening models. The datasets and implementation of all solutions are available as a MATLAB toolbox online at www.cbrc.kaust.edu.sa/dramote and can be found on Figshare.

Improving binding mode and binding affinity predictions of docking by ligand-based search of protein conformations: evaluation in D3R grand challenge 2015

Science.gov (United States)

Xu, Xianjin; Yan, Chengfei; Zou, Xiaoqin

2017-08-01

The growing number of protein-ligand complex structures, particularly the structures of proteins co-bound with different ligands, in the Protein Data Bank helps us tackle two major challenges in molecular docking studies: the protein flexibility and the scoring function. Here, we introduced a systematic strategy by using the information embedded in the known protein-ligand complex structures to improve both binding mode and binding affinity predictions. Specifically, a ligand similarity calculation method was employed to search a receptor structure with a bound ligand sharing high similarity with the query ligand for the docking use. The strategy was applied to the two datasets (HSP90 and MAP4K4) in recent D3R Grand Challenge 2015. In addition, for the HSP90 dataset, a system-specific scoring function (ITScore2_hsp90) was generated by recalibrating our statistical potential-based scoring function (ITScore2) using the known protein-ligand complex structures and the statistical mechanics-based iterative method. For the HSP90 dataset, better performances were achieved for both binding mode and binding affinity predictions comparing with the original ITScore2 and with ensemble docking. For the MAP4K4 dataset, although there were only eight known protein-ligand complex structures, our docking strategy achieved a comparable performance with ensemble docking. Our method for receptor conformational selection and iterative method for the development of system-specific statistical potential-based scoring functions can be easily applied to other protein targets that have a number of protein-ligand complex structures available to improve predictions on binding.

The Drosophila DOCK family protein Sponge is required for development of the air sac primordium

Energy Technology Data Exchange (ETDEWEB)

Morishita, Kazushge; Anh Suong, Dang Ngoc; Yoshida, Hideki; Yamaguchi, Masamitsu, E-mail: myamaguc@kit.ac.jp

2017-05-15

Dedicator of cytokinesis (DOCK) family genes are known as DOCK1-DOCK11 in mammals. DOCK family proteins mainly regulate actin filament polymerization and/or depolymerization and are GEF proteins, which contribute to cellular signaling events by activating small G proteins. Sponge (Spg) is a Drosophila counterpart to mammalian DOCK3/DOCK4, and plays a role in embryonic central nervous system development, R7 photoreceptor cell differentiation, and adult thorax development. In order to conduct further functional analyses on Spg in vivo, we examined its localization in third instar larval wing imaginal discs. Immunostaining with purified anti-Spg IgG revealed that Spg mainly localized in the air sac primordium (ASP) in wing imaginal discs. Spg is therefore predicted to play an important role in the ASP. The specific knockdown of Spg by the breathless-GAL4 driver in tracheal cells induced lethality accompanied with a defect in ASP development and the induction of apoptosis. The monitoring of ERK signaling activity in wing imaginal discs by immunostaining with anti-diphospho-ERK IgG revealed reductions in the ERK signal cascade in Spg knockdown clones. Furthermore, the overexpression of D-raf suppressed defects in survival and the proliferation of cells in the ASP induced by the knockdown of Spg. Collectively, these results indicate that Spg plays a critical role in ASP development and tracheal cell viability that is mediated by the ERK signaling pathway. - Highlights: • Spg mainly localizes in the air sac primordium in wing imaginal discs. • Spg plays a critical role in air sac primordium development. • Spg positively regulates the ERK signal cascade.

Binding free energy analysis of protein-protein docking model structures by evERdock.

Science.gov (United States)

Takemura, Kazuhiro; Matubayasi, Nobuyuki; Kitao, Akio

2018-03-14

To aid the evaluation of protein-protein complex model structures generated by protein docking prediction (decoys), we previously developed a method to calculate the binding free energies for complexes. The method combines a short (2 ns) all-atom molecular dynamics simulation with explicit solvent and solution theory in the energy representation (ER). We showed that this method successfully selected structures similar to the native complex structure (near-native decoys) as the lowest binding free energy structures. In our current work, we applied this method (evERdock) to 100 or 300 model structures of four protein-protein complexes. The crystal structures and the near-native decoys showed the lowest binding free energy of all the examined structures, indicating that evERdock can successfully evaluate decoys. Several decoys that show low interface root-mean-square distance but relatively high binding free energy were also identified. Analysis of the fraction of native contacts, hydrogen bonds, and salt bridges at the protein-protein interface indicated that these decoys were insufficiently optimized at the interface. After optimizing the interactions around the interface by including interfacial water molecules, the binding free energies of these decoys were improved. We also investigated the effect of solute entropy on binding free energy and found that consideration of the entropy term does not necessarily improve the evaluations of decoys using the normal model analysis for entropy calculation.

QSAR Study on Caffeine Derivatives Docked on Poly(ARNA Polymerase Protein Cid1

Directory of Open Access Journals (Sweden)

Teodora E. Harsa

2016-06-01

Full Text Available Caffeine is the most commonly ingested alkylxantine and is recognized as a psycho-stimulant. It improves some aspects of cognitive performance, however it reduces the cerebral blood flow both in animals and humans. In this paper a QSAR study on caffeine derivatives, docked on the Poly(ARNA polymerase protein cid1, is reported. A set of forty caffeine derivatives, downloaded from PubChem, was modeled, within the hypermolecule strategy; the predicted activity was LD50 and prediction was done on similarity clusters with the leaders chosen as the best docked ligands on the Poly(ARNA polymerase protein cid1. It was concluded that LD50 of the studied caffeines is not influenced by their binding to the target protein. This work is licensed under a Creative Commons Attribution 4.0 International License.

Defining the limits of homology modeling in information-driven protein docking

NARCIS (Netherlands)

Garcia Lopes Maia Rodrigues, João; Melquiond, A S J; Karaca, E; Trellet, M; van Dijk, M; van Zundert, G C P; Schmitz, C; de Vries, S J; Bordogna, A; Bonati, L; Kastritis, P L; Bonvin, Alexandre M J J; Garcia Lopes Maia Rodrigues, João

2013-01-01

Information-driven docking is currently one of the most successful approaches to obtain structural models of protein interactions as demonstrated in the latest round of CAPRI. While various experimental and computational techniques can be used to retrieve information about the binding mode, the

Organization of functional domains in the docking protein p130Cas

International Nuclear Information System (INIS)

Nasertorabi, Fariborz; Garcia-Guzman, Miguel; Briknarova, Klara; Larsen, Elise; Havert, Marnie L.; Vuori, Kristiina; Ely, Kathryn R.

2004-01-01

The docking protein p130Cas becomes phosphorylated upon cell adhesion to extracellular matrix proteins, and is thought to play an essential role in cell transformation. Cas transmits signals through interactions with the Src-homology 3 (SH3) and Src-homology 2 domains of FAK or v-Crk signaling molecules, or with 14-3-3 protein, as well as phosphatases PTP1B and PTP-PEST. The large (130 kDa), multi-domain Cas molecule contains an SH3 domain, a Src-binding domain, a serine-rich protein interaction region, and a C-terminal region that participates in protein interactions implicated in antiestrogen resistance in breast cancer. In this study, as part of a long-term goal to examine the protein interactions of Cas by X-ray crystallography and nuclear magnetic resonance spectroscopy, molecular constructs were designed to express two adjacent domains, the serine-rich domain and the Src-binding domain, that each participate in intermolecular contacts dependent on protein phosphorylation. The protein products are soluble, homogeneous, monodisperse, and highly suitable for structural studies to define the role of Cas in integrin-mediated cell signaling

Robust, high-throughput solution structural analyses by small angle X-ray scattering (SAXS)

Energy Technology Data Exchange (ETDEWEB)

Hura, Greg L.; Menon, Angeli L.; Hammel, Michal; Rambo, Robert P.; Poole II, Farris L.; Tsutakawa, Susan E.; Jenney Jr, Francis E.; Classen, Scott; Frankel, Kenneth A.; Hopkins, Robert C.; Yang, Sungjae; Scott, Joseph W.; Dillard, Bret D.; Adams, Michael W. W.; Tainer, John A.

2009-07-20

We present an efficient pipeline enabling high-throughput analysis of protein structure in solution with small angle X-ray scattering (SAXS). Our SAXS pipeline combines automated sample handling of microliter volumes, temperature and anaerobic control, rapid data collection and data analysis, and couples structural analysis with automated archiving. We subjected 50 representative proteins, mostly from Pyrococcus furiosus, to this pipeline and found that 30 were multimeric structures in solution. SAXS analysis allowed us to distinguish aggregated and unfolded proteins, define global structural parameters and oligomeric states for most samples, identify shapes and similar structures for 25 unknown structures, and determine envelopes for 41 proteins. We believe that high-throughput SAXS is an enabling technology that may change the way that structural genomics research is done.

A recombinant fusion protein-based, fluorescent protease assay for high throughput-compatible substrate screening.

Science.gov (United States)

Bozóki, Beáta; Gazda, Lívia; Tóth, Ferenc; Miczi, Márió; Mótyán, János András; Tőzsér, József

2018-01-01

In connection with the intensive investigation of proteases, several methods have been developed for analysis of the substrate specificity. Due to the great number of proteases and the expected target molecules to be analyzed, time- and cost-efficient high-throughput screening (HTS) methods are preferred. Here we describe the development and application of a separation-based HTS-compatible fluorescent protease assay, which is based on the use of recombinant fusion proteins as substrates of proteases. The protein substrates used in this assay consists of N-terminal (hexahistidine and maltose binding protein) fusion tags, cleavage sequences of the tobacco etch virus (TEV) and HIV-1 proteases, and a C-terminal fluorescent protein (mApple or mTurquoise2). The assay is based on the fluorimetric detection of the fluorescent proteins, which are released from the magnetic bead-attached substrates by the proteolytic cleavage. The protease assay has been applied for activity measurements of TEV and HIV-1 proteases to test the suitability of the system for enzyme kinetic measurements, inhibition studies, and determination of pH optimum. We also found that denatured fluorescent proteins can be renatured after SDS-PAGE of denaturing conditions, but showed differences in their renaturation abilities. After in-gel renaturation both substrates and cleavage products can be identified by in-gel UV detection. Copyright © 2017 Elsevier Inc. All rights reserved.

A New Approach for Flexible Molecular Docking Based on Swarm Intelligence

Directory of Open Access Journals (Sweden)

Yi Fu

2015-01-01

Full Text Available Molecular docking methods play an important role in the field of computer-aided drug design. In the work, on the basis of the molecular docking program AutoDock, we present QLDock as a tool for flexible molecular docking. For the energy evaluation, the algorithm uses the binding free energy function that is provided by the AutoDock 4.2 tool. The new search algorithm combines the features of a quantum-behaved particle swarm optimization (QPSO algorithm and local search method of Solis and Wets for solving the highly flexible protein-ligand docking problem. We compute the interaction of 23 protein-ligand complexes and compare the results with those of the QDock and AutoDock programs. The experimental results show that our approach leads to substantially lower docking energy and higher docking precision in comparison to Lamarckian genetic algorithm and QPSO algorithm alone. QPSO-ls algorithm was able to identify the correct binding mode of 74% of the complexes. In comparison, the accuracy of QPSO and LGA is 52% and 61%, respectively. This difference in performance rises with increasing complexity of the ligand. Thus, the novel algorithm QPSO-ls may be used to dock ligand with many rotatable bonds with high accuracy.

High Throughput Facility

Data.gov (United States)

Federal Laboratory Consortium — Argonne?s high throughput facility provides highly automated and parallel approaches to material and materials chemistry development. The facility allows scientists...

Quantitative in vitro-to-in vivo extrapolation in a high-throughput environment

International Nuclear Information System (INIS)

Wetmore, Barbara A.

2015-01-01

High-throughput in vitro toxicity screening provides an efficient way to identify potential biological targets for environmental and industrial chemicals while conserving limited testing resources. However, reliance on the nominal chemical concentrations in these in vitro assays as an indicator of bioactivity may misrepresent potential in vivo effects of these chemicals due to differences in clearance, protein binding, bioavailability, and other pharmacokinetic factors. Development of high-throughput in vitro hepatic clearance and protein binding assays and refinement of quantitative in vitro-to-in vivo extrapolation (QIVIVE) methods have provided key tools to predict xenobiotic steady state pharmacokinetics. Using a process known as reverse dosimetry, knowledge of the chemical steady state behavior can be incorporated with HTS data to determine the external in vivo oral exposure needed to achieve internal blood concentrations equivalent to those eliciting bioactivity in the assays. These daily oral doses, known as oral equivalents, can be compared to chronic human exposure estimates to assess whether in vitro bioactivity would be expected at the dose-equivalent level of human exposure. This review will describe the use of QIVIVE methods in a high-throughput environment and the promise they hold in shaping chemical testing priorities and, potentially, high-throughput risk assessment strategies

Docking ligands into flexible and solvated macromolecules. 7. Impact of protein flexibility and water molecules on docking-based virtual screening accuracy.

Science.gov (United States)

Therrien, Eric; Weill, Nathanael; Tomberg, Anna; Corbeil, Christopher R; Lee, Devin; Moitessier, Nicolas

2014-11-24

The use of predictive computational methods in the drug discovery process is in a state of continual growth. Over the last two decades, an increasingly large number of docking tools have been developed to identify hits or optimize lead molecules through in-silico screening of chemical libraries to proteins. In recent years, the focus has been on implementing protein flexibility and water molecules. Our efforts led to the development of Fitted first reported in 2007 and further developed since then. In this study, we wished to evaluate the impact of protein flexibility and occurrence of water molecules on the accuracy of the Fitted docking program to discriminate active compounds from inactive compounds in virtual screening (VS) campaigns. For this purpose, a total of 171 proteins cocrystallized with small molecules representing 40 unique enzymes and receptors as well as sets of known ligands and decoys were selected from the Protein Data Bank (PDB) and the Directory of Useful Decoys (DUD), respectively. This study revealed that implementing displaceable crystallographic or computationally placed particle water molecules and protein flexibility can improve the enrichment in active compounds. In addition, an informed decision based on library diversity or research objectives (hit discovery vs lead optimization) on which implementation to use may lead to significant improvements.

Octopus: a platform for the virtual high-throughput screening of a pool of compounds against a set of molecular targets.

Science.gov (United States)

Maia, Eduardo Habib Bechelane; Campos, Vinícius Alves; Dos Reis Santos, Bianca; Costa, Marina Santos; Lima, Iann Gabriel; Greco, Sandro J; Ribeiro, Rosy I M A; Munayer, Felipe M; da Silva, Alisson Marques; Taranto, Alex Gutterres

2017-01-01

Octopus is an automated workflow management tool that is scalable for virtual high-throughput screening (vHTS). It integrates MOPAC2016, MGLTools, PyMOL, and AutoDock Vina. In contrast to other platforms, Octopus can perform docking simulations of an unlimited number of compounds into a set of molecular targets. After generating the ligands in a drawing package in the Protein Data Bank (PDB) format, Octopus can carry out geometry refinement using the semi-empirical method PM7 implemented in MOPAC2016. Docking simulations can be performed using AutoDock Vina and can utilize the Our Own Molecular Targets (OOMT) databank. Finally, the proposed software compiles the best binding energies into a standard table. Here, we describe two successful case studies that were verified by biological assay. In the first case study, the vHTS process was carried out for 22 (phenylamino)urea derivatives. The vHTS process identified a metalloprotease with the PDB code 1GKC as a molecular target for derivative LE&007. In a biological assay, compound LE&007 was found to inhibit 80% of the activity of this enzyme. In the second case study, compound Tx001 was submitted to the Octopus routine, and the results suggested that Plasmodium falciparum ATP6 (PfATP6) as a molecular target for this compound. Following an antimalarial assay, Tx001 was found to have an inhibitory concentration (IC 50 ) of 8.2 μM against PfATP6. These successful examples illustrate the utility of this software for finding appropriate molecular targets for compounds. Hits can then be identified and optimized as new antineoplastic and antimalarial drugs. Finally, Octopus has a friendly Linux-based user interface, and is available at www.drugdiscovery.com.br . Graphical Abstract Octopus: A platform for inverse virtual screening (IVS) to search new molecular targets for drugs.

On the computation of molecular surface correlations for protein docking using fourier techniques.

Science.gov (United States)

Sakk, Eric

2007-08-01

The computation of surface correlations using a variety of molecular models has been applied to the unbound protein docking problem. Because of the computational complexity involved in examining all possible molecular orientations, the fast Fourier transform (FFT) (a fast numerical implementation of the discrete Fourier transform (DFT)) is generally applied to minimize the number of calculations. This approach is rooted in the convolution theorem which allows one to inverse transform the product of two DFTs in order to perform the correlation calculation. However, such a DFT calculation results in a cyclic or "circular" correlation which, in general, does not lead to the same result as the linear correlation desired for the docking problem. In this work, we provide computational bounds for constructing molecular models used in the molecular surface correlation problem. The derived bounds are then shown to be consistent with various intuitive guidelines previously reported in the protein docking literature. Finally, these bounds are applied to different molecular models in order to investigate their effect on the correlation calculation.

An Efficient Implementation of the Nwat-MMGBSA Method to Rescore Docking Results in Medium-Throughput Virtual Screenings

Directory of Open Access Journals (Sweden)

Irene Maffucci

2018-03-01

Full Text Available 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 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.

An Efficient Implementation of the Nwat-MMGBSA Method to Rescore Docking Results in Medium-Throughput Virtual Screenings

Science.gov (United States)

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.

The focal adhesion-associated proteins DOCK5 and GIT2 comprise a rheostat in control of epithelial invasion

DEFF Research Database (Denmark)

Frank, Scott R; Köllmann, C P; van Lidth de Jeude, J F

2017-01-01

DOCK proteins are guanine nucleotide exchange factors for Rac and Cdc42 GTPases. DOCK1 is the founding member of the family and acts downstream of integrins via the canonical Crk-p130Cas complex to activate Rac GTPases in numerous contexts. In contrast, DOCK5, which possesses the greatest similar......:10.1038/onc.2016.345....

New generation of docking programs: Supercomputer validation of force fields and quantum-chemical methods for docking.

Science.gov (United States)

Sulimov, Alexey V; Kutov, Danil C; Katkova, Ekaterina V; Ilin, Ivan S; Sulimov, Vladimir B

2017-11-01

Discovery of new inhibitors of the protein associated with a given disease is the initial and most important stage of the whole process of the rational development of new pharmaceutical substances. New inhibitors block the active site of the target protein and the disease is cured. Computer-aided molecular modeling can considerably increase effectiveness of new inhibitors development. Reliable predictions of the target protein inhibition by a small molecule, ligand, is defined by the accuracy of docking programs. Such programs position a ligand in the target protein and estimate the protein-ligand binding energy. Positioning accuracy of modern docking programs is satisfactory. However, the accuracy of binding energy calculations is too low to predict good inhibitors. For effective application of docking programs to new inhibitors development the accuracy of binding energy calculations should be higher than 1kcal/mol. Reasons of limited accuracy of modern docking programs are discussed. One of the most important aspects limiting this accuracy is imperfection of protein-ligand energy calculations. Results of supercomputer validation of several force fields and quantum-chemical methods for docking are presented. The validation was performed by quasi-docking as follows. First, the low energy minima spectra of 16 protein-ligand complexes were found by exhaustive minima search in the MMFF94 force field. Second, energies of the lowest 8192 minima are recalculated with CHARMM force field and PM6-D3H4X and PM7 quantum-chemical methods for each complex. The analysis of minima energies reveals the docking positioning accuracies of the PM7 and PM6-D3H4X quantum-chemical methods and the CHARMM force field are close to one another and they are better than the positioning accuracy of the MMFF94 force field. Copyright © 2017 Elsevier Inc. All rights reserved.

High-throughput continuous cryopump

International Nuclear Information System (INIS)

Foster, C.A.

1986-01-01

A cryopump with a unique method of regeneration which allows continuous operation at high throughput has been constructed and tested. Deuterium was pumped continuously at a throughput of 30 Torr.L/s at a speed of 2000 L/s and a compression ratio of 200. Argon was pumped at a throughput of 60 Torr.L/s at a speed of 1275 L/s. To produce continuous operation of the pump, a method of regeneration that does not thermally cycle the pump is employed. A small chamber (the ''snail'') passes over the pumping surface and removes the frost from it either by mechanical action with a scraper or by local heating. The material removed is topologically in a secondary vacuum system with low conductance into the primary vacuum; thus, the exhaust can be pumped at pressures up to an effective compression ratio determined by the ratio of the pumping speed to the leakage conductance of the snail. The pump, which is all-metal-sealed and dry and which regenerates every 60 s, would be an ideal system for pumping tritium. Potential fusion applications are for mpmp limiters, for repeating pneumatic pellet injection lines, and for the centrifuge pellet injector spin tank, all of which will require pumping tritium at high throughput. Industrial applications requiring ultraclean pumping of corrosive gases at high throughput, such as the reactive ion etch semiconductor process, may also be feasible

Docking-based modeling of protein-protein interfaces for extensive structural and functional characterization of missense mutations.

Science.gov (United States)

Barradas-Bautista, Didier; Fernández-Recio, Juan

2017-01-01

Next-generation sequencing (NGS) technologies are providing genomic information for an increasing number of healthy individuals and patient populations. In the context of the large amount of generated genomic data that is being generated, understanding the effect of disease-related mutations at molecular level can contribute to close the gap between genotype and phenotype and thus improve prevention, diagnosis or treatment of a pathological condition. In order to fully characterize the effect of a pathological mutation and have useful information for prediction purposes, it is important first to identify whether the mutation is located at a protein-binding interface, and second to understand the effect on the binding affinity of the affected interaction/s. Computational methods, such as protein docking are currently used to complement experimental efforts and could help to build the human structural interactome. Here we have extended the original pyDockNIP method to predict the location of disease-associated nsSNPs at protein-protein interfaces, when there is no available structure for the protein-protein complex. We have applied this approach to the pathological interaction networks of six diseases with low structural data on PPIs. This approach can almost double the number of nsSNPs that can be characterized and identify edgetic effects in many nsSNPs that were previously unknown. This can help to annotate and interpret genomic data from large-scale population studies, and to achieve a better understanding of disease at molecular level.

Docking-based modeling of protein-protein interfaces for extensive structural and functional characterization of missense mutations.

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Didier Barradas-Bautista

Full Text Available Next-generation sequencing (NGS technologies are providing genomic information for an increasing number of healthy individuals and patient populations. In the context of the large amount of generated genomic data that is being generated, understanding the effect of disease-related mutations at molecular level can contribute to close the gap between genotype and phenotype and thus improve prevention, diagnosis or treatment of a pathological condition. In order to fully characterize the effect of a pathological mutation and have useful information for prediction purposes, it is important first to identify whether the mutation is located at a protein-binding interface, and second to understand the effect on the binding affinity of the affected interaction/s. Computational methods, such as protein docking are currently used to complement experimental efforts and could help to build the human structural interactome. Here we have extended the original pyDockNIP method to predict the location of disease-associated nsSNPs at protein-protein interfaces, when there is no available structure for the protein-protein complex. We have applied this approach to the pathological interaction networks of six diseases with low structural data on PPIs. This approach can almost double the number of nsSNPs that can be characterized and identify edgetic effects in many nsSNPs that were previously unknown. This can help to annotate and interpret genomic data from large-scale population studies, and to achieve a better understanding of disease at molecular level.

Screening small-molecule compound microarrays for protein ligands without fluorescence labeling with a high-throughput scanning microscope.

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Fei, Yiyan; Landry, James P; Sun, Yungshin; Zhu, Xiangdong; Wang, Xiaobing; Luo, Juntao; Wu, Chun-Yi; Lam, Kit S

2010-01-01

We describe a high-throughput scanning optical microscope for detecting small-molecule compound microarrays on functionalized glass slides. It is based on measurements of oblique-incidence reflectivity difference and employs a combination of a y-scan galvometer mirror and an x-scan translation stage with an effective field of view of 2 cm x 4 cm. Such a field of view can accommodate a printed small-molecule compound microarray with as many as 10,000 to 20,000 targets. The scanning microscope is capable of measuring kinetics as well as endpoints of protein-ligand reactions simultaneously. We present the experimental results on solution-phase protein reactions with small-molecule compound microarrays synthesized from one-bead, one-compound combinatorial chemistry and immobilized on a streptavidin-functionalized glass slide.

PaFlexPepDock: parallel ab-initio docking of peptides onto their receptors with full flexibility based on Rosetta.

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Li, Haiou; Lu, Liyao; Chen, Rong; Quan, Lijun; Xia, Xiaoyan; Lü, Qiang

2014-01-01

Structural information related to protein-peptide complexes can be very useful for novel drug discovery and design. The computational docking of protein and peptide can supplement the structural information available on protein-peptide interactions explored by experimental ways. Protein-peptide docking of this paper can be described as three processes that occur in parallel: ab-initio peptide folding, peptide docking with its receptor, and refinement of some flexible areas of the receptor as the peptide is approaching. Several existing methods have been used to sample the degrees of freedom in the three processes, which are usually triggered in an organized sequential scheme. In this paper, we proposed a parallel approach that combines all the three processes during the docking of a folding peptide with a flexible receptor. This approach mimics the actual protein-peptide docking process in parallel way, and is expected to deliver better performance than sequential approaches. We used 22 unbound protein-peptide docking examples to evaluate our method. Our analysis of the results showed that the explicit refinement of the flexible areas of the receptor facilitated more accurate modeling of the interfaces of the complexes, while combining all of the moves in parallel helped the constructing of energy funnels for predictions.

PaFlexPepDock: parallel ab-initio docking of peptides onto their receptors with full flexibility based on Rosetta.

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Haiou Li

Full Text Available Structural information related to protein-peptide complexes can be very useful for novel drug discovery and design. The computational docking of protein and peptide can supplement the structural information available on protein-peptide interactions explored by experimental ways. Protein-peptide docking of this paper can be described as three processes that occur in parallel: ab-initio peptide folding, peptide docking with its receptor, and refinement of some flexible areas of the receptor as the peptide is approaching. Several existing methods have been used to sample the degrees of freedom in the three processes, which are usually triggered in an organized sequential scheme. In this paper, we proposed a parallel approach that combines all the three processes during the docking of a folding peptide with a flexible receptor. This approach mimics the actual protein-peptide docking process in parallel way, and is expected to deliver better performance than sequential approaches. We used 22 unbound protein-peptide docking examples to evaluate our method. Our analysis of the results showed that the explicit refinement of the flexible areas of the receptor facilitated more accurate modeling of the interfaces of the complexes, while combining all of the moves in parallel helped the constructing of energy funnels for predictions.

High-throughput transformation of Saccharomyces cerevisiae using liquid handling robots.

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Guangbo Liu

Full Text Available Saccharomyces cerevisiae (budding yeast is a powerful eukaryotic model organism ideally suited to high-throughput genetic analyses, which time and again has yielded insights that further our understanding of cell biology processes conserved in humans. Lithium Acetate (LiAc transformation of yeast with DNA for the purposes of exogenous protein expression (e.g., plasmids or genome mutation (e.g., gene mutation, deletion, epitope tagging is a useful and long established method. However, a reliable and optimized high throughput transformation protocol that runs almost no risk of human error has not been described in the literature. Here, we describe such a method that is broadly transferable to most liquid handling high-throughput robotic platforms, which are now commonplace in academic and industry settings. Using our optimized method, we are able to comfortably transform approximately 1200 individual strains per day, allowing complete transformation of typical genomic yeast libraries within 6 days. In addition, use of our protocol for gene knockout purposes also provides a potentially quicker, easier and more cost-effective approach to generating collections of double mutants than the popular and elegant synthetic genetic array methodology. In summary, our methodology will be of significant use to anyone interested in high throughput molecular and/or genetic analysis of yeast.

A python-based docking program utilizing a receptor bound ligand shape: PythDock.

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Chung, Jae Yoon; Cho, Seung Joo; Hah, Jung-Mi

2011-09-01

PythDock is a heuristic docking program that uses Python programming language with a simple scoring function and a population based search engine. The scoring function considers electrostatic and dispersion/repulsion terms. The search engine utilizes a particle swarm optimization algorithm. A grid potential map is generated using the shape information of a bound ligand within the active site. Therefore, the searching area is more relevant to the ligand binding. To evaluate the docking performance of PythDock, two well-known docking programs (AutoDock and DOCK) were also used with the same data. The accuracy of docked results were measured by the difference of the ligand structure between x-ray structure, and docked pose, i.e., average root mean squared deviation values of the bound ligand were compared for fourteen protein-ligand complexes. Since the number of ligands' rotational flexibility is an important factor affecting the accuracy of a docking, the data set was chosen to have various degrees of flexibility. Although PythDock has a scoring function simpler than those of other programs (AutoDock and DOCK), our results showed that PythDock predicted more accurate poses than both AutoDock4.2 and DOCK6.2. This indicates that PythDock could be a useful tool to study ligand-receptor interactions and could also be beneficial in structure based drug design.

Cytotoxicity Test Based on Human Cells Labeled with Fluorescent Proteins: Fluorimetry, Photography, and Scanning for High-Throughput Assay.

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Kalinina, Marina A; Skvortsov, Dmitry A; Rubtsova, Maria P; Komarova, Ekaterina S; Dontsova, Olga A

2018-06-01

High- and medium-throughput assays are now routine methods for drug screening and toxicology investigations on mammalian cells. However, a simple and cost-effective analysis of cytotoxicity that can be carried out with commonly used laboratory equipment is still required. The developed cytotoxicity assays are based on human cell lines stably expressing eGFP, tdTomato, mCherry, or Katushka2S fluorescent proteins. Red fluorescent proteins exhibit a higher signal-to-noise ratio, due to less interference by medium autofluorescence, in comparison to green fluorescent protein. Measurements have been performed on a fluorescence scanner, a plate fluorimeter, and a camera photodocumentation system. For a 96-well plate assay, the sensitivity per well and the measurement duration were 250 cells and 15 min for the scanner, 500 cells and 2 min for the plate fluorimeter, and 1000 cells and less than 1 min for the camera detection. These sensitivities are similar to commonly used MTT (tetrazolium dye) assays. The used scanner and the camera had not been previously applied for cytotoxicity evaluation. An image processing scheme for the high-resolution scanner is proposed that significantly diminishes the number of control wells, even for a library containing fluorescent substances. The suggested cytotoxicity assay has been verified by measurements of the cytotoxicity of several well-known cytotoxic drugs and further applied to test a set of novel bacteriotoxic compounds in a medium-throughput format. The fluorescent signal of living cells is detected without disturbing them and adding any reagents, thus allowing to investigate time-dependent cytotoxicity effects on the same sample of cells. A fast, simple and cost-effective assay is suggested for cytotoxicity evaluation based on mammalian cells expressing fluorescent proteins and commonly used laboratory equipment.

Use of high-throughput mass spectrometry to elucidate host-pathogen interactions in Salmonella

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Rodland, Karin D.; Adkins, Joshua N.; Ansong, Charles; Chowdhury, Saiful M.; Manes, Nathan P.; Shi, Liang; Yoon, Hyunjin; Smith, Richard D.; Heffron, Fred

2008-12-01

New improvements to mass spectrometry include increased sensitivity, improvements in analyzing the collected data, and most important, from the standpoint of this review, a much higher throughput allowing analysis of many samples in a single day. This short review describes how host-pathogen interactions can be dissected by mass spectrometry using Salmonella as a model system. The approach allowed direct identification of the majority of annotate Salmonella proteins, how expression changed under various in vitro growth conditions, and how this relates to virulence and expression within host cell cells. One of the most significant findings is that a very high percentage of the all annotated genes (>20%) are regulated post-transcriptionally. In addition, new and unexpected interactions have been identified for several Salmonella virulence regulators that involve protein-protein interactions suggesting additional functions of the regulator in coordinating virulence expression. Overall high throughput mass spectrometer provides a new view of pathogen-host interaction emphasizing the protein products and defining how protein interactions determine the outcome of infection.

High-throughput oxidation screen of antibody-drug conjugates by analytical protein A chromatography following IdeS digest.

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Buecheler, Jakob W; Winzer, Matthias; Weber, Christian; Gieseler, Henning

2018-05-01

Oxidation of protein therapeutics is a major chemical degradation pathway which may impact bioactivity, serum half-life and stability. Therefore, oxidation is a relevant parameter which has to be monitored throughout formulation development. Methods such as HIC, RPLC and LC/MS achieve a separation of oxidized and non-oxidized species by differences in hydrophobicity. Antibody-drug conjugates (ADC) although are highly more complex due to the heterogeneity in linker, drug, drug-to-antibody ratio (DAR) and conjugation site. The analytical protein A chromatography can provide a simple and fast alternative to these common methods. A miniature analytical protein A chromatography method in combination with an IdeS digest was developed to analyse ADCs. The IdeS digest efficiency of an IgG1 was monitored using SEC-HPLC and non-reducing SDS-PAGE. An antibody-fluorescent dye conjugate was conjugated at different dye-to-antibody ratios as model construct to mimic an ADC. With IdeS, an almost complete digest of a model IgG1 can be achieved (digested protein amount >98%). This enables subsequent analytical protein A chromatography, which consequently eliminates any interference of payload with the stationary phase. A novel high-throughput method for an interchain cysteine-linked ADC oxidation screens during formulation development was developed. © 2018 Royal Pharmaceutical Society.

A collaborative filtering approach for protein-protein docking scoring functions.

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Bourquard, Thomas; Bernauer, Julie; Azé, Jérôme; Poupon, Anne

2011-04-22

A protein-protein docking procedure traditionally consists in two successive tasks: a search algorithm generates a large number of candidate conformations mimicking the complex existing in vivo between two proteins, and a scoring function is used to rank them in order to extract a native-like one. We have already shown that using Voronoi constructions and a well chosen set of parameters, an accurate scoring function could be designed and optimized. However to be able to perform large-scale in silico exploration of the interactome, a near-native solution has to be found in the ten best-ranked solutions. This cannot yet be guaranteed by any of the existing scoring functions. In this work, we introduce a new procedure for conformation ranking. We previously developed a set of scoring functions where learning was performed using a genetic algorithm. These functions were used to assign a rank to each possible conformation. We now have a refined rank using different classifiers (decision trees, rules and support vector machines) in a collaborative filtering scheme. The scoring function newly obtained is evaluated using 10 fold cross-validation, and compared to the functions obtained using either genetic algorithms or collaborative filtering taken separately. This new approach was successfully applied to the CAPRI scoring ensembles. We show that for 10 targets out of 12, we are able to find a near-native conformation in the 10 best ranked solutions. Moreover, for 6 of them, the near-native conformation selected is of high accuracy. Finally, we show that this function dramatically enriches the 100 best-ranking conformations in near-native structures.

Categorizing Biases in High-Confidence High-Throughput Protein-Protein Interaction Data Sets*

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Yu, Xueping; Ivanic, Joseph; Memišević, Vesna; Wallqvist, Anders; Reifman, Jaques

2011-01-01

We characterized and evaluated the functional attributes of three yeast high-confidence protein-protein interaction data sets derived from affinity purification/mass spectrometry, protein-fragment complementation assay, and yeast two-hybrid experiments. The interacting proteins retrieved from these data sets formed distinct, partially overlapping sets with different protein-protein interaction characteristics. These differences were primarily a function of the deployed experimental technologies used to recover these interactions. This affected the total coverage of interactions and was especially evident in the recovery of interactions among different functional classes of proteins. We found that the interaction data obtained by the yeast two-hybrid method was the least biased toward any particular functional characterization. In contrast, interacting proteins in the affinity purification/mass spectrometry and protein-fragment complementation assay data sets were over- and under-represented among distinct and different functional categories. We delineated how these differences affected protein complex organization in the network of interactions, in particular for strongly interacting complexes (e.g. RNA and protein synthesis) versus weak and transient interacting complexes (e.g. protein transport). We quantified methodological differences in detecting protein interactions from larger protein complexes, in the correlation of protein abundance among interacting proteins, and in their connectivity of essential proteins. In the latter case, we showed that minimizing inherent methodology biases removed many of the ambiguous conclusions about protein essentiality and protein connectivity. We used these findings to rationalize how biological insights obtained by analyzing data sets originating from different sources sometimes do not agree or may even contradict each other. An important corollary of this work was that discrepancies in biological insights did not

High-throughput characterization methods for lithium batteries

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Yingchun Lyu

2017-09-01

Full Text Available The development of high-performance lithium ion batteries requires the discovery of new materials and the optimization of key components. By contrast with traditional one-by-one method, high-throughput method can synthesize and characterize a large number of compositionally varying samples, which is able to accelerate the pace of discovery, development and optimization process of materials. Because of rapid progress in thin film and automatic control technologies, thousands of compounds with different compositions could be synthesized rapidly right now, even in a single experiment. However, the lack of rapid or combinatorial characterization technologies to match with high-throughput synthesis methods, limit the application of high-throughput technology. Here, we review a series of representative high-throughput characterization methods used in lithium batteries, including high-throughput structural and electrochemical characterization methods and rapid measuring technologies based on synchrotron light sources.

High-throughput protein crystallization on the World Community Grid and the GPU

International Nuclear Information System (INIS)

Kotseruba, Yulia; Cumbaa, Christian A; Jurisica, Igor

2012-01-01

We have developed CPU and GPU versions of an automated image analysis and classification system for protein crystallization trial images from the Hauptman Woodward Institute's High-Throughput Screening lab. The analysis step computes 12,375 numerical features per image. Using these features, we have trained a classifier that distinguishes 11 different crystallization outcomes, recognizing 80% of all crystals, 94% of clear drops, 94% of precipitates. The computing requirements for this analysis system are large. The complete HWI archive of 120 million images is being processed by the donated CPU cycles on World Community Grid, with a GPU phase launching in early 2012. The main computational burden of the analysis is the measure of textural (GLCM) features within the image at multiple neighbourhoods, distances, and at multiple greyscale intensity resolutions. CPU runtime averages 4,092 seconds (single threaded) on an Intel Xeon, but only 65 seconds on an NVIDIA Tesla C2050. We report on the process of adapting the C++ code to OpenCL, optimized for multiple platforms.

Use of high-throughput mass spectrometry to elucidate host pathogen interactions in Salmonella

Energy Technology Data Exchange (ETDEWEB)

Rodland, Karin D.; Adkins, Joshua N.; Ansong, Charles; Chowdhury, Saiful M.; Manes, Nathan P.; Shi, Liang; Yoon, Hyunjin; Smith, Richard D.; Heffron, Fred

2008-12-01

Capabilities in mass spectrometry are evolving rapidly, with recent improvements in sensitivity, data analysis, and most important, from the standpoint of this review, much higher throughput allowing analysis of many samples in a single day. This short review describes how these improvements in mass spectrometry can be used to dissect host-pathogen interactions using Salmonella as a model system. This approach enabled direct identification of the majority of annotated Salmonella proteins, quantitation of expression changes under various in vitro growth conditions, and new insights into virulence and expression of Salmonella proteins within host cell cells. One of the most significant findings is that a very high percentage of the all annotated genes (>20%) in Salmonella are regulated post-transcriptionally. In addition, new and unexpected interactions have been identified for several Salmonella virulence regulators that involve protein-protein interactions, suggesting additional functions of these regulators in coordinating virulence expression. Overall high throughput mass spectrometry provides a new view of pathogen-host interactions emphasizing the protein products and defining how protein interactions determine the outcome of infection.

Improving Docking Performance Using Negative Image-Based Rescoring.

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Kurkinen, Sami T; Niinivehmas, Sanna; Ahinko, Mira; Lätti, Sakari; Pentikäinen, Olli T; Postila, Pekka A

2018-01-01

Despite the large computational costs of molecular docking, the default scoring functions are often unable to recognize the active hits from the inactive molecules in large-scale virtual screening experiments. Thus, even though a correct binding pose might be sampled during the docking, the active compound or its biologically relevant pose is not necessarily given high enough score to arouse the attention. Various rescoring and post-processing approaches have emerged for improving the docking performance. Here, it is shown that the very early enrichment (number of actives scored higher than 1% of the highest ranked decoys) can be improved on average 2.5-fold or even 8.7-fold by comparing the docking-based ligand conformers directly against the target protein's cavity shape and electrostatics. The similarity comparison of the conformers is performed without geometry optimization against the negative image of the target protein's ligand-binding cavity using the negative image-based (NIB) screening protocol. The viability of the NIB rescoring or the R-NiB, pioneered in this study, was tested with 11 target proteins using benchmark libraries. By focusing on the shape/electrostatics complementarity of the ligand-receptor association, the R-NiB is able to improve the early enrichment of docking essentially without adding to the computing cost. By implementing consensus scoring, in which the R-NiB and the original docking scoring are weighted for optimal outcome, the early enrichment is improved to a level that facilitates effective drug discovery. Moreover, the use of equal weight from the original docking scoring and the R-NiB scoring improves the yield in most cases.

GeauxDock: Accelerating Structure-Based Virtual Screening with Heterogeneous Computing

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Fang, Ye; Ding, Yun; Feinstein, Wei P.; Koppelman, David M.; Moreno, Juana; Jarrell, Mark; Ramanujam, J.; Brylinski, Michal

2016-01-01

Computational modeling of drug binding to proteins is an integral component of direct drug design. Particularly, structure-based virtual screening is often used to perform large-scale modeling of putative associations between small organic molecules and their pharmacologically relevant protein targets. Because of a large number of drug candidates to be evaluated, an accurate and fast docking engine is a critical element of virtual screening. Consequently, highly optimized docking codes are of paramount importance for the effectiveness of virtual screening methods. In this communication, we describe the implementation, tuning and performance characteristics of GeauxDock, a recently developed molecular docking program. GeauxDock is built upon the Monte Carlo algorithm and features a novel scoring function combining physics-based energy terms with statistical and knowledge-based potentials. Developed specifically for heterogeneous computing platforms, the current version of GeauxDock can be deployed on modern, multi-core Central Processing Units (CPUs) as well as massively parallel accelerators, Intel Xeon Phi and NVIDIA Graphics Processing Unit (GPU). First, we carried out a thorough performance tuning of the high-level framework and the docking kernel to produce a fast serial code, which was then ported to shared-memory multi-core CPUs yielding a near-ideal scaling. Further, using Xeon Phi gives 1.9× performance improvement over a dual 10-core Xeon CPU, whereas the best GPU accelerator, GeForce GTX 980, achieves a speedup as high as 3.5×. On that account, GeauxDock can take advantage of modern heterogeneous architectures to considerably accelerate structure-based virtual screening applications. GeauxDock is open-sourced and publicly available at www.brylinski.org/geauxdock and https://figshare.com/articles/geauxdock_tar_gz/3205249. PMID:27420300

GeauxDock: Accelerating Structure-Based Virtual Screening with Heterogeneous Computing.

Directory of Open Access Journals (Sweden)

Ye Fang

Full Text Available Computational modeling of drug binding to proteins is an integral component of direct drug design. Particularly, structure-based virtual screening is often used to perform large-scale modeling of putative associations between small organic molecules and their pharmacologically relevant protein targets. Because of a large number of drug candidates to be evaluated, an accurate and fast docking engine is a critical element of virtual screening. Consequently, highly optimized docking codes are of paramount importance for the effectiveness of virtual screening methods. In this communication, we describe the implementation, tuning and performance characteristics of GeauxDock, a recently developed molecular docking program. GeauxDock is built upon the Monte Carlo algorithm and features a novel scoring function combining physics-based energy terms with statistical and knowledge-based potentials. Developed specifically for heterogeneous computing platforms, the current version of GeauxDock can be deployed on modern, multi-core Central Processing Units (CPUs as well as massively parallel accelerators, Intel Xeon Phi and NVIDIA Graphics Processing Unit (GPU. First, we carried out a thorough performance tuning of the high-level framework and the docking kernel to produce a fast serial code, which was then ported to shared-memory multi-core CPUs yielding a near-ideal scaling. Further, using Xeon Phi gives 1.9× performance improvement over a dual 10-core Xeon CPU, whereas the best GPU accelerator, GeForce GTX 980, achieves a speedup as high as 3.5×. On that account, GeauxDock can take advantage of modern heterogeneous architectures to considerably accelerate structure-based virtual screening applications. GeauxDock is open-sourced and publicly available at www.brylinski.org/geauxdock and https://figshare.com/articles/geauxdock_tar_gz/3205249.

Interaction of the minocycline with extracelluar protein and intracellular protein by multi-spectral techniques and molecular docking

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Fang, Qing; Wang, Yirun; Hu, Taoying; Liu, Ying

2017-02-01

The interaction of minocyeline (MNC) with extracelluar protein (lysozyme, LYSO) or intracellular protein (bovine hemoglobin, BHb) was investigated using multi-spectral techniques and molecular docking in vitro. Fluorescence studies suggested that MNC quenched LYSO/BHb fluorescence in a static mode with binding constants of 2.01 and 0.26 × 104 L•mol-1 at 298 K, respectively. The LYZO-MNC system was more easily influenced by temperature (298 and 310 K) than the BHb-MNC system. The thermodynamic parameters demonstrated that hydrogen bonds and van der Waals forces played the major role in the binding process. Based on the Förster theory of nonradiative energy transfer, the binding distances between MNC and the inner tryptophan residues of LYSO and BHb were calculated to be 4.34 and 3.49 nm, respectively. Furthermore, circular dichroism spectra (CD), Fourier transforms infrared (FTIR), UV-vis, and three-dimensional fluorescence spectra results indicated the secondary structures of LYSO and BHb were partially destroyed by MNC with the α-helix percentage of LYZO-MNC increased (17.8-28.6%) while that of BHb-MNC was decreased (41.6-39.6%). UV-vis spectral results showed these binding interactions could cause conformational and some micro-environmental changes of LYSO and BHb. In accordance with the results of molecular docking, In LYZO-MNC system, MNC was mainly bound in the active site hinge region where Trp-62 and Trp-63 are located, and in MNC-BHb system, MNC was close to the subunit α 1 of BHb, molecular docking analysis supported the thermodynamic results well. The work contributes to clarify the mechanism of MNC with two proteins at molecular level.

Generation and evaluation of mammalian secreted and membrane protein expression libraries for high-throughput target discovery.

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Panavas, Tadas; Lu, Jin; Liu, Xuesong; Winkis, Ann-Marie; Powers, Gordon; Naso, Michael F; Amegadzie, Bernard

2011-09-01

Expressed protein libraries are becoming a critical tool for new target discovery in the pharmaceutical industry. In order to get the most meaningful and comprehensive results from protein library screens, it is essential to have library proteins in their native conformation with proper post-translation modifications. This goal is achieved by expressing untagged human proteins in a human cell background. We optimized the transfection and cell culture conditions to maximize protein expression in a 96-well format so that the expression levels were comparable with the levels observed in shake flasks. For detection purposes, we engineered a 'tag after stop codon' system. Depending on the expression conditions, it was possible to express either native or tagged proteins from the same expression vector set. We created a human secretion protein library of 1432 candidates and a small plasma membrane protein set of about 500 candidates. Utilizing the optimized expression conditions, we expressed and analyzed both libraries by SDS-PAGE gel electrophoresis and Western blotting. Two thirds of secreted proteins could be detected by Western-blot analyses; almost half of them were visible on Coomassie stained gels. In this paper, we describe protein expression libraries that can be easily produced in mammalian expression systems in a 96-well format, with one protein expressed per well. The libraries and methods described allow for the development of robust, high-throughput functional screens designed to assay for protein specific functions associated with a relevant disease-specific activity. Copyright © 2011 Elsevier Inc. All rights reserved.

Solvated protein–DNA docking using HADDOCK

International Nuclear Information System (INIS)

Dijk, Marc van; Visscher, Koen M.; Kastritis, Panagiotis L.; Bonvin, Alexandre M. J. J.

2013-01-01

Interfacial water molecules play an important role in many aspects of protein–DNA specificity and recognition. Yet they have been mostly neglected in the computational modeling of these complexes. We present here a solvated docking protocol that allows explicit inclusion of water molecules in the docking of protein–DNA complexes and demonstrate its feasibility on a benchmark of 30 high-resolution protein–DNA complexes containing crystallographically-determined water molecules at their interfaces. Our protocol is capable of reproducing the solvation pattern at the interface and recovers hydrogen-bonded water-mediated contacts in many of the benchmark cases. Solvated docking leads to an overall improvement in the quality of the generated protein–DNA models for cases with limited conformational change of the partners upon complex formation. The applicability of this approach is demonstrated on real cases by docking a representative set of 6 complexes using unbound protein coordinates, model-built DNA and knowledge-based restraints. As HADDOCK supports the inclusion of a variety of NMR restraints, solvated docking is also applicable for NMR-based structure calculations of protein–DNA complexes.

Combinatorial chemoenzymatic synthesis and high-throughput screening of sialosides.

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Chokhawala, Harshal A; Huang, Shengshu; Lau, Kam; Yu, Hai; Cheng, Jiansong; Thon, Vireak; Hurtado-Ziola, Nancy; Guerrero, Juan A; Varki, Ajit; Chen, Xi

2008-09-19

Although the vital roles of structures containing sialic acid in biomolecular recognition are well documented, limited information is available on how sialic acid structural modifications, sialyl linkages, and the underlying glycan structures affect the binding or the activity of sialic acid-recognizing proteins and related downstream biological processes. A novel combinatorial chemoenzymatic method has been developed for the highly efficient synthesis of biotinylated sialosides containing different sialic acid structures and different underlying glycans in 96-well plates from biotinylated sialyltransferase acceptors and sialic acid precursors. By transferring the reaction mixtures to NeutrAvidin-coated plates and assaying for the yields of enzymatic reactions using lectins recognizing sialyltransferase acceptors but not the sialylated products, the biotinylated sialoside products can be directly used, without purification, for high-throughput screening to quickly identify the ligand specificity of sialic acid-binding proteins. For a proof-of-principle experiment, 72 biotinylated alpha2,6-linked sialosides were synthesized in 96-well plates from 4 biotinylated sialyltransferase acceptors and 18 sialic acid precursors using a one-pot three-enzyme system. High-throughput screening assays performed in NeutrAvidin-coated microtiter plates show that whereas Sambucus nigra Lectin binds to alpha2,6-linked sialosides with high promiscuity, human Siglec-2 (CD22) is highly selective for a number of sialic acid structures and the underlying glycans in its sialoside ligands.

MetaUniDec: High-Throughput Deconvolution of Native Mass Spectra

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Reid, Deseree J.; Diesing, Jessica M.; Miller, Matthew A.; Perry, Scott M.; Wales, Jessica A.; Montfort, William R.; Marty, Michael T.

2018-04-01

The expansion of native mass spectrometry (MS) methods for both academic and industrial applications has created a substantial need for analysis of large native MS datasets. Existing software tools are poorly suited for high-throughput deconvolution of native electrospray mass spectra from intact proteins and protein complexes. The UniDec Bayesian deconvolution algorithm is uniquely well suited for high-throughput analysis due to its speed and robustness but was previously tailored towards individual spectra. Here, we optimized UniDec for deconvolution, analysis, and visualization of large data sets. This new module, MetaUniDec, centers around a hierarchical data format 5 (HDF5) format for storing datasets that significantly improves speed, portability, and file size. It also includes code optimizations to improve speed and a new graphical user interface for visualization, interaction, and analysis of data. To demonstrate the utility of MetaUniDec, we applied the software to analyze automated collision voltage ramps with a small bacterial heme protein and large lipoprotein nanodiscs. Upon increasing collisional activation, bacterial heme-nitric oxide/oxygen binding (H-NOX) protein shows a discrete loss of bound heme, and nanodiscs show a continuous loss of lipids and charge. By using MetaUniDec to track changes in peak area or mass as a function of collision voltage, we explore the energetic profile of collisional activation in an ultra-high mass range Orbitrap mass spectrometer. [Figure not available: see fulltext.

Fragment-based drug discovery and molecular docking in drug design.

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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.

Computational and statistical methods for high-throughput mass spectrometry-based PTM analysis

DEFF Research Database (Denmark)

Schwämmle, Veit; Vaudel, Marc

2017-01-01

Cell signaling and functions heavily rely on post-translational modifications (PTMs) of proteins. Their high-throughput characterization is thus of utmost interest for multiple biological and medical investigations. In combination with efficient enrichment methods, peptide mass spectrometry analy...

Setting up a Bioluminescence Resonance Energy Transfer high throughput screening assay to search for protein/protein interaction inhibitors in mammalian cells.

Directory of Open Access Journals (Sweden)

Cyril eCouturier

2012-09-01

Full Text Available Each step of the cell life and its response or adaptation to its environment are mediated by a network of protein/protein interactions termed interactome. Our knowledge of this network keeps growing due to the development of sensitive techniques devoted to study these interactions. The bioluminescence resonance energy transfer (BRET technique was primarily developed to allow the dynamic monitoring of protein-protein interactions in living cells, and has widely been used to study receptor activation by intra- or extra-molecular conformational changes within receptors and activated complexes in mammal cells. Some interactions are described as crucial in human pathological processes, and a new class of drugs targeting them has recently emerged. The BRET method is well suited to identify inhibitors of protein-protein interactions and here is described why and how to set up and optimize a High Throughput Screening assay based on BRET to search for such inhibitory compounds. The different parameters to take into account when developing such BRET assays in mammal cells are reviewed to give general guidelines: considerations on the targeted interaction, choice of BRET version, inducibility of the interaction, kinetic of the monitored interaction, and of the BRET reading, influence substrate concentration, number of cells and medium composition used on the Z’ factor, and expected interferences for colored or fluorescent compounds.

The high throughput biomedicine unit at the institute for molecular medicine Finland: high throughput screening meets precision medicine.

Science.gov (United States)

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.

Prediction of homoprotein and heteroprotein complexes by protein docking and template-based modeling : A CASP-CAPRI experiment

NARCIS (Netherlands)

Lensink, Marc F.; Velankar, Sameer; Kryshtafovych, Andriy; Huang, Shen You; Schneidman-Duhovny, Dina; Sali, Andrej; Segura, Joan; Fernandez-Fuentes, Narcis; Viswanath, Shruthi; Elber, Ron; Grudinin, Sergei; Popov, Petr; Neveu, Emilie; Lee, Hasup; Baek, Minkyung; Park, Sangwoo; Heo, Lim; Rie Lee, Gyu; Seok, Chaok; Qin, Sanbo; Zhou, Huan Xiang; Ritchie, David W.; Maigret, Bernard; Devignes, Marie Dominique; Ghoorah, Anisah; Torchala, Mieczyslaw; Chaleil, Raphaël A G; Bates, Paul A.; Ben-Zeev, Efrat; Eisenstein, Miriam; Negi, Surendra S.; Weng, Zhiping; Vreven, Thom; Pierce, Brian G.; Borrman, Tyler M.; Yu, Jinchao; Ochsenbein, Françoise; Guerois, Raphaël; Vangone, Anna; Garcia Lopes Maia Rodrigues, João; van Zundert, Gydo; Nellen, Mehdi; Xue, Li; Karaca, Ezgi; Melquiond, Adrien S J; Visscher, Koen; Kastritis, Panagiotis L.; Bonvin, Alexandre M J J; Xu, Xianjin; Qiu, Liming; Yan, Chengfei; Li, Jilong; Ma, Zhiwei; Cheng, Jianlin; Zou, Xiaoqin; Shen, Yang; Peterson, Lenna X.; Kim, Hyung Rae; Roy, Amit; Han, Xusi; Esquivel-Rodriguez, Juan; Kihara, Daisuke; Yu, Xiaofeng; Bruce, Neil J.; Fuller, Jonathan C.; Wade, Rebecca C.; Anishchenko, Ivan; Kundrotas, Petras J.; Vakser, Ilya A.; Imai, Kenichiro; Yamada, Kazunori; Oda, Toshiyuki; Nakamura, Tsukasa; Tomii, Kentaro; Pallara, Chiara; Romero-Durana, Miguel; Jiménez-García, Brian; Moal, Iain H.; Férnandez-Recio, Juan; Joung, Jong Young; Kim, Jong Yun; Joo, Keehyoung; Lee, Jooyoung; Kozakov, Dima; Vajda, Sandor; Mottarella, Scott; Hall, David R.; Beglov, Dmitri; Mamonov, Artem; Xia, Bing; Bohnuud, Tanggis; Del Carpio, Carlos A.; Ichiishi, Eichiro; Marze, Nicholas; Kuroda, Daisuke; Roy Burman, Shourya S.; Gray, Jeffrey J.; Chermak, Edrisse; Cavallo, Luigi; Oliva, Romina; Tovchigrechko, Andrey; Wodak, Shoshana J.

2016-01-01

We present the results for CAPRI Round 30, the first joint CASP-CAPRI experiment, which brought together experts from the protein structure prediction and protein-protein docking communities. The Round comprised 25 targets from amongst those submitted for the CASP11 prediction experiment of 2014.

Prediction of homoprotein and heteroprotein complexes by protein docking and template-based modeling: A CASP-CAPRI experiment

NARCIS (Netherlands)

Lensink, Marc F.; Velankar, Sameer; Kryshtafovych, Andriy; Huang, Shen You; Schneidman-Duhovny, Dina; Sali, Andrej; Segura, Joan; Fernandez-Fuentes, Narcis; Viswanath, Shruthi; Elber, Ron; Grudinin, Sergei; Popov, Petr; Neveu, Emilie; Lee, Hasup; Baek, Minkyung; Park, Sangwoo; Heo, Lim; Lee, Gyu Rie; Seok, Chaok; Qin, Sanbo; Zhou, Huan Xiang; Ritchie, David W.; Maigret, Bernard; Devignes, Marie Dominique; Ghoorah, Anisah; Torchala, Mieczyslaw; Chaleil, Raphaël A.G.; Bates, Paul A.; Ben-Zeev, Efrat; Eisenstein, Miriam; Negi, Surendra S.; Weng, Zhiping; Vreven, Thom; Pierce, Brian G.; Borrman, Tyler M.; Yu, Jinchao; Ochsenbein, Françoise; Guerois, Raphaël; Vangone, Anna; Rodrigues, João P.G.L.M.; Van Zundert, Gydo; Nellen, Mehdi; Xue, Li; Karaca, Ezgi; Melquiond, Adrien S.J.; Visscher, Koen; Kastritis, Panagiotis L.; Bonvin, Alexandre M.J.J.; Xu, Xianjin; Qiu, Liming; Yan, Chengfei; Li, Jilong; Ma, Zhiwei; Cheng, Jianlin; Zou, Xiaoqin; Shen, Yang; Peterson, Lenna X.; Kim, Hyung Rae; Roy, Amit; Han, Xusi; Esquivel-Rodriguez, Juan; Kihara, Daisuke; Yu, Xiaofeng; Bruce, Neil J.; Fuller, Jonathan C.; Wade, Rebecca C.; Anishchenko, Ivan; Kundrotas, Petras J.; Vakser, Ilya A.; Imai, Kenichiro; Yamada, Kazunori; Oda, Toshiyuki; Nakamura, Tsukasa; Tomii, Kentaro; Pallara, Chiara; Romero-Durana, Miguel; Jiménez-García, Brian; Moal, Iain H.; Férnandez-Recio, Juan; Joung, Jong Young; Kim, Jong Yun; Joo, Keehyoung; Lee, Jooyoung; Kozakov, Dima; Vajda, Sandor; Mottarella, Scott; Hall, David R.; Beglov, Dmitri; Mamonov, Artem; Xia, Bing; Bohnuud, Tanggis; Del Carpio, Carlos A.; Ichiishi, Eichiro; Marze, Nicholas; Kuroda, Daisuke; Roy Burman, Shourya S.; Gray, Jeffrey J.; Chermak, Edrisse; Cavallo, Luigi; Oliva, Romina; Tovchigrechko, Andrey; Wodak, Shoshana J.

2016-01-01

We present the results for CAPRI Round 30, the first joint CASP-CAPRI experiment, which brought together experts from the protein structure prediction and protein-protein docking communities. The Round comprised 25 targets from amongst those submitted for the CASP11 prediction experiment of 2014.

ReFlexIn: a flexible receptor protein-ligand docking scheme evaluated on HIV-1 protease.

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Simon Leis

Full Text Available For many targets of pharmaceutical importance conformational changes of the receptor protein are relevant during the ligand binding process. A new docking approach, ReFlexIn (Receptor Flexibility by Interpolation, that combines receptor flexibility with the computationally efficient potential grid representation of receptor molecules has been evaluated on the retroviral HIV-1 (Human Immunodeficiency Virus 1 protease system. An approximate inclusion of receptor flexibility is achieved by using interpolation between grid representations of individual receptor conformations. For the retroviral protease the method was tested on an ensemble of protease structures crystallized in the presence of different ligands and on a set of structures obtained from morphing between the unbound and a ligand-bound protease structure. Docking was performed on ligands known to bind to the protease and several non-binders. For the binders the ReFlexIn method yielded in almost all cases ligand placements in similar or closer agreement with experiment than docking to any of the ensemble members without degrading the discrimination with respect to non-binders. The improved docking performance compared to docking to rigid receptors allows for systematic virtual screening applications at very small additional computational cost.

X-CHIP: an integrated platform for high-throughput protein crystallization and on-the-chip X-ray diffraction data collection

International Nuclear Information System (INIS)

Kisselman, Gera; Qiu, Wei; Romanov, Vladimir; Thompson, Christine M.; Lam, Robert; Battaile, Kevin P.; Pai, Emil F.; Chirgadze, Nickolay Y.

2011-01-01

The X-CHIP (X-ray Crystallography High-throughput Integrated Platform) is a novel microchip that has been developed to combine multiple steps of the crystallographic pipeline from crystallization to diffraction data collection on a single device to streamline the entire process. The X-CHIP (X-ray Crystallization High-throughput Integrated Platform) is a novel microchip that has been developed to combine multiple steps of the crystallographic pipeline from crystallization to diffraction data collection on a single device to streamline the entire process. The system has been designed for crystallization condition screening, visual crystal inspection, initial X-ray screening and data collection in a high-throughput fashion. X-ray diffraction data acquisition can be performed directly on-the-chip at room temperature using an in situ approach. The capabilities of the chip eliminate the necessity for manual crystal handling and cryoprotection of crystal samples, while allowing data collection from multiple crystals in the same drop. This technology would be especially beneficial for projects with large volumes of data, such as protein-complex studies and fragment-based screening. The platform employs hydrophilic and hydrophobic concentric ring surfaces on a miniature plate transparent to visible light and X-rays to create a well defined and stable microbatch crystallization environment. The results of crystallization and data-collection experiments demonstrate that high-quality well diffracting crystals can be grown and high-resolution diffraction data sets can be collected using this technology. Furthermore, the quality of a single-wavelength anomalous dispersion data set collected with the X-CHIP at room temperature was sufficient to generate interpretable electron-density maps. This technology is highly resource-efficient owing to the use of nanolitre-scale drop volumes. It does not require any modification for most in-house and synchrotron beamline systems and offers

X-CHIP: an integrated platform for high-throughput protein crystallization and on-the-chip X-ray diffraction data collection

Energy Technology Data Exchange (ETDEWEB)

Kisselman, Gera; Qiu, Wei; Romanov, Vladimir; Thompson, Christine M.; Lam, Robert [Ontario Cancer Institute, Princess Margaret Hospital, University Health Network, Toronto, Ontario M5G 2C4 (Canada); Battaile, Kevin P. [Argonne National Laboratory, Argonne, Illinois 60439 (United States); Pai, Emil F.; Chirgadze, Nickolay Y., E-mail: nchirgad@uhnresearch.ca [Ontario Cancer Institute, Princess Margaret Hospital, University Health Network, Toronto, Ontario M5G 2C4 (Canada); University of Toronto, Toronto, Ontario M5S 1A8 (Canada)

2011-06-01

The X-CHIP (X-ray Crystallography High-throughput Integrated Platform) is a novel microchip that has been developed to combine multiple steps of the crystallographic pipeline from crystallization to diffraction data collection on a single device to streamline the entire process. The X-CHIP (X-ray Crystallization High-throughput Integrated Platform) is a novel microchip that has been developed to combine multiple steps of the crystallographic pipeline from crystallization to diffraction data collection on a single device to streamline the entire process. The system has been designed for crystallization condition screening, visual crystal inspection, initial X-ray screening and data collection in a high-throughput fashion. X-ray diffraction data acquisition can be performed directly on-the-chip at room temperature using an in situ approach. The capabilities of the chip eliminate the necessity for manual crystal handling and cryoprotection of crystal samples, while allowing data collection from multiple crystals in the same drop. This technology would be especially beneficial for projects with large volumes of data, such as protein-complex studies and fragment-based screening. The platform employs hydrophilic and hydrophobic concentric ring surfaces on a miniature plate transparent to visible light and X-rays to create a well defined and stable microbatch crystallization environment. The results of crystallization and data-collection experiments demonstrate that high-quality well diffracting crystals can be grown and high-resolution diffraction data sets can be collected using this technology. Furthermore, the quality of a single-wavelength anomalous dispersion data set collected with the X-CHIP at room temperature was sufficient to generate interpretable electron-density maps. This technology is highly resource-efficient owing to the use of nanolitre-scale drop volumes. It does not require any modification for most in-house and synchrotron beamline systems and offers

A FRET-based high throughput screening assay to identify inhibitors of anthrax protective antigen binding to capillary morphogenesis gene 2 protein.

Directory of Open Access Journals (Sweden)

Michael S Rogers

Full Text Available Anti-angiogenic therapies are effective for the treatment of cancer, a variety of ocular diseases, and have potential benefits in cardiovascular disease, arthritis, and psoriasis. We have previously shown that anthrax protective antigen (PA, a non-pathogenic component of anthrax toxin, is an inhibitor of angiogenesis, apparently as a result of interaction with the cell surface receptors capillary morphogenesis gene 2 (CMG2 protein and tumor endothelial marker 8 (TEM8. Hence, molecules that bind the anthrax toxin receptors may be effective to slow or halt pathological vascular growth. Here we describe development and testing of an effective homogeneous steady-state fluorescence resonance energy transfer (FRET high throughput screening assay designed to identify molecules that inhibit binding of PA to CMG2. Molecules identified in the screen can serve as potential lead compounds for the development of anti-angiogenic and anti-anthrax therapies. The assay to screen for inhibitors of this protein-protein interaction is sensitive and robust, with observed Z' values as high as 0.92. Preliminary screens conducted with a library of known bioactive compounds identified tannic acid and cisplatin as inhibitors of the PA-CMG2 interaction. We have confirmed that tannic acid both binds CMG2 and has anti-endothelial properties. In contrast, cisplatin appears to inhibit PA-CMG2 interaction by binding both PA and CMG2, and observed cisplatin anti-angiogenic effects are not mediated by interaction with CMG2. This work represents the first reported high throughput screening assay targeting CMG2 to identify possible inhibitors of both angiogenesis and anthrax intoxication.

Streptococcus mutans Protein Synthesis during Mixed-Species Biofilm Development by High-Throughput Quantitative Proteomics

Science.gov (United States)

Klein, Marlise I.; Xiao, Jin; Lu, Bingwen; Delahunty, Claire M.; Yates, John R.; Koo, Hyun

2012-01-01

Biofilms formed on tooth surfaces are comprised of mixed microbiota enmeshed in an extracellular matrix. Oral biofilms are constantly exposed to environmental changes, which influence the microbial composition, matrix formation and expression of virulence. Streptococcus mutans and sucrose are key modulators associated with the evolution of virulent-cariogenic biofilms. In this study, we used a high-throughput quantitative proteomics approach to examine how S. mutans produces relevant proteins that facilitate its establishment and optimal survival during mixed-species biofilms development induced by sucrose. Biofilms of S. mutans, alone or mixed with Actinomyces naeslundii and Streptococcus oralis, were initially formed onto saliva-coated hydroxyapatite surface under carbohydrate-limiting condition. Sucrose (1%, w/v) was then introduced to cause environmental changes, and to induce biofilm accumulation. Multidimensional protein identification technology (MudPIT) approach detected up to 60% of proteins encoded by S. mutans within biofilms. Specific proteins associated with exopolysaccharide matrix assembly, metabolic and stress adaptation processes were highly abundant as the biofilm transit from earlier to later developmental stages following sucrose introduction. Our results indicate that S. mutans within a mixed-species biofilm community increases the expression of specific genes associated with glucan synthesis and remodeling (gtfBC, dexA) and glucan-binding (gbpB) during this transition (Pmutans up-regulates specific adaptation mechanisms to cope with acidic environments (F1F0-ATPase system, fatty acid biosynthesis, branched chain amino acids metabolism), and molecular chaperones (GroEL). Interestingly, the protein levels and gene expression are in general augmented when S. mutans form mixed-species biofilms (vs. single-species biofilms) demonstrating fundamental differences in the matrix assembly, survival and biofilm maintenance in the presence of other

Generalized schemes for high throughput manipulation of the Desulfovibrio vulgaris Hildenborough genome

Energy Technology Data Exchange (ETDEWEB)

Chhabra, S.R.; Butland, G.; Elias, D.; Chandonia, J.-M.; Fok, V.; Juba, T.; Gorur, A.; Allen, S.; Leung, C.-M.; Keller, K.; Reveco, S.; Zane, G.; Semkiw, E.; Prathapam, R.; Gold, B.; Singer, M.; Ouellet, M.; Sazakal, E.; Jorgens, D.; Price, M.; Witkowska, E.; Beller, H.; Hazen, T.C.; Biggin, M.; Auer, M.; Wall, J.; Keasling, J.

2011-07-15

The ability to conduct advanced functional genomic studies of the thousands of sequenced bacteria has been hampered by the lack of available tools for making high- throughput chromosomal manipulations in a systematic manner that can be applied across diverse species. In this work, we highlight the use of synthetic biological tools to assemble custom suicide vectors with reusable and interchangeable DNA “parts” to facilitate chromosomal modification at designated loci. These constructs enable an array of downstream applications including gene replacement and creation of gene fusions with affinity purification or localization tags. We employed this approach to engineer chromosomal modifications in a bacterium that has previously proven difficult to manipulate genetically, Desulfovibrio vulgaris Hildenborough, to generate a library of over 700 strains. Furthermore, we demonstrate how these modifications can be used for examining metabolic pathways, protein-protein interactions, and protein localization. The ubiquity of suicide constructs in gene replacement throughout biology suggests that this approach can be applied to engineer a broad range of species for a diverse array of systems biological applications and is amenable to high-throughput implementation.

A rapid enzymatic assay for high-throughput screening of adenosine-producing strains

Science.gov (United States)

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

Statistical removal of background signals from high-throughput 1H NMR line-broadening ligand-affinity screens

International Nuclear Information System (INIS)

Worley, Bradley; Sisco, Nicholas J.; Powers, Robert

2015-01-01

NMR ligand-affinity screens are vital to drug discovery, are routinely used to screen fragment-based libraries, and used to verify chemical leads from high-throughput assays and virtual screens. NMR ligand-affinity screens are also a highly informative first step towards identifying functional epitopes of unknown proteins, as well as elucidating the biochemical functions of protein–ligand interaction at their binding interfaces. While simple one-dimensional 1 H NMR experiments are capable of indicating binding through a change in ligand line shape, they are plagued by broad, ill-defined background signals from protein 1 H resonances. We present an uncomplicated method for subtraction of protein background in high-throughput ligand-based affinity screens, and show that its performance is maximized when phase-scatter correction is applied prior to subtraction

Incorporation of protein flexibility and conformational energy penalties in docking screens to improve ligand discovery

Science.gov (United States)

Fischer, Marcus; Coleman, Ryan G.; Fraser, James S.; Shoichet, Brian K.

2014-07-01

Proteins fluctuate between alternative conformations, which presents a challenge for ligand discovery because such flexibility is difficult to treat computationally owing to problems with conformational sampling and energy weighting. Here we describe a flexible docking method that samples and weights protein conformations using experimentally derived conformations as a guide. The crystallographically refined occupancies of these conformations, which are observable in an apo receptor structure, define energy penalties for docking. In a large prospective library screen, we identified new ligands that target specific receptor conformations of a cavity in cytochrome c peroxidase, and we confirm both ligand pose and associated receptor conformation predictions by crystallography. The inclusion of receptor flexibility led to ligands with new chemotypes and physical properties. By exploiting experimental measures of loop and side-chain flexibility, this method can be extended to the discovery of new ligands for hundreds of targets in the Protein Data Bank for which similar experimental information is available.

High throughput sample processing and automated scoring

Directory of Open Access Journals (Sweden)

Gunnar eBrunborg

2014-10-01

Full Text Available The comet assay is a sensitive and versatile method for assessing DNA damage in cells. In the traditional version of the assay, there are many manual steps involved and few samples can be treated in one experiment. High throughput modifications have been developed during recent years, and they are reviewed and discussed. These modifications include accelerated scoring of comets; other important elements that have been studied and adapted to high throughput are cultivation and manipulation of cells or tissues before and after exposure, and freezing of treated samples until comet analysis and scoring. High throughput methods save time and money but they are useful also for other reasons: large-scale experiments may be performed which are otherwise not practicable (e.g., analysis of many organs from exposed animals, and human biomonitoring studies, and automation gives more uniform sample treatment and less dependence on operator performance. The high throughput modifications now available vary largely in their versatility, capacity, complexity and costs. The bottleneck for further increase of throughput appears to be the scoring.

Mass Spectrometry-based Assay for High Throughput and High Sensitivity Biomarker Verification

Energy Technology Data Exchange (ETDEWEB)

Guo, Xuejiang; Tang, Keqi

2017-06-14

Searching for disease specific biomarkers has become a major undertaking in the biomedical research field as the effective diagnosis, prognosis and treatment of many complex human diseases are largely determined by the availability and the quality of the biomarkers. A successful biomarker as an indicator to a specific biological or pathological process is usually selected from a large group of candidates by a strict verification and validation process. To be clinically useful, the validated biomarkers must be detectable and quantifiable by the selected testing techniques in their related tissues or body fluids. Due to its easy accessibility, protein biomarkers would ideally be identified in blood plasma or serum. However, most disease related protein biomarkers in blood exist at very low concentrations (<1ng/mL) and are “masked” by many none significant species at orders of magnitude higher concentrations. The extreme requirements of measurement sensitivity, dynamic range and specificity make the method development extremely challenging. The current clinical protein biomarker measurement primarily relies on antibody based immunoassays, such as ELISA. Although the technique is sensitive and highly specific, the development of high quality protein antibody is both expensive and time consuming. The limited capability of assay multiplexing also makes the measurement an extremely low throughput one rendering it impractical when hundreds to thousands potential biomarkers need to be quantitatively measured across multiple samples. Mass spectrometry (MS)-based assays have recently shown to be a viable alternative for high throughput and quantitative candidate protein biomarker verification. Among them, the triple quadrupole MS based assay is the most promising one. When it is coupled with liquid chromatography (LC) separation and electrospray ionization (ESI) source, a triple quadrupole mass spectrometer operating in a special selected reaction monitoring (SRM) mode

Empirical scoring functions for advanced protein-ligand docking with PLANTS.

Science.gov (United States)

Korb, Oliver; Stützle, Thomas; Exner, Thomas E

2009-01-01

In this paper we present two empirical scoring functions, PLANTS(CHEMPLP) and PLANTS(PLP), designed for our docking algorithm PLANTS (Protein-Ligand ANT System), which is based on ant colony optimization (ACO). They are related, regarding their functional form, to parts of already published scoring functions and force fields. The parametrization procedure described here was able to identify several parameter settings showing an excellent performance for the task of pose prediction on two test sets comprising 298 complexes in total. Up to 87% of the complexes of the Astex diverse set and 77% of the CCDC/Astex clean listnc (noncovalently bound complexes of the clean list) could be reproduced with root-mean-square deviations of less than 2 A with respect to the experimentally determined structures. A comparison with the state-of-the-art docking tool GOLD clearly shows that this is, especially for the druglike Astex diverse set, an improvement in pose prediction performance. Additionally, optimized parameter settings for the search algorithm were identified, which can be used to balance pose prediction reliability and search speed.

Discovery of novel inhibitors of Mycobacterium tuberculosis MurG: homology modelling, structure based pharmacophore, molecular docking, and molecular dynamics simulations.

Science.gov (United States)

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.

Automated high-throughput protein purification using an ÄKTApurifier and a CETAC autosampler.

Science.gov (United States)

Yoo, Daniel; Provchy, Justin; Park, Cynthia; Schulz, Craig; Walker, Kenneth

2014-05-30

As the pace of drug discovery accelerates there is an increased focus on screening larger numbers of protein therapeutic candidates to identify those that are functionally superior and to assess manufacturability earlier in the process. Although there have been advances toward high throughput (HT) cloning and expression, protein purification is still an area where improvements can be made to conventional techniques. Current methodologies for purification often involve a tradeoff between HT automation or capacity and quality. We present an ÄKTA combined with an autosampler, the ÄKTA-AS, which has the capability of purifying up to 240 samples in two chromatographic dimensions without the need for user intervention. The ÄKTA-AS has been shown to be reliable with sample volumes between 0.5 mL and 100 mL, and the innovative use of a uniquely configured loading valve ensures reliability by efficiently removing air from the system as well as preventing sample cross contamination. Incorporation of a sample pump flush minimizes sample loss and enables recoveries ranging from the low tens of micrograms to milligram quantities of protein. In addition, when used in an affinity capture-buffer exchange format the final samples are formulated in a buffer compatible with most assays without requirement of additional downstream processing. The system is designed to capture samples in 96-well microplate format allowing for seamless integration of downstream HT analytic processes such as microfluidic or HPLC analysis. Most notably, there is minimal operator intervention to operate this system, thereby increasing efficiency, sample consistency and reducing the risk of human error. Copyright © 2014 Elsevier B.V. All rights reserved.

High Throughput Neuro-Imaging Informatics

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Michael I Miller

2013-12-01

Full Text Available This paper describes neuroinformatics technologies at 1 mm anatomical scale based on high throughput 3D functional and structural imaging technologies of the human brain. The core is an abstract pipeline for converting functional and structural imagery into their high dimensional neuroinformatic representations index containing O(E3-E4 discriminating dimensions. The pipeline is based on advanced image analysis coupled to digital knowledge representations in the form of dense atlases of the human brain at gross anatomical scale. We demonstrate the integration of these high-dimensional representations with machine learning methods, which have become the mainstay of other fields of science including genomics as well as social networks. Such high throughput facilities have the potential to alter the way medical images are stored and utilized in radiological workflows. The neuroinformatics pipeline is used to examine cross-sectional and personalized analyses of neuropsychiatric illnesses in clinical applications as well as longitudinal studies. We demonstrate the use of high throughput machine learning methods for supporting (i cross-sectional image analysis to evaluate the health status of individual subjects with respect to the population data, (ii integration of image and non-image information for diagnosis and prognosis.

An in silico high-throughput screen identifies potential selective inhibitors for the non-receptor tyrosine kinase Pyk2

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Meirson T

2017-05-01

Full Text Available Tomer Meirson, Abraham O Samson, Hava Gil-Henn Faculty of Medicine in the Galilee, Bar-Ilan University, Safed, Israel Abstract: 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. Keywords: virtual screen, efficiency metrics, MM-GBSA, molecular dynamics

Flavivirus NS3 and NS5 proteins interaction network: a high-throughput yeast two-hybrid screen

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Canard Bruno

2011-10-01

Full Text Available Abstract Background The genus Flavivirus encompasses more than 50 distinct species of arthropod-borne viruses, including several major human pathogens, such as West Nile virus, yellow fever virus, Japanese encephalitis virus and the four serotypes of dengue viruses (DENV type 1-4. Each year, flaviviruses cause more than 100 million infections worldwide, some of which lead to life-threatening conditions such as encephalitis or haemorrhagic fever. Among the viral proteins, NS3 and NS5 proteins constitute the major enzymatic components of the viral replication complex and are essential to the flavivirus life cycle. Results We report here the results of a high-throughput yeast two-hybrid screen to identify the interactions between human host proteins and the flavivirus NS3 and NS5 proteins. Using our screen results and literature curation, we performed a global analysis of the NS3 and NS5 cellular targets based on functional annotation with the Gene Ontology features. We finally created the first flavivirus NS3 and NS5 proteins interaction network and analysed the topological features of this network. Our proteome mapping screen identified 108 human proteins interacting with NS3 or NS5 proteins or both. The global analysis of the cellular targets revealed the enrichment of host proteins involved in RNA binding, transcription regulation, vesicular transport or innate immune response regulation. Conclusions We proposed that the selective disruption of these newly identified host/virus interactions could represent a novel and attractive therapeutic strategy in treating flavivirus infections. Our virus-host interaction map provides a basis to unravel fundamental processes about flavivirus subversion of the host replication machinery and/or immune defence strategy.

Integrated analysis of RNA-binding protein complexes using in vitro selection and high-throughput sequencing and sequence specificity landscapes (SEQRS).

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Lou, Tzu-Fang; Weidmann, Chase A; Killingsworth, Jordan; Tanaka Hall, Traci M; Goldstrohm, Aaron C; Campbell, Zachary T

2017-04-15

RNA-binding proteins (RBPs) collaborate to control virtually every aspect of RNA function. Tremendous progress has been made in the area of global assessment of RBP specificity using next-generation sequencing approaches both in vivo and in vitro. Understanding how protein-protein interactions enable precise combinatorial regulation of RNA remains a significant problem. Addressing this challenge requires tools that can quantitatively determine the specificities of both individual proteins and multimeric complexes in an unbiased and comprehensive way. One approach utilizes in vitro selection, high-throughput sequencing, and sequence-specificity landscapes (SEQRS). We outline a SEQRS experiment focused on obtaining the specificity of a multi-protein complex between Drosophila RBPs Pumilio (Pum) and Nanos (Nos). We discuss the necessary controls in this type of experiment and examine how the resulting data can be complemented with structural and cell-based reporter assays. Additionally, SEQRS data can be integrated with functional genomics data to uncover biological function. Finally, we propose extensions of the technique that will enhance our understanding of multi-protein regulatory complexes assembled onto RNA. Copyright © 2016 Elsevier Inc. All rights reserved.

FlexAID: Revisiting Docking on Non-Native-Complex Structures.

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Gaudreault, Francis; Najmanovich, Rafael J

2015-07-27

Small-molecule protein docking is an essential tool in drug design and to understand molecular recognition. In the present work we introduce FlexAID, a small-molecule docking algorithm that accounts for target side-chain flexibility and utilizes a soft scoring function, i.e. one that is not highly dependent on specific geometric criteria, based on surface complementarity. The pairwise energy parameters were derived from a large dataset of true positive poses and negative decoys from the PDBbind database through an iterative process using Monte Carlo simulations. The prediction of binding poses is tested using the widely used Astex dataset as well as the HAP2 dataset, while performance in virtual screening is evaluated using a subset of the DUD dataset. We compare FlexAID to AutoDock Vina, FlexX, and rDock in an extensive number of scenarios to understand the strengths and limitations of the different programs as well as to reported results for Glide, GOLD, and DOCK6 where applicable. The most relevant among these scenarios is that of docking on flexible non-native-complex structures where as is the case in reality, the target conformation in the bound form is not known a priori. We demonstrate that FlexAID, unlike other programs, is robust against increasing structural variability. FlexAID obtains equivalent sampling success as GOLD and performs better than AutoDock Vina or FlexX in all scenarios against non-native-complex structures. FlexAID is better than rDock when there is at least one critical side-chain movement required upon ligand binding. In virtual screening, FlexAID results are lower on average than those of AutoDock Vina and rDock. The higher accuracy in flexible targets where critical movements are required, intuitive PyMOL-integrated graphical user interface and free source code as well as precompiled executables for Windows, Linux, and Mac OS make FlexAID a welcome addition to the arsenal of existing small-molecule protein docking methods.

Molecular Docking Explains Atomic Interaction between Plant-originated Ligands and Oncogenic E7 Protein of High Risk Human Papillomavirus Type 16

Directory of Open Access Journals (Sweden)

Satish Kumar

2014-12-01

Full Text Available Cervical cancer caused by Human papillomavirus (HPV is one of the leading causes of cancer mortality in women worldwide, particularly in the developing countries. In the last few decades, various compounds from plant origin such as Curcumin, Epigallocatechin gallate (EGCG, Jaceosidin, Resveratrol etc. have been used as anti cancer therapeutic agents. Different studies have shown these plant-originated compounds are able to suppress HPV infection. The E6 and E7 oncoproteins of high-risk HPV play a key role in HPV related cancers. In this study, we explored these ligands from plants origin against E7 oncoprotein of high risk HPV 16, which is known to inactivate tumor suppressor pRb protein. A robust homology model of HPV 16 E7 was built to foresee the interaction mechanism of E7 oncoprotein with these ligands using structure-based drug designing approach. Docking studies demonstrate the interaction of these ligands with pRb binding site of E7 protein by residues Tyr52, Asn53, Val55, Phe57, Cys59, Ser63, Thr64, Thr72, Arg77, Glu80 and Asp81 and help restoration of pRb functioning. This in silico based atomic interaction between these ligands and E7 protein may assist in validating the plant-originated ligands as effective drugs against HPV.

Na(+),K (+)-ATPase as a docking station: protein-protein complexes of the Na(+),K (+)-ATPase.

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Reinhard, Linda; Tidow, Henning; Clausen, Michael J; Nissen, Poul

2013-01-01

The Na(+),K(+)-ATPase, or sodium pump, is well known for its role in ion transport across the plasma membrane of animal cells. It carries out the transport of Na(+) ions out of the cell and of K(+) ions into the cell and thus maintains electrolyte and fluid balance. In addition to the fundamental ion-pumping function of the Na(+),K(+)-ATPase, recent work has suggested additional roles for Na(+),K(+)-ATPase in signal transduction and biomembrane structure. Several signaling pathways have been found to involve Na(+),K(+)-ATPase, which serves as a docking station for a fast-growing number of protein interaction partners. In this review, we focus on Na(+),K(+)-ATPase as a signal transducer, but also briefly discuss other Na(+),K(+)-ATPase protein-protein interactions, providing a comprehensive overview of the diverse signaling functions ascribed to this well-known enzyme.

High-throughput simultaneous analysis of RNA, protein, and lipid biomarkers in heterogeneous tissue samples.

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Reiser, Vladimír; Smith, Ryan C; Xue, Jiyan; Kurtz, Marc M; Liu, Rong; Legrand, Cheryl; He, Xuanmin; Yu, Xiang; Wong, Peggy; Hinchcliffe, John S; Tanen, Michael R; Lazar, Gloria; Zieba, Renata; Ichetovkin, Marina; Chen, Zhu; O'Neill, Edward A; Tanaka, Wesley K; Marton, Matthew J; Liao, Jason; Morris, Mark; Hailman, Eric; Tokiwa, George Y; Plump, Andrew S

2011-11-01

With expanding biomarker discovery efforts and increasing costs of drug development, it is critical to maximize the value of mass-limited clinical samples. The main limitation of available methods is the inability to isolate and analyze, from a single sample, molecules requiring incompatible extraction methods. Thus, we developed a novel semiautomated method for tissue processing and tissue milling and division (TMAD). We used a SilverHawk atherectomy catheter to collect atherosclerotic plaques from patients requiring peripheral atherectomy. Tissue preservation by flash freezing was compared with immersion in RNAlater®, and tissue grinding by traditional mortar and pestle was compared with TMAD. Comparators were protein, RNA, and lipid yield and quality. Reproducibility of analyte yield from aliquots of the same tissue sample processed by TMAD was also measured. The quantity and quality of biomarkers extracted from tissue prepared by TMAD was at least as good as that extracted from tissue stored and prepared by traditional means. TMAD enabled parallel analysis of gene expression (quantitative reverse-transcription PCR, microarray), protein composition (ELISA), and lipid content (biochemical assay) from as little as 20 mg of tissue. The mean correlation was r = 0.97 in molecular composition (RNA, protein, or lipid) between aliquots of individual samples generated by TMAD. We also demonstrated that it is feasible to use TMAD in a large-scale clinical study setting. The TMAD methodology described here enables semiautomated, high-throughput sampling of small amounts of heterogeneous tissue specimens by multiple analytical techniques with generally improved quality of recovered biomolecules.

High-throughput screening of filamentous fungi using nanoliter-range droplet-based microfluidics

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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.

Gateway-compatible vectors for high-throughput protein expression in pro- and eukaryotic cell-free systems.

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Gagoski, Dejan; Mureev, Sergey; Giles, Nichole; Johnston, Wayne; Dahmer-Heath, Mareike; Škalamera, Dubravka; Gonda, Thomas J; Alexandrov, Kirill

2015-02-10

Although numerous techniques for protein expression and production are available the pace of genome sequencing outstrips our ability to analyze the encoded proteins. To address this bottleneck, we have established a system for parallelized cloning, DNA production and cell-free expression of large numbers of proteins. This system is based on a suite of pCellFree Gateway destination vectors that utilize a Species Independent Translation Initiation Sequence (SITS) that mediates recombinant protein expression in any in vitro translation system. These vectors introduce C or N terminal EGFP and mCherry fluorescent and affinity tags, enabling direct analysis and purification of the expressed proteins. To maximize throughput and minimize the cost of protein production we combined Gateway cloning with Rolling Circle DNA Amplification. We demonstrate that as little as 0.1 ng of plasmid DNA is sufficient for template amplification and production of recombinant human protein in Leishmania tarentolae and Escherichia coli cell-free expression systems. Our experiments indicate that this approach can be applied to large gene libraries as it can be reliably performed in multi-well plates. The resulting protein expression pipeline provides a valuable new tool for applications of the post genomic era. Copyright © 2014 Elsevier B.V. All rights reserved.

A robust robotic high-throughput antibody purification platform.

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Schmidt, Peter M; Abdo, Michael; Butcher, Rebecca E; Yap, Min-Yin; Scotney, Pierre D; Ramunno, Melanie L; Martin-Roussety, Genevieve; Owczarek, Catherine; Hardy, Matthew P; Chen, Chao-Guang; Fabri, Louis J

2016-07-15

Monoclonal antibodies (mAbs) have become the fastest growing segment in the drug market with annual sales of more than 40 billion US$ in 2013. The selection of lead candidate molecules involves the generation of large repertoires of antibodies from which to choose a final therapeutic candidate. Improvements in the ability to rapidly produce and purify many antibodies in sufficient quantities reduces the lead time for selection which ultimately impacts on the speed with which an antibody may transition through the research stage and into product development. Miniaturization and automation of chromatography using micro columns (RoboColumns(®) from Atoll GmbH) coupled to an automated liquid handling instrument (ALH; Freedom EVO(®) from Tecan) has been a successful approach to establish high throughput process development platforms. Recent advances in transient gene expression (TGE) using the high-titre Expi293F™ system have enabled recombinant mAb titres of greater than 500mg/L. These relatively high protein titres reduce the volume required to generate several milligrams of individual antibodies for initial biochemical and biological downstream assays, making TGE in the Expi293F™ system ideally suited to high throughput chromatography on an ALH. The present publication describes a novel platform for purifying Expi293F™-expressed recombinant mAbs directly from cell-free culture supernatant on a Perkin Elmer JANUS-VariSpan ALH equipped with a plate shuttle device. The purification platform allows automated 2-step purification (Protein A-desalting/size exclusion chromatography) of several hundred mAbs per week. The new robotic method can purify mAbs with high recovery (>90%) at sub-milligram level with yields of up to 2mg from 4mL of cell-free culture supernatant. Copyright © 2016 Elsevier B.V. All rights reserved.

A docking study of enhanced intracellular survival protein from Mycobacterium tuberculosis with human DUSP16/MKP-7

International Nuclear Information System (INIS)

Yoon, Hye-Jin; Kim, Kyoung Hoon; Yang, Jin Kuk; Suh, Se Won; Kim, Hyunsik; Jang, Soonmin

2013-01-01

A docking study of Mtb Eis with its substrate DUSP16/MKP-7 was performed. The docking model suggests dissociation of hexameric Mtb Eis into dimers or monomers. The intracellular pathogen Mycobacterium tuberculosis (Mtb) causes tuberculosis, and one of its secreted effector proteins, called enhanced intracellular survival (Eis) protein, enhances its survival in macrophages. Mtb Eis activates JNK-specific dual-specificity protein phosphatase 16 (DUSP16)/mitogen-activated protein kinase phosphatase-7 (MKP-7) through the acetylation on Lys55, thus inactivating JNK by dephosphorylation. Based on the recently reported crystal structure of Mtb Eis, a docking model for the binding of Mtb Eis to DUSP16/MKP-7 was generated. In the docking model, the substrate helix containing Lys55 of DUSP16/MKP-7 fits nicely into the active-site cleft of Mtb Eis; the twisted β-sheet of Eis domain II embraces the substrate helix from one side. Most importantly, the side-chain of Lys55 is inserted toward acetyl-CoA and the resulting distance is 4.6 Å between the NZ atom of Lys55 and the carbonyl carbon of the acetyl group in acetyl-CoA. The binding of Mtb Eis and DUSP16/MKP-7 is maintained by strong electrostatic interactions. The active-site cleft of Mtb Eis has a negatively charged surface formed by Asp25, Glu138, Asp286, Glu395 and the terminal carboxylic group of Phe396. In contrast, DUSP16/MKP-7 contains five basic residues, Lys52, Lys55, Arg56, Arg57 and Lys62, which point toward the negatively charged surface of the active-site pocket of Mtb Eis. Thus, the current docking model suggests that the binding of DUSP16/MKP-7 to Mtb Eis should be established by charge complementarity in addition to a very favorable geometric arrangement. The suggested mode of binding requires the dissociation of the hexameric Mtb Eis into dimers or monomers. This study may be useful for future studies aiming to develop inhibitors of Mtb Eis as a new anti-tuberculosis drug candidate

A docking study of enhanced intracellular survival protein from Mycobacterium tuberculosis with human DUSP16/MKP-7

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Yoon, Hye-Jin, E-mail: yoonhj@snu.ac.kr; Kim, Kyoung Hoon [Seoul National University, Seoul 151-747 (Korea, Republic of); Yang, Jin Kuk [Soongsil University, Seoul 156-743 (Korea, Republic of); Suh, Se Won [Seoul National University, Seoul 151-747 (Korea, Republic of); Seoul National University, Seoul 151-747 (Korea, Republic of); Kim, Hyunsik; Jang, Soonmin, E-mail: yoonhj@snu.ac.kr [Sejong University, Seoul 143-747 (Korea, Republic of)

2013-11-01

A docking study of Mtb Eis with its substrate DUSP16/MKP-7 was performed. The docking model suggests dissociation of hexameric Mtb Eis into dimers or monomers. The intracellular pathogen Mycobacterium tuberculosis (Mtb) causes tuberculosis, and one of its secreted effector proteins, called enhanced intracellular survival (Eis) protein, enhances its survival in macrophages. Mtb Eis activates JNK-specific dual-specificity protein phosphatase 16 (DUSP16)/mitogen-activated protein kinase phosphatase-7 (MKP-7) through the acetylation on Lys55, thus inactivating JNK by dephosphorylation. Based on the recently reported crystal structure of Mtb Eis, a docking model for the binding of Mtb Eis to DUSP16/MKP-7 was generated. In the docking model, the substrate helix containing Lys55 of DUSP16/MKP-7 fits nicely into the active-site cleft of Mtb Eis; the twisted β-sheet of Eis domain II embraces the substrate helix from one side. Most importantly, the side-chain of Lys55 is inserted toward acetyl-CoA and the resulting distance is 4.6 Å between the NZ atom of Lys55 and the carbonyl carbon of the acetyl group in acetyl-CoA. The binding of Mtb Eis and DUSP16/MKP-7 is maintained by strong electrostatic interactions. The active-site cleft of Mtb Eis has a negatively charged surface formed by Asp25, Glu138, Asp286, Glu395 and the terminal carboxylic group of Phe396. In contrast, DUSP16/MKP-7 contains five basic residues, Lys52, Lys55, Arg56, Arg57 and Lys62, which point toward the negatively charged surface of the active-site pocket of Mtb Eis. Thus, the current docking model suggests that the binding of DUSP16/MKP-7 to Mtb Eis should be established by charge complementarity in addition to a very favorable geometric arrangement. The suggested mode of binding requires the dissociation of the hexameric Mtb Eis into dimers or monomers. This study may be useful for future studies aiming to develop inhibitors of Mtb Eis as a new anti-tuberculosis drug candidate.

A simple and reliable approach to docking protein-protein complexes from very sparse NOE-derived intermolecular distance restraints

International Nuclear Information System (INIS)

Tang, Chun; Clore, G. Marius

2006-01-01

A simple and reliable approach for docking protein-protein complexes from very sparse NOE-derived intermolecular distance restraints (as few as three from a single point) in combination with a novel representation for an attractive potential between mapped interaction surfaces is described. Unambiguous assignments of very sparse intermolecular NOEs are obtained using a reverse labeling strategy in which one the components is fully deuterated with the exception of selective protonation of the δ-methyl groups of isoleucine, while the other component is uniformly 13 C-labeled. This labeling strategy can be readily extended to selective protonation of Ala, Leu, Val or Met. The attractive potential is described by a 'reduced' radius of gyration potential applied specifically to a subset of interfacial residues (those with an accessible surface area ≥ 50% in the free proteins) that have been delineated by chemical shift perturbation. Docking is achieved by rigid body minimization on the basis of a target function comprising the sparse NOE distance restraints, a van der Waals repulsion potential and the 'reduced' radius of gyration potential. The method is demonstrated for two protein-protein complexes (EIN-HPr and IIA Glc -HPr) from the bacterial phosphotransferase system. In both cases, starting from 100 different random orientations of the X-ray structures of the free proteins, 100% convergence is achieved to a single cluster (with near identical atomic positions) with an overall backbone accuracy of ∼2 A. The approach described is not limited to NMR, since interfaces can also be mapped by alanine scanning mutagenesis, and sparse intermolecular distance restraints can be derived from double cycle mutagenesis, cross-linking combined with mass spectrometry, or fluorescence energy transfer

Rosetta FlexPepDock ab-initio: simultaneous folding, docking and refinement of peptides onto their receptors.

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Raveh, Barak; London, Nir; Zimmerman, Lior; Schueler-Furman, Ora

2011-04-29

Flexible peptides that fold upon binding to another protein molecule mediate a large number of regulatory interactions in the living cell and may provide highly specific recognition modules. We present Rosetta FlexPepDock ab-initio, a protocol for simultaneous docking and de-novo folding of peptides, starting from an approximate specification of the peptide binding site. Using the Rosetta fragments library and a coarse-grained structural representation of the peptide and the receptor, FlexPepDock ab-initio samples efficiently and simultaneously the space of possible peptide backbone conformations and rigid-body orientations over the receptor surface of a given binding site. The subsequent all-atom refinement of the coarse-grained models includes full side-chain modeling of both the receptor and the peptide, resulting in high-resolution models in which key side-chain interactions are recapitulated. The protocol was applied to a benchmark in which peptides were modeled over receptors in either their bound backbone conformations or in their free, unbound form. Near-native peptide conformations were identified in 18/26 of the bound cases and 7/14 of the unbound cases. The protocol performs well on peptides from various classes of secondary structures, including coiled peptides with unusual turns and kinks. The results presented here significantly extend the scope of state-of-the-art methods for high-resolution peptide modeling, which can now be applied to a wide variety of peptide-protein interactions where no prior information about the peptide backbone conformation is available, enabling detailed structure-based studies and manipulation of those interactions. © 2011 Raveh et al.

Some Aspects of Crystal Centering During X-ray High-throughput Protein Crystallography Experiment

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Gaponov, Yu. A.; Matsugaki, N.; Sasajima, K.; Igarashi, N.; Wakatsuki, S.

A set of algorithms and procedures of a crystal loop centering during X-ray high-throughput protein crystallography experiment has been designed and developed. A simple algorithm of the crystal loop detection and preliminary recognition has been designed and developed. The crystal loop detection algorithm is based on finding out the crystal loop ending point (opposite to the crystal loop pin) using image cross section (digital image column) profile analysis. The crystal loop preliminary recognition procedure is based on finding out the crystal loop sizes and position using image cross section profile analysis. The crystal loop fine recognition procedure based on Hooke-Jeeves pattern search method with an ellipse as a fitting pattern has been designed and developed. The procedure of restoring missing coordinate of the crystal loop is described. Based on developed algorithms and procedures the optimal auto-centering procedure has been designed and developed. A procedure of optimal manual crystal centering (Two Clicks Procedure) has been designed and developed. Developed procedures have been integrated into control software system PCCS installed at crystallography beamlines Photon Factory BL5A and PF-AR NW12, KEK.

An Evaluation of Explicit Receptor Flexibility in Molecular Docking Using Molecular Dynamics and Torsion Angle Molecular Dynamics.

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Armen, Roger S; Chen, Jianhan; Brooks, Charles L

2009-10-13

Incorporating receptor flexibility into molecular docking should improve results for flexible proteins. However, the incorporation of explicit all-atom flexibility with molecular dynamics for the entire protein chain may also introduce significant error and "noise" that could decrease docking accuracy and deteriorate the ability of a scoring function to rank native-like poses. We address this apparent paradox by comparing the success of several flexible receptor models in cross-docking and multiple receptor ensemble docking for p38α mitogen-activated protein (MAP) kinase. Explicit all-atom receptor flexibility has been incorporated into a CHARMM-based molecular docking method (CDOCKER) using both molecular dynamics (MD) and torsion angle molecular dynamics (TAMD) for the refinement of predicted protein-ligand binding geometries. These flexible receptor models have been evaluated, and the accuracy and efficiency of TAMD sampling is directly compared to MD sampling. Several flexible receptor models are compared, encompassing flexible side chains, flexible loops, multiple flexible backbone segments, and treatment of the entire chain as flexible. We find that although including side chain and some backbone flexibility is required for improved docking accuracy as expected, docking accuracy also diminishes as additional and unnecessary receptor flexibility is included into the conformational search space. Ensemble docking results demonstrate that including protein flexibility leads to to improved agreement with binding data for 227 active compounds. This comparison also demonstrates that a flexible receptor model enriches high affinity compound identification without significantly increasing the number of false positives from low affinity compounds.

High Throughput Transcriptomics @ USEPA (Toxicology ...

Science.gov (United States)

The ideal chemical testing approach will provide complete coverage of all relevant toxicological responses. It should be sensitive and specific It should identify the mechanism/mode-of-action (with dose-dependence). It should identify responses relevant to the species of interest. Responses should ideally be translated into tissue-, organ-, and organism-level effects. It must be economical and scalable. Using a High Throughput Transcriptomics platform within US EPA provides broader coverage of biological activity space and toxicological MOAs and helps fill the toxicological data gap. Slide presentation at the 2016 ToxForum on using High Throughput Transcriptomics at US EPA for broader coverage biological activity space and toxicological MOAs.

Leptospira borgpetersenii hybrid leucine-rich repeat protein: Cloning and expression, immunogenic identification and molecular docking evaluation.

Science.gov (United States)

Sritrakul, Tepyuda; Nitipan, Supachai; Wajjwalku, Worawidh; La-Ard, Anchalee; Suphatpahirapol, Chattip; Petkarnjanapong, Wimol; Ongphiphadhanakul, Boonsong; Prapong, Siriwan

2017-11-01

Leptospirosis is an important zoonotic disease, and the major outbreak of this disease in Thailand in 1999 was due largely to the Leptospira borgpetersenii serovar Sejroe. Identification of the leucine-rich repeat (LRR) LBJ_2271 protein containing immunogenic epitopes and the discovery of the LBJ_2271 ortholog in Leptospira serovar Sejroe, KU_Sej_R21_2271, led to further studies of the antigenic immune properties of KU_Sej_LRR_2271. The recombinant hybrid (rh) protein was created and expressed from a hybrid PCR fragment of KU_Sej_R21_2271 fused with DNA encoding the LBJ_2271 signal sequence for targeting protein as a membrane-anchoring protein. The fusion DNA was cloned into pET160/GW/D-TOPO® to form the pET160_hKU_R21_2271 plasmid. The plasmid was used to express the rhKU_Sej_LRR_2271 protein in Escherichia coli BL21 Star™ (DE3). The expressed protein was immunologically detected by Western blotting and immunoreactivity detection with hyperimmune sera, T cell epitope prediction by HLA allele and epitope peptide binding affinity, and potential T cell reactivity analysis. The immunogenic epitopes of the protein were evaluated and verified by HLA allele and epitope peptide complex structure molecular docking. Among fourteen best allele epitopes of this protein, binding affinity values of 12 allele epitopes remained unchanged compared to LBJ_2271. Two epitopes for alleles HLA-A0202 and -A0301 had higher IC 50 values, while T cell reactivity values of these peptides were better than values from LBJ_2271 epitopes. Eight of twelve epitope peptides had positive T-cell reactivity scores. Although the molecular docking of two epitopes, 3FPLLKEFLV11/47FPLLKEFLV55 and 50KLSTVPEGV58, into an HLA-A0202 model revealed a good fit in the docked structures, 50KLSTVPEGV58 and 94KLSTVPEEV102 are still considered as the proteins' best epitopes for allele HLA-A0202. The results of this study showed that rhKU_Sej_LRR_2271 protein contained natural immunological properties that should

Application of ToxCast High-Throughput Screening and ...

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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

High-throughput screening identifies Ceefourin 1 and Ceefourin 2 as highly selective inhibitors of multidrug resistance protein 4 (MRP4).

Science.gov (United States)

Cheung, Leanna; Flemming, Claudia L; Watt, Fujiko; Masada, Nanako; Yu, Denise M T; Huynh, Tony; Conseil, Gwenaëlle; Tivnan, Amanda; Polinsky, Alexander; Gudkov, Andrei V; Munoz, Marcia A; Vishvanath, Anasuya; Cooper, Dermot M F; Henderson, Michelle J; Cole, Susan P C; Fletcher, Jamie I; Haber, Michelle; Norris, Murray D

2014-09-01

Multidrug resistance protein 4 (MRP4/ABCC4), a member of the ATP-binding cassette (ABC) transporter superfamily, is an organic anion transporter capable of effluxing a wide range of physiologically important signalling molecules and drugs. MRP4 has been proposed to contribute to numerous functions in both health and disease; however, in most cases these links remain to be unequivocally established. A major limitation to understanding the physiological and pharmacological roles of MRP4 has been the absence of specific small molecule inhibitors, with the majority of established inhibitors also targeting other ABC transporter family members, or inhibiting the production, function or degradation of important MRP4 substrates. We therefore set out to identify more selective and well tolerated inhibitors of MRP4 that might be used to study the many proposed functions of this transporter. Using high-throughput screening, we identified two chemically distinct small molecules, Ceefourin 1 and Ceefourin 2, that inhibit transport of a broad range of MRP4 substrates, yet are highly selective for MRP4 over other ABC transporters, including P-glycoprotein (P-gp), ABCG2 (Breast Cancer Resistance Protein; BCRP) and MRP1 (multidrug resistance protein 1; ABCC1). Both compounds are more potent MRP4 inhibitors in cellular assays than the most widely used inhibitor, MK-571, requiring lower concentrations to effect a comparable level of inhibition. Furthermore, Ceefourin 1 and Ceefourin 2 have low cellular toxicity, and high microsomal and acid stability. These newly identified inhibitors should be of great value for efforts to better understand the biological roles of MRP4, and may represent classes of compounds with therapeutic application. Copyright © 2014 Elsevier Inc. All rights reserved.

Subnuclear foci quantification using high-throughput 3D image cytometry

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Wadduwage, Dushan N.; Parrish, Marcus; Choi, Heejin; Engelward, Bevin P.; Matsudaira, Paul; So, Peter T. C.

2015-07-01

Ionising radiation causes various types of DNA damages including double strand breaks (DSBs). DSBs are often recognized by DNA repair protein ATM which forms gamma-H2AX foci at the site of the DSBs that can be visualized using immunohistochemistry. However most of such experiments are of low throughput in terms of imaging and image analysis techniques. Most of the studies still use manual counting or classification. Hence they are limited to counting a low number of foci per cell (5 foci per nucleus) as the quantification process is extremely labour intensive. Therefore we have developed a high throughput instrumentation and computational pipeline specialized for gamma-H2AX foci quantification. A population of cells with highly clustered foci inside nuclei were imaged, in 3D with submicron resolution, using an in-house developed high throughput image cytometer. Imaging speeds as high as 800 cells/second in 3D were achieved by using HiLo wide-field depth resolved imaging and a remote z-scanning technique. Then the number of foci per cell nucleus were quantified using a 3D extended maxima transform based algorithm. Our results suggests that while most of the other 2D imaging and manual quantification studies can count only up to about 5 foci per nucleus our method is capable of counting more than 100. Moreover we show that 3D analysis is significantly superior compared to the 2D techniques.

A high throughput DNA extraction method with high yield and quality

Directory of Open Access Journals (Sweden)

Xin Zhanguo

2012-07-01

Full Text Available Abstract Background Preparation of large quantity and high quality genomic DNA from a large number of plant samples is a major bottleneck for most genetic and genomic analyses, such as, genetic mapping, TILLING (Targeting Induced Local Lesion IN Genome, and next-generation sequencing directly from sheared genomic DNA. A variety of DNA preparation methods and commercial kits are available. However, they are either low throughput, low yield, or costly. Here, we describe a method for high throughput genomic DNA isolation from sorghum [Sorghum bicolor (L. Moench] leaves and dry seeds with high yield, high quality, and affordable cost. Results We developed a high throughput DNA isolation method by combining a high yield CTAB extraction method with an improved cleanup procedure based on MagAttract kit. The method yielded large quantity and high quality DNA from both lyophilized sorghum leaves and dry seeds. The DNA yield was improved by nearly 30 fold with 4 times less consumption of MagAttract beads. The method can also be used in other plant species, including cotton leaves and pine needles. Conclusion A high throughput system for DNA extraction from sorghum leaves and seeds was developed and validated. The main advantages of the method are low cost, high yield, high quality, and high throughput. One person can process two 96-well plates in a working day at a cost of $0.10 per sample of magnetic beads plus other consumables that other methods will also need.

A simple and reliable approach to docking protein-protein complexes from very sparse NOE-derived intermolecular distance restraints

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Tang, Chun; Clore, G. Marius [National Institutes of Health, Laboratory of Chemical Physics, National Institute of Diabetes and Digestive and Kidney Diseases (United States)], E-mail: mariusc@intra.niddk.nih.gov

2006-09-15

A simple and reliable approach for docking protein-protein complexes from very sparse NOE-derived intermolecular distance restraints (as few as three from a single point) in combination with a novel representation for an attractive potential between mapped interaction surfaces is described. Unambiguous assignments of very sparse intermolecular NOEs are obtained using a reverse labeling strategy in which one the components is fully deuterated with the exception of selective protonation of the {delta}-methyl groups of isoleucine, while the other component is uniformly {sup 13}C-labeled. This labeling strategy can be readily extended to selective protonation of Ala, Leu, Val or Met. The attractive potential is described by a 'reduced' radius of gyration potential applied specifically to a subset of interfacial residues (those with an accessible surface area {>=} 50% in the free proteins) that have been delineated by chemical shift perturbation. Docking is achieved by rigid body minimization on the basis of a target function comprising the sparse NOE distance restraints, a van der Waals repulsion potential and the 'reduced' radius of gyration potential. The method is demonstrated for two protein-protein complexes (EIN-HPr and IIA{sup Glc}-HPr) from the bacterial phosphotransferase system. In both cases, starting from 100 different random orientations of the X-ray structures of the free proteins, 100% convergence is achieved to a single cluster (with near identical atomic positions) with an overall backbone accuracy of {approx}2 A. The approach described is not limited to NMR, since interfaces can also be mapped by alanine scanning mutagenesis, and sparse intermolecular distance restraints can be derived from double cycle mutagenesis, cross-linking combined with mass spectrometry, or fluorescence energy transfer.

Development of a high-throughput method for the systematic identification of human proteins nuclear translocation potential

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Kawai Jun

2009-09-01

Full Text Available Abstract Background Important clues to the function of novel and uncharacterized proteins can be obtained by identifying their ability to translocate in the nucleus. In addition, a comprehensive definition of the nuclear proteome undoubtedly represents a key step toward a better understanding of the biology of this organelle. Although several high-throughput experimental methods have been developed to explore the sub-cellular localization of proteins, these methods tend to focus on the predominant localizations of gene products and may fail to provide a complete catalog of proteins that are able to transiently locate into the nucleus. Results We have developed a method for examining the nuclear localization potential of human gene products at the proteome scale by adapting a mammalian two-hybrid system we have previously developed. Our system is composed of three constructs co-transfected into a mammalian cell line. First, it contains a PCR construct encoding a fusion protein composed of a tested protein, the PDZ-protein TIP-1, and the transactivation domain of TNNC2 (referred to as ACT construct. Second, our system contains a PCR construct encoding a fusion protein composed of the DNA binding domain of GAL4 and the PDZ binding domain of rhotekin (referred to as the BIND construct. Third, a GAL4-responsive luciferase reporter is used to detect the reconstitution of a transcriptionally active BIND-ACT complex through the interaction of TIP-1 and rhotekin, which indicates the ability of the tested protein to translocate into the nucleus. We validated our method in a small-scale feasibility study by comparing it to green fluorescent protein (GFP fusion-based sub-cellular localization assays, sequence-based computational prediction of protein sub-cellular localization, and current sub-cellular localization data available from the literature for 22 gene products. Conclusion Our reporter-based system can rapidly screen gene products for their ability

CrossCheck: an open-source web tool for high-throughput screen data analysis.

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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.

Identification of Rift Valley fever virus nucleocapsid protein-RNA binding inhibitors using a high-throughput screening assay.

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Ellenbecker, Mary; Lanchy, Jean-Marc; Lodmell, J Stephen

2012-09-01

Rift Valley fever virus (RVFV) is an emerging infectious pathogen that causes severe disease in humans and livestock and has the potential for global spread. Currently, there is no proven effective treatment for RVFV infection, and there is no licensed vaccine. Inhibition of RNA binding to the essential viral nucleocapsid (N) protein represents a potential antiviral therapeutic strategy because all of the functions performed by N during infection involve RNA binding. To target this interaction, we developed a fluorescence polarization-based high-throughput drug-screening assay and tested 26 424 chemical compounds for their ability to disrupt an N-RNA complex. From libraries of Food and Drug Administration-approved drugs, druglike molecules, and natural product extracts, we identified several lead compounds that are promising candidates for medicinal chemistry.

Automated image alignment for 2D gel electrophoresis in a high-throughput proteomics pipeline.

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Dowsey, Andrew W; Dunn, Michael J; Yang, Guang-Zhong

2008-04-01

The quest for high-throughput proteomics has revealed a number of challenges in recent years. Whilst substantial improvements in automated protein separation with liquid chromatography and mass spectrometry (LC/MS), aka 'shotgun' proteomics, have been achieved, large-scale open initiatives such as the Human Proteome Organization (HUPO) Brain Proteome Project have shown that maximal proteome coverage is only possible when LC/MS is complemented by 2D gel electrophoresis (2-DE) studies. Moreover, both separation methods require automated alignment and differential analysis to relieve the bioinformatics bottleneck and so make high-throughput protein biomarker discovery a reality. The purpose of this article is to describe a fully automatic image alignment framework for the integration of 2-DE into a high-throughput differential expression proteomics pipeline. The proposed method is based on robust automated image normalization (RAIN) to circumvent the drawbacks of traditional approaches. These use symbolic representation at the very early stages of the analysis, which introduces persistent errors due to inaccuracies in modelling and alignment. In RAIN, a third-order volume-invariant B-spline model is incorporated into a multi-resolution schema to correct for geometric and expression inhomogeneity at multiple scales. The normalized images can then be compared directly in the image domain for quantitative differential analysis. Through evaluation against an existing state-of-the-art method on real and synthetically warped 2D gels, the proposed analysis framework demonstrates substantial improvements in matching accuracy and differential sensitivity. High-throughput analysis is established through an accelerated GPGPU (general purpose computation on graphics cards) implementation. Supplementary material, software and images used in the validation are available at http://www.proteomegrid.org/rain/.

Chromatographic Monoliths for High-Throughput Immunoaffinity Isolation of Transferrin from Human Plasma

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Irena Trbojević-Akmačić

2016-06-01

Full Text Available Changes in protein glycosylation are related to different diseases and have a potential as diagnostic and prognostic disease biomarkers. Transferrin (Tf glycosylation changes are common marker for congenital disorders of glycosylation. However, biological interindividual variability of Tf N-glycosylation and genes involved in glycosylation regulation are not known. Therefore, high-throughput Tf isolation method and large scale glycosylation studies are needed in order to address these questions. Due to their unique chromatographic properties, the use of chromatographic monoliths enables very fast analysis cycle, thus significantly increasing sample preparation throughput. Here, we are describing characterization of novel immunoaffinity-based monolithic columns in a 96-well plate format for specific high-throughput purification of human Tf from blood plasma. We optimized the isolation and glycan preparation procedure for subsequent ultra performance liquid chromatography (UPLC analysis of Tf N-glycosylation and managed to increase the sensitivity for approximately three times compared to initial experimental conditions, with very good reproducibility. This work is licensed under a Creative Commons Attribution 4.0 International License.

Emory University: High-Throughput Protein-Protein Interaction Dataset for Lung Cancer-Associated Genes | Office of Cancer Genomics

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To discover novel PPI signaling hubs for lung cancer, CTD2 Center at Emory utilized large-scale genomics datasets and literature to compile a set of lung cancer-associated genes. A library of expression vectors were generated for these genes and utilized for detecting pairwise PPIs with cell lysate-based TR-FRET assays in high-throughput screening format. Read the abstract.

Identification of natural compound inhibitors for multidrug efflux pumps of Escherichia coli and Pseudomonas aeruginosa using in silico high-throughput virtual screening and in vitro validation.

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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

Identification of natural compound inhibitors for multidrug efflux pumps of Escherichia coli and Pseudomonas aeruginosa using in silico high-throughput virtual screening and in vitro validation.

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Vasudevan Aparna

Full Text Available 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

Adaptation to high throughput batch chromatography enhances multivariate screening.

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Barker, Gregory A; Calzada, Joseph; Herzer, Sibylle; Rieble, Siegfried

2015-09-01

High throughput process development offers unique approaches to explore complex process design spaces with relatively low material consumption. Batch chromatography is one technique that can be used to screen chromatographic conditions in a 96-well plate. Typical batch chromatography workflows examine variations in buffer conditions or comparison of multiple resins in a given process, as opposed to the assessment of protein loading conditions in combination with other factors. A modification to the batch chromatography paradigm is described here where experimental planning, programming, and a staggered loading approach increase the multivariate space that can be explored with a liquid handling system. The iterative batch chromatography (IBC) approach is described, which treats every well in a 96-well plate as an individual experiment, wherein protein loading conditions can be varied alongside other factors such as wash and elution buffer conditions. As all of these factors are explored in the same experiment, the interactions between them are characterized and the number of follow-up confirmatory experiments is reduced. This in turn improves statistical power and throughput. Two examples of the IBC method are shown and the impact of the load conditions are assessed in combination with the other factors explored. Copyright © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Protein Comparability Assessments and Potential Applicability of High Throughput Biophysical Methods and Data Visualization Tools to Compare Physical Stability Profiles

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Mohammad A. Alsenaidy

2014-03-01

Full Text Available In this review, some of the challenges and opportunities encountered during protein comparability assessments are summarized with an emphasis on developing new analytical approaches to better monitor higher-order protein structures. Several case studies are presented using high throughput biophysical methods to collect protein physical stability data as function of temperature, agitation, ionic strength and/or solution pH. These large data sets were then used to construct empirical phase diagrams (EPDs, radar charts, and comparative signature diagrams (CSDs for data visualization and structural comparisons between the different proteins. Protein samples with different sizes, post-translational modifications, and inherent stability are presented: acidic fibroblast growth factor (FGF-1 mutants, different glycoforms of an IgG1 mAb prepared by deglycosylation, as well as comparisons of different formulations of an IgG1 mAb and granulocyte colony stimulating factor (GCSF. Using this approach, differences in structural integrity and conformational stability profiles were detected under stress conditions that could not be resolved by using the same techniques under ambient conditions (i.e., no stress. Thus, an evaluation of conformational stability differences may serve as an effective surrogate to monitor differences in higher-order structure between protein samples. These case studies are discussed in the context of potential utility in protein comparability studies.

Protein comparability assessments and potential applicability of high throughput biophysical methods and data visualization tools to compare physical stability profiles.

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Alsenaidy, Mohammad A; Jain, Nishant K; Kim, Jae H; Middaugh, C Russell; Volkin, David B

2014-01-01

In this review, some of the challenges and opportunities encountered during protein comparability assessments are summarized with an emphasis on developing new analytical approaches to better monitor higher-order protein structures. Several case studies are presented using high throughput biophysical methods to collect protein physical stability data as function of temperature, agitation, ionic strength and/or solution pH. These large data sets were then used to construct empirical phase diagrams (EPDs), radar charts, and comparative signature diagrams (CSDs) for data visualization and structural comparisons between the different proteins. Protein samples with different sizes, post-translational modifications, and inherent stability are presented: acidic fibroblast growth factor (FGF-1) mutants, different glycoforms of an IgG1 mAb prepared by deglycosylation, as well as comparisons of different formulations of an IgG1 mAb and granulocyte colony stimulating factor (GCSF). Using this approach, differences in structural integrity and conformational stability profiles were detected under stress conditions that could not be resolved by using the same techniques under ambient conditions (i.e., no stress). Thus, an evaluation of conformational stability differences may serve as an effective surrogate to monitor differences in higher-order structure between protein samples. These case studies are discussed in the context of potential utility in protein comparability studies.

A high content, high throughput cellular thermal stability assay for measuring drug-target engagement in living cells.

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Massey, Andrew J

2018-01-01

Determining and understanding drug target engagement is critical for drug discovery. This can be challenging within living cells as selective readouts are often unavailable. Here we describe a novel method for measuring target engagement in living cells based on the principle of altered protein thermal stabilization / destabilization in response to ligand binding. This assay (HCIF-CETSA) utilizes high content, high throughput single cell immunofluorescent detection to determine target protein levels following heating of adherent cells in a 96 well plate format. We have used target engagement of Chk1 by potent small molecule inhibitors to validate the assay. Target engagement measured by this method was subsequently compared to target engagement measured by two alternative methods (autophosphorylation and CETSA). The HCIF-CETSA method appeared robust and a good correlation in target engagement measured by this method and CETSA for the selective Chk1 inhibitor V158411 was observed. However, these EC50 values were 23- and 12-fold greater than the autophosphorylation IC50. The described method is therefore a valuable advance in the CETSA method allowing the high throughput determination of target engagement in adherent cells.

A high-throughput surface plasmon resonance biosensor based on differential interferometric imaging

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Wang, Daqian; Ding, Lili; Zhang, Wei; Zhang, Enyao; Yu, Xinglong; Luo, Zhaofeng; Ou, Huichao

2012-01-01

A new high-throughput surface plasmon resonance (SPR) biosensor based on differential interferometric imaging is reported. The two SPR interferograms of the sensing surface are imaged on two CCD cameras. The phase difference between the two interferograms is 180°. The refractive index related factor (RIRF) of the sensing surface is calculated from the two simultaneously acquired interferograms. The simulation results indicate that the RIRF exhibits a linear relationship with the refractive index of the sensing surface and is unaffected by the noise, drift and intensity distribution of the light source. The affinity and kinetic information can be extracted in real time from continuously acquired RIRF distributions. The results of refractometry experiments show that the dynamic detection range of SPR differential interferometric imaging system can be over 0.015 refractive index unit (RIU). High refractive index resolution is down to 0.45 RU (1 RU = 1 × 10 −6 RIU). Imaging and protein microarray experiments demonstrate the ability of high-throughput detection. The aptamer experiments demonstrate that the SPR sensor based on differential interferometric imaging has a great capability to be implemented for high-throughput aptamer kinetic evaluation. These results suggest that this biosensor has the potential to be utilized in proteomics and drug discovery after further improvement. (paper)

Rapid 2,2'-bicinchoninic-based xylanase assay compatible with high throughput screening

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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...

Using high-throughput barcode sequencing to efficiently map connectomes.

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Peikon, Ian D; Kebschull, Justus M; Vagin, Vasily V; Ravens, Diana I; Sun, Yu-Chi; Brouzes, Eric; Corrêa, Ivan R; Bressan, Dario; Zador, Anthony M

2017-07-07

The function of a neural circuit is determined by the details of its synaptic connections. At present, the only available method for determining a neural wiring diagram with single synapse precision-a 'connectome'-is based on imaging methods that are slow, labor-intensive and expensive. Here, we present SYNseq, a method for converting the connectome into a form that can exploit the speed and low cost of modern high-throughput DNA sequencing. In SYNseq, each neuron is labeled with a unique random nucleotide sequence-an RNA 'barcode'-which is targeted to the synapse using engineered proteins. Barcodes in pre- and postsynaptic neurons are then associated through protein-protein crosslinking across the synapse, extracted from the tissue, and joined into a form suitable for sequencing. Although our failure to develop an efficient barcode joining scheme precludes the widespread application of this approach, we expect that with further development SYNseq will enable tracing of complex circuits at high speed and low cost. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

A high-throughput fluorescence resonance energy transfer (FRET)-based endothelial cell apoptosis assay and its application for screening vascular disrupting agents

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Zhu, Xiaoming; Fu, Afu; Luo, Kathy Qian

2012-01-01

Highlights: ► An endothelial cell apoptosis assay using FRET-based biosensor was developed. ► The fluorescence of the cells changed from green to blue during apoptosis. ► This method was developed into a high-throughput assay in 96-well plates. ► This assay was applied to screen vascular disrupting agents. -- Abstract: In this study, we developed a high-throughput endothelial cell apoptosis assay using a fluorescence resonance energy transfer (FRET)-based biosensor. After exposure to apoptotic inducer UV-irradiation or anticancer drugs such as paclitaxel, the fluorescence of the cells changed from green to blue. We developed this method into a high-throughput assay in 96-well plates by measuring the emission ratio of yellow fluorescent protein (YFP) to cyan fluorescent protein (CFP) to monitor the activation of a key protease, caspase-3, during apoptosis. The Z′ factor for this assay was above 0.5 which indicates that this assay is suitable for a high-throughput analysis. Finally, we applied this functional high-throughput assay for screening vascular disrupting agents (VDA) which could induce endothelial cell apoptosis from our in-house compounds library and dioscin was identified as a hit. As this assay allows real time and sensitive detection of cell apoptosis, it will be a useful tool for monitoring endothelial cell apoptosis in living cell situation and for identifying new VDA candidates via a high-throughput screening.

High Throughput PBTK: Open-Source Data and Tools for ...

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Presentation on High Throughput PBTK at the PBK Modelling in Risk Assessment meeting in Ispra, Italy Presentation on High Throughput PBTK at the PBK Modelling in Risk Assessment meeting in Ispra, Italy

Molecular docking study of Papaver alkaloids to some alkaloid receptors

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A. Nofallah

2017-11-01

Full Text Available Background and objectives: More than 40 different alkaloids have been obtained from opium the most important of which are morphine, codeine, papaverine, noscapine and tabaine. Opioid alkaloids produce analgesia by affecting areas of the brain that have peptides with pharmacological pseudo-opioid properties. These alkaloids show important effects on some intracellular peptides like mu, delta, and kappa receptors. Therefore, studying the effects of these alkaloids on different receptors is essential. Methods: Molecular docking is a well-known method in exploring the protein-ligand interactions. In this research, five important alkaloids were docked to crystal structure of human mu opioid receptor (4DKL, human delta opioid receptor (4EJ4 and human kappa opioid receptor (4DJH which were retrieved from protein databank. The 3D-structures of alkaloids were drawn by chembiooffice2010 and minimized with hyperchem package and submitted to molecular docking utilizing autodock-vina. Flexibility of the proteins was considered. The docking studies were performed to compare the affinity of these five alkaloids to the mentioned receptors. Results: We computationally docked each alkaloid compound onto each receptor structure and estimated their binding affinity based on dock scores. Dock score is a criteria including binding energy which utilized here for prediction and comparison of the binding affinities. Binding interactions of the docked alkaloids in receptor pockets were also visually inspected and compared. Conclusion: In this approach, using docking study as a computational method provided a valuable insight of opioid receptor pocket structures which would be essential to design more efficient drugs in pain managements and addiction treatments.

Modeling complexes of modeled proteins.

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Anishchenko, Ivan; Kundrotas, Petras J; Vakser, Ilya A

2017-03-01

Structural characterization of proteins is essential for understanding life processes at the molecular level. However, only a fraction of known proteins have experimentally determined structures. This fraction is even smaller for protein-protein complexes. Thus, structural modeling of protein-protein interactions (docking) primarily has to rely on modeled structures of the individual proteins, which typically are less accurate than the experimentally determined ones. Such "double" modeling is the Grand Challenge of structural reconstruction of the interactome. Yet it remains so far largely untested in a systematic way. We present a comprehensive validation of template-based and free docking on a set of 165 complexes, where each protein model has six levels of structural accuracy, from 1 to 6 Å C α RMSD. Many template-based docking predictions fall into acceptable quality category, according to the CAPRI criteria, even for highly inaccurate proteins (5-6 Å RMSD), although the number of such models (and, consequently, the docking success rate) drops significantly for models with RMSD > 4 Å. The results show that the existing docking methodologies can be successfully applied to protein models with a broad range of structural accuracy, and the template-based docking is much less sensitive to inaccuracies of protein models than the free docking. Proteins 2017; 85:470-478. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Sensitivity of molecular docking to induced fit effects in influenza virus neuraminidase

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Birch, Louise; Murray, Christopher W.; Hartshorn, Michael J.; Tickle, Ian J.; Verdonk, Marcel L.

2002-12-01

Many proteins undergo small side chain or even backbone movements on binding of different ligands into the same protein structure. This is known as induced fit and is potentially problematic for virtual screening of databases against protein targets. In this report we investigate the limits of the rigid protein approximation used by the docking program, GOLD, through cross-docking using protein structures of influenza neuraminidase. Neuraminidase is known to exhibit small but significant induced fit effects on ligand binding. Some neuraminidase crystal structures caused concern due to the bound ligand conformation and GOLD performed poorly on these complexes. A `clean' set, which contained unique, unambiguous complexes, was defined. For this set, the lowest energy structure was correctly docked (i.e. RMSD < 1.5 Å away from the crystal reference structure) in 84% of proteins, and the most promiscuous protein (1mwe) was able to dock all 15 ligands accurately including those that normally required an induced fit movement. This is considerably better than the 70% success rate seen with GOLD against general validation sets. Inclusion of specific water molecules involved in water-mediated hydrogen bonds did not significantly improve the docking performance for ligands that formed water-mediated contacts but it did prevent docking of ligands that displaced these waters. Our data supports the use of a single protein structure for virtual screening with GOLD in some applications involving induced fit effects, although care must be taken to identify the protein structure that performs best against a wide variety of ligands. The performance of GOLD was significantly better than the GOLD implementation of ChemScore and the reasons for this are discussed. Overall, GOLD has shown itself to be an extremely good, robust docking program for this system.

Design of a High-Throughput Biological Crystallography Beamline for Superconducting Wiggler

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Tseng, P.C.; Chang, C.H.; Fung, H.S.; Ma, C.I.; Huang, L.J.; Jean, Y.C.; Song, Y.F.; Huang, Y.S.; Tsang, K.L.; Chen, C.T.

2004-01-01

We are constructing a high-throughput biological crystallography beamline BL13B, which utilizes the radiation generated from a 3.2 Tesla, 32-pole superconducting multipole wiggler, for multi-wavelength anomalous diffraction (MAD), single-wavelength anomalous diffraction (SAD), and other related experiments. This beamline is a standard double crystal monochromator (DCM) x-ray beamline equipped with a collimating mirror (CM) and a focusing mirror (FM). Both the CM and FM are one meter long and made of Si substrate, and the CM is side-cooled by water. Based on detailed thermal analysis, liquid nitrogen (LN2) cooling for both crystals of the DCM has been adopted to optimize the energy resolution and photon beam throughput. This beamline will deliver, through a 100 μm diameter pinhole, photon flux of greater than 1011 photons/sec in the energy range from 6.5 keV to 19 keV, which is comparable to existing protein crystallography beamlines from bending magnet source at high energy storage rings

A cross docking pipeline for improving pose prediction and virtual screening performance

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Kumar, Ashutosh; Zhang, Kam Y. J.

2018-01-01

Pose prediction and virtual screening performance of a molecular docking method depend on the choice of protein structures used for docking. Multiple structures for a target protein are often used to take into account the receptor flexibility and problems associated with a single receptor structure. However, the use of multiple receptor structures is computationally expensive when docking a large library of small molecules. Here, we propose a new cross-docking pipeline suitable to dock a large library of molecules while taking advantage of multiple target protein structures. Our method involves the selection of a suitable receptor for each ligand in a screening library utilizing ligand 3D shape similarity with crystallographic ligands. We have prospectively evaluated our method in D3R Grand Challenge 2 and demonstrated that our cross-docking pipeline can achieve similar or better performance than using either single or multiple-receptor structures. Moreover, our method displayed not only decent pose prediction performance but also better virtual screening performance over several other methods.

High Diversity of Myocyanophage in Various Aquatic Environments Revealed by High-Throughput Sequencing of Major Capsid Protein Gene With a New Set of Primers

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Weiguo Hou

2018-05-01

Full Text Available Myocyanophages, a group of viruses infecting cyanobacteria, are abundant and play important roles in elemental cycling. Here we investigated the particle-associated viral communities retained on 0.2 μm filters and in sediment samples (representing ancient cyanophage communities from four ocean and three lake locations, using high-throughput sequencing and a newly designed primer pair targeting a gene fragment (∼145-bp in length encoding the cyanophage gp23 major capsid protein (MCP. Diverse viral communities were detected in all samples. The fragments of 142-, 145-, and 148-bp in length were most abundant in the amplicons, and most sequences (>92% belonged to cyanophages. Additionally, different sequencing depths resulted in different diversity estimates of the viral community. Operational taxonomic units obtained from deep sequencing of the MCP gene covered the majority of those obtained from shallow sequencing, suggesting that deep sequencing exhibited a more complete picture of cyanophage community than shallow sequencing. Our results also revealed a wide geographic distribution of marine myocyanophages, i.e., higher dissimilarities of the myocyanophage communities corresponded with the larger distances between the sampling sites. Collectively, this study suggests that the newly designed primer pair can be effectively used to study the community and diversity of myocyanophage from different environments, and the high-throughput sequencing represents a good method to understand viral diversity.

Rationalization of activity cliffs of a sulfonamide inhibitor of DNA methyltransferases with induced-fit docking.

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Medina-Franco, José L; Méndez-Lucio, Oscar; Yoo, Jakyung

2014-02-21

Inhibitors of human DNA methyltransferases (DNMT) are of increasing interest to develop novel epi-drugs for the treatment of cancer and other diseases. As the number of compounds with reported DNMT inhibition is increasing, molecular docking is shedding light to elucidate their mechanism of action and further interpret structure-activity relationships. Herein, we present a structure-based rationalization of the activity of SW155246, a distinct sulfonamide compound recently reported as an inhibitor of human DNMT1 obtained from high-throughput screening. We used flexible and induce-fit docking to develop a binding model of SW155246 with a crystallographic structure of human DNMT1. Results were in excellent agreement with experimental information providing a three-dimensional structural interpretation of 'activity cliffs', e.g., analogues of SW155246 with a high structural similarity to the sulfonamide compound, but with no activity in the enzymatic assay.

Rationalization of Activity Cliffs of a Sulfonamide Inhibitor of DNA Methyltransferases with Induced-Fit Docking

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José L. Medina-Franco

2014-02-01

Full Text Available Inhibitors of human DNA methyltransferases (DNMT are of increasing interest to develop novel epi-drugs for the treatment of cancer and other diseases. As the number of compounds with reported DNMT inhibition is increasing, molecular docking is shedding light to elucidate their mechanism of action and further interpret structure–activity relationships. Herein, we present a structure-based rationalization of the activity of SW155246, a distinct sulfonamide compound recently reported as an inhibitor of human DNMT1 obtained from high-throughput screening. We used flexible and induce-fit docking to develop a binding model of SW155246 with a crystallographic structure of human DNMT1. Results were in excellent agreement with experimental information providing a three-dimensional structural interpretation of ‘activity cliffs’, e.g., analogues of SW155246 with a high structural similarity to the sulfonamide compound, but with no activity in the enzymatic assay.

Meta-Analysis of High-Throughput Datasets Reveals Cellular Responses Following Hemorrhagic Fever Virus Infection

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Gavin C. Bowick

2011-05-01

Full Text Available The continuing use of high-throughput assays to investigate cellular responses to infection is providing a large repository of information. Due to the large number of differentially expressed transcripts, often running into the thousands, the majority of these data have not been thoroughly investigated. Advances in techniques for the downstream analysis of high-throughput datasets are providing additional methods for the generation of additional hypotheses for further investigation. The large number of experimental observations, combined with databases that correlate particular genes and proteins with canonical pathways, functions and diseases, allows for the bioinformatic exploration of functional networks that may be implicated in replication or pathogenesis. Herein, we provide an example of how analysis of published high-throughput datasets of cellular responses to hemorrhagic fever virus infection can generate additional functional data. We describe enrichment of genes involved in metabolism, post-translational modification and cardiac damage; potential roles for specific transcription factors and a conserved involvement of a pathway based around cyclooxygenase-2. We believe that these types of analyses can provide virologists with additional hypotheses for continued investigation.

High throughput screening method for assessing heterogeneity of microorganisms

NARCIS (Netherlands)

Ingham, C.J.; Sprenkels, A.J.; van Hylckama Vlieg, J.E.T.; Bomer, Johan G.; de Vos, W.M.; van den Berg, Albert

2006-01-01

The invention relates to the field of microbiology. Provided is a method which is particularly powerful for High Throughput Screening (HTS) purposes. More specific a high throughput method for determining heterogeneity or interactions of microorganisms is provided.

HAMS: High-Affinity Mass Spectrometry Screening. A High-Throughput Screening Method for Identifying the Tightest-Binding Lead Compounds for Target Proteins with No False Positive Identifications.

Science.gov (United States)

Imaduwage, Kasun P; Go, Eden P; Zhu, Zhikai; Desaire, Heather

2016-11-01

A major challenge in drug discovery is the identification of high affinity lead compounds that bind a particular target protein; these leads are typically identified by high throughput screens. Mass spectrometry has become a detection method of choice in drug screening assays because the target and the ligand need not be modified. Label-free assays are advantageous because they can be developed more rapidly than assays requiring labels, and they eliminate the risk of the label interfering with the binding event. However, in commonly used MS-based screening methods, detection of false positives is a major challenge. Here, we describe a detection strategy designed to eliminate false positives. In this approach, the protein and the ligands are incubated together, and the non-binders are separated for detection. Hits (protein binders) are not detectable by MS after incubation with the protein, but readily identifiable by MS when the target protein is not present in the incubation media. The assay was demonstrated using three different proteins and hundreds of non-inhibitors; no false positive hits were identified in any experiment. The assay can be tuned to select for ligands of a particular binding affinity by varying the quantity of protein used and the immobilization method. As examples, the method selectively detected inhibitors that have K i values of 0.2 μM, 50 pM, and 700 pM. These findings demonstrate that the approach described here compares favorably with traditional MS-based screening methods. Graphical Abstract ᅟ.

High-Throughput Analysis of Enzyme Activities

Energy Technology Data Exchange (ETDEWEB)

Lu, Guoxin [Iowa State Univ., Ames, IA (United States)

2007-01-01

High-throughput screening (HTS) techniques have been applied to many research fields nowadays. Robot microarray printing technique and automation microtiter handling technique allows HTS performing in both heterogeneous and homogeneous formats, with minimal sample required for each assay element. In this dissertation, new HTS techniques for enzyme activity analysis were developed. First, patterns of immobilized enzyme on nylon screen were detected by multiplexed capillary system. The imaging resolution is limited by the outer diameter of the capillaries. In order to get finer images, capillaries with smaller outer diameters can be used to form the imaging probe. Application of capillary electrophoresis allows separation of the product from the substrate in the reaction mixture, so that the product doesn't have to have different optical properties with the substrate. UV absorption detection allows almost universal detection for organic molecules. Thus, no modifications of either the substrate or the product molecules are necessary. This technique has the potential to be used in screening of local distribution variations of specific bio-molecules in a tissue or in screening of multiple immobilized catalysts. Another high-throughput screening technique is developed by directly monitoring the light intensity of the immobilized-catalyst surface using a scientific charge-coupled device (CCD). Briefly, the surface of enzyme microarray is focused onto a scientific CCD using an objective lens. By carefully choosing the detection wavelength, generation of product on an enzyme spot can be seen by the CCD. Analyzing the light intensity change over time on an enzyme spot can give information of reaction rate. The same microarray can be used for many times. Thus, high-throughput kinetic studies of hundreds of catalytic reactions are made possible. At last, we studied the fluorescence emission spectra of ADP and obtained the detection limits for ADP under three different

GOMoDo: A GPCRs online modeling and docking webserver.

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Massimo Sandal

Full Text Available G-protein coupled receptors (GPCRs are a superfamily of cell signaling membrane proteins that include >750 members in the human genome alone. They are the largest family of drug targets. The vast diversity and relevance of GPCRs contrasts with the paucity of structures available: only 21 unique GPCR structures have been experimentally determined as of the beginning of 2013. User-friendly modeling and small molecule docking tools are thus in great demand. While both GPCR structural predictions and docking servers exist separately, with GOMoDo (GPCR Online Modeling and Docking, we provide a web server to seamlessly model GPCR structures and dock ligands to the models in a single consistent pipeline. GOMoDo can automatically perform template choice, homology modeling and either blind or information-driven docking by combining together proven, state of the art bioinformatic tools. The web server gives the user the possibility of guiding the whole procedure. The GOMoDo server is freely accessible at http://molsim.sci.univr.it/gomodo.

"Flexible Ligand Docking Studies of Matrix Metalloproteinase Inhibitors Using Lamarckian Genetic Algorithm "

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lOrkideh Ghorban Dadrass

2004-06-01

Full Text Available As important therapeutic drug targets, matrix metalloproteinases (MMPs have recently attracted great interest in the search for potent and selective inhibitors using computer-aided molecular modelling and docking techniques. Availability of more than 60 X-ray crystal structures or NMR solution structures related to MMPs in Protein Data Bank (PDB of which more than half of them are in complex with various MMP inhibitors (MMPIs, provides a great opportunity for docking studies. In this study AutoDock 3.0.5 along with its LGA algorithm were used for automated flexible ligand docking of 32 MMPI-MMP complexes and docking accuracy and reliability of the estimated inhibition constants were evaluated. Twenty-six out of 32 docks had RMSD less than 3.0 Å which is considered as well-docked, however, for the most of the cases (15 out of 27, predicted pKi values were considerably overestimated in comparison to experimental values. To improve pKi prediction regarding MMPI-MMP complexes, inclusion of at least one such a complex in calibration of empirical free energy function in the next release of AutoDock is highly recommended.

High-throughput sample adaptive offset hardware architecture for high-efficiency video coding

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Zhou, Wei; Yan, Chang; Zhang, Jingzhi; Zhou, Xin

2018-03-01

A high-throughput hardware architecture for a sample adaptive offset (SAO) filter in the high-efficiency video coding video coding standard is presented. First, an implementation-friendly and simplified bitrate estimation method of rate-distortion cost calculation is proposed to reduce the computational complexity in the mode decision of SAO. Then, a high-throughput VLSI architecture for SAO is presented based on the proposed bitrate estimation method. Furthermore, multiparallel VLSI architecture for in-loop filters, which integrates both deblocking filter and SAO filter, is proposed. Six parallel strategies are applied in the proposed in-loop filters architecture to improve the system throughput and filtering speed. Experimental results show that the proposed in-loop filters architecture can achieve up to 48% higher throughput in comparison with prior work. The proposed architecture can reach a high-operating clock frequency of 297 MHz with TSMC 65-nm library and meet the real-time requirement of the in-loop filters for 8 K × 4 K video format at 132 fps.

High throughput, cell type-specific analysis of key proteins in human endometrial biopsies of women from fertile and infertile couples

Science.gov (United States)

Leach, Richard E.; Jessmon, Philip; Coutifaris, Christos; Kruger, Michael; Myers, Evan R.; Ali-Fehmi, Rouba; Carson, Sandra A.; Legro, Richard S.; Schlaff, William D.; Carr, Bruce R.; Steinkampf, Michael P.; Silva, Susan; Leppert, Phyllis C.; Giudice, Linda; Diamond, Michael P.; Armant, D. Randall

2012-01-01

BACKGROUND Although histological dating of endometrial biopsies provides little help for prediction or diagnosis of infertility, analysis of individual endometrial proteins, proteomic profiling and transcriptome analysis have suggested several biomarkers with altered expression arising from intrinsic abnormalities, inadequate stimulation by or in response to gonadal steroids or altered function due to systemic disorders. The objective of this study was to delineate the developmental dynamics of potentially important proteins in the secretory phase of the menstrual cycle, utilizing a collection of endometrial biopsies from women of fertile (n = 89) and infertile (n = 89) couples. METHODS AND RESULTS Progesterone receptor-B (PGR-B), leukemia inhibitory factor, glycodelin/progestagen-associated endometrial protein (PAEP), homeobox A10, heparin-binding EGF-like growth factor, calcitonin and chemokine ligand 14 (CXCL14) were measured using a high-throughput, quantitative immunohistochemical method. Significant cyclic and tissue-specific regulation was documented for each protein, as well as their dysregulation in women of infertile couples. Infertile patients demonstrated a delay early in the secretory phase in the decline of PGR-B (P localization provided important insights into the potential roles of these proteins in normal and pathological development of the endometrium that is not attainable from transcriptome analysis, establishing a basis for biomarker, diagnostic and targeted drug development for women with infertility. PMID:22215622

Dissecting the salt dependence of the Tus-Ter protein-DNA complexes by high-throughput differential scanning fluorimetry of a GFP-tagged Tus.

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Moreau, Morgane J J; Schaeffer, Patrick M

2013-12-01

The analysis of the salt dependence of protein-DNA complexes provides useful information about the non-specific electrostatic and sequence-specific parameters driving complex formation and stability. The differential scanning fluorimetry of GFP-tagged protein (DSF-GTP) assay has been geared with an automatic Tm peak recognition system and was applied for the high-throughput (HT) determination of salt-induced effects on the GFP-tagged DNA replication protein Tus in complex with various Ter and Ter-lock sequences. The system was designed to generate two-dimensional heat map profiles of Tus-GFP protein stability allowing for a comparative study of the effect of eight increasing salt concentrations on ten different Ter DNA species at once. The data obtained with the new HT DSF-GTP allowed precise dissection of the non-specific electrostatic and sequence-specific parameters driving Tus-Ter and Tus-Ter-lock complex formation and stability. The major factor increasing the thermal resistance of Tus-Ter-lock complexes in high-salt is the formation of the TT-lock, e.g. a 10-fold higher Kspe was obtained for Tus-GFP:Ter-lockB than for Tus-GFP:TerB. It is anticipated that the system can be easily adapted for the study of other protein-DNA complexes.

A High-Throughput Biological Calorimetry Core: Steps to Startup, Run, and Maintain a Multiuser Facility.

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Yennawar, Neela H; Fecko, Julia A; Showalter, Scott A; Bevilacqua, Philip C

2016-01-01

Many labs have conventional calorimeters where denaturation and binding experiments are setup and run one at a time. While these systems are highly informative to biopolymer folding and ligand interaction, they require considerable manual intervention for cleaning and setup. As such, the throughput for such setups is limited typically to a few runs a day. With a large number of experimental parameters to explore including different buffers, macromolecule concentrations, temperatures, ligands, mutants, controls, replicates, and instrument tests, the need for high-throughput automated calorimeters is on the rise. Lower sample volume requirements and reduced user intervention time compared to the manual instruments have improved turnover of calorimetry experiments in a high-throughput format where 25 or more runs can be conducted per day. The cost and efforts to maintain high-throughput equipment typically demands that these instruments be housed in a multiuser core facility. We describe here the steps taken to successfully start and run an automated biological calorimetry facility at Pennsylvania State University. Scientists from various departments at Penn State including Chemistry, Biochemistry and Molecular Biology, Bioengineering, Biology, Food Science, and Chemical Engineering are benefiting from this core facility. Samples studied include proteins, nucleic acids, sugars, lipids, synthetic polymers, small molecules, natural products, and virus capsids. This facility has led to higher throughput of data, which has been leveraged into grant support, attracting new faculty hire and has led to some exciting publications. © 2016 Elsevier Inc. All rights reserved.

Ranking docking poses by graph matching of protein-ligand interactions: lessons learned from the D3R Grand Challenge 2

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da Silva Figueiredo Celestino Gomes, Priscila; Da Silva, Franck; Bret, Guillaume; Rognan, Didier

2018-01-01

A novel docking challenge has been set by the Drug Design Data Resource (D3R) in order to predict the pose and affinity ranking of a set of Farnesoid X receptor (FXR) agonists, prior to the public release of their bound X-ray structures and potencies. In a first phase, 36 agonists were docked to 26 Protein Data Bank (PDB) structures of the FXR receptor, and next rescored using the in-house developed GRIM method. GRIM aligns protein-ligand interaction patterns of docked poses to those of available PDB templates for the target protein, and rescore poses by a graph matching method. In agreement with results obtained during the previous 2015 docking challenge, we clearly show that GRIM rescoring improves the overall quality of top-ranked poses by prioritizing interaction patterns already visited in the PDB. Importantly, this challenge enables us to refine the applicability domain of the method by better defining the conditions of its success. We notably show that rescoring apolar ligands in hydrophobic pockets leads to frequent GRIM failures. In the second phase, 102 FXR agonists were ranked by decreasing affinity according to the Gibbs free energy of the corresponding GRIM-selected poses, computed by the HYDE scoring function. Interestingly, this fast and simple rescoring scheme provided the third most accurate ranking method among 57 contributions. Although the obtained ranking is still unsuitable for hit to lead optimization, the GRIM-HYDE scoring scheme is accurate and fast enough to post-process virtual screening data.

Structural Bioinformatics and Protein Docking Analysis of the Molecular Chaperone-Kinase Interactions: Towards Allosteric Inhibition of Protein Kinases by Targeting the Hsp90-Cdc37 Chaperone Machinery

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Gennady Verkhivker

2013-11-01

Full Text Available A fundamental role of the Hsp90-Cdc37 chaperone system in mediating maturation of protein kinase clients and supporting kinase functional activity is essential for the integrity and viability of signaling pathways involved in cell cycle control and organism development. Despite significant advances in understanding structure and function of molecular chaperones, the molecular mechanisms and guiding principles of kinase recruitment to the chaperone system are lacking quantitative characterization. Structural and thermodynamic characterization of Hsp90-Cdc37 binding with protein kinase clients by modern experimental techniques is highly challenging, owing to a transient nature of chaperone-mediated interactions. In this work, we used experimentally-guided protein docking to probe the allosteric nature of the Hsp90-Cdc37 binding with the cyclin-dependent kinase 4 (Cdk4 kinase clients. The results of docking simulations suggest that the kinase recognition and recruitment to the chaperone system may be primarily determined by Cdc37 targeting of the N-terminal kinase lobe. The interactions of Hsp90 with the C-terminal kinase lobe may provide additional “molecular brakes” that can lock (or unlock kinase from the system during client loading (release stages. The results of this study support a central role of the Cdc37 chaperone in recognition and recruitment of the kinase clients. Structural analysis may have useful implications in developing strategies for allosteric inhibition of protein kinases by targeting the Hsp90-Cdc37 chaperone machinery.

Application of the docking program SOL for CSAR benchmark.

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Sulimov, Alexey V; Kutov, Danil C; Oferkin, Igor V; Katkova, Ekaterina V; Sulimov, Vladimir B

2013-08-26

This paper is devoted to results obtained by the docking program SOL and the post-processing program DISCORE at the CSAR benchmark. SOL and DISCORE programs are described. SOL is the original docking program developed on the basis of the genetic algorithm, MMFF94 force field, rigid protein, precalculated energy grid including desolvation in the frame of simplified GB model, vdW, and electrostatic interactions and taking into account the ligand internal strain energy. An important SOL feature is the single- or multi-processor performance for up to hundreds of CPUs. DISCORE improves the binding energy scoring by the local energy optimization of the ligand docked pose and a simple linear regression on the base of available experimental data. The docking program SOL has demonstrated a good ability for correct ligand positioning in the active sites of the tested proteins in most cases of CSAR exercises. SOL and DISCORE have not demonstrated very exciting results on the protein-ligand binding free energy estimation. Nevertheless, for some target proteins, SOL and DISCORE were among the first in prediction of inhibition activity. Ways to improve SOL and DISCORE are discussed.

Nanoscale Synaptic Membrane Mimetic Allows Unbiased High Throughput Screen That Targets Binding Sites for Alzheimer?s-Associated A? Oligomers

OpenAIRE

Wilcox, Kyle C.; Marunde, Matthew R.; Das, Aditi; Velasco, Pauline T.; Kuhns, Benjamin D.; Marty, Michael T.; Jiang, Haoming; Luan, Chi-Hao; Sligar, Stephen G.; Klein, William L.

2015-01-01

Despite their value as sources of therapeutic drug targets, membrane proteomes are largely inaccessible to high-throughput screening (HTS) tools designed for soluble proteins. An important example comprises the membrane proteins that bind amyloid β oligomers (AβOs). AβOs are neurotoxic ligands thought to instigate the synapse damage that leads to Alzheimer's dementia. At present, the identities of initial AβO binding sites are highly uncertain, largely because of extensive protein-protein int...

High Throughput Determinations of Critical Dosing Parameters (IVIVE workshop)

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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...

High quality protein microarray using in situ protein purification

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Fleischmann Robert D

2009-08-01

Full Text Available Abstract Background In the postgenomic era, high throughput protein expression and protein microarray technologies have progressed markedly permitting screening of therapeutic reagents and discovery of novel protein functions. Hexa-histidine is one of the most commonly used fusion tags for protein expression due to its small size and convenient purification via immobilized metal ion affinity chromatography (IMAC. This purification process has been adapted to the protein microarray format, but the quality of in situ His-tagged protein purification on slides has not been systematically evaluated. We established methods to determine the level of purification of such proteins on metal chelate-modified slide surfaces. Optimized in situ purification of His-tagged recombinant proteins has the potential to become the new gold standard for cost-effective generation of high-quality and high-density protein microarrays. Results Two slide surfaces were examined, chelated Cu2+ slides suspended on a polyethylene glycol (PEG coating and chelated Ni2+ slides immobilized on a support without PEG coating. Using PEG-coated chelated Cu2+ slides, consistently higher purities of recombinant proteins were measured. An optimized wash buffer (PBST composed of 10 mM phosphate buffer, 2.7 mM KCl, 140 mM NaCl and 0.05% Tween 20, pH 7.4, further improved protein purity levels. Using Escherichia coli cell lysates expressing 90 recombinant Streptococcus pneumoniae proteins, 73 proteins were successfully immobilized, and 66 proteins were in situ purified with greater than 90% purity. We identified several antigens among the in situ-purified proteins via assays with anti-S. pneumoniae rabbit antibodies and a human patient antiserum, as a demonstration project of large scale microarray-based immunoproteomics profiling. The methodology is compatible with higher throughput formats of in vivo protein expression, eliminates the need for resin-based purification and circumvents

Human and server docking prediction for CAPRI round 30-35 using LZerD with combined scoring functions.

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Peterson, Lenna X; Kim, Hyungrae; Esquivel-Rodriguez, Juan; Roy, Amitava; Han, Xusi; Shin, Woong-Hee; Zhang, Jian; Terashi, Genki; Lee, Matt; Kihara, Daisuke

2017-03-01

We report the performance of protein-protein docking predictions by our group for recent rounds of the Critical Assessment of Prediction of Interactions (CAPRI), a community-wide assessment of state-of-the-art docking methods. Our prediction procedure uses a protein-protein docking program named LZerD developed in our group. LZerD represents a protein surface with 3D Zernike descriptors (3DZD), which are based on a mathematical series expansion of a 3D function. The appropriate soft representation of protein surface with 3DZD makes the method more tolerant to conformational change of proteins upon docking, which adds an advantage for unbound docking. Docking was guided by interface residue prediction performed with BindML and cons-PPISP as well as literature information when available. The generated docking models were ranked by a combination of scoring functions, including PRESCO, which evaluates the native-likeness of residues' spatial environments in structure models. First, we discuss the overall performance of our group in the CAPRI prediction rounds and investigate the reasons for unsuccessful cases. Then, we examine the performance of several knowledge-based scoring functions and their combinations for ranking docking models. It was found that the quality of a pool of docking models generated by LZerD, that is whether or not the pool includes near-native models, can be predicted by the correlation of multiple scores. Although the current analysis used docking models generated by LZerD, findings on scoring functions are expected to be universally applicable to other docking methods. Proteins 2017; 85:513-527. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

High-Throughput Next-Generation Sequencing of Polioviruses

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Montmayeur, Anna M.; Schmidt, Alexander; Zhao, Kun; Magaña, Laura; Iber, Jane; Castro, Christina J.; Chen, Qi; Henderson, Elizabeth; Ramos, Edward; Shaw, Jing; Tatusov, Roman L.; Dybdahl-Sissoko, Naomi; Endegue-Zanga, Marie Claire; Adeniji, Johnson A.; Oberste, M. Steven; Burns, Cara C.

2016-01-01

ABSTRACT The poliovirus (PV) is currently targeted for worldwide eradication and containment. Sanger-based sequencing of the viral protein 1 (VP1) capsid region is currently the standard method for PV surveillance. However, the whole-genome sequence is sometimes needed for higher resolution global surveillance. In this study, we optimized whole-genome sequencing protocols for poliovirus isolates and FTA cards using next-generation sequencing (NGS), aiming for high sequence coverage, efficiency, and throughput. We found that DNase treatment of poliovirus RNA followed by random reverse transcription (RT), amplification, and the use of the Nextera XT DNA library preparation kit produced significantly better results than other preparations. The average viral reads per total reads, a measurement of efficiency, was as high as 84.2% ± 15.6%. PV genomes covering >99 to 100% of the reference length were obtained and validated with Sanger sequencing. A total of 52 PV genomes were generated, multiplexing as many as 64 samples in a single Illumina MiSeq run. This high-throughput, sequence-independent NGS approach facilitated the detection of a diverse range of PVs, especially for those in vaccine-derived polioviruses (VDPV), circulating VDPV, or immunodeficiency-related VDPV. In contrast to results from previous studies on other viruses, our results showed that filtration and nuclease treatment did not discernibly increase the sequencing efficiency of PV isolates. However, DNase treatment after nucleic acid extraction to remove host DNA significantly improved the sequencing results. This NGS method has been successfully implemented to generate PV genomes for molecular epidemiology of the most recent PV isolates. Additionally, the ability to obtain full PV genomes from FTA cards will aid in facilitating global poliovirus surveillance. PMID:27927929

Manual evaluation of tissue microarrays in a high-throughput research project: The contribution of Indian surgical pathology to the Human Protein Atlas (HPA) project.

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Navani, Sanjay

2016-04-01

The Human Protein Atlas (HPA) program (www.proteinatlas.org) is an international program that has been set up to allow for a systematic exploration of the human proteome using antibody-based proteomics. This is accomplished by combining high-throughput generation of affinity-purified (mono-specific) antibodies with protein profiling in a multitude of tissues/cell types assembled in tissue microarrays. Twenty-six surgical pathologists over a seven-and-half year period have annotated and curated approximately sixteen million tissue images derived from immunostaining of normal and cancer tissues by approximately 23 000 antibodies. Web-based annotation software that allows for a basic and rapid evaluation of immunoreactivity in tissues has been utilized. Intensity, fraction of immunoreactive cells and subcellular localization were recorded for each given cell population. A text comment summarizing the characteristics for each antibody was added. The methods used and the challenges encountered for this exercise, the largest effort ever by a single group of surgical pathologists, are discussed. Manual annotation of digital images is an important tool that may be successfully utilized in high-throughput research projects. This is the first time an Indian private pathology laboratory has been associated with cutting-edge research internationally providing a classic example of developed and emerging nation collaboration. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Multi-structure docking analysis of BACE1 crystal structures and non-peptidic ligands.

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Haghighijoo, Zahra; Hemmateenejad, Bahram; Edraki, Najmeh; Miri, Ramin; Emami, Saeed

2017-09-01

In order to design novel non-peptidic inhibitors of BACE1, many research groups have attempted using computational studies including docking analyses. Since there are too many 3D structures for BACE1 in the protein database, the selection of suitable crystal structures is a key prerequisite for the successful application of molecular docking. We employed a multi-structure docking protocol. In which 615 ligands' structures were docked into 150 BACE1 structures. The large number of the resultant docking scores were post-processed by different data analysis methods including exploratory data analysis, regression analysis and discriminant analysis. It was found that using one crystal structure for docking did not result in high accuracy for predicting activity of the BACE1 inhibitors. Instead, using of the multi-structural docking scores, post-processed by chemometrics methods arrived to highly accurate predictive models. In this regards, the PDB accession codes of 4B70, 4DVF and 2WEZ could discriminate between active and inactive compounds, with higher accuracy. Clustering of the BACE1 structures based on principal component analysis of the crystallographic structures the revealed that the discriminant structures are in the center of the clusters. Thus, these structures can be selected as predominant crystal structures for docking studies of non-peptidic BACE1 inhibitors. Copyright © 2017 Elsevier Inc. All rights reserved.

Applications of ambient mass spectrometry in high-throughput screening.

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Li, Li-Ping; Feng, Bao-Sheng; Yang, Jian-Wang; Chang, Cui-Lan; Bai, Yu; Liu, Hu-Wei

2013-06-07

The development of rapid screening and identification techniques is of great importance for drug discovery, doping control, forensic identification, food safety and quality control. Ambient mass spectrometry (AMS) allows rapid and direct analysis of various samples in open air with little sample preparation. Recently, its applications in high-throughput screening have been in rapid progress. During the past decade, various ambient ionization techniques have been developed and applied in high-throughput screening. This review discusses typical applications of AMS, including DESI (desorption electrospray ionization), DART (direct analysis in real time), EESI (extractive electrospray ionization), etc., in high-throughput screening (HTS).

High-throughput screening of saliva for early detection of oral cancer: a pilot study.

Science.gov (United States)

Szanto, I; Mark, L; Bona, A; Maasz, G; Sandor, B; Gelencser, G; Turi, Z; Gallyas, F

2012-04-01

The success of tumour therapy depends considerably on early diagnosis. Therefore, we aimed to develop a widely available, cheap, non-invasive, high-throughput method suitable for screening high-risk populations, at least, for early signs of malignant transformation in the oral cavity. First, in order to identify suitable tumour marker candidates, we compared the protein patterns of five selected saliva samples obtained from healthy controls and tumour patients after electrophoretic separation, excised the bands that were consistently up-regulated in the tumour patients only, and performed matrix-assisted laser-desorption ionisation (MALDI)-time of flight (TOF) tandem mass spectrometry (MS/MS) analysis of the proteins in these bands after in-gel tryptic digestion. From the panel of proteins identified, we chose annexin 1 and peroxiredoxin 2 for further studies based on their presence in the saliva of all five oral cancer patients only. Then, we performed a homology search of protein databases using the primary sequence of each in silico tryptic fragment peptide of these two proteins as bait, and selected a unique peptide for each. Finally, we performed targeted MALDI-TOF MS peptide analysis in a blinded fashion on all samples obtained from 20 healthy controls and 22 tumour patients for the presence of these peptides. We found both peptides present in the saliva samples of all cancer patients only. Even though these tumour markers should be validated in a wider population, our results indicate that targeted MALDI-TOF MS analysis of unique peptides of putative saliva protein tumour biomarkers could be the method of choice for cost-efficient, high-throughput screening for the early detection of oral cancer.

Rosetta Ligand docking with flexible XML protocols.

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Lemmon, Gordon; Meiler, Jens

2012-01-01

RosettaLigand is premiere software for predicting how a protein and a small molecule interact. Benchmark studies demonstrate that 70% of the top scoring RosettaLigand predicted interfaces are within 2Å RMSD from the crystal structure [1]. The latest release of Rosetta ligand software includes many new features, such as (1) docking of multiple ligands simultaneously, (2) representing ligands as fragments for greater flexibility, (3) redesign of the interface during docking, and (4) an XML script based interface that gives the user full control of the ligand docking protocol.

Identification of Novel Aldose Reductase Inhibitors from Spices: A Molecular Docking and Simulation Study.

Directory of Open Access Journals (Sweden)

Priya Antony

Full Text Available Hyperglycemia in diabetic patients results in a diverse range of complications such as diabetic retinopathy, neuropathy, nephropathy and cardiovascular diseases. The role of aldose reductase (AR, the key enzyme in the polyol pathway, in these complications is well established. Due to notable side-effects of several drugs, phytochemicals as an alternative has gained considerable importance for the treatment of several ailments. In order to evaluate the inhibitory effects of dietary spices on AR, a collection of phytochemicals were identified from Zingiber officinale (ginger, Curcuma longa (turmeric Allium sativum (garlic and Trigonella foenum graecum (fenugreek. Molecular docking was performed for lead identification and molecular dynamics simulations were performed to study the dynamic behaviour of these protein-ligand interactions. Gingerenones A, B and C, lariciresinol, quercetin and calebin A from these spices exhibited high docking score, binding affinity and sustained protein-ligand interactions. Rescoring of protein ligand interactions at the end of MD simulations produced binding scores that were better than the initially docked conformations. Docking results, ligand interactions and ADMET properties of these molecules were significantly better than commercially available AR inhibitors like epalrestat, sorbinil and ranirestat. Thus, these natural molecules could be potent AR inhibitors.

Identification of Novel Aldose Reductase Inhibitors from Spices: A Molecular Docking and Simulation Study.

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Antony, Priya; Vijayan, Ranjit

2015-01-01

Hyperglycemia in diabetic patients results in a diverse range of complications such as diabetic retinopathy, neuropathy, nephropathy and cardiovascular diseases. The role of aldose reductase (AR), the key enzyme in the polyol pathway, in these complications is well established. Due to notable side-effects of several drugs, phytochemicals as an alternative has gained considerable importance for the treatment of several ailments. In order to evaluate the inhibitory effects of dietary spices on AR, a collection of phytochemicals were identified from Zingiber officinale (ginger), Curcuma longa (turmeric) Allium sativum (garlic) and Trigonella foenum graecum (fenugreek). Molecular docking was performed for lead identification and molecular dynamics simulations were performed to study the dynamic behaviour of these protein-ligand interactions. Gingerenones A, B and C, lariciresinol, quercetin and calebin A from these spices exhibited high docking score, binding affinity and sustained protein-ligand interactions. Rescoring of protein ligand interactions at the end of MD simulations produced binding scores that were better than the initially docked conformations. Docking results, ligand interactions and ADMET properties of these molecules were significantly better than commercially available AR inhibitors like epalrestat, sorbinil and ranirestat. Thus, these natural molecules could be potent AR inhibitors.

Novel high-throughput cell-based hybridoma screening methodology using the Celigo Image Cytometer.

Science.gov (United States)

Zhang, Haohai; Chan, Leo Li-Ying; Rice, William; Kassam, Nasim; Longhi, Maria Serena; Zhao, Haitao; Robson, Simon C; Gao, Wenda; Wu, Yan

2017-08-01

Hybridoma screening is a critical step for antibody discovery, which necessitates prompt identification of potential clones from hundreds to thousands of hybridoma cultures against the desired immunogen. Technical issues associated with ELISA- and flow cytometry-based screening limit accuracy and diminish high-throughput capability, increasing time and cost. Conventional ELISA screening with coated antigen is also impractical for difficult-to-express hydrophobic membrane antigens or multi-chain protein complexes. Here, we demonstrate novel high-throughput screening methodology employing the Celigo Image Cytometer, which avoids nonspecific signals by contrasting antibody binding signals directly on living cells, with and without recombinant antigen expression. The image cytometry-based high-throughput screening method was optimized by detecting the binding of hybridoma supernatants to the recombinant antigen CD39 expressed on Chinese hamster ovary (CHO) cells. Next, the sensitivity of the image cytometer was demonstrated by serial dilution of purified CD39 antibody. Celigo was used to measure antibody affinities of commercial and in-house antibodies to membrane-bound CD39. This cell-based screening procedure can be completely accomplished within one day, significantly improving throughput and efficiency of hybridoma screening. Furthermore, measuring direct antibody binding to living cells eliminated both false positive and false negative hits. The image cytometry method was highly sensitive and versatile, and could detect positive antibody in supernatants at concentrations as low as ~5ng/mL, with concurrent K d binding affinity coefficient determination. We propose that this screening method will greatly facilitate antibody discovery and screening technologies. Copyright © 2017 Elsevier B.V. All rights reserved.

Theory and Applications of Covalent Docking in Drug Discovery: Merits and Pitfalls

Directory of Open Access Journals (Sweden)

Hezekiel Mathambo Kumalo

2015-01-01

Full Text Available he present art of drug discovery and design of new drugs is based on suicidal irreversible inhibitors. Covalent inhibition is the strategy that is used to achieve irreversible inhibition. Irreversible inhibitors interact with their targets in a time-dependent fashion, and the reaction proceeds to completion rather than to equilibrium. Covalent inhibitors possessed some significant advantages over non-covalent inhibitors such as covalent warheads can target rare, non-conserved residue of a particular target protein and thus led to development of highly selective inhibitors, covalent inhibitors can be effective in targeting proteins with shallow binding cleavage which will led to development of novel inhibitors with increased potency than non-covalent inhibitors. Several computational approaches have been developed to simulate covalent interactions; however, this is still a challenging area to explore. Covalent molecular docking has been recently implemented in the computer-aided drug design workflows to describe covalent interactions between inhibitors and biological targets. In this review we highlight: (i covalent interactions in biomolecular systems; (ii the mathematical framework of covalent molecular docking; (iii implementation of covalent docking protocol in drug design workflows; (iv applications covalent docking: case studies and (v shortcomings and future perspectives of covalent docking. To the best of our knowledge; this review is the first account that highlights different aspects of covalent docking with its merits and pitfalls. We believe that the method and applications highlighted in this study will help future efforts towards the design of irreversible inhibitors.

High-throughput evaluation of interactions between biomaterials, proteins and cells using patterned superhydrophobic substrates

OpenAIRE

Neto, Ana I.; Custódio, Catarina A.; Wenlong Song; Mano, J. F.

2011-01-01

We propose a new low cost platform for high-throughput analysis that permits screening the biological performance of independent combinations of biomaterials, cells and culture media. Patterned superhydrophobic flat substrates with controlled wettable spots are used to produce microarray chips for accelerated multiplexing evaluation. This work was partially supported by Fundação para a Ciência e Tecnologia (FCT) under project PTDC/FIS/68517/2006.

High throughput proteomic analysis of the secretome in an explant model of articular cartilage inflammation

Science.gov (United States)

Clutterbuck, Abigail L.; Smith, Julia R.; Allaway, David; Harris, Pat; Liddell, Susan; Mobasheri, Ali

2011-01-01

This study employed a targeted high-throughput proteomic approach to identify the major proteins present in the secretome of articular cartilage. Explants from equine metacarpophalangeal joints were incubated alone or with interleukin-1beta (IL-1β, 10 ng/ml), with or without carprofen, a non-steroidal anti-inflammatory drug, for six days. After tryptic digestion of culture medium supernatants, resulting peptides were separated by HPLC and detected in a Bruker amaZon ion trap instrument. The five most abundant peptides in each MS scan were fragmented and the fragmentation patterns compared to mammalian entries in the Swiss-Prot database, using the Mascot search engine. Tryptic peptides originating from aggrecan core protein, cartilage oligomeric matrix protein (COMP), fibronectin, fibromodulin, thrombospondin-1 (TSP-1), clusterin (CLU), cartilage intermediate layer protein-1 (CILP-1), chondroadherin (CHAD) and matrix metalloproteinases MMP-1 and MMP-3 were detected. Quantitative western blotting confirmed the presence of CILP-1, CLU, MMP-1, MMP-3 and TSP-1. Treatment with IL-1β increased MMP-1, MMP-3 and TSP-1 and decreased the CLU precursor but did not affect CILP-1 and CLU levels. Many of the proteins identified have well-established extracellular matrix functions and are involved in early repair/stress responses in cartilage. This high throughput approach may be used to study the changes that occur in the early stages of osteoarthritis. PMID:21354348

Automated docking screens: a feasibility study.

Science.gov (United States)

Irwin, John J; Shoichet, Brian K; Mysinger, Michael M; Huang, Niu; Colizzi, Francesco; Wassam, Pascal; Cao, Yiqun

2009-09-24

Molecular docking is the most practical approach to leverage protein structure for ligand discovery, but the technique retains important liabilities that make it challenging to deploy on a large scale. We have therefore created an expert system, DOCK Blaster, to investigate the feasibility of full automation. The method requires a PDB code, sometimes with a ligand structure, and from that alone can launch a full screen of large libraries. A critical feature is self-assessment, which estimates the anticipated reliability of the automated screening results using pose fidelity and enrichment. Against common benchmarks, DOCK Blaster recapitulates the crystal ligand pose within 2 A rmsd 50-60% of the time; inferior to an expert, but respectrable. Half the time the ligand also ranked among the top 5% of 100 physically matched decoys chosen on the fly. Further tests were undertaken culminating in a study of 7755 eligible PDB structures. In 1398 cases, the redocked ligand ranked in the top 5% of 100 property-matched decoys while also posing within 2 A rmsd, suggesting that unsupervised prospective docking is viable. DOCK Blaster is available at http://blaster.docking.org .

HTP-OligoDesigner: An Online Primer Design Tool for High-Throughput Gene Cloning and Site-Directed Mutagenesis.

Science.gov (United States)

Camilo, Cesar M; Lima, Gustavo M A; Maluf, Fernando V; Guido, Rafael V C; Polikarpov, Igor

2016-01-01

Following burgeoning genomic and transcriptomic sequencing data, biochemical and molecular biology groups worldwide are implementing high-throughput cloning and mutagenesis facilities in order to obtain a large number of soluble proteins for structural and functional characterization. Since manual primer design can be a time-consuming and error-generating step, particularly when working with hundreds of targets, the automation of primer design process becomes highly desirable. HTP-OligoDesigner was created to provide the scientific community with a simple and intuitive online primer design tool for both laboratory-scale and high-throughput projects of sequence-independent gene cloning and site-directed mutagenesis and a Tm calculator for quick queries.

High-throughput screening (HTS) and modeling of the retinoid ...

Science.gov (United States)

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

Medium-Throughput Screen of Microbially Produced Serotonin via a G-Protein-Coupled Receptor-Based Sensor.

Science.gov (United States)

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.

EVpedia: an integrated database of high-throughput data for systemic analyses of extracellular vesicles

Directory of Open Access Journals (Sweden)

Dae-Kyum Kim

2013-03-01

Full Text Available Secretion of extracellular vesicles is a general cellular activity that spans the range from simple unicellular organisms (e.g. archaea; Gram-positive and Gram-negative bacteria to complex multicellular ones, suggesting that this extracellular vesicle-mediated communication is evolutionarily conserved. Extracellular vesicles are spherical bilayered proteolipids with a mean diameter of 20–1,000 nm, which are known to contain various bioactive molecules including proteins, lipids, and nucleic acids. Here, we present EVpedia, which is an integrated database of high-throughput datasets from prokaryotic and eukaryotic extracellular vesicles. EVpedia provides high-throughput datasets of vesicular components (proteins, mRNAs, miRNAs, and lipids present on prokaryotic, non-mammalian eukaryotic, and mammalian extracellular vesicles. In addition, EVpedia also provides an array of tools, such as the search and browse of vesicular components, Gene Ontology enrichment analysis, network analysis of vesicular proteins and mRNAs, and a comparison of vesicular datasets by ortholog identification. Moreover, publications on extracellular vesicle studies are listed in the database. This free web-based database of EVpedia (http://evpedia.info might serve as a fundamental repository to stimulate the advancement of extracellular vesicle studies and to elucidate the novel functions of these complex extracellular organelles.

Fast, accurate, and reliable molecular docking with QuickVina 2.

Science.gov (United States)

Alhossary, Amr; Handoko, Stephanus Daniel; Mu, Yuguang; Kwoh, Chee-Keong

2015-07-01

The need for efficient molecular docking tools for high-throughput screening is growing alongside the rapid growth of drug-fragment databases. AutoDock Vina ('Vina') is a widely used docking tool with parallelization for speed. QuickVina ('QVina 1') then further enhanced the speed via a heuristics, requiring high exhaustiveness. With low exhaustiveness, its accuracy was compromised. We present in this article the latest version of QuickVina ('QVina 2') that inherits both the speed of QVina 1 and the reliability of the original Vina. We tested the efficacy of QVina 2 on the core set of PDBbind 2014. With the default exhaustiveness level of Vina (i.e. 8), a maximum of 20.49-fold and an average of 2.30-fold acceleration with a correlation coefficient of 0.967 for the first mode and 0.911 for the sum of all modes were attained over the original Vina. A tendency for higher acceleration with increased number of rotatable bonds as the design variables was observed. On the accuracy, Vina wins over QVina 2 on 30% of the data with average energy difference of only 0.58 kcal/mol. On the same dataset, GOLD produced RMSD smaller than 2 Å on 56.9% of the data while QVina 2 attained 63.1%. The C++ source code of QVina 2 is available at (www.qvina.org). aalhossary@pmail.ntu.edu.sg Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

The development of an affinity evaluation and prediction system by using protein–protein docking simulations and parameter tuning

Directory of Open Access Journals (Sweden)

Koki Tsukamoto

2009-01-01

Full Text Available Koki Tsukamoto1, Tatsuya Yoshikawa1,2, Kiyonobu Yokota1, Yuichiro Hourai1, Kazuhiko Fukui11Computational Biology Research Center (CBRC, National Institute of Advanced Industrial Science and Technology (AIST, Koto-ku, Tokyo, Japan; 2Department of Bioinformatic Engineering, Graduate School of Information Science and Technology, Osaka University, Toyonaka, Osaka, JapanAbstract: A system was developed to evaluate and predict the interaction between protein pairs by using the widely used shape complementarity search method as the algorithm for docking simulations between the proteins. We used this system, which we call the affinity evaluation and prediction (AEP system, to evaluate the interaction between 20 protein pairs. The system first executes a “round robin” shape complementarity search of the target protein group, and evaluates the interaction between the complex structures obtained by the search. These complex structures are selected by using a statistical procedure that we developed called ‘grouping’. At a prevalence of 5.0%, our AEP system predicted protein–protein interactions with a 50.0% recall, 55.6% precision, 95.5% accuracy, and an F-measure of 0.526. By optimizing the grouping process, our AEP system successfully predicted 10 protein pairs (among 20 pairs that were biologically relevant combinations. Our ultimate goal is to construct an affinity database that will provide cell biologists and drug designers with crucial information obtained using our AEP system.Keywords: protein–protein interaction, affinity analysis, protein–protein docking, FFT, massive parallel computing

Novel Acoustic Loading of a Mass Spectrometer: Toward Next-Generation High-Throughput MS Screening.

Science.gov (United States)

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.

High-throughput screening assay of hepatitis C virus helicase inhibitors using fluorescence-quenching phenomenon

International Nuclear Information System (INIS)

Tani, Hidenori; Akimitsu, Nobuyoshi; Fujita, Osamu; Matsuda, Yasuyoshi; Miyata, Ryo; Tsuneda, Satoshi; Igarashi, Masayuki; Sekiguchi, Yuji; Noda, Naohiro

2009-01-01

We have developed a novel high-throughput screening assay of hepatitis C virus (HCV) nonstructural protein 3 (NS3) helicase inhibitors using the fluorescence-quenching phenomenon via photoinduced electron transfer between fluorescent dyes and guanine bases. We prepared double-stranded DNA (dsDNA) with a 5'-fluorescent-dye (BODIPY FL)-labeled strand hybridized with a complementary strand, the 3'-end of which has guanine bases. When dsDNA is unwound by helicase, the dye emits fluorescence owing to its release from the guanine bases. Our results demonstrate that this assay is suitable for quantitative assay of HCV NS3 helicase activity and useful for high-throughput screening for inhibitors. Furthermore, we applied this assay to the screening for NS3 helicase inhibitors from cell extracts of microorganisms, and found several cell extracts containing potential inhibitors.

High-throughput scoring of seed germination

NARCIS (Netherlands)

Ligterink, Wilco; Hilhorst, Henk W.M.

2017-01-01

High-throughput analysis of seed germination for phenotyping large genetic populations or mutant collections is very labor intensive and would highly benefit from an automated setup. Although very often used, the total germination percentage after a nominated period of time is not very

Homology modeling, molecular docking and DNA binding studies of nucleotide excision repair UvrC protein from M. tuberculosis.

Science.gov (United States)

Parulekar, Rishikesh S; Barage, Sagar H; Jalkute, Chidambar B; Dhanavade, Maruti J; Fandilolu, Prayagraj M; Sonawane, Kailas D

2013-08-01

Mycobacterium tuberculosis is a Gram positive, acid-fast bacteria belonging to genus Mycobacterium, is the leading causative agent of most cases of tuberculosis. The pathogenicity of the bacteria is enhanced by its developed DNA repair mechanism which consists of machineries such as nucleotide excision repair. Nucleotide excision repair consists of excinuclease protein UvrABC endonuclease, multi-enzymatic complex which carries out repair of damaged DNA in sequential manner. UvrC protein is a part of this complex and thus helps to repair the damaged DNA of M. tuberculosis. Hence, structural bioinformatics study of UvrC protein from M. tuberculosis was carried out using homology modeling and molecular docking techniques. Assessment of the reliability of the homology model was carried out by predicting its secondary structure along with its model validation. The predicted structure was docked with the ATP and the interacting amino acid residues of UvrC protein with the ATP were found to be TRP539, PHE89, GLU536, ILE402 and ARG575. The binding of UvrC protein with the DNA showed two different domains. The residues from domain I of the protein VAL526, THR524 and LEU521 interact with the DNA whereas, amino acids interacting from the domain II of the UvrC protein included ARG597, GLU595, GLY594 and GLY592 residues. This predicted model could be useful to design new inhibitors of UvrC enzyme to prevent pathogenesis of Mycobacterium and so the tuberculosis.

Optimization and high-throughput screening of antimicrobial peptides.

Science.gov (United States)

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.

A high-throughput sample preparation method for cellular proteomics using 96-well filter plates.

Science.gov (United States)

Switzar, Linda; van Angeren, Jordy; Pinkse, Martijn; Kool, Jeroen; Niessen, Wilfried M A

2013-10-01

A high-throughput sample preparation protocol based on the use of 96-well molecular weight cutoff (MWCO) filter plates was developed for shotgun proteomics of cell lysates. All sample preparation steps, including cell lysis, buffer exchange, protein denaturation, reduction, alkylation and proteolytic digestion are performed in a 96-well plate format, making the platform extremely well suited for processing large numbers of samples and directly compatible with functional assays for cellular proteomics. In addition, the usage of a single plate for all sample preparation steps following cell lysis reduces potential samples losses and allows for automation. The MWCO filter also enables sample concentration, thereby increasing the overall sensitivity, and implementation of washing steps involving organic solvents, for example, to remove cell membranes constituents. The optimized protocol allowed for higher throughput with improved sensitivity in terms of the number of identified cellular proteins when compared to an established protocol employing gel-filtration columns. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

mIMT-visHTS: A novel method for multiplexing isobaric mass tagged datasets with an accompanying visualization high throughput screening tool for protein profiling.

Science.gov (United States)

Ricchiuto, Piero; Iwata, Hiroshi; Yabusaki, Katsumi; Yamada, Iwao; Pieper, Brett; Sharma, Amitabh; Aikawa, Masanori; Singh, Sasha A

2015-10-14

Isobaric mass tagging (IMT) methods enable the analysis of thousands of proteins simultaneously. We used tandem mass tagging reagents (TMT™) to monitor the relative changes in the proteome of the mouse macrophage cell line RAW264.7 at the same six time points after no stimulation (baseline phenotype), stimulation with interferon gamma (pro-inflammatory phenotype) or stimulation with interleukin-4 (anti-inflammatory phenotype). The combined TMT datasets yielded nearly 12,000 protein profiles for comparison. To facilitate this large analysis, we developed a novel method that combines or multiplexes the separate IMT (mIMT) datasets into a single super dataset for subsequent model-based clustering and co-regulation analysis. Specially designed visual High Throughput Screening (visHTS) software screened co-regulated proteins. visHTS generates an interactive and visually intuitive color-coded bullseye plot that enables users to browse the cluster outputs and identify co-regulated proteins. Copyright © 2015 Elsevier B.V. All rights reserved.

20180311 - High Throughput Transcriptomics: From screening to pathways (SOT 2018)

Science.gov (United States)

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...

High throughput label-free platform for statistical bio-molecular sensing

DEFF Research Database (Denmark)

Bosco, Filippo; Hwu, En-Te; Chen, Ching-Hsiu

2011-01-01

Sensors are crucial in many daily operations including security, environmental control, human diagnostics and patient monitoring. Screening and online monitoring require reliable and high-throughput sensing. We report on the demonstration of a high-throughput label-free sensor platform utilizing...

Combining self- and cross-docking as benchmark tools: the performance of DockBench in the D3R Grand Challenge 2

Science.gov (United States)

Salmaso, Veronica; Sturlese, Mattia; Cuzzolin, Alberto; Moro, Stefano

2018-01-01

Molecular docking is a powerful tool in the field of computer-aided molecular design. In particular, it is the technique of choice for the prediction of a ligand pose within its target binding site. A multitude of docking methods is available nowadays, whose performance may vary depending on the data set. Therefore, some non-trivial choices should be made before starting a docking simulation. In the same framework, the selection of the target structure to use could be challenging, since the number of available experimental structures is increasing. Both issues have been explored within this work. The pose prediction of a pool of 36 compounds provided by D3R Grand Challenge 2 organizers was preceded by a pipeline to choose the best protein/docking-method couple for each blind ligand. An integrated benchmark approach including ligand shape comparison and cross-docking evaluations was implemented inside our DockBench software. The results are encouraging and show that bringing attention to the choice of the docking simulation fundamental components improves the results of the binding mode predictions.

MOLECULAR DOCKING AND DYNAMICS STUDIES ON THE PROTEIN-PROTEIN INTERACTIONS OF ELECTRICALLY ACTIVE PILIN NANOWIRES OF GEOBACTER SULFURREDUCENS.

Directory of Open Access Journals (Sweden)

D. Jeya Sundara Sharmila1 *

2017-06-01

Full Text Available Molecular interactions are key aspects in biological recognitions applicable in nano/micro systems. Bacterial nanowires are pilus filament based structures that can conduct electrons. The transport of electron is proposed to be facilitated by filamentous fibers made up of polymeric assemblies of proteins called pilin. Geobacter sulfurreducens is capable of delivering electrons through extracellular electron transport (EET by employing conductive nanowires, which are pilin proteins composed of type IV subunit PilA. Protein-protein interactions play an important role in the stabilization of the pilin nanowire assembly complex and it contains transmembrane (TM domain. In current study, protein-protein docking and multiple molecular dynamic (MD simulations were performed to understand the binding mode of pilin nanowires. The MD result explains the conformational behavior and folding of pilin nanowires in water environment in different time scale duration 20, 5, 5, 10 and 20ns (total of 60ns. Direct hydrogen bonds and water mediated hydrogen bonds that play a crucial role during the simulation were investigated. The conformational state, folding, end-toend distance profile and hydrogen bonding behavior had indicated that the Geobacter sulfurreducens pilin nanowires have electrical conductivity properties.

A bead-based western for high-throughput cellular signal transduction analyses

Science.gov (United States)

Treindl, Fridolin; Ruprecht, Benjamin; Beiter, Yvonne; Schultz, Silke; Döttinger, Anette; Staebler, Annette; Joos, Thomas O.; Kling, Simon; Poetz, Oliver; Fehm, Tanja; Neubauer, Hans; Kuster, Bernhard; Templin, Markus F.

2016-01-01

Dissecting cellular signalling requires the analysis of large number of proteins. The DigiWest approach we describe here transfers the western blot to a bead-based microarray platform. By combining gel-based protein separation with immobilization on microspheres, hundreds of replicas of the initial blot are created, thus enabling the comprehensive analysis of limited material, such as cells collected by laser capture microdissection, and extending traditional western blotting to reach proteomic scales. The combination of molecular weight resolution, sensitivity and signal linearity on an automated platform enables the rapid quantification of hundreds of specific proteins and protein modifications in complex samples. This high-throughput western blot approach allowed us to identify and characterize alterations in cellular signal transduction that occur during the development of resistance to the kinase inhibitor Lapatinib, revealing major changes in the activation state of Ephrin-mediated signalling and a central role for p53-controlled processes. PMID:27659302

Improvement of an automated protein crystal exchange system PAM for high-throughput data collection

International Nuclear Information System (INIS)

Hiraki, Masahiko; Yamada, Yusuke; Chavas, Leonard M. G.; Wakatsuki, Soichi; Matsugaki, Naohiro

2013-01-01

A special liquid-nitrogen Dewar with double capacity for the sample-exchange robot has been created at AR-NE3A at the Photon Factory, allowing continuous fully automated data collection. In this work, this new system is described and the stability of its calibration is discussed. Photon Factory Automated Mounting system (PAM) protein crystal exchange systems are available at the following Photon Factory macromolecular beamlines: BL-1A, BL-5A, BL-17A, AR-NW12A and AR-NE3A. The beamline AR-NE3A has been constructed for high-throughput macromolecular crystallography and is dedicated to structure-based drug design. The PAM liquid-nitrogen Dewar can store a maximum of three SSRL cassettes. Therefore, users have to interrupt their experiments and replace the cassettes when using four or more of them during their beam time. As a result of investigation, four or more cassettes were used in AR-NE3A alone. For continuous automated data collection, the size of the liquid-nitrogen Dewar for the AR-NE3A PAM was increased, doubling the capacity. In order to check the calibration with the new Dewar and the cassette stand, calibration experiments were repeatedly performed. Compared with the current system, the parameters of the novel system are shown to be stable

Improvement of an automated protein crystal exchange system PAM for high-throughput data collection

Energy Technology Data Exchange (ETDEWEB)

Hiraki, Masahiko, E-mail: masahiko.hiraki@kek.jp; Yamada, Yusuke; Chavas, Leonard M. G. [High Energy Accelerator Research Organization, 1-1 Oho, Tsukuba, Ibaraki 305-0801 (Japan); Wakatsuki, Soichi [High Energy Accelerator Research Organization, 1-1 Oho, Tsukuba, Ibaraki 305-0801 (Japan); SLAC National Accelerator Laboratory, 2575 Sand Hill Road, MS 69, Menlo Park, CA 94025-7015 (United States); Stanford University, Beckman Center B105, Stanford, CA 94305-5126 (United States); Matsugaki, Naohiro [High Energy Accelerator Research Organization, 1-1 Oho, Tsukuba, Ibaraki 305-0801 (Japan)

2013-11-01

A special liquid-nitrogen Dewar with double capacity for the sample-exchange robot has been created at AR-NE3A at the Photon Factory, allowing continuous fully automated data collection. In this work, this new system is described and the stability of its calibration is discussed. Photon Factory Automated Mounting system (PAM) protein crystal exchange systems are available at the following Photon Factory macromolecular beamlines: BL-1A, BL-5A, BL-17A, AR-NW12A and AR-NE3A. The beamline AR-NE3A has been constructed for high-throughput macromolecular crystallography and is dedicated to structure-based drug design. The PAM liquid-nitrogen Dewar can store a maximum of three SSRL cassettes. Therefore, users have to interrupt their experiments and replace the cassettes when using four or more of them during their beam time. As a result of investigation, four or more cassettes were used in AR-NE3A alone. For continuous automated data collection, the size of the liquid-nitrogen Dewar for the AR-NE3A PAM was increased, doubling the capacity. In order to check the calibration with the new Dewar and the cassette stand, calibration experiments were repeatedly performed. Compared with the current system, the parameters of the novel system are shown to be stable.

Domain wise docking analyses of the modular chitin binding protein CBP50 from Bacillus thuringiensis serovar konkukian S4.

Science.gov (United States)

Sehar, Ujala; Mehmood, Muhammad Aamer; Hussain, Khadim; Nawaz, Salman; Nadeem, Shahid; Siddique, Muhammad Hussnain; Nadeem, Habibullah; Gull, Munazza; Ahmad, Niaz; Sohail, Iqra; Gill, Saba Shahid; Majeed, Summera

2013-01-01

This paper presents an in silico characterization of the chitin binding protein CBP50 from B. thuringiensis serovar konkukian S4 through homology modeling and molecular docking. The CBP50 has shown a modular structure containing an N-terminal CBM33 domain, two consecutive fibronectin-III (Fn-III) like domains and a C-terminal CBM5 domain. The protein presented a unique modular structure which could not be modeled using ordinary procedures. So, domain wise modeling using MODELLER and docking analyses using Autodock Vina were performed. The best conformation for each domain was selected using standard procedure. It was revealed that four amino acid residues Glu-71, Ser-74, Glu-76 and Gln-90 from N-terminal domain are involved in protein-substrate interaction. Similarly, amino acid residues Trp-20, Asn-21, Ser-23 and Val-30 of Fn-III like domains and Glu-15, Ala-17, Ser-18 and Leu-35 of C-terminal domain were involved in substrate binding. Site-directed mutagenesis of these proposed amino acid residues in future will elucidate the key amino acids involved in chitin binding activity of CBP50 protein.

High throughput techniques to reveal the molecular physiology and evolution of digestion in spiders.

Science.gov (United States)

Fuzita, Felipe J; Pinkse, Martijn W H; Patane, José S L; Verhaert, Peter D E M; Lopes, Adriana R

2016-09-07

Spiders are known for their predatory efficiency and for their high capacity of digesting relatively large prey. They do this by combining both extracorporeal and intracellular digestion. Whereas many high throughput ("-omics") techniques focus on biomolecules in spider venom, so far this approach has not yet been applied to investigate the protein composition of spider midgut diverticula (MD) and digestive fluid (DF). We here report on our investigations of both MD and DF of the spider Nephilingis (Nephilengys) cruentata through the use of next generation sequencing and shotgun proteomics. This shows that the DF is composed of a variety of hydrolases including peptidases, carbohydrases, lipases and nuclease, as well as of toxins and regulatory proteins. We detect 25 astacins in the DF. Phylogenetic analysis of the corresponding transcript(s) in Arachnida suggests that astacins have acquired an unprecedented role for extracorporeal digestion in Araneae, with different orthologs used by each family. The results of a comparative study of spiders in distinct physiological conditions allow us to propose some digestion mechanisms in this interesting animal taxon. All the high throughput data allowed the demonstration that DF is a secretion originating from the MD. We identified enzymes involved in the extracellular and intracellular phases of digestion. Besides that, data analyses show a large gene duplication event in Araneae digestive process evolution, mainly of astacin genes. We were also able to identify proteins expressed and translated in the digestive system, which until now had been exclusively associated to venom glands.

High-throughput sequence alignment using Graphics Processing Units

Directory of Open Access Journals (Sweden)

Trapnell Cole

2007-12-01

Full Text Available Abstract Background The recent availability of new, less expensive high-throughput DNA sequencing technologies has yielded a dramatic increase in the volume of sequence data that must be analyzed. These data are being generated for several purposes, including genotyping, genome resequencing, metagenomics, and de novo genome assembly projects. Sequence alignment programs such as MUMmer have proven essential for analysis of these data, but researchers will need ever faster, high-throughput alignment tools running on inexpensive hardware to keep up with new sequence technologies. Results This paper describes MUMmerGPU, an open-source high-throughput parallel pairwise local sequence alignment program that runs on commodity Graphics Processing Units (GPUs in common workstations. MUMmerGPU uses the new Compute Unified Device Architecture (CUDA from nVidia to align multiple query sequences against a single reference sequence stored as a suffix tree. By processing the queries in parallel on the highly parallel graphics card, MUMmerGPU achieves more than a 10-fold speedup over a serial CPU version of the sequence alignment kernel, and outperforms the exact alignment component of MUMmer on a high end CPU by 3.5-fold in total application time when aligning reads from recent sequencing projects using Solexa/Illumina, 454, and Sanger sequencing technologies. Conclusion MUMmerGPU is a low cost, ultra-fast sequence alignment program designed to handle the increasing volume of data produced by new, high-throughput sequencing technologies. MUMmerGPU demonstrates that even memory-intensive applications can run significantly faster on the relatively low-cost GPU than on the CPU.

Development of a high-throughput microscale cell disruption platform for Pichia pastoris in rapid bioprocess design.

Science.gov (United States)

Bláha, Benjamin A F; Morris, Stephen A; Ogonah, Olotu W; Maucourant, Sophie; Crescente, Vincenzo; Rosenberg, William; Mukhopadhyay, Tarit K

2018-01-01

The time and cost benefits of miniaturized fermentation platforms can only be gained by employing complementary techniques facilitating high-throughput at small sample volumes. Microbial cell disruption is a major bottleneck in experimental throughput and is often restricted to large processing volumes. Moreover, for rigid yeast species, such as Pichia pastoris, no effective high-throughput disruption methods exist. The development of an automated, miniaturized, high-throughput, noncontact, scalable platform based on adaptive focused acoustics (AFA) to disrupt P. pastoris and recover intracellular heterologous protein is described. Augmented modes of AFA were established by investigating vessel designs and a novel enzymatic pretreatment step. Three different modes of AFA were studied and compared to the performance high-pressure homogenization. For each of these modes of cell disruption, response models were developed to account for five different performance criteria. Using multiple responses not only demonstrated that different operating parameters are required for different response optima, with highest product purity requiring suboptimal values for other criteria, but also allowed for AFA-based methods to mimic large-scale homogenization processes. These results demonstrate that AFA-mediated cell disruption can be used for a wide range of applications including buffer development, strain selection, fermentation process development, and whole bioprocess integration. © 2017 American Institute of Chemical Engineers Biotechnol. Prog., 34:130-140, 2018. © 2017 American Institute of Chemical Engineers.

Combination of scoring schemes for protein docking

Directory of Open Access Journals (Sweden)

Schomburg Dietmar

2007-08-01

Full Text Available Abstract Background Docking algorithms are developed to predict in which orientation two proteins are likely to bind under natural conditions. The currently used methods usually consist of a sampling step followed by a scoring step. We developed a weighted geometric correlation based on optimised atom specific weighting factors and combined them with our previously published amino acid specific scoring and with a comprehensive SVM-based scoring function. Results The scoring with the atom specific weighting factors yields better results than the amino acid specific scoring. In combination with SVM-based scoring functions the percentage of complexes for which a near native structure can be predicted within the top 100 ranks increased from 14% with the geometric scoring to 54% with the combination of all scoring functions. Especially for the enzyme-inhibitor complexes the results of the ranking are excellent. For half of these complexes a near-native structure can be predicted within the first 10 proposed structures and for more than 86% of all enzyme-inhibitor complexes within the first 50 predicted structures. Conclusion We were able to develop a combination of different scoring schemes which considers a series of previously described and some new scoring criteria yielding a remarkable improvement of prediction quality.

High throughput imaging cytometer with acoustic focussing.

Science.gov (United States)

Zmijan, Robert; Jonnalagadda, Umesh S; Carugo, Dario; Kochi, Yu; Lemm, Elizabeth; Packham, Graham; Hill, Martyn; Glynne-Jones, Peter

2015-10-31

We demonstrate an imaging flow cytometer that uses acoustic levitation to assemble cells and other particles into a sheet structure. This technique enables a high resolution, low noise CMOS camera to capture images of thousands of cells with each frame. While ultrasonic focussing has previously been demonstrated for 1D cytometry systems, extending the technology to a planar, much higher throughput format and integrating imaging is non-trivial, and represents a significant jump forward in capability, leading to diagnostic possibilities not achievable with current systems. A galvo mirror is used to track the images of the moving cells permitting exposure times of 10 ms at frame rates of 50 fps with motion blur of only a few pixels. At 80 fps, we demonstrate a throughput of 208 000 beads per second. We investigate the factors affecting motion blur and throughput, and demonstrate the system with fluorescent beads, leukaemia cells and a chondrocyte cell line. Cells require more time to reach the acoustic focus than beads, resulting in lower throughputs; however a longer device would remove this constraint.

High-throughput GPU-based LDPC decoding

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Chang, Yang-Lang; Chang, Cheng-Chun; Huang, Min-Yu; Huang, Bormin

2010-08-01

Low-density parity-check (LDPC) code is a linear block code known to approach the Shannon limit via the iterative sum-product algorithm. LDPC codes have been adopted in most current communication systems such as DVB-S2, WiMAX, WI-FI and 10GBASE-T. LDPC for the needs of reliable and flexible communication links for a wide variety of communication standards and configurations have inspired the demand for high-performance and flexibility computing. Accordingly, finding a fast and reconfigurable developing platform for designing the high-throughput LDPC decoder has become important especially for rapidly changing communication standards and configurations. In this paper, a new graphic-processing-unit (GPU) LDPC decoding platform with the asynchronous data transfer is proposed to realize this practical implementation. Experimental results showed that the proposed GPU-based decoder achieved 271x speedup compared to its CPU-based counterpart. It can serve as a high-throughput LDPC decoder.

Evaluating High Throughput Toxicokinetics and Toxicodynamics for IVIVE (WC10)

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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...

Determining the optimal size of small molecule mixtures for high throughput NMR screening

International Nuclear Information System (INIS)

Mercier, Kelly A.; Powers, Robert

2005-01-01

High-throughput screening (HTS) using NMR spectroscopy has become a common component of the drug discovery effort and is widely used throughout the pharmaceutical industry. NMR provides additional information about the nature of small molecule-protein interactions compared to traditional HTS methods. In order to achieve comparable efficiency, small molecules are often screened as mixtures in NMR-based assays. Nevertheless, an analysis of the efficiency of mixtures and a corresponding determination of the optimum mixture size (OMS) that minimizes the amount of material and instrumentation time required for an NMR screen has been lacking. A model for calculating OMS based on the application of the hypergeometric distribution function to determine the probability of a 'hit' for various mixture sizes and hit rates is presented. An alternative method for the deconvolution of large screening mixtures is also discussed. These methods have been applied in a high-throughput NMR screening assay using a small, directed library

GREEN: A program package for docking studies in rational drug design

Science.gov (United States)

Tomioka, Nobuo; Itai, Akiko

1994-08-01

A program package, GREEN, has been developed that enables docking studies between ligand molecules and a protein molecule. Based on the structure of the protein molecule, the physical and chemical environment of the ligand-binding site is expressed as three-dimensional grid-point data. The grid-point data are used for the real-time evaluation of the protein-ligand interaction energy, as well as for the graphical representation of the binding-site environment. The interactive docking operation is facilitated by various built-in functions, such as energy minimization, energy contribution analysis and logging of the manipulation trajectory. Interactive modeling functions are incorporated for designing new ligand molecules while considering the binding-site environment and the protein-ligand interaction. As an example of the application of GREEN, a docking study is presented on the complex between trypsin and a synthetic trypsin inhibitor. The program package will be useful for rational drug design, based on the 3D structure of the target protein.

A high-throughput 2D-analytical technique to obtain single protein parameters from complex cell lysates for in silico process development of ion exchange chromatography.

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Kröner, Frieder; Elsäßer, Dennis; Hubbuch, Jürgen

2013-11-29

The accelerating growth of the market for biopharmaceutical proteins, the market entry of biosimilars and the growing interest in new, more complex molecules constantly pose new challenges for bioseparation process development. In the presented work we demonstrate the application of a multidimensional, analytical separation approach to obtain the relevant physicochemical parameters of single proteins in a complex mixture for in silico chromatographic process development. A complete cell lysate containing a low titre target protein was first fractionated by multiple linear salt gradient anion exchange chromatography (AEC) with varying gradient length. The collected fractions were subsequently analysed by high-throughput capillary gel electrophoresis (HT-CGE) after being desalted and concentrated. From the obtained data of the 2D-separation the retention-volumes and the concentration of the single proteins were determined. The retention-volumes of the single proteins were used to calculate the related steric-mass action model parameters. In a final evaluation experiment the received parameters were successfully applied to predict the retention behaviour of the single proteins in salt gradient AEC. Copyright © 2013 Elsevier B.V. All rights reserved.

Binding of ethyl pyruvate to bovine serum albumin: Calorimetric, spectroscopic and molecular docking studies

Energy Technology Data Exchange (ETDEWEB)

Pathak, Mallika [Department of Chemistry, Miranda House, University of Delhi, Delhi 11007 (India); Mishra, Rashmi; Agarwala, Paban K. [Department of Radiation Genetics and Epigenetics, Division of Radioprotective Drug Development Research, Institute of Nuclear Medicine and Allied Sciences, Delhi 110054 (India); Ojha, Himanshu, E-mail: himanshu.drdo@gmail.com [Department of Radiation Genetics and Epigenetics, Division of Radioprotective Drug Development Research, Institute of Nuclear Medicine and Allied Sciences, Delhi 110054 (India); Singh, Bhawna [Department of Radiation Genetics and Epigenetics, Division of Radioprotective Drug Development Research, Institute of Nuclear Medicine and Allied Sciences, Delhi 110054 (India); Singh, Anju; Kukreti, Shrikant [Nucleic Acid Research Laboratory, Department of Chemistry, University of Delhi, Delhi 11007 (India)

2016-06-10

Highlights: • ITC study showed binding of ethyl pyruvate with BSA with high binding affinity. • Ethyl pyruvate binding caused conformation alteration of BSA. • Fluorescence quenching mechanism is static in nature. • Electrostatic, hydrogen bonding and hydrophobic forces involved in binding. • Docking confirmed role of electrostatic, hydrogen bonding and hydrophobic forces. - Abstract: Various in vitro and in vivo studies have shown the anti-inflammatory and anticancer potential role of ethyl pyruvate. Bio-distribution of drugs is significantly influenced by the drug-serum protein binding. Therefore, the binding mechanism of the ethyl pyruvate with bovine serum albumin was investigated using UV–vis absorption, fluorescence, circular dichroism, isothermal titration calorimetry and molecular docking techniques. Absorption and fluorescence quenching studies indicated the binding of ethyl pyruvate with protein. Circular dichroism spectra of bovine serum albumin confirmed significant change in the conformation of protein upon binding. Thermodynamic data confirmed that ethyl pyruvate binds to bovine serum albumin at the two different sites with high affinity. Binding of ethyl pyruvate to bovine serum albumin involves hydrogen bonding, van der Waal and hydrophobic interactions. Further, docking studies indicated that ethyl pyruvate could bind significantly at the three binding sites. The results will definitely contribute to the development of ethyl pyruvate as drug.

In-situ nanoelectrospray for high-throughput screening of enzymes and real-time monitoring of reactions.

Science.gov (United States)

Yang, Yuhan; Han, Feifei; Ouyang, Jin; Zhao, Yunling; Han, Juan; Na, Na

2016-01-01

The in-situ and high-throughput evaluation of enzymes and real-time monitoring of enzyme catalyzed reactions in liquid phase is quite significant in the catalysis industry. In-situ nanoelectrospray, the direct sampling and ionization method for mass spectrometry, has been applied for high-throughput evaluation of enzymes, as well as the on-line monitoring of reactions. Simply inserting a capillary into a liquid system with high-voltage applied, analytes in liquid reaction system can be directly ionized at the capillary tip with small volume consumption. With no sample pre-treatment or injection procedure, different analytes such as saccharides, amino acids, alkaloids, peptides and proteins can be rapidly and directly extracted from liquid phase and ionized at the capillary tip. Taking irreversible transesterification reaction of vinyl acetate and ethanol as an example, this technique has been used for the high-throughput evaluation of enzymes, fast optimizations, as well as real-time monitoring of reaction catalyzed by different enzymes. In addition, it is even softer than traditional electrospray ionization. The present method can also be used for the monitoring of other homogenous and heterogeneous reactions in liquid phases, which will show potentials in the catalysis industry. Copyright © 2015 Elsevier B.V. All rights reserved.

High Throughput, Label-free Screening Small Molecule Compound Libraries for Protein-Ligands using Combination of Small Molecule Microarrays and a Special Ellipsometry-based Optical Scanner.

Science.gov (United States)

Landry, James P; Fei, Yiyan; Zhu, X D

2011-12-01

Small-molecule compounds remain the major source of therapeutic and preventative drugs. Developing new drugs against a protein target often requires screening large collections of compounds with diverse structures for ligands or ligand fragments that exhibit sufficiently affinity and desirable inhibition effect on the target before further optimization and development. Since the number of small molecule compounds is large, high-throughput screening (HTS) methods are needed. Small-molecule microarrays (SMM) on a solid support in combination with a suitable binding assay form a viable HTS platform. We demonstrate that by combining an oblique-incidence reflectivity difference optical scanner with SMM we can screen 10,000 small-molecule compounds on a single glass slide for protein ligands without fluorescence labeling. Furthermore using such a label-free assay platform we can simultaneously acquire binding curves of a solution-phase protein to over 10,000 immobilized compounds, thus enabling full characterization of protein-ligand interactions over a wide range of affinity constants.

Assessment and Challenges of Ligand Docking into Comparative Models of G-Protein Coupled Receptors

DEFF Research Database (Denmark)

Nguyen, E.D.; Meiler, J.; Norn, C.

2013-01-01

screening and to design and optimize drug candidates. However, low sequence identity between receptors, conformational flexibility, and chemical diversity of ligands present an enormous challenge to molecular modeling approaches. It is our hypothesis that rapid Monte-Carlo sampling of protein backbone...... extracellular loop. Furthermore, these models are consistently correlated with low Rosetta energy score. To predict their binding modes, ligand conformers of the 14 ligands co-crystalized with the GPCRs were docked against the top ranked comparative models. In contrast to the comparative models themselves...

Abseq: Ultrahigh-throughput single cell protein profiling with droplet microfluidic barcoding

Science.gov (United States)

Shahi, Payam; Kim, Samuel C.; Haliburton, John R.; Gartner, Zev J.; Abate, Adam R.

2017-03-01

Proteins are the primary effectors of cellular function, including cellular metabolism, structural dynamics, and information processing. However, quantitative characterization of proteins at the single-cell level is challenging due to the tiny amount of protein available. Here, we present Abseq, a method to detect and quantitate proteins in single cells at ultrahigh throughput. Like flow and mass cytometry, Abseq uses specific antibodies to detect epitopes of interest; however, unlike these methods, antibodies are labeled with sequence tags that can be read out with microfluidic barcoding and DNA sequencing. We demonstrate this novel approach by characterizing surface proteins of different cell types at the single-cell level and distinguishing between the cells by their protein expression profiles. DNA-tagged antibodies provide multiple advantages for profiling proteins in single cells, including the ability to amplify low-abundance tags to make them detectable with sequencing, to use molecular indices for quantitative results, and essentially limitless multiplexing.

High-throughput optical system for HDES hyperspectral imager

Science.gov (United States)

Václavík, Jan; Melich, Radek; Pintr, Pavel; Pleštil, Jan

2015-01-01

Affordable, long-wave infrared hyperspectral imaging calls for use of an uncooled FPA with high-throughput optics. This paper describes the design of the optical part of a stationary hyperspectral imager in a spectral range of 7-14 um with a field of view of 20°×10°. The imager employs a push-broom method made by a scanning mirror. High throughput and a demand for simplicity and rigidity led to a fully refractive design with highly aspheric surfaces and off-axis positioning of the detector array. The design was optimized to exploit the machinability of infrared materials by the SPDT method and a simple assemblage.

Exponential Repulsion Improves Structural Predictability of Molecular Docking

Czech Academy of Sciences Publication Activity Database

Bazgier, Václav; Berka, K.; Otyepka, M.; Banáš, P.

2016-01-01

Roč. 37, č. 28 (2016), s. 2485-2494 ISSN 0192-8651 Institutional support: RVO:61389030 Keywords : cyclin-dependent kinases * structure-based design * scoring functions * cdk2 inhibitors * force-field * ligand interactions * drug discovery * purine * potent * protein-kinase-2 * molecular docking * dock 6.6 * drug design * cyclin-dependent kinase 2 * directory of decoys Subject RIV: CF - Physical ; Theoretical Chemistry Impact factor: 3.229, year: 2016

Design and construction of a first-generation high-throughput integrated robotic molecular biology platform for bioenergy applications.

Science.gov (United States)

Hughes, Stephen R; Butt, Tauseef R; Bartolett, Scott; Riedmuller, Steven B; Farrelly, Philip

2011-08-01

The molecular biological techniques for plasmid-based assembly and cloning of gene open reading frames are essential for elucidating the function of the proteins encoded by the genes. High-throughput integrated robotic molecular biology platforms that have the capacity to rapidly clone and express heterologous gene open reading frames in bacteria and yeast and to screen large numbers of expressed proteins for optimized function are an important technology for improving microbial strains for biofuel production. The process involves the production of full-length complementary DNA libraries as a source of plasmid-based clones to express the desired proteins in active form for determination of their functions. Proteins that were identified by high-throughput screening as having desired characteristics are overexpressed in microbes to enable them to perform functions that will allow more cost-effective and sustainable production of biofuels. Because the plasmid libraries are composed of several thousand unique genes, automation of the process is essential. This review describes the design and implementation of an automated integrated programmable robotic workcell capable of producing complementary DNA libraries, colony picking, isolating plasmid DNA, transforming yeast and bacteria, expressing protein, and performing appropriate functional assays. These operations will allow tailoring microbial strains to use renewable feedstocks for production of biofuels, bioderived chemicals, fertilizers, and other coproducts for profitable and sustainable biorefineries. Published by Elsevier Inc.

High throughput and accurate serum proteome profiling by integrated sample preparation technology and single-run data independent mass spectrometry analysis.

Science.gov (United States)

Lin, Lin; Zheng, Jiaxin; Yu, Quan; Chen, Wendong; Xing, Jinchun; Chen, Chenxi; Tian, Ruijun

2018-03-01

Mass spectrometry (MS)-based serum proteome analysis is extremely challenging due to its high complexity and dynamic range of protein abundances. Developing high throughput and accurate serum proteomic profiling approach capable of analyzing large cohorts is urgently needed for biomarker discovery. Herein, we report a streamlined workflow for fast and accurate proteomic profiling from 1μL of blood serum. The workflow combined an integrated technique for highly sensitive and reproducible sample preparation and a new data-independent acquisition (DIA)-based MS method. Comparing with standard data dependent acquisition (DDA) approach, the optimized DIA method doubled the number of detected peptides and proteins with better reproducibility. Without protein immunodepletion and prefractionation, the single-run DIA analysis enables quantitative profiling of over 300 proteins with 50min gradient time. The quantified proteins span more than five orders of magnitude of abundance range and contain over 50 FDA-approved disease markers. The workflow allowed us to analyze 20 serum samples per day, with about 358 protein groups per sample being identified. A proof-of-concept study on renal cell carcinoma (RCC) serum samples confirmed the feasibility of the workflow for large scale serum proteomic profiling and disease-related biomarker discovery. Blood serum or plasma is the predominant specimen for clinical proteomic studies while the analysis is extremely challenging for its high complexity. Many efforts had been made in the past for serum proteomics for maximizing protein identifications, whereas few have been concerned with throughput and reproducibility. Here, we establish a rapid, robust and high reproducible DIA-based workflow for streamlined serum proteomic profiling from 1μL serum. The workflow doesn't need protein depletion and pre-fractionation, while still being able to detect disease-relevant proteins accurately. The workflow is promising in clinical application

High Performance Computing Modernization Program Kerberos Throughput Test Report

Science.gov (United States)

2017-10-26

Naval Research Laboratory Washington, DC 20375-5320 NRL/MR/5524--17-9751 High Performance Computing Modernization Program Kerberos Throughput Test ...NUMBER 5d. PROJECT NUMBER 5e. TASK NUMBER 5f. WORK UNIT NUMBER 2. REPORT TYPE1. REPORT DATE (DD-MM-YYYY) 4. TITLE AND SUBTITLE 6. AUTHOR(S) 8. PERFORMING...PAGE 18. NUMBER OF PAGES 17. LIMITATION OF ABSTRACT High Performance Computing Modernization Program Kerberos Throughput Test Report Daniel G. Gdula* and

High-Throughput Screening of a Luciferase Reporter of Gene Silencing on the Inactive X Chromosome.

Science.gov (United States)

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.

Application Of Empirical Phase Diagrams For Multidimensional Data Visualization Of High Throughput Microbatch Crystallization Experiments.

Science.gov (United States)

Klijn, Marieke E; Hubbuch, Jürgen

2018-04-27

Protein phase diagrams are a tool to investigate cause and consequence of solution conditions on protein phase behavior. The effects are scored according to aggregation morphologies such as crystals or amorphous precipitates. Solution conditions affect morphological features, such as crystal size, as well as kinetic features, such as crystal growth time. Common used data visualization techniques include individual line graphs or symbols-based phase diagrams. These techniques have limitations in terms of handling large datasets, comprehensiveness or completeness. To eliminate these limitations, morphological and kinetic features obtained from crystallization images generated with high throughput microbatch experiments have been visualized with radar charts in combination with the empirical phase diagram (EPD) method. Morphological features (crystal size, shape, and number, as well as precipitate size) and kinetic features (crystal and precipitate onset and growth time) are extracted for 768 solutions with varying chicken egg white lysozyme concentration, salt type, ionic strength and pH. Image-based aggregation morphology and kinetic features were compiled into a single and easily interpretable figure, thereby showing that the EPD method can support high throughput crystallization experiments in its data amount as well as its data complexity. Copyright © 2018. Published by Elsevier Inc.

Nanoscale Synaptic Membrane Mimetic Allows Unbiased High Throughput Screen That Targets Binding Sites for Alzheimer's-Associated Aβ Oligomers.

Directory of Open Access Journals (Sweden)

Kyle C Wilcox

Full Text Available Despite their value as sources of therapeutic drug targets, membrane proteomes are largely inaccessible to high-throughput screening (HTS tools designed for soluble proteins. An important example comprises the membrane proteins that bind amyloid β oligomers (AβOs. AβOs are neurotoxic ligands thought to instigate the synapse damage that leads to Alzheimer's dementia. At present, the identities of initial AβO binding sites are highly uncertain, largely because of extensive protein-protein interactions that occur following attachment of AβOs to surface membranes. Here, we show that AβO binding sites can be obtained in a state suitable for unbiased HTS by encapsulating the solubilized synaptic membrane proteome into nanoscale lipid bilayers (Nanodiscs. This method gives a soluble membrane protein library (SMPL--a collection of individualized synaptic proteins in a soluble state. Proteins within SMPL Nanodiscs showed enzymatic and ligand binding activity consistent with conformational integrity. AβOs were found to bind SMPL Nanodiscs with high affinity and specificity, with binding dependent on intact synaptic membrane proteins, and selective for the higher molecular weight oligomers known to accumulate at synapses. Combining SMPL Nanodiscs with a mix-incubate-read chemiluminescence assay provided a solution-based HTS platform to discover antagonists of AβO binding. Screening a library of 2700 drug-like compounds and natural products yielded one compound that potently reduced AβO binding to SMPL Nanodiscs, synaptosomes, and synapses in nerve cell cultures. Although not a therapeutic candidate, this small molecule inhibitor of synaptic AβO binding will provide a useful experimental antagonist for future mechanistic studies of AβOs in Alzheimer's model systems. Overall, results provide proof of concept for using SMPLs in high throughput screening for AβO binding antagonists, and illustrate in general how a SMPL Nanodisc system can

Nanoscale Synaptic Membrane Mimetic Allows Unbiased High Throughput Screen That Targets Binding Sites for Alzheimer's-Associated Aβ Oligomers.

Science.gov (United States)

Wilcox, Kyle C; Marunde, Matthew R; Das, Aditi; Velasco, Pauline T; Kuhns, Benjamin D; Marty, Michael T; Jiang, Haoming; Luan, Chi-Hao; Sligar, Stephen G; Klein, William L

2015-01-01

Despite their value as sources of therapeutic drug targets, membrane proteomes are largely inaccessible to high-throughput screening (HTS) tools designed for soluble proteins. An important example comprises the membrane proteins that bind amyloid β oligomers (AβOs). AβOs are neurotoxic ligands thought to instigate the synapse damage that leads to Alzheimer's dementia. At present, the identities of initial AβO binding sites are highly uncertain, largely because of extensive protein-protein interactions that occur following attachment of AβOs to surface membranes. Here, we show that AβO binding sites can be obtained in a state suitable for unbiased HTS by encapsulating the solubilized synaptic membrane proteome into nanoscale lipid bilayers (Nanodiscs). This method gives a soluble membrane protein library (SMPL)--a collection of individualized synaptic proteins in a soluble state. Proteins within SMPL Nanodiscs showed enzymatic and ligand binding activity consistent with conformational integrity. AβOs were found to bind SMPL Nanodiscs with high affinity and specificity, with binding dependent on intact synaptic membrane proteins, and selective for the higher molecular weight oligomers known to accumulate at synapses. Combining SMPL Nanodiscs with a mix-incubate-read chemiluminescence assay provided a solution-based HTS platform to discover antagonists of AβO binding. Screening a library of 2700 drug-like compounds and natural products yielded one compound that potently reduced AβO binding to SMPL Nanodiscs, synaptosomes, and synapses in nerve cell cultures. Although not a therapeutic candidate, this small molecule inhibitor of synaptic AβO binding will provide a useful experimental antagonist for future mechanistic studies of AβOs in Alzheimer's model systems. Overall, results provide proof of concept for using SMPLs in high throughput screening for AβO binding antagonists, and illustrate in general how a SMPL Nanodisc system can facilitate drug discovery

New developments of RNAi in Paracoccidioides brasiliensis: prospects for high-throughput, genome-wide, functional genomics.

Directory of Open Access Journals (Sweden)

Tercio Goes

2014-10-01

Full Text Available The Fungal Genome Initiative of the Broad Institute, in partnership with the Paracoccidioides research community, has recently sequenced the genome of representative isolates of this human-pathogen dimorphic fungus: Pb18 (S1, Pb03 (PS2 and Pb01. The accomplishment of future high-throughput, genome-wide, functional genomics will rely upon appropriate molecular tools and straightforward techniques to streamline the generation of stable loss-of-function phenotypes. In the past decades, RNAi has emerged as the most robust genetic technique to modulate or to suppress gene expression in diverse eukaryotes, including fungi. These molecular tools and techniques, adapted for RNAi, were up until now unavailable for P. brasiliensis.In this paper, we report Agrobacterium tumefaciens mediated transformation of yeast cells for high-throughput applications with which higher transformation frequencies of 150±24 yeast cell transformants per 1×106 viable yeast cells were obtained. Our approach is based on a bifunctional selective marker fusion protein consisted of the Streptoalloteichus hindustanus bleomycin-resistance gene (Shble and the intrinsically fluorescent monomeric protein mCherry which was codon-optimized for heterologous expression in P. brasiliensis. We also report successful GP43 gene knock-down through the expression of intron-containing hairpin RNA (ihpRNA from a Gateway-adapted cassette (cALf which was purpose-built for gene silencing in a high-throughput manner. Gp43 transcript levels were reduced by 73.1±22.9% with this approach.We have a firm conviction that the genetic transformation technique and the molecular tools herein described will have a relevant contribution in future Paracoccidioides spp. functional genomics research.

High-throughput theoretical design of lithium battery materials

International Nuclear Information System (INIS)

Ling Shi-Gang; Gao Jian; Xiao Rui-Juan; Chen Li-Quan

2016-01-01

The rapid evolution of high-throughput theoretical design schemes to discover new lithium battery materials is reviewed, including high-capacity cathodes, low-strain cathodes, anodes, solid state electrolytes, and electrolyte additives. With the development of efficient theoretical methods and inexpensive computers, high-throughput theoretical calculations have played an increasingly important role in the discovery of new materials. With the help of automatic simulation flow, many types of materials can be screened, optimized and designed from a structural database according to specific search criteria. In advanced cell technology, new materials for next generation lithium batteries are of great significance to achieve performance, and some representative criteria are: higher energy density, better safety, and faster charge/discharge speed. (topical review)

Cell surface profiling using high-throughput flow cytometry: a platform for biomarker discovery and analysis of cellular heterogeneity.

Directory of Open Access Journals (Sweden)

Craig A Gedye

Full Text Available Cell surface proteins have a wide range of biological functions, and are often used as lineage-specific markers. Antibodies that recognize cell surface antigens are widely used as research tools, diagnostic markers, and even therapeutic agents. The ability to obtain broad cell surface protein profiles would thus be of great value in a wide range of fields. There are however currently few available methods for high-throughput analysis of large numbers of cell surface proteins. We describe here a high-throughput flow cytometry (HT-FC platform for rapid analysis of 363 cell surface antigens. Here we demonstrate that HT-FC provides reproducible results, and use the platform to identify cell surface antigens that are influenced by common cell preparation methods. We show that multiple populations within complex samples such as primary tumors can be simultaneously analyzed by co-staining of cells with lineage-specific antibodies, allowing unprecedented depth of analysis of heterogeneous cell populations. Furthermore, standard informatics methods can be used to visualize, cluster and downsample HT-FC data to reveal novel signatures and biomarkers. We show that the cell surface profile provides sufficient molecular information to classify samples from different cancers and tissue types into biologically relevant clusters using unsupervised hierarchical clustering. Finally, we describe the identification of a candidate lineage marker and its subsequent validation. In summary, HT-FC combines the advantages of a high-throughput screen with a detection method that is sensitive, quantitative, highly reproducible, and allows in-depth analysis of heterogeneous samples. The use of commercially available antibodies means that high quality reagents are immediately available for follow-up studies. HT-FC has a wide range of applications, including biomarker discovery, molecular classification of cancers, or identification of novel lineage specific or stem cell

Cell surface profiling using high-throughput flow cytometry: a platform for biomarker discovery and analysis of cellular heterogeneity.

Science.gov (United States)

Gedye, Craig A; Hussain, Ali; Paterson, Joshua; Smrke, Alannah; Saini, Harleen; Sirskyj, Danylo; Pereira, Keira; Lobo, Nazleen; Stewart, Jocelyn; Go, Christopher; Ho, Jenny; Medrano, Mauricio; Hyatt, Elzbieta; Yuan, Julie; Lauriault, Stevan; Meyer, Mona; Kondratyev, Maria; van den Beucken, Twan; Jewett, Michael; Dirks, Peter; Guidos, Cynthia J; Danska, Jayne; Wang, Jean; Wouters, Bradly; Neel, Benjamin; Rottapel, Robert; Ailles, Laurie E

2014-01-01

Cell surface proteins have a wide range of biological functions, and are often used as lineage-specific markers. Antibodies that recognize cell surface antigens are widely used as research tools, diagnostic markers, and even therapeutic agents. The ability to obtain broad cell surface protein profiles would thus be of great value in a wide range of fields. There are however currently few available methods for high-throughput analysis of large numbers of cell surface proteins. We describe here a high-throughput flow cytometry (HT-FC) platform for rapid analysis of 363 cell surface antigens. Here we demonstrate that HT-FC provides reproducible results, and use the platform to identify cell surface antigens that are influenced by common cell preparation methods. We show that multiple populations within complex samples such as primary tumors can be simultaneously analyzed by co-staining of cells with lineage-specific antibodies, allowing unprecedented depth of analysis of heterogeneous cell populations. Furthermore, standard informatics methods can be used to visualize, cluster and downsample HT-FC data to reveal novel signatures and biomarkers. We show that the cell surface profile provides sufficient molecular information to classify samples from different cancers and tissue types into biologically relevant clusters using unsupervised hierarchical clustering. Finally, we describe the identification of a candidate lineage marker and its subsequent validation. In summary, HT-FC combines the advantages of a high-throughput screen with a detection method that is sensitive, quantitative, highly reproducible, and allows in-depth analysis of heterogeneous samples. The use of commercially available antibodies means that high quality reagents are immediately available for follow-up studies. HT-FC has a wide range of applications, including biomarker discovery, molecular classification of cancers, or identification of novel lineage specific or stem cell markers.

Insight into the intermolecular recognition mechanism between Keap1 and IKKβ combining homology modelling, protein-protein docking, molecular dynamics simulations and virtual alanine mutation.

Directory of Open Access Journals (Sweden)

Zheng-Yu Jiang

Full Text Available Degradation of certain proteins through the ubiquitin-proteasome pathway is a common strategy taken by the key modulators responsible for stress responses. Kelch-like ECH-associated protein-1(Keap1, a substrate adaptor component of the Cullin3 (Cul3-based ubiquitin E3 ligase complex, mediates the ubiquitination of two key modulators, NF-E2-related factor 2 (Nrf2 and IκB kinase β (IKKβ, which are involved in the redox control of gene transcription. However, compared to the Keap1-Nrf2 protein-protein interaction (PPI, the intermolecular recognition mechanism of Keap1 and IKKβ has been poorly investigated. In order to explore the binding pattern between Keap1 and IKKβ, the PPI model of Keap1 and IKKβ was investigated. The structure of human IKKβ was constructed by means of the homology modeling method and using reported crystal structure of Xenopus laevis IKKβ as the template. A protein-protein docking method was applied to develop the Keap1-IKKβ complex model. After the refinement and visual analysis of docked proteins, the chosen pose was further optimized through molecular dynamics simulations. The resulting structure was utilized to conduct the virtual alanine mutation for the exploration of hot-spots significant for the intermolecular interaction. Overall, our results provided structural insights into the PPI model of Keap1-IKKβ and suggest that the substrate specificity of Keap1 depend on the interaction with the key tyrosines, namely Tyr525, Tyr574 and Tyr334. The study presented in the current project may be useful to design molecules that selectively modulate Keap1. The selective recognition mechanism of Keap1 with IKKβ or Nrf2 will be helpful to further know the crosstalk between NF-κB and Nrf2 signaling.

High-Throughput Block Optical DNA Sequence Identification.

Science.gov (United States)

Sagar, Dodderi Manjunatha; Korshoj, Lee Erik; Hanson, Katrina Bethany; Chowdhury, Partha Pratim; Otoupal, Peter Britton; Chatterjee, Anushree; Nagpal, Prashant

2018-01-01

Optical techniques for molecular diagnostics or DNA sequencing generally rely on small molecule fluorescent labels, which utilize light with a wavelength of several hundred nanometers for detection. Developing a label-free optical DNA sequencing technique will require nanoscale focusing of light, a high-throughput and multiplexed identification method, and a data compression technique to rapidly identify sequences and analyze genomic heterogeneity for big datasets. Such a method should identify characteristic molecular vibrations using optical spectroscopy, especially in the "fingerprinting region" from ≈400-1400 cm -1 . Here, surface-enhanced Raman spectroscopy is used to demonstrate label-free identification of DNA nucleobases with multiplexed 3D plasmonic nanofocusing. While nanometer-scale mode volumes prevent identification of single nucleobases within a DNA sequence, the block optical technique can identify A, T, G, and C content in DNA k-mers. The content of each nucleotide in a DNA block can be a unique and high-throughput method for identifying sequences, genes, and other biomarkers as an alternative to single-letter sequencing. Additionally, coupling two complementary vibrational spectroscopy techniques (infrared and Raman) can improve block characterization. These results pave the way for developing a novel, high-throughput block optical sequencing method with lossy genomic data compression using k-mer identification from multiplexed optical data acquisition. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Docking studies of antidepressants against single crystal structure of tryptophan 2, 3-dioxygenase using Molegro Virtual Docker software.

Science.gov (United States)

Dawood, Shazia; Zarina, Shamshad; Bano, Samina

2014-09-01

Tryptophan 2, 3-dioxygenase (TDO) a heme containing enzyme found in mammalian liver is responsible for tryptophan (Trp) catabolism. Trp is an essential amino acid that is degraded in to N-formylkynurenine by the action of TDO. The protein ligand interaction plays a significant role in structural based drug designing. The current study illustrates the binding of established antidepressants (ADs) against TDO enzyme using in-silico docking studies. For this purpose, Fluoxetine, Paroxetine, Sertraline, Fluvoxamine, Seproxetine, Citalopram, Moclobamide, Hyperforin and Amoxepine were selected. In-silico docking studies were carried out using Molegro Virtual Docker (MVD) software. Docking results show that all ADs fit well in the active site of TDO moreover Hyperforin and Paroxetine exhibited high docking scores of -152.484k cal/mol and -139.706k cal/mol, respectively. It is concluded that Hyperforin and Paroxetine are possible lead molecules because of their high docking scores as compared to other ADs examined. Therefore, these two ADs stand as potent inhibitors of TDO enzyme.

Structural interface parameters are discriminatory in recognising near-native poses of protein-protein interactions.

Directory of Open Access Journals (Sweden)

Sony Malhotra

Full Text Available Interactions at the molecular level in the cellular environment play a very crucial role in maintaining the physiological functioning of the cell. These molecular interactions exist at varied levels viz. protein-protein interactions, protein-nucleic acid interactions or protein-small molecules interactions. Presently in the field, these interactions and their mechanisms mark intensively studied areas. Molecular interactions can also be studied computationally using the approach named as Molecular Docking. Molecular docking employs search algorithms to predict the possible conformations for interacting partners and then calculates interaction energies. However, docking proposes number of solutions as different docked poses and hence offers a serious challenge to identify the native (or near native structures from the pool of these docked poses. Here, we propose a rigorous scoring scheme called DockScore which can be used to rank the docked poses and identify the best docked pose out of many as proposed by docking algorithm employed. The scoring identifies the optimal interactions between the two protein partners utilising various features of the putative interface like area, short contacts, conservation, spatial clustering and the presence of positively charged and hydrophobic residues. DockScore was first trained on a set of 30 protein-protein complexes to determine the weights for different parameters. Subsequently, we tested the scoring scheme on 30 different protein-protein complexes and native or near-native structure were assigned the top rank from a pool of docked poses in 26 of the tested cases. We tested the ability of DockScore to discriminate likely dimer interactions that differ substantially within a homologous family and also demonstrate that DOCKSCORE can distinguish correct pose for all 10 recent CAPRI targets.

Hot-spot analysis for drug discovery targeting protein-protein interactions.

Science.gov (United States)

Rosell, Mireia; Fernández-Recio, Juan

2018-04-01

Protein-protein interactions are important for biological processes and pathological situations, and are attractive targets for drug discovery. However, rational drug design targeting protein-protein interactions is still highly challenging. Hot-spot residues are seen as the best option to target such interactions, but their identification requires detailed structural and energetic characterization, which is only available for a tiny fraction of protein interactions. Areas covered: In this review, the authors cover a variety of computational methods that have been reported for the energetic analysis of protein-protein interfaces in search of hot-spots, and the structural modeling of protein-protein complexes by docking. This can help to rationalize the discovery of small-molecule inhibitors of protein-protein interfaces of therapeutic interest. Computational analysis and docking can help to locate the interface, molecular dynamics can be used to find suitable cavities, and hot-spot predictions can focus the search for inhibitors of protein-protein interactions. Expert opinion: A major difficulty for applying rational drug design methods to protein-protein interactions is that in the majority of cases the complex structure is not available. Fortunately, computational docking can complement experimental data. An interesting aspect to explore in the future is the integration of these strategies for targeting PPIs with large-scale mutational analysis.

High-throughput micro-scale cultivations and chromatography modeling: Powerful tools for integrated process development.

Science.gov (United States)

Baumann, Pascal; Hahn, Tobias; Hubbuch, Jürgen

2015-10-01

Upstream processes are rather complex to design and the productivity of cells under suitable cultivation conditions is hard to predict. The method of choice for examining the design space is to execute high-throughput cultivation screenings in micro-scale format. Various predictive in silico models have been developed for many downstream processes, leading to a reduction of time and material costs. This paper presents a combined optimization approach based on high-throughput micro-scale cultivation experiments and chromatography modeling. The overall optimized system must not necessarily be the one with highest product titers, but the one resulting in an overall superior process performance in up- and downstream. The methodology is presented in a case study for the Cherry-tagged enzyme Glutathione-S-Transferase from Escherichia coli SE1. The Cherry-Tag™ (Delphi Genetics, Belgium) which can be fused to any target protein allows for direct product analytics by simple VIS absorption measurements. High-throughput cultivations were carried out in a 48-well format in a BioLector micro-scale cultivation system (m2p-Labs, Germany). The downstream process optimization for a set of randomly picked upstream conditions producing high yields was performed in silico using a chromatography modeling software developed in-house (ChromX). The suggested in silico-optimized operational modes for product capturing were validated subsequently. The overall best system was chosen based on a combination of excellent up- and downstream performance. © 2015 Wiley Periodicals, Inc.

High-Throughput Scoring of Seed Germination.

Science.gov (United States)

Ligterink, Wilco; Hilhorst, Henk W M

2017-01-01

High-throughput analysis of seed germination for phenotyping large genetic populations or mutant collections is very labor intensive and would highly benefit from an automated setup. Although very often used, the total germination percentage after a nominated period of time is not very informative as it lacks information about start, rate, and uniformity of germination, which are highly indicative of such traits as dormancy, stress tolerance, and seed longevity. The calculation of cumulative germination curves requires information about germination percentage at various time points. We developed the GERMINATOR package: a simple, highly cost-efficient, and flexible procedure for high-throughput automatic scoring and evaluation of germination that can be implemented without the use of complex robotics. The GERMINATOR package contains three modules: (I) design of experimental setup with various options to replicate and randomize samples; (II) automatic scoring of germination based on the color contrast between the protruding radicle and seed coat on a single image; and (III) curve fitting of cumulative germination data and the extraction, recap, and visualization of the various germination parameters. GERMINATOR is a freely available package that allows the monitoring and analysis of several thousands of germination tests, several times a day by a single person.

Dynamic Docking: A Paradigm Shift in Computational Drug Discovery

Directory of Open Access Journals (Sweden)

Dario Gioia

2017-11-01

Full Text Available Molecular docking is the methodology of choice for studying in silico protein-ligand binding and for prioritizing compounds to discover new lead candidates. Traditional docking simulations suffer from major limitations, mostly related to the static or semi-flexible treatment of ligands and targets. They also neglect solvation and entropic effects, which strongly limits their predictive power. During the last decade, methods based on full atomistic molecular dynamics (MD have emerged as a valid alternative for simulating macromolecular complexes. In principle, compared to traditional docking, MD allows the full exploration of drug-target recognition and binding from both the mechanistic and energetic points of view (dynamic docking. Binding and unbinding kinetic constants can also be determined. While dynamic docking is still too computationally expensive to be routinely used in fast-paced drug discovery programs, the advent of faster computing architectures and advanced simulation methodologies are changing this scenario. It is feasible that dynamic docking will replace static docking approaches in the near future, leading to a major paradigm shift in in silico drug discovery. Against this background, we review the key achievements that have paved the way for this progress.

High throughput salt separation from uranium deposits

Energy Technology Data Exchange (ETDEWEB)

Kwon, S.W.; Park, K.M.; Kim, J.G.; Kim, I.T.; Park, S.B., E-mail: swkwon@kaeri.re.kr [Korea Atomic Energy Research Inst. (Korea, Republic of)

2014-07-01

It is very important to increase the throughput of the salt separation system owing to the high uranium content of spent nuclear fuel and high salt fraction of uranium dendrites in pyroprocessing. Multilayer porous crucible system was proposed to increase a throughput of the salt distiller in this study. An integrated sieve-crucible assembly was also investigated for the practical use of the porous crucible system. The salt evaporation behaviors were compared between the conventional nonporous crucible and the porous crucible. Two step weight reductions took place in the porous crucible, whereas the salt weight reduced only at high temperature by distillation in a nonporous crucible. The first weight reduction in the porous crucible was caused by the liquid salt penetrated out through the perforated crucible during the temperature elevation until the distillation temperature. Multilayer porous crucibles have a benefit to expand the evaporation surface area. (author)

GROMACS 4.5: A high-throughput and highly parallel open source molecular simulation toolkit

Energy Technology Data Exchange (ETDEWEB)

Pronk, Sander [Science for Life Lab., Stockholm (Sweden); KTH Royal Institute of Technology, Stockholm (Sweden); Pall, Szilard [Science for Life Lab., Stockholm (Sweden); KTH Royal Institute of Technology, Stockholm (Sweden); Schulz, Roland [Univ. of Tennessee, Knoxville, TN (United States); Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Larsson, Per [Univ. of Virginia, Charlottesville, VA (United States); Bjelkmar, Par [Science for Life Lab., Stockholm (Sweden); Stockholm Univ., Stockholm (Sweden); Apostolov, Rossen [Science for Life Lab., Stockholm (Sweden); KTH Royal Institute of Technology, Stockholm (Sweden); Shirts, Michael R. [Univ. of Virginia, Charlottesville, VA (United States); Smith, Jeremy C. [Univ. of Tennessee, Knoxville, TN (United States); Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States); Kasson, Peter M. [Univ. of Virginia, Charlottesville, VA (United States); van der Spoel, David [Science for Life Lab., Stockholm (Sweden); Uppsala Univ., Uppsala (Sweden); Hess, Berk [Science for Life Lab., Stockholm (Sweden); KTH Royal Institute of Technology, Stockholm (Sweden); Lindahl, Erik [Science for Life Lab., Stockholm (Sweden); KTH Royal Institute of Technology, Stockholm (Sweden); Stockholm Univ., Stockholm (Sweden)

2013-02-13

In this study, molecular simulation has historically been a low-throughput technique, but faster computers and increasing amounts of genomic and structural data are changing this by enabling large-scale automated simulation of, for instance, many conformers or mutants of biomolecules with or without a range of ligands. At the same time, advances in performance and scaling now make it possible to model complex biomolecular interaction and function in a manner directly testable by experiment. These applications share a need for fast and efficient software that can be deployed on massive scale in clusters, web servers, distributed computing or cloud resources. As a result, we present a range of new simulation algorithms and features developed during the past 4 years, leading up to the GROMACS 4.5 software package. The software now automatically handles wide classes of biomolecules, such as proteins, nucleic acids and lipids, and comes with all commonly used force fields for these molecules built-in. GROMACS supports several implicit solvent models, as well as new free-energy algorithms, and the software now uses multithreading for efficient parallelization even on low-end systems, including windows-based workstations. Together with hand-tuned assembly kernels and state-of-the-art parallelization, this provides extremely high performance and cost efficiency for high-throughput as well as massively parallel simulations.

Efficient visualization of high-throughput targeted proteomics experiments: TAPIR.

Science.gov (United States)

Röst, Hannes L; Rosenberger, George; Aebersold, Ruedi; Malmström, Lars

2015-07-15

Targeted mass spectrometry comprises a set of powerful methods to obtain accurate and consistent protein quantification in complex samples. To fully exploit these techniques, a cross-platform and open-source software stack based on standardized data exchange formats is required. We present TAPIR, a fast and efficient Python visualization software for chromatograms and peaks identified in targeted proteomics experiments. The input formats are open, community-driven standardized data formats (mzML for raw data storage and TraML encoding the hierarchical relationships between transitions, peptides and proteins). TAPIR is scalable to proteome-wide targeted proteomics studies (as enabled by SWATH-MS), allowing researchers to visualize high-throughput datasets. The framework integrates well with existing automated analysis pipelines and can be extended beyond targeted proteomics to other types of analyses. TAPIR is available for all computing platforms under the 3-clause BSD license at https://github.com/msproteomicstools/msproteomicstools. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

High throughput, low set-up time reconfigurable linear feedback shift registers

NARCIS (Netherlands)

Nas, R.J.M.; Berkel, van C.H.

2010-01-01

This paper presents a hardware design for a scalable, high throughput, configurable LFSR. High throughput is achieved by producing L consecutive outputs per clock cycle with a clock cycle period that, for practical cases, increases only logarithmically with the block size L and the length of the

High-throughput epitope identification for snakebite antivenom

DEFF Research Database (Denmark)

Engmark, Mikael; De Masi, Federico; Laustsen, Andreas Hougaard

Insight into the epitopic recognition pattern for polyclonal antivenoms is a strong tool for accurate prediction of antivenom cross-reactivity and provides a basis for design of novel antivenoms. In this work, a high-throughput approach was applied to characterize linear epitopes in 966 individua...... toxins from pit vipers (Crotalidae) using the ICP Crotalidae antivenom. Due to an abundance of snake venom metalloproteinases and phospholipase A2s in the venoms used for production of the investigated antivenom, this study focuses on these toxin families.......Insight into the epitopic recognition pattern for polyclonal antivenoms is a strong tool for accurate prediction of antivenom cross-reactivity and provides a basis for design of novel antivenoms. In this work, a high-throughput approach was applied to characterize linear epitopes in 966 individual...

Dimerization of the docking/adaptor protein HEF1 via a carboxy-terminal helix-loop-helix domain.

Science.gov (United States)

Law, S F; Zhang, Y Z; Fashena, S J; Toby, G; Estojak, J; Golemis, E A

1999-10-10

HEF1, p130(Cas), and Efs define a family of multidomain docking proteins which plays a central coordinating role for tyrosine-kinase-based signaling related to cell adhesion. HEF1 function has been specifically implicated in signaling pathways important for cell adhesion and differentiation in lymphoid and epithelial cells. While the SH3 domains and SH2-binding site domains (substrate domains) of HEF1 family proteins are well characterized and binding partners known, to date the highly conserved carboxy-terminal domains of the three proteins have lacked functional definition. In this study, we have determined that the carboxy-terminal domain of HEF1 contains a divergent helix-loop-helix (HLH) motif. This motif mediates HEF1 homodimerization and HEF1 heterodimerization with a recognition specificity similar to that of the transcriptional regulatory HLH proteins Id2, E12, and E47. We had previously demonstrated that the HEF1 carboxy-terminus expressed as a separate domain in yeast reprograms cell division patterns, inducing constitutive pseudohyphal growth. Here we show that pseudohyphal induction by HEF1 requires an intact HLH, further supporting the idea that this motif has an effector activity for HEF1, and implying that HEF1 pseudohyphal activity derives in part from interactions with yeast helix-loop-helix proteins. These combined results provide initial insight into the mode of function of the HEF1 carboxy-terminal domain and suggest that the HEF1 protein may interact with cellular proteins which control differentiation. Copyright 1999 Academic Press.

Towards a high throughput droplet-based agglutination assay

KAUST Repository

Kodzius, Rimantas; Castro, David; Foulds, Ian G.

2013-01-01

This work demonstrates the detection method for a high throughput droplet based agglutination assay system. Using simple hydrodynamic forces to mix and aggregate functionalized microbeads we avoid the need to use magnetic assistance or mixing structures. The concentration of our target molecules was estimated by agglutination strength, obtained through optical image analysis. Agglutination in droplets was performed with flow rates of 150 µl/min and occurred in under a minute, with potential to perform high-throughput measurements. The lowest target concentration detected in droplet microfluidics was 0.17 nM, which is three orders of magnitude more sensitive than a conventional card based agglutination assay.

Towards a high throughput droplet-based agglutination assay

KAUST Repository

Kodzius, Rimantas

2013-10-22

This work demonstrates the detection method for a high throughput droplet based agglutination assay system. Using simple hydrodynamic forces to mix and aggregate functionalized microbeads we avoid the need to use magnetic assistance or mixing structures. The concentration of our target molecules was estimated by agglutination strength, obtained through optical image analysis. Agglutination in droplets was performed with flow rates of 150 µl/min and occurred in under a minute, with potential to perform high-throughput measurements. The lowest target concentration detected in droplet microfluidics was 0.17 nM, which is three orders of magnitude more sensitive than a conventional card based agglutination assay.

DockBench: An Integrated Informatic Platform Bridging the Gap between the Robust Validation of Docking Protocols and Virtual Screening Simulations

Directory of Open Access Journals (Sweden)

Alberto Cuzzolin

2015-05-01

Full Text Available Virtual screening (VS is a computational methodology that streamlines the drug discovery process by reducing costs and required resources through the in silico identification of potential drug candidates. Structure-based VS (SBVS exploits knowledge about the three-dimensional (3D structure of protein targets and uses the docking methodology as search engine for novel hits. The success of a SBVS campaign strongly depends upon the accuracy of the docking protocol used to select the candidates from large chemical libraries. The identification of suitable protocols is therefore a crucial step in the setup of SBVS experiments. Carrying out extensive benchmark studies, however, is usually a tangled task that requires users’ proficiency in handling different file formats and philosophies at the basis of the plethora of existing software packages. We present here DockBench 1.0, a platform available free of charge that eases the pipeline by automating the entire procedure, from docking benchmark to VS setups. In its current implementation, DockBench 1.0 handles seven docking software packages and offers the possibility to test up to seventeen different protocols. The main features of our platform are presented here and the results of the benchmark study of human Checkpoint kinase 1 (hChk1 are discussed as validation test.

Evaluating the binding efficiency of pheromone binding protein with its natural ligand using molecular docking and fluorescence analysis

Science.gov (United States)

Ilayaraja, Renganathan; Rajkumar, Ramalingam; Rajesh, Durairaj; Muralidharan, Arumugam Ramachandran; Padmanabhan, Parasuraman; Archunan, Govindaraju

2014-06-01

Chemosignals play a crucial role in social and sexual communication among inter- and intra-species. Chemical cues are bound with protein that is present in the pheromones irrespective of sex are commonly called as pheromone binding protein (PBP). In rats, the pheromone compounds are bound with low molecular lipocalin protein α2u-globulin (α2u). We reported farnesol is a natural endogenous ligand (compound) present in rat preputial gland as a bound volatile compound. In the present study, an attempt has been made through computational method to evaluating the binding efficiency of α2u with the natural ligand (farnesol) and standard fluorescent molecule (2-naphthol). The docking analysis revealed that the binding energy of farnesol and 2-naphthol was almost equal and likely to share some binding pocket of protein. Further, to extrapolate the results generated through computational approach, the α2u protein was purified and subjected to fluorescence titration and binding assay. The results showed that the farnesol is replaced by 2-naphthol with high hydrophobicity of TYR120 in binding sites of α2u providing an acceptable dissociation constant indicating the binding efficiency of α2u. The obtained results are in corroboration with the data made through computational approach.

High-throughput screening of small molecule libraries using SAMDI mass spectrometry.

Science.gov (United States)

Gurard-Levin, Zachary A; Scholle, Michael D; Eisenberg, Adam H; Mrksich, Milan

2011-07-11

High-throughput screening is a common strategy used to identify compounds that modulate biochemical activities, but many approaches depend on cumbersome fluorescent reporters or antibodies and often produce false-positive hits. The development of "label-free" assays addresses many of these limitations, but current approaches still lack the throughput needed for applications in drug discovery. This paper describes a high-throughput, label-free assay that combines self-assembled monolayers with mass spectrometry, in a technique called SAMDI, as a tool for screening libraries of 100,000 compounds in one day. This method is fast, has high discrimination, and is amenable to a broad range of chemical and biological applications.

Activated Cdc42 kinase regulates Dock localization in male germ cells during Drosophila spermatogenesis.

Science.gov (United States)

Abdallah, Abbas M; Zhou, Xin; Kim, Christine; Shah, Kushani K; Hogden, Christopher; Schoenherr, Jessica A; Clemens, James C; Chang, Henry C

2013-06-15

Deregulation of the non-receptor tyrosine kinase ACK1 (Activated Cdc42-associated kinase) correlates with poor prognosis in cancers and has been implicated in promoting metastasis. To further understand its in vivo function, we have characterized the developmental defects of a null mutation in Drosophila Ack, which bears a high degree of sequence similarity to mammalian ACK1 but lacks a CRIB domain. We show that Ack, while not essential for viability, is critical for sperm formation. This function depends on Ack tyrosine kinase activity and is required cell autonomously in differentiating male germ cells at or after the spermatocyte stage. Ack associates predominantly with endocytic clathrin sites in spermatocytes, but disruption of Ack function has no apparent effect on clathrin localization and receptor-mediated internalization of Boss (Bride of sevenless) protein in eye discs. Instead, Ack is required for the subcellular distribution of Dock (dreadlocks), the Drosophila homolog of the SH2- and SH3-containing adaptor protein Nck. Moreover, Dock forms a complex with Ack, and the localization of Dock in male germ cells depends on its SH2 domain. Together, our results suggest that Ack-dependent tyrosine phosphorylation recruits Dock to promote sperm differentiation. Copyright © 2013 Elsevier Inc. All rights reserved.

Preliminary High-Throughput Metagenome Assembly

Energy Technology Data Exchange (ETDEWEB)

Dusheyko, Serge; Furman, Craig; Pangilinan, Jasmyn; Shapiro, Harris; Tu, Hank

2007-03-26

Metagenome data sets present a qualitatively different assembly problem than traditional single-organism whole-genome shotgun (WGS) assembly. The unique aspects of such projects include the presence of a potentially large number of distinct organisms and their representation in the data set at widely different fractions. In addition, multiple closely related strains could be present, which would be difficult to assemble separately. Failure to take these issues into account can result in poor assemblies that either jumble together different strains or which fail to yield useful results. The DOE Joint Genome Institute has sequenced a number of metagenomic projects and plans to considerably increase this number in the coming year. As a result, the JGI has a need for high-throughput tools and techniques for handling metagenome projects. We present the techniques developed to handle metagenome assemblies in a high-throughput environment. This includes a streamlined assembly wrapper, based on the JGI?s in-house WGS assembler, Jazz. It also includes the selection of sensible defaults targeted for metagenome data sets, as well as quality control automation for cleaning up the raw results. While analysis is ongoing, we will discuss preliminary assessments of the quality of the assembly results (http://fames.jgi-psf.org).

Nanoscale Synaptic Membrane Mimetic Allows Unbiased High Throughput Screen That Targets Binding Sites for Alzheimer’s-Associated Aβ Oligomers

Science.gov (United States)

Wilcox, Kyle C.; Marunde, Matthew R.; Das, Aditi; Velasco, Pauline T.; Kuhns, Benjamin D.; Marty, Michael T.; Jiang, Haoming; Luan, Chi-Hao; Sligar, Stephen G.; Klein, William L.

2015-01-01

Despite their value as sources of therapeutic drug targets, membrane proteomes are largely inaccessible to high-throughput screening (HTS) tools designed for soluble proteins. An important example comprises the membrane proteins that bind amyloid β oligomers (AβOs). AβOs are neurotoxic ligands thought to instigate the synapse damage that leads to Alzheimer’s dementia. At present, the identities of initial AβO binding sites are highly uncertain, largely because of extensive protein-protein interactions that occur following attachment of AβOs to surface membranes. Here, we show that AβO binding sites can be obtained in a state suitable for unbiased HTS by encapsulating the solubilized synaptic membrane proteome into nanoscale lipid bilayers (Nanodiscs). This method gives a soluble membrane protein library (SMPL)—a collection of individualized synaptic proteins in a soluble state. Proteins within SMPL Nanodiscs showed enzymatic and ligand binding activity consistent with conformational integrity. AβOs were found to bind SMPL Nanodiscs with high affinity and specificity, with binding dependent on intact synaptic membrane proteins, and selective for the higher molecular weight oligomers known to accumulate at synapses. Combining SMPL Nanodiscs with a mix-incubate-read chemiluminescence assay provided a solution-based HTS platform to discover antagonists of AβO binding. Screening a library of 2700 drug-like compounds and natural products yielded one compound that potently reduced AβO binding to SMPL Nanodiscs, synaptosomes, and synapses in nerve cell cultures. Although not a therapeutic candidate, this small molecule inhibitor of synaptic AβO binding will provide a useful experimental antagonist for future mechanistic studies of AβOs in Alzheimer’s model systems. Overall, results provide proof of concept for using SMPLs in high throughput screening for AβO binding antagonists, and illustrate in general how a SMPL Nanodisc system can facilitate drug

Looking for inhibitors of the dengue virus NS5 RNA-dependent RNA-polymerase using a molecular docking approach

Directory of Open Access Journals (Sweden)

Galiano V

2016-10-01

Full Text Available Vicente Galiano,1 Pablo Garcia-Valtanen,2 Vicente Micol,3,4 José Antonio Encinar3 1Physics and Computer Architecture Department, Miguel Hernández University (UMH, Elche, Spain; 2Experimental Therapeutics Laboratory, Hanson and Sansom Institute for Health Research, School of Pharmacy and Medical Science, University of South Australia, Adelaide, Australia; 3Molecular and Cell Biology Institute, Miguel Hernández University (UMH, Elche, Spain; 4CIBER: CB12/03/30038, Physiopathology of the Obesity and Nutrition, CIBERobn, Instituto de Salud Carlos III, Palma de Mallorca, Spain Abstract: The dengue virus (DENV nonstructural protein 5 (NS5 contains both an N-terminal methyltransferase domain and a C-terminal RNA-dependent RNA polymerase domain. Polymerase activity is responsible for viral RNA synthesis by a de novo initiation mechanism and represents an attractive target for antiviral therapy. The incidence of DENV has grown rapidly and it is now estimated that half of the human population is at risk of becoming infected with this virus. Despite this, there are no effective drugs to treat DENV infections. The present in silico study aimed at finding new inhibitors of the NS5 RNA-dependent RNA polymerase of the four serotypes of DENV. We used a chemical library comprising 372,792 nonnucleotide compounds (around 325,319 natural compounds to perform molecular docking experiments against a binding site of the RNA template tunnel of the virus polymerase. Compounds with high negative free energy variation (ΔG <-10.5 kcal/mol were selected as putative inhibitors. Additional filters for favorable druggability and good absorption, distribution, metabolism, excretion, and toxicity were applied. Finally, after the screening process was completed, we identified 39 compounds as lead DENV polymerase inhibitor candidates. Potentially, these compounds could act as efficient DENV polymerase inhibitors in vitro and in vivo. Keywords: virtual screening, molecular

High-throughput bioscreening system utilizing high-performance affinity magnetic carriers exhibiting minimal non-specific protein binding

International Nuclear Information System (INIS)

Hanyu, Naohiro; Nishio, Kosuke; Hatakeyama, Mamoru; Yasuno, Hiroshi; Tanaka, Toshiyuki; Tada, Masaru; Nakagawa, Takashi; Sandhu, Adarsh; Abe, Masanori; Handa, Hiroshi

2009-01-01

For affinity purification of drug target protein we have developed magnetic carriers, narrow in size distribution (184±9 nm), which exhibit minimal non-specific binding of unwanted proteins. The carriers were highly dispersed in aqueous solutions and highly resistant to organic solvents, which enabled immobilization of various hydrophobic chemicals as probes on the carrier surfaces. Utilizing the carriers we have automated the process of separation and purification of the target proteins that had been done by manual operation previously.

High-throughput sperm differential proteomics suggests that epigenetic alterations contribute to failed assisted reproduction.

Science.gov (United States)

Azpiazu, Rubén; Amaral, Alexandra; Castillo, Judit; Estanyol, Josep Maria; Guimerà, Marta; Ballescà, Josep Lluís; Balasch, Juan; Oliva, Rafael

2014-06-01

Are there quantitative alterations in the proteome of normozoospermic sperm samples that are able to complete IVF but whose female partner does not achieve pregnancy? Normozoospermic sperm samples with different IVF outcomes (pregnancy versus no pregnancy) differed in the levels of at least 66 proteins. The analysis of the proteome of sperm samples with distinct fertilization capacity using low-throughput proteomic techniques resulted in the detection of a few differential proteins. Current high-throughput mass spectrometry approaches allow the identification and quantification of a substantially higher number of proteins. This was a case-control study including 31 men with normozoospermic sperm and their partners who underwent IVF with successful fertilization recruited between 2007 and 2008. Normozoospermic sperm samples from 15 men whose female partners did not achieve pregnancy after IVF (no pregnancy) and 16 men from couples that did achieve pregnancy after IVF (pregnancy) were included in this study. To perform the differential proteomic experiments, 10 no pregnancy samples and 10 pregnancy samples were separately pooled and subsequently used for tandem mass tags (TMT) protein labelling, sodium dodecyl sulphate-polyacrylamide gel electrophoresis, liquid chromatography tandem mass spectrometry (LC-MS/MS) identification and peak intensity relative protein quantification. Bioinformatic analyses were performed using UniProt Knowledgebase, DAVID and Reactome. Individual samples (n = 5 no pregnancy samples; n = 6 pregnancy samples) and aliquots from the above TMT pools were used for western blotting. By using TMT labelling and LC-MS/MS, we have detected 31 proteins present at lower abundance (ratio no pregnancy/pregnancy 1.5) in the no pregnancy group. Bioinformatic analyses showed that the proteins with differing abundance are involved in chromatin assembly and lipoprotein metabolism (P values Economia y Competividad; FEDER BFU 2009-07118 and PI13/00699) and

Covalent docking of selected boron-based serine beta-lactamase inhibitors

Science.gov (United States)

Sgrignani, Jacopo; Novati, Beatrice; Colombo, Giorgio; Grazioso, Giovanni

2015-05-01

AmpC β-lactamase is a hydrolytic enzyme conferring resistance to β-lactam antibiotics in multiple Gram-negative bacteria. Therefore, identification of non-β-lactam compounds able to inhibit the enzyme is crucial for the development of novel antibacterial therapies. In general, AmpC inhibitors have to engage the highly solvent-exposed catalytic site of the enzyme. Therefore, understanding the implications of ligand-protein induced-fit and water-mediated interactions behind the inhibitor-enzyme recognition process is fundamental for undertaking structure-based drug design process. Here, we focus on boronic acids, a promising class of beta-lactamase covalent inhibitors. First, we optimized a docking protocol able to reproduce the experimentally determined binding mode of AmpC inhibitors bearing a boronic group. This goal was pursued (1) performing rigid and flexible docking calculations aiming to establish the role of the side chain conformations; and (2) investigating the role of specific water molecules in shaping the enzyme active site and mediating ligand protein interactions. Our calculations showed that some water molecules, conserved in the majority of the considered X-ray structures, are needed to correctly predict the binding pose of known covalent AmpC inhibitors. On this basis, we formalized our findings in a docking and scoring protocol that could be useful for the structure-based design of new boronic acid AmpC inhibitors.

A high-throughput multiplex method adapted for GMO detection.

Science.gov (United States)

Chaouachi, Maher; Chupeau, Gaëlle; Berard, Aurélie; McKhann, Heather; Romaniuk, Marcel; Giancola, Sandra; Laval, Valérie; Bertheau, Yves; Brunel, Dominique

2008-12-24

A high-throughput multiplex assay for the detection of genetically modified organisms (GMO) was developed on the basis of the existing SNPlex method designed for SNP genotyping. This SNPlex assay allows the simultaneous detection of up to 48 short DNA sequences (approximately 70 bp; "signature sequences") from taxa endogenous reference genes, from GMO constructions, screening targets, construct-specific, and event-specific targets, and finally from donor organisms. This assay avoids certain shortcomings of multiplex PCR-based methods already in widespread use for GMO detection. The assay demonstrated high specificity and sensitivity. The results suggest that this assay is reliable, flexible, and cost- and time-effective for high-throughput GMO detection.

Using the multi-objective optimization replica exchange Monte Carlo enhanced sampling method for protein-small molecule docking.

Science.gov (United States)

Wang, Hongrui; Liu, Hongwei; Cai, Leixin; Wang, Caixia; Lv, Qiang

2017-07-10

In this study, we extended the replica exchange Monte Carlo (REMC) sampling method to protein-small molecule docking conformational prediction using RosettaLigand. In contrast to the traditional Monte Carlo (MC) and REMC sampling methods, these methods use multi-objective optimization Pareto front information to facilitate the selection of replicas for exchange. The Pareto front information generated to select lower energy conformations as representative conformation structure replicas can facilitate the convergence of the available conformational space, including available near-native structures. Furthermore, our approach directly provides min-min scenario Pareto optimal solutions, as well as a hybrid of the min-min and max-min scenario Pareto optimal solutions with lower energy conformations for use as structure templates in the REMC sampling method. These methods were validated based on a thorough analysis of a benchmark data set containing 16 benchmark test cases. An in-depth comparison between MC, REMC, multi-objective optimization-REMC (MO-REMC), and hybrid MO-REMC (HMO-REMC) sampling methods was performed to illustrate the differences between the four conformational search strategies. Our findings demonstrate that the MO-REMC and HMO-REMC conformational sampling methods are powerful approaches for obtaining protein-small molecule docking conformational predictions based on the binding energy of complexes in RosettaLigand.

APSY-NMR for protein backbone assignment in high-throughput structural biology

Energy Technology Data Exchange (ETDEWEB)

Dutta, Samit Kumar; Serrano, Pedro; Proudfoot, Andrew; Geralt, Michael [The Scripps Research Institute, Department of Integrative Structural and Computational Biology (United States); Pedrini, Bill [Paul Scherrer Institute (PSI), SwissFEL Project (Switzerland); Herrmann, Torsten [Université de Lyon, Institut des Sciences Analytiques, Centre de RMN à Très Hauts Champs, UMR 5280 CNRS, ENS Lyon, UCB Lyon 1 (France); Wüthrich, Kurt, E-mail: wuthrich@scripps.edu [The Scripps Research Institute, Department of Integrative Structural and Computational Biology (United States)

2015-01-15

A standard set of three APSY-NMR experiments has been used in daily practice to obtain polypeptide backbone NMR assignments in globular proteins with sizes up to about 150 residues, which had been identified as targets for structure determination by the Joint Center for Structural Genomics (JCSG) under the auspices of the Protein Structure Initiative (PSI). In a representative sample of 30 proteins, initial fully automated data analysis with the software UNIO-MATCH-2014 yielded complete or partial assignments for over 90 % of the residues. For most proteins the APSY data acquisition was completed in less than 30 h. The results of the automated procedure provided a basis for efficient interactive validation and extension to near-completion of the assignments by reference to the same 3D heteronuclear-resolved [{sup 1}H,{sup 1}H]-NOESY spectra that were subsequently used for the collection of conformational constraints. High-quality structures were obtained for all 30 proteins, using the J-UNIO protocol, which includes extensive automation of NMR structure determination.

Quantification of rapid Myosin regulatory light chain phosphorylation using high-throughput in-cell Western assays: comparison to Western immunoblots.

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Hector N Aguilar

2010-04-01

Full Text Available Quantification of phospho-proteins (PPs is crucial when studying cellular signaling pathways. Western immunoblotting (WB is commonly used for the measurement of relative levels of signaling intermediates in experimental samples. However, WB is in general a labour-intensive and low-throughput technique. Because of variability in protein yield and phospho-signal preservation during protein harvesting, and potential loss of antigen during protein transfer, WB provides only semi-quantitative data. By comparison, the "in-cell western" (ICW technique has high-throughput capacity and requires less extensive sample preparation. Thus, we compared the ICW technique to WB for measuring phosphorylated myosin regulatory light chain (PMLC(20 in primary cultures of uterine myocytes to assess their relative specificity, sensitivity, precision, and quantification of biologically relevant responses.ICWs are cell-based microplate assays for quantification of protein targets in their cellular context. ICWs utilize a two-channel infrared (IR scanner (Odyssey(R to quantify signals arising from near-infrared (NIR fluorophores conjugated to secondary antibodies. One channel is dedicated to measuring the protein of interest and the second is used for data normalization of the signal in each well of the microplate. Using uterine myocytes, we assessed oxytocin (OT-stimulated MLC(20 phosphorylation measured by ICW and WB, both using NIR fluorescence. ICW and WB data were comparable regarding signal linearity, signal specificity, and time course of phosphorylation response to OT.ICW and WB yield comparable biological data. The advantages of ICW over WB are its high-throughput capacity, improved precision, and reduced sample preparation requirements. ICW might provide better sensitivity and precision with low-quantity samples or for protocols requiring large numbers of samples. These features make the ICW technique an excellent tool for the study of phosphorylation endpoints

Ranking multiple docking solutions based on the conservation of inter-residue contacts

KAUST Repository

Oliva, Romina M.

2013-06-17

Molecular docking is the method of choice for investigating the molecular basis of recognition in a large number of functional protein complexes. However, correctly scoring the obtained docking solutions (decoys) to rank native-like (NL) conformations in the top positions is still an open problem. Herein we present CONSRANK, a simple and effective tool to rank multiple docking solutions, which relies on the conservation of inter-residue contacts in the analyzed decoys ensemble. First it calculates a conservation rate for each inter-residue contact, then it ranks decoys according to their ability to match the more frequently observed contacts. We applied CONSRANK to 102 targets from three different benchmarks, RosettaDock, DOCKGROUND, and Critical Assessment of PRedicted Interactions (CAPRI). The method performs consistently well, both in terms of NL solutions ranked in the top positions and of values of the area under the receiver operating characteristic curve. Its ideal application is to solutions coming from different docking programs and procedures, as in the case of CAPRI targets. For all the analyzed CAPRI targets where a comparison is feasible, CONSRANK outperforms the CAPRI scorers. The fraction of NL solutions in the top ten positions in the RosettaDock, DOCKGROUND, and CAPRI benchmarks is enriched on average by a factor of 3.0, 1.9, and 9.9, respectively. Interestingly, CONSRANK is also able to specifically single out the high/medium quality (HMQ) solutions from the docking decoys ensemble: it ranks 46.2 and 70.8% of the total HMQ solutions available for the RosettaDock and CAPRI targets, respectively, within the top 20 positions. © 2013 Wiley Periodicals, Inc.

Versatile High-Throughput Fluorescence Assay for Monitoring Cas9 Activity.

Science.gov (United States)

Seamon, Kyle J; Light, Yooli K; Saada, Edwin A; Schoeniger, Joseph S; Harmon, Brooke

2018-06-05

The RNA-guided DNA nuclease Cas9 is now widely used for the targeted modification of genomes of human cells and various organisms. Despite the extensive use of Clustered Regularly Interspaced Palindromic Repeats (CRISPR) systems for genome engineering and the rapid discovery and engineering of new CRISPR-associated nucleases, there are no high-throughput assays for measuring enzymatic activity. The current laboratory and future therapeutic uses of CRISPR technology have a significant risk of accidental exposure or clinical off-target effects, underscoring the need for therapeutically effective inhibitors of Cas9. Here, we develop a fluorescence assay for monitoring Cas9 nuclease activity and demonstrate its utility with S. pyogenes (Spy), S. aureus (Sau), and C. jejuni (Cje) Cas9. The assay was validated by quantitatively profiling the species specificity of published anti-CRISPR (Acr) proteins, confirming the reported inhibition of Spy Cas9 by AcrIIA4 and Cje Cas9 by AcrIIC1 and no inhibition of Sau Cas9 by either anti-CRISPR. To identify drug-like inhibitors, we performed a screen of 189 606 small molecules for inhibition of Spy Cas9. Of 437 hits (0.2% hit rate), six were confirmed as Cas9 inhibitors in a direct gel electrophoresis secondary assay. The high-throughput nature of this assay makes it broadly applicable for the discovery of additional Cas9 inhibitors or the characterization of Cas9 enzyme variants.

High Throughput T Epitope Mapping and Vaccine Development

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Giuseppina Li Pira

2010-01-01

Full Text Available Mapping of antigenic peptide sequences from proteins of relevant pathogens recognized by T helper (Th and by cytolytic T lymphocytes (CTL is crucial for vaccine development. In fact, mapping of T-cell epitopes provides useful information for the design of peptide-based vaccines and of peptide libraries to monitor specific cellular immunity in protected individuals, patients and vaccinees. Nevertheless, epitope mapping is a challenging task. In fact, large panels of overlapping peptides need to be tested with lymphocytes to identify the sequences that induce a T-cell response. Since numerous peptide panels from antigenic proteins are to be screened, lymphocytes available from human subjects are a limiting factor. To overcome this limitation, high throughput (HTP approaches based on miniaturization and automation of T-cell assays are needed. Here we consider the most recent applications of the HTP approach to T epitope mapping. The alternative or complementary use of in silico prediction and experimental epitope definition is discussed in the context of the recent literature. The currently used methods are described with special reference to the possibility of applying the HTP concept to make epitope mapping an easier procedure in terms of time, workload, reagents, cells and overall cost.

High Throughput Analysis of Photocatalytic Water Purification

NARCIS (Netherlands)

Sobral Romao, J.I.; Baiao Barata, David; Habibovic, Pamela; Mul, Guido; Baltrusaitis, Jonas

2014-01-01

We present a novel high throughput photocatalyst efficiency assessment method based on 96-well microplates and UV-Vis spectroscopy. We demonstrate the reproducibility of the method using methyl orange (MO) decomposition, and compare kinetic data obtained with those provided in the literature for

High Throughput Synthesis and Screening for Agents Inhibiting Androgen Receptor Mediated Gene Transcription

National Research Council Canada - National Science Library

Boger, Dale L

2005-01-01

.... This entails the high throughput synthesis of DNA binding agents related to distamycin, their screening for binding to androgen response elements using a new high throughput DNA binding screen...

High Throughput Synthesis and Screening for Agents Inhibiting Androgen Receptor Mediated Gene Transcription

National Research Council Canada - National Science Library

Boger, Dale

2004-01-01

.... This entails the high throughput synthesis of DNA binding agents related to distamycin, their screening for binding to androgen response elements using a new high throughput DNA binding screen...

A CRISPR CASe for High-Throughput Silencing

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Jacob eHeintze

2013-10-01

Full Text Available Manipulation of gene expression on a genome-wide level is one of the most important systematic tools in the post-genome era. Such manipulations have largely been enabled by expression cloning approaches using sequence-verified cDNA libraries, large-scale RNA interference libraries (shRNA or siRNA and zinc finger nuclease technologies. More recently, the CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats and CRISPR-associated (Cas9-mediated gene editing technology has been described that holds great promise for future use of this technology in genomic manipulation. It was suggested that the CRISPR system has the potential to be used in high-throughput, large-scale loss of function screening. Here we discuss some of the challenges in engineering of CRISPR/Cas genomic libraries and some of the aspects that need to be addressed in order to use this technology on a high-throughput scale.

Virtual screening for HIV protease inhibitors: a comparison of AutoDock 4 and Vina.

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Max W Chang

Full Text Available BACKGROUND: The AutoDock family of software has been widely used in protein-ligand docking research. This study compares AutoDock 4 and AutoDock Vina in the context of virtual screening by using these programs to select compounds active against HIV protease. METHODOLOGY/PRINCIPAL FINDINGS: Both programs were used to rank the members of two chemical libraries, each containing experimentally verified binders to HIV protease. In the case of the NCI Diversity Set II, both AutoDock 4 and Vina were able to select active compounds significantly better than random (AUC = 0.69 and 0.68, respectively; p<0.001. The binding energy predictions were highly correlated in this case, with r = 0.63 and iota = 0.82. For a set of larger, more flexible compounds from the Directory of Universal Decoys, the binding energy predictions were not correlated, and only Vina was able to rank compounds significantly better than random. CONCLUSIONS/SIGNIFICANCE: In ranking smaller molecules with few rotatable bonds, AutoDock 4 and Vina were equally capable, though both exhibited a size-related bias in scoring. However, as Vina executes more quickly and is able to more accurately rank larger molecules, researchers should look to it first when undertaking a virtual screen.

GROMACS 4.5: a high-throughput and highly parallel open source molecular simulation toolkit.

Science.gov (United States)

Pronk, Sander; Páll, Szilárd; Schulz, Roland; Larsson, Per; Bjelkmar, Pär; Apostolov, Rossen; Shirts, Michael R; Smith, Jeremy C; Kasson, Peter M; van der Spoel, David; Hess, Berk; Lindahl, Erik

2013-04-01

Molecular simulation has historically been a low-throughput technique, but faster computers and increasing amounts of genomic and structural data are changing this by enabling large-scale automated simulation of, for instance, many conformers or mutants of biomolecules with or without a range of ligands. At the same time, advances in performance and scaling now make it possible to model complex biomolecular interaction and function in a manner directly testable by experiment. These applications share a need for fast and efficient software that can be deployed on massive scale in clusters, web servers, distributed computing or cloud resources. Here, we present a range of new simulation algorithms and features developed during the past 4 years, leading up to the GROMACS 4.5 software package. The software now automatically handles wide classes of biomolecules, such as proteins, nucleic acids and lipids, and comes with all commonly used force fields for these molecules built-in. GROMACS supports several implicit solvent models, as well as new free-energy algorithms, and the software now uses multithreading for efficient parallelization even on low-end systems, including windows-based workstations. Together with hand-tuned assembly kernels and state-of-the-art parallelization, this provides extremely high performance and cost efficiency for high-throughput as well as massively parallel simulations. GROMACS is an open source and free software available from http://www.gromacs.org. Supplementary data are available at Bioinformatics online.

SAMPL4 & DOCK3.7: lessons for automated docking procedures

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Coleman, Ryan G.; Sterling, Teague; Weiss, Dahlia R.

2014-03-01

The SAMPL4 challenges were used to test current automated methods for solvation energy, virtual screening, pose and affinity prediction of the molecular docking pipeline DOCK 3.7. Additionally, first-order models of binding affinity were proposed as milestones for any method predicting binding affinity. Several important discoveries about the molecular docking software were made during the challenge: (1) Solvation energies of ligands were five-fold worse than any other method used in SAMPL4, including methods that were similarly fast, (2) HIV Integrase is a challenging target, but automated docking on the correct allosteric site performed well in terms of virtual screening and pose prediction (compared to other methods) but affinity prediction, as expected, was very poor, (3) Molecular docking grid sizes can be very important, serious errors were discovered with default settings that have been adjusted for all future work. Overall, lessons from SAMPL4 suggest many changes to molecular docking tools, not just DOCK 3.7, that could improve the state of the art. Future difficulties and projects will be discussed.

High throughput route selection in multi-rate wireless mesh networks

Institute of Scientific and Technical Information of China (English)

WEI Yi-fei; GUO Xiang-li; SONG Mei; SONG Jun-de

2008-01-01

Most existing Ad-hoc routing protocols use the shortest path algorithm with a hop count metric to select paths. It is appropriate in single-rate wireless networks, but has a tendency to select paths containing long-distance links that have low data rates and reduced reliability in multi-rate networks. This article introduces a high throughput routing algorithm utilizing the multi-rate capability and some mesh characteristics in wireless fidelity (WiFi) mesh networks. It uses the medium access control (MAC) transmission time as the routing metric, which is estimated by the information passed up from the physical layer. When the proposed algorithm is adopted, the Ad-hoc on-demand distance vector (AODV) routing can be improved as high throughput AODV (HT-AODV). Simulation results show that HT-AODV is capable of establishing a route that has high data-rate, short end-to-end delay and great network throughput.

Alginate Immobilization of Metabolic Enzymes (AIME) for High-Throughput Screening Assays (SOT)

Science.gov (United States)

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...

Docking screens: right for the right reasons?

Science.gov (United States)

Kolb, Peter; Irwin, John J

2009-01-01

Whereas docking screens have emerged as the most practical way to use protein structure for ligand discovery, an inconsistent track record raises questions about how well docking actually works. In its favor, a growing number of publications report the successful discovery of new ligands, often supported by experimental affinity data and controls for artifacts. Few reports, however, actually test the underlying structural hypotheses that docking makes. To be successful and not just lucky, prospective docking must not only rank a true ligand among the top scoring compounds, it must also correctly orient the ligand so the score it receives is biophysically sound. If the correct binding pose is not predicted, a skeptic might well infer that the discovery was serendipitous. Surveying over 15 years of the docking literature, we were surprised to discover how rarely sufficient evidence is presented to establish whether docking actually worked for the right reasons. The paucity of experimental tests of theoretically predicted poses undermines confidence in a technique that has otherwise become widely accepted. Of course, solving a crystal structure is not always possible, and even when it is, it can be a lot of work, and is not readily accessible to all groups. Even when a structure can be determined, investigators may prefer to gloss over an erroneous structural prediction to better focus on their discovery. Still, the absence of a direct test of theory by experiment is a loss for method developers seeking to understand and improve docking methods. We hope this review will motivate investigators to solve structures and compare them with their predictions whenever possible, to advance the field.

High-throughput phenotyping and genomic selection: the frontiers of crop breeding converge.

Science.gov (United States)

Cabrera-Bosquet, Llorenç; Crossa, José; von Zitzewitz, Jarislav; Serret, María Dolors; Araus, José Luis

2012-05-01

Genomic selection (GS) and high-throughput phenotyping have recently been captivating the interest of the crop breeding community from both the public and private sectors world-wide. Both approaches promise to revolutionize the prediction of complex traits, including growth, yield and adaptation to stress. Whereas high-throughput phenotyping may help to improve understanding of crop physiology, most powerful techniques for high-throughput field phenotyping are empirical rather than analytical and comparable to genomic selection. Despite the fact that the two methodological approaches represent the extremes of what is understood as the breeding process (phenotype versus genome), they both consider the targeted traits (e.g. grain yield, growth, phenology, plant adaptation to stress) as a black box instead of dissecting them as a set of secondary traits (i.e. physiological) putatively related to the target trait. Both GS and high-throughput phenotyping have in common their empirical approach enabling breeders to use genome profile or phenotype without understanding the underlying biology. This short review discusses the main aspects of both approaches and focuses on the case of genomic selection of maize flowering traits and near-infrared spectroscopy (NIRS) and plant spectral reflectance as high-throughput field phenotyping methods for complex traits such as crop growth and yield. © 2012 Institute of Botany, Chinese Academy of Sciences.

Ultra-high-throughput screening of an in vitro-synthesized horseradish peroxidase displayed on microbeads using cell sorter.

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Bo Zhu

Full Text Available The C1a isoenzyme of horseradish peroxidase (HRP is an industrially important heme-containing enzyme that utilizes hydrogen peroxide to oxidize a wide variety of inorganic and organic compounds for practical applications, including synthesis of fine chemicals, medical diagnostics, and bioremediation. To develop a ultra-high-throughput screening system for HRP, we successfully produced active HRP in an Escherichia coli cell-free protein synthesis system, by adding disulfide bond isomerase DsbC and optimizing the concentrations of hemin and calcium ions and the temperature. The biosynthesized HRP was fused with a single-chain Cro (scCro DNA-binding tag at its N-terminal and C-terminal sites. The addition of the scCro-tag at both ends increased the solubility of the protein. Next, HRP and its fusion proteins were successfully synthesized in a water droplet emulsion by using hexadecane as the oil phase and SunSoft No. 818SK as the surfactant. HRP fusion proteins were displayed on microbeads attached with double-stranded DNA (containing the scCro binding sequence via scCro-DNA interactions. The activities of the immobilized HRP fusion proteins were detected with a tyramide-based fluorogenic assay using flow cytometry. Moreover, a model microbead library containing wild type hrp (WT and inactive mutant (MUT genes was screened using fluorescence-activated cell-sorting, thus efficiently enriching the WT gene from the 1:100 (WT:MUT library. The technique described here could serve as a novel platform for the ultra-high-throughput discovery of more useful HRP mutants and other heme-containing peroxidases.

High-throughput single nucleotide polymorphism genotyping using nanofluidic Dynamic Arrays

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Crenshaw Andrew

2009-01-01

Full Text Available Abstract Background Single nucleotide polymorphisms (SNPs have emerged as the genetic marker of choice for mapping disease loci and candidate gene association studies, because of their high density and relatively even distribution in the human genomes. There is a need for systems allowing medium multiplexing (ten to hundreds of SNPs with high throughput, which can efficiently and cost-effectively generate genotypes for a very large sample set (thousands of individuals. Methods that are flexible, fast, accurate and cost-effective are urgently needed. This is also important for those who work on high throughput genotyping in non-model systems where off-the-shelf assays are not available and a flexible platform is needed. Results We demonstrate the use of a nanofluidic Integrated Fluidic Circuit (IFC - based genotyping system for medium-throughput multiplexing known as the Dynamic Array, by genotyping 994 individual human DNA samples on 47 different SNP assays, using nanoliter volumes of reagents. Call rates of greater than 99.5% and call accuracies of greater than 99.8% were achieved from our study, which demonstrates that this is a formidable genotyping platform. The experimental set up is very simple, with a time-to-result for each sample of about 3 hours. Conclusion Our results demonstrate that the Dynamic Array is an excellent genotyping system for medium-throughput multiplexing (30-300 SNPs, which is simple to use and combines rapid throughput with excellent call rates, high concordance and low cost. The exceptional call rates and call accuracy obtained may be of particular interest to those working on validation and replication of genome- wide- association (GWA studies.

HTTK: R Package for High-Throughput Toxicokinetics

Science.gov (United States)

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...

High-throughput microfluidic mixing and multiparametric cell sorting for bioactive compound screening.

Science.gov (United States)

Young, Susan M; Curry, Mark S; Ransom, John T; Ballesteros, Juan A; Prossnitz, Eric R; Sklar, Larry A; Edwards, Bruce S

2004-03-01

HyperCyt, an automated sample handling system for flow cytometry that uses air bubbles to separate samples sequentially introduced from multiwell plates by an autosampler. In a previously documented HyperCyt configuration, air bubble separated compounds in one sample line and a continuous stream of cells in another are mixed in-line for serial flow cytometric cell response analysis. To expand capabilities for high-throughput bioactive compound screening, the authors investigated using this system configuration in combination with automated cell sorting. Peptide ligands were sampled from a 96-well plate, mixed in-line with fluo-4-loaded, formyl peptide receptor-transfected U937 cells, and screened at a rate of 3 peptide reactions per minute with approximately 10,000 cells analyzed per reaction. Cell Ca(2+) responses were detected to as little as 10(-11) M peptide with no detectable carryover between samples at up to 10(-7) M peptide. After expansion in culture, cells sort-purified from the 10% highest responders exhibited enhanced sensitivity and more sustained responses to peptide. Thus, a highly responsive cell subset was isolated under high-throughput mixing and sorting conditions in which response detection capability spanned a 1000-fold range of peptide concentration. With single-cell readout systems for protein expression libraries, this technology offers the promise of screening millions of discrete compound interactions per day.

Quantitative high throughput analytics to support polysaccharide production process development.

Science.gov (United States)

Noyes, Aaron; Godavarti, Ranga; Titchener-Hooker, Nigel; Coffman, Jonathan; Mukhopadhyay, Tarit

2014-05-19

The rapid development of purification processes for polysaccharide vaccines is constrained by a lack of analytical tools current technologies for the measurement of polysaccharide recovery and process-related impurity clearance are complex, time-consuming, and generally not amenable to high throughput process development (HTPD). HTPD is envisioned to be central to the improvement of existing polysaccharide manufacturing processes through the identification of critical process parameters that potentially impact the quality attributes of the vaccine and to the development of de novo processes for clinical candidates, across the spectrum of downstream processing. The availability of a fast and automated analytics platform will expand the scope, robustness, and evolution of Design of Experiment (DOE) studies. This paper details recent advances in improving the speed, throughput, and success of in-process analytics at the micro-scale. Two methods, based on modifications of existing procedures, are described for the rapid measurement of polysaccharide titre in microplates without the need for heating steps. A simplification of a commercial endotoxin assay is also described that features a single measurement at room temperature. These assays, along with existing assays for protein and nucleic acids are qualified for deployment in the high throughput screening of polysaccharide feedstreams. Assay accuracy, precision, robustness, interference, and ease of use are assessed and described. In combination, these assays are capable of measuring the product concentration and impurity profile of a microplate of 96 samples in less than one day. This body of work relies on the evaluation of a combination of commercially available and clinically relevant polysaccharides to ensure maximum versatility and reactivity of the final assay suite. Together, these advancements reduce overall process time by up to 30-fold and significantly reduce sample volume over current practices. The

Identification of adiponectin receptor agonist utilizing a fluorescence polarization based high throughput assay.

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Yiyi Sun

Full Text Available Adiponectin, the adipose-derived hormone, plays an important role in the suppression of metabolic disorders that can result in type 2 diabetes, obesity, and atherosclerosis. It has been shown that up-regulation of adiponectin or adiponectin receptor has a number of therapeutic benefits. Given that it is hard to convert the full size adiponectin protein into a viable drug, adiponectin receptor agonists could be designed or identified using high-throughput screening. Here, we report on the development of a two-step screening process to identify adiponectin agonists. First step, we developed a high throughput screening assay based on fluorescence polarization to identify adiponectin ligands. The fluorescence polarization assay reported here could be adapted to screening against larger small molecular compound libraries. A natural product library containing 10,000 compounds was screened and 9 hits were selected for validation. These compounds have been taken for the second-step in vitro tests to confirm their agonistic activity. The most active adiponectin receptor 1 agonists are matairesinol, arctiin, (--arctigenin and gramine. The most active adiponectin receptor 2 agonists are parthenolide, taxifoliol, deoxyschizandrin, and syringin. These compounds may be useful drug candidates for hypoadiponectin related diseases.

High-throughput liquid chromatography for drug analysis in biological fluids: investigation of extraction column life.

Science.gov (United States)

Zeng, Wei; Fisher, Alison L; Musson, Donald G; Wang, Amy Qiu

2004-07-05

A novel method was developed and assessed to extend the lifetime of extraction columns of high-throughput liquid chromatography (HTLC) for bioanalysis of human plasma samples. In this method, a 15% acetic acid solution and 90% THF were respectively used as mobile phases to clean up the proteins in human plasma samples and residual lipids from the extraction and analytical columns. The 15% acetic acid solution weakens the interactions between proteins and the stationary phase of the extraction column and increases the protein solubility in the mobile phase. The 90% THF mobile phase prevents the accumulation of lipids and thus reduces the potential damage on the columns. Using this novel method, the extraction column lifetime has been extended to about 2000 direct plasma injections, and this is the first time that high concentration acetic acid and THF are used in HTLC for on-line cleanup and extraction column lifetime extension.

Biallelic loss-of-function variants in DOCK3 cause muscle hypotonia, ataxia, and intellectual disability.

Science.gov (United States)

Helbig, K L; Mroske, C; Moorthy, D; Sajan, S A; Velinov, M

2017-10-01

DOCK3 encodes the dedicator of cytokinesis 3 protein, a member of the DOCK180 family of proteins that are characterized by guanine-nucleotide exchange factor activity. DOCK3 is expressed exclusively in the central nervous system and plays an important role in axonal outgrowth and cytoskeleton reorganization. Dock3 knockout mice exhibit motor deficiencies with abnormal ataxic gait and impaired learning. We report 2 siblings with biallelic loss-of-function variants in DOCK3. Diagnostic whole-exome sequencing (WES) and chromosomal microarray were performed on a proband with severe developmental disability, hypotonia, and ataxic gait. Testing was also performed on the proband's similarly affected brother. A paternally inherited 458 kb deletion in chromosomal region 3p21.2 disrupting the DOCK3 gene was identified in both affected siblings. WES identified a nonsense variant c.382C>G (p.Gln128*) in the DOCK3 gene (NM_004947) on the maternal allele in both siblings. Common features in both affected individuals include severe developmental disability, ataxic gait, and severe hypotonia, which recapitulates the Dock3 knockout mouse phenotype. We show that complete DOCK3 deficiency in humans leads to developmental disability with significant hypotonia and gait ataxia, probably due to abnormal axonal development. © 2017 The Authors. Clinical Genetics published by John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

A high-throughput, multi-channel photon-counting detector with picosecond timing

CERN Document Server

Lapington, J S; Miller, G M; Ashton, T J R; Jarron, P; Despeisse, M; Powolny, F; Howorth, J; Milnes, J

2009-01-01

High-throughput photon counting with high time resolution is a niche application area where vacuum tubes can still outperform solid-state devices. Applications in the life sciences utilizing time-resolved spectroscopies, particularly in the growing field of proteomics, will benefit greatly from performance enhancements in event timing and detector throughput. The HiContent project is a collaboration between the University of Leicester Space Research Centre, the Microelectronics Group at CERN, Photek Ltd., and end-users at the Gray Cancer Institute and the University of Manchester. The goal is to develop a detector system specifically designed for optical proteomics, capable of high content (multi-parametric) analysis at high throughput. The HiContent detector system is being developed to exploit this niche market. It combines multi-channel, high time resolution photon counting in a single miniaturized detector system with integrated electronics. The combination of enabling technologies; small pore microchanne...

Improved performance in CAPRI round 37 using LZerD docking and template-based modeling with combined scoring functions.

Science.gov (United States)

Peterson, Lenna X; Shin, Woong-Hee; Kim, Hyungrae; Kihara, Daisuke

2018-03-01

We report our group's performance for protein-protein complex structure prediction and scoring in Round 37 of the Critical Assessment of PRediction of Interactions (CAPRI), an objective assessment of protein-protein complex modeling. We demonstrated noticeable improvement in both prediction and scoring compared to previous rounds of CAPRI, with our human predictor group near the top of the rankings and our server scorer group at the top. This is the first time in CAPRI that a server has been the top scorer group. To predict protein-protein complex structures, we used both multi-chain template-based modeling (TBM) and our protein-protein docking program, LZerD. LZerD represents protein surfaces using 3D Zernike descriptors (3DZD), which are based on a mathematical series expansion of a 3D function. Because 3DZD are a soft representation of the protein surface, LZerD is tolerant to small conformational changes, making it well suited to docking unbound and TBM structures. The key to our improved performance in CAPRI Round 37 was to combine multi-chain TBM and docking. As opposed to our previous strategy of performing docking for all target complexes, we used TBM when multi-chain templates were available and docking otherwise. We also describe the combination of multiple scoring functions used by our server scorer group, which achieved the top rank for the scorer phase. © 2017 Wiley Periodicals, Inc.