A Game of Hide and Seek: Expectations of Clumpy Resources Influence Hiding and Searching Patterns

PubMed Central

Wilke, Andreas; Minich, Steven; Panis, Megane; Langen, Tom A.; Skufca, Joseph D.; Todd, Peter M.

2015-01-01

Resources are often distributed in clumps or patches in space, unless an agent is trying to protect them from discovery and theft using a dispersed distribution. We uncover human expectations of such spatial resource patterns in collaborative and competitive settings via a sequential multi-person game in which participants hid resources for the next participant to seek. When collaborating, resources were mostly hidden in clumpy distributions, but when competing, resources were hidden in more dispersed (random or hyperdispersed) patterns to increase the searching difficulty for the other player. More dispersed resource distributions came at the cost of higher overall hiding (as well as searching) times, decreased payoffs, and an increased difficulty when the hider had to recall earlier hiding locations at the end of the experiment. Participants’ search strategies were also affected by their underlying expectations, using a win-stay lose-shift strategy appropriate for clumpy resources when searching for collaboratively-hidden items, but moving equally far after finding or not finding an item in competitive settings, as appropriate for dispersed resources. Thus participants showed expectations for clumpy versus dispersed spatial resources that matched the distributions commonly found in collaborative versus competitive foraging settings. PMID:26154661

Pharmacokinetic properties and in silico ADME modeling in drug discovery.

PubMed

Honório, Kathia M; Moda, Tiago L; Andricopulo, Adriano D

2013-03-01

The discovery and development of a new drug are time-consuming, difficult and expensive. This complex process has evolved from classical methods into an integration of modern technologies and innovative strategies addressed to the design of new chemical entities to treat a variety of diseases. The development of new drug candidates is often limited by initial compounds lacking reasonable chemical and biological properties for further lead optimization. Huge libraries of compounds are frequently selected for biological screening using a variety of techniques and standard models to assess potency, affinity and selectivity. In this context, it is very important to study the pharmacokinetic profile of the compounds under investigation. Recent advances have been made in the collection of data and the development of models to assess and predict pharmacokinetic properties (ADME--absorption, distribution, metabolism and excretion) of bioactive compounds in the early stages of drug discovery projects. This paper provides a brief perspective on the evolution of in silico ADME tools, addressing challenges, limitations, and opportunities in medicinal chemistry.

Open discovery: An integrated live Linux platform of Bioinformatics tools.

PubMed

Vetrivel, Umashankar; Pilla, Kalabharath

2008-01-01

Historically, live linux distributions for Bioinformatics have paved way for portability of Bioinformatics workbench in a platform independent manner. Moreover, most of the existing live Linux distributions limit their usage to sequence analysis and basic molecular visualization programs and are devoid of data persistence. Hence, open discovery - a live linux distribution has been developed with the capability to perform complex tasks like molecular modeling, docking and molecular dynamics in a swift manner. Furthermore, it is also equipped with complete sequence analysis environment and is capable of running windows executable programs in Linux environment. Open discovery portrays the advanced customizable configuration of fedora, with data persistency accessible via USB drive or DVD. The Open Discovery is distributed free under Academic Free License (AFL) and can be downloaded from http://www.OpenDiscovery.org.in.

Open discovery: An integrated live Linux platform of Bioinformatics tools

PubMed Central

Vetrivel, Umashankar; Pilla, Kalabharath

2008-01-01

Historically, live linux distributions for Bioinformatics have paved way for portability of Bioinformatics workbench in a platform independent manner. Moreover, most of the existing live Linux distributions limit their usage to sequence analysis and basic molecular visualization programs and are devoid of data persistence. Hence, open discovery ‐ a live linux distribution has been developed with the capability to perform complex tasks like molecular modeling, docking and molecular dynamics in a swift manner. Furthermore, it is also equipped with complete sequence analysis environment and is capable of running windows executable programs in Linux environment. Open discovery portrays the advanced customizable configuration of fedora, with data persistency accessible via USB drive or DVD. Availability The Open Discovery is distributed free under Academic Free License (AFL) and can be downloaded from http://www.OpenDiscovery.org.in PMID:19238235

Discovery of the Dinoponera lucida male (Hymenoptera, Formicidae), a threatened giant ant from the Atlantic rain forest.

PubMed

Escárraga, Mayron E; Lattke, John E; Azevedo, Celso O

2017-11-10

The male of the endangered ant Dinoponera lucida Emery is described, providing morphometric measurements, high-resolution images, and a distribution map of the species. This ant inhabits the Brazilian Atlantic forest, an ecosystem strongly impacted by fragmentation. The males show clear morphological differences from the known males of other species of Dinoponera. We briefly discuss the relevance of the male description for the conservation strategies of this ant.

5-Hydroxymethylcytosine Profiling in Human DNA.

PubMed

Thomson, John P; Nestor, Colm E; Meehan, Richard R

2017-01-01

Since its "re-discovery" in 2009, there has been significant interest in defining the genome-wide distribution of DNA marked by 5-hydroxymethylation at cytosine bases (5hmC). In recent years, technological advances have resulted in a multitude of unique strategies to map 5hmC across the human genome. Here we discuss the wide range of approaches available to map this modification and describe in detail the affinity based methods which result in the enrichment of 5hmC marked DNA for downstream analysis.

Comparison between project-based learning and discovery learning toward students' metacognitive strategies on global warming concept

NASA Astrophysics Data System (ADS)

Tumewu, Widya Anjelia; Wulan, Ana Ratna; Sanjaya, Yayan

2017-05-01

The purpose of this study was to know comparing the effectiveness of learning using Project-based learning (PjBL) and Discovery Learning (DL) toward students metacognitive strategies on global warming concept. A quasi-experimental research design with a The Matching-Only Pretest-Posttest Control Group Design was used in this study. The subjects were students of two classes 7th grade of one of junior high school in Bandung City, West Java of 2015/2016 academic year. The study was conducted on two experimental class, that were project-based learning treatment on the experimental class I and discovery learning treatment was done on the experimental class II. The data was collected through questionnaire to know students metacognitive strategies. The statistical analysis showed that there were statistically significant differences in students metacognitive strategies between project-based learning and discovery learning.

Combining knowledge discovery from databases (KDD) and case-based reasoning (CBR) to support diagnosis of medical images

NASA Astrophysics Data System (ADS)

Stranieri, Andrew; Yearwood, John; Pham, Binh

1999-07-01

The development of data warehouses for the storage and analysis of very large corpora of medical image data represents a significant trend in health care and research. Amongst other benefits, the trend toward warehousing enables the use of techniques for automatically discovering knowledge from large and distributed databases. In this paper, we present an application design for knowledge discovery from databases (KDD) techniques that enhance the performance of the problem solving strategy known as case- based reasoning (CBR) for the diagnosis of radiological images. The problem of diagnosing the abnormality of the cervical spine is used to illustrate the method. The design of a case-based medical image diagnostic support system has three essential characteristics. The first is a case representation that comprises textual descriptions of the image, visual features that are known to be useful for indexing images, and additional visual features to be discovered by data mining many existing images. The second characteristic of the approach presented here involves the development of a case base that comprises an optimal number and distribution of cases. The third characteristic involves the automatic discovery, using KDD techniques, of adaptation knowledge to enhance the performance of the case based reasoner. Together, the three characteristics of our approach can overcome real time efficiency obstacles that otherwise mitigate against the use of CBR to the domain of medical image analysis.

Distributed Drug Discovery: Advancing Chemical Education through Contextualized Combinatorial Solid-Phase Organic Laboratories

ERIC Educational Resources Information Center

Scott, William L.; Denton, Ryan E.; Marrs, Kathleen A.; Durrant, Jacob D.; Samaritoni, J. Geno; Abraham, Milata M.; Brown, Stephen P.; Carnahan, Jon M.; Fischer, Lindsey G.; Glos, Courtney E.; Sempsrott, Peter J.; O'Donnell, Martin J.

2015-01-01

The Distributed Drug Discovery (D3) program trains students in three drug discovery disciplines (synthesis, computational analysis, and biological screening) while addressing the important challenge of discovering drug leads for neglected diseases. This article focuses on implementation of the synthesis component in the second-semester…

Microfluidics Expanding the Frontiers of Microbial Ecology

PubMed Central

Rusconi, Roberto; Garren, Melissa; Stocker, Roman

2014-01-01

The ability afforded by microfluidics to observe the behaviors of microbes in highly controlled and confined microenvironments, across scales from a single cell to mixed communities, has significantly contributed to expand the frontiers of microbial ecology over the last decade. Spatially and temporally varying distributions of organisms and chemical cues that mimic natural microbial habitats can now be established by exploiting physics at the micrometer scale and by incorporating structures with specific geometries and materials. Here we review applications of microfluidics that have resulted in highly insightful discoveries on fundamental aspects of microbial life, ranging from growth and sensing to cell-cell interactions and population dynamics. We anticipate that this flexible, multidisciplinary technology will continue to facilitate discoveries regarding the ecology of microorganisms and help uncover strategies to control phenomena such as biofilm formation and antibiotic resistance. PMID:24773019

Microfluidics expanding the frontiers of microbial ecology.

PubMed

Rusconi, Roberto; Garren, Melissa; Stocker, Roman

2014-01-01

Microfluidics has significantly contributed to the expansion of the frontiers of microbial ecology over the past decade by allowing researchers to observe the behaviors of microbes in highly controlled microenvironments, across scales from a single cell to mixed communities. Spatially and temporally varying distributions of organisms and chemical cues that mimic natural microbial habitats can now be established by exploiting physics at the micrometer scale and by incorporating structures with specific geometries and materials. In this article, we review applications of microfluidics that have resulted in insightful discoveries on fundamental aspects of microbial life, ranging from growth and sensing to cell-cell interactions and population dynamics. We anticipate that this flexible multidisciplinary technology will continue to facilitate discoveries regarding the ecology of microorganisms and help uncover strategies to control microbial processes such as biofilm formation and antibiotic resistance.

Using Simplified Sudoku to Promote and Improve Pattern Discovery Skills among School Children

ERIC Educational Resources Information Center

Tengah, Khairul A.

2011-01-01

As part of promoting and improving pattern discovery skills among school children, a Sudoku puzzle can be used as example of a problem solving task. A simplified version of the puzzle will be used first to explain the aim and reinforce the rules of solving the puzzle. Three strategies--"Strategy of Obvious Missing Number, Strategy of…

Drug discovery strategies to outer membrane targets in Gram-negative pathogens.

PubMed

Brown, Dean G

2016-12-15

This review will cover selected recent examples of drug discovery strategies which target the outer membrane (OM) of Gram-negative bacteria either by disruption of outer membrane function or by inhibition of essential gene products necessary for outer membrane assembly. Significant advances in pathway elucidation, structural biology and molecular inhibitor designs have created new opportunities for drug discovery within this target-class space. Copyright © 2016 Elsevier Ltd. All rights reserved.

Social and natural sciences differ in their research strategies, adapted to work for different knowledge landscapes.

PubMed

Jaffe, Klaus

2014-01-01

Do different fields of knowledge require different research strategies? A numerical model exploring different virtual knowledge landscapes, revealed two diverging optimal search strategies. Trend following is maximized when the popularity of new discoveries determine the number of individuals researching it. This strategy works best when many researchers explore few large areas of knowledge. In contrast, individuals or small groups of researchers are better in discovering small bits of information in dispersed knowledge landscapes. Bibliometric data of scientific publications showed a continuous bipolar distribution of these strategies, ranging from natural sciences, with highly cited publications in journals containing a large number of articles, to the social sciences, with rarely cited publications in many journals containing a small number of articles. The natural sciences seem to adapt their research strategies to landscapes with large concentrated knowledge clusters, whereas social sciences seem to have adapted to search in landscapes with many small isolated knowledge clusters. Similar bipolar distributions were obtained when comparing levels of insularity estimated by indicators of international collaboration and levels of country-self citations: researchers in academic areas with many journals such as social sciences, arts and humanities, were the most isolated, and that was true in different regions of the world. The work shows that quantitative measures estimating differences between academic disciplines improve our understanding of different research strategies, eventually helping interdisciplinary research and may be also help improve science policies worldwide.

Modern approaches to accelerate discovery of new antischistosomal drugs.

PubMed

Neves, Bruno Junior; Muratov, Eugene; Machado, Renato Beilner; Andrade, Carolina Horta; Cravo, Pedro Vitor Lemos

2016-06-01

The almost exclusive use of only praziquantel for the treatment of schistosomiasis has raised concerns about the possible emergence of drug-resistant schistosomes. Consequently, there is an urgent need for new antischistosomal drugs. The identification of leads and the generation of high quality data are crucial steps in the early stages of schistosome drug discovery projects. Herein, the authors focus on the current developments in antischistosomal lead discovery, specifically referring to the use of automated in vitro target-based and whole-organism screens and virtual screening of chemical databases. They highlight the strengths and pitfalls of each of the above-mentioned approaches, and suggest possible roadmaps towards the integration of several strategies, which may contribute for optimizing research outputs and led to more successful and cost-effective drug discovery endeavors. Increasing partnerships and access to funding for drug discovery have strengthened the battle against schistosomiasis in recent years. However, the authors believe this battle also includes innovative strategies to overcome scientific challenges. In this context, significant advances of in vitro screening as well as computer-aided drug discovery have contributed to increase the success rate and reduce the costs of drug discovery campaigns. Although some of these approaches were already used in current antischistosomal lead discovery pipelines, the integration of these strategies in a solid workflow should allow the production of new treatments for schistosomiasis in the near future.

The genetic and molecular basis for sunscreen biosynthesis in cyanobacteria

PubMed Central

Balskus, Emily P.; Walsh, Christopher T.

2011-01-01

UV-A and UV-B radiation are harmful to living systems, causing damage to biological macromolecules. An important strategy for dealing with UV exposure is the biosynthesis of small molecule sunscreens. Among such metabolites, the mycosporine and mycosporine-like amino acids (MAAs) are remarkable for their wide phylogenetic distribution and their unique chemical structures. Here we report the identification of a MAA biosynthetic gene cluster in a cyanobacterium and the discovery of analogous pathways in other sequenced organisms. We have expressed the cluster in a heterologous bacterial host and characterized all four biosynthetic enzymes in vitro. In addition to clarifying the origin of the MAAs, these efforts have revealed two unprecedented enzymatic strategies for imine formation. PMID:20813918

Distribution and licensing of drug discovery tools – NIH perspectives

PubMed Central

Kim, J. P.

2009-01-01

Now, more than ever, drug discovery conducted at industrial or academic facilities requires rapid access to state-of-the-art research tools. Unreasonable restrictions or delays in the distribution or use of such tools can stifle new discoveries, thus limiting the development of future biomedical products. In grants and its own research programs the National Institutes of Health (NIH) is implementing its new policy to facilitate the exchanges of these tools for research discoveries and product development. PMID:12546842

Fostering First-Graders' Reasoning Strategies with the Most Basic Sums

ERIC Educational Resources Information Center

Purpura, David J.; Baroody, Arthur J.; Eiland, Michael D.; Reid, Erin E.

2012-01-01

In a meta-analysis of 164 studies, Alfieri, Brooks, Aldrich, and Tenenbaum (2010) found that assisted discovery learning was more effective than explicit instruction or unassisted discovery learning and that explicit instruction resulted in more favorable outcomes than unassisted discovery learning. In other words, "unassisted discovery does…

Finding novel pharmaceuticals in the systems biology era using multiple effective drug targets, phenotypic screening and knowledge of transporters: where drug discovery went wrong and how to fix it.

PubMed

Kell, Douglas B

2013-12-01

Despite the sequencing of the human genome, the rate of innovative and successful drug discovery in the pharmaceutical industry has continued to decrease. Leaving aside regulatory matters, the fundamental and interlinked intellectual issues proposed to be largely responsible for this are: (a) the move from 'function-first' to 'target-first' methods of screening and drug discovery; (b) the belief that successful drugs should and do interact solely with single, individual targets, despite natural evolution's selection for biochemical networks that are robust to individual parameter changes; (c) an over-reliance on the rule-of-5 to constrain biophysical and chemical properties of drug libraries; (d) the general abandoning of natural products that do not obey the rule-of-5; (e) an incorrect belief that drugs diffuse passively into (and presumably out of) cells across the bilayers portions of membranes, according to their lipophilicity; (f) a widespread failure to recognize the overwhelmingly important role of proteinaceous transporters, as well as their expression profiles, in determining drug distribution in and between different tissues and individual patients; and (g) the general failure to use engineering principles to model biology in parallel with performing 'wet' experiments, such that 'what if?' experiments can be performed in silico to assess the likely success of any strategy. These facts/ideas are illustrated with a reasonably extensive literature review. Success in turning round drug discovery consequently requires: (a) decent systems biology models of human biochemical networks; (b) the use of these (iteratively with experiments) to model how drugs need to interact with multiple targets to have substantive effects on the phenotype; (c) the adoption of polypharmacology and/or cocktails of drugs as a desirable goal in itself; (d) the incorporation of drug transporters into systems biology models, en route to full and multiscale systems biology models that incorporate drug absorption, distribution, metabolism and excretion; (e) a return to 'function-first' or phenotypic screening; and (f) novel methods for inferring modes of action by measuring the properties on system variables at all levels of the 'omes. Such a strategy offers the opportunity of achieving a state where we can hope to predict biological processes and the effect of pharmaceutical agents upon them. Consequently, this should both lower attrition rates and raise the rates of discovery of effective drugs substantially. © 2013 The Author Journal compilation © 2013 FEBS.

Four disruptive strategies for removing drug discovery bottlenecks.

PubMed

Ekins, Sean; Waller, Chris L; Bradley, Mary P; Clark, Alex M; Williams, Antony J

2013-03-01

Drug discovery is shifting focus from industry to outside partners and, in the process, creating new bottlenecks. Technologies like high throughput screening (HTS) have moved to a larger number of academic and institutional laboratories in the USA, with little coordination or consideration of the outputs and creating a translational gap. Although there have been collaborative public-private partnerships in Europe to share pharmaceutical data, the USA has seemingly lagged behind and this may hold it back. Sharing precompetitive data and models may accelerate discovery across the board, while finding the best collaborators, mining social media and mobile approaches to open drug discovery should be evaluated in our efforts to remove drug discovery bottlenecks. We describe four strategies to rectify the current unsustainable situation. Copyright © 2012 Elsevier Ltd. All rights reserved.

Open Science Meets Stem Cells: A New Drug Discovery Approach for Neurodegenerative Disorders

PubMed Central

Han, Chanshuai; Chaineau, Mathilde; Chen, Carol X.-Q.; Beitel, Lenore K.; Durcan, Thomas M.

2018-01-01

Neurodegenerative diseases are a challenge for drug discovery, as the biological mechanisms are complex and poorly understood, with a paucity of models that faithfully recapitulate these disorders. Recent advances in stem cell technology have provided a paradigm shift, providing researchers with tools to generate human induced pluripotent stem cells (iPSCs) from patient cells. With the potential to generate any human cell type, we can now generate human neurons and develop “first-of-their-kind” disease-relevant assays for small molecule screening. Now that the tools are in place, it is imperative that we accelerate discoveries from the bench to the clinic. Using traditional closed-door research systems raises barriers to discovery, by restricting access to cells, data and other research findings. Thus, a new strategy is required, and the Montreal Neurological Institute (MNI) and its partners are piloting an “Open Science” model. One signature initiative will be that the MNI biorepository will curate and disseminate patient samples in a more accessible manner through open transfer agreements. This feeds into the MNI open drug discovery platform, focused on developing industry-standard assays with iPSC-derived neurons. All cell lines, reagents and assay findings developed in this open fashion will be made available to academia and industry. By removing the obstacles many universities and companies face in distributing patient samples and assay results, our goal is to accelerate translational medical research and the development of new therapies for devastating neurodegenerative disorders. PMID:29467610

Open Science Meets Stem Cells: A New Drug Discovery Approach for Neurodegenerative Disorders.

PubMed

Han, Chanshuai; Chaineau, Mathilde; Chen, Carol X-Q; Beitel, Lenore K; Durcan, Thomas M

2018-01-01

Neurodegenerative diseases are a challenge for drug discovery, as the biological mechanisms are complex and poorly understood, with a paucity of models that faithfully recapitulate these disorders. Recent advances in stem cell technology have provided a paradigm shift, providing researchers with tools to generate human induced pluripotent stem cells (iPSCs) from patient cells. With the potential to generate any human cell type, we can now generate human neurons and develop "first-of-their-kind" disease-relevant assays for small molecule screening. Now that the tools are in place, it is imperative that we accelerate discoveries from the bench to the clinic. Using traditional closed-door research systems raises barriers to discovery, by restricting access to cells, data and other research findings. Thus, a new strategy is required, and the Montreal Neurological Institute (MNI) and its partners are piloting an "Open Science" model. One signature initiative will be that the MNI biorepository will curate and disseminate patient samples in a more accessible manner through open transfer agreements. This feeds into the MNI open drug discovery platform, focused on developing industry-standard assays with iPSC-derived neurons. All cell lines, reagents and assay findings developed in this open fashion will be made available to academia and industry. By removing the obstacles many universities and companies face in distributing patient samples and assay results, our goal is to accelerate translational medical research and the development of new therapies for devastating neurodegenerative disorders.

Paraphrasing and Prediction with Self-Explanation as Generative Strategies for Learning Science Principles in a Simulation

ERIC Educational Resources Information Center

Morrison, Jennifer R.; Bol, Linda; Ross, Steven M.; Watson, Ginger S.

2015-01-01

This study examined the incorporation of generative strategies for the guided discovery of physics principles in a simulation. Participants who either paraphrased or predicted and self-explained guided discovery assignments exhibited improved performance on an achievement test as compared to a control group. Calibration accuracy (the…

Triple Scheme of Learning Support Design for Scientific Discovery Learning Based on Computer Simulation: Experimental Research

ERIC Educational Resources Information Center

Zhang, Jianwei; Chen, Qi; Sun, Yanquing; Reid, David J.

2004-01-01

Learning support studies involving simulation-based scientific discovery learning have tended to adopt an ad hoc strategies-oriented approach in which the support strategies are typically pre-specified according to learners' difficulties in particular activities. This article proposes a more integrated approach, a triple scheme for learning…

Strategies to support drug discovery through integration of systems and data.

PubMed

Waller, Chris L; Shah, Ajay; Nolte, Matthias

2007-08-01

Much progress has been made over the past several years to provide technologies for the integration of drug discovery software applications and the underlying data bits. Integration at the application layer has focused primarily on developing and delivering applications that support specific workflows within the drug discovery arena. A fine balance between creating behemoth applications and providing business value must be maintained. Heterogeneous data sources have typically been integrated at the data level in an effort to provide a more holistic view of the data packages supporting key decision points. This review will highlight past attempts, current status, and potential future directions for systems and data integration strategies in support of drug discovery efforts.

The Goal Specificity Effect on Strategy Use and Instructional Efficiency during Computer-Based Scientific Discovery Learning

ERIC Educational Resources Information Center

Kunsting, Josef; Wirth, Joachim; Paas, Fred

2011-01-01

Using a computer-based scientific discovery learning environment on buoyancy in fluids we investigated the "effects of goal specificity" (nonspecific goals vs. specific goals) for two goal types (problem solving goals vs. learning goals) on "strategy use" and "instructional efficiency". Our empirical findings close an important research gap,…

Choosing experiments to accelerate collective discovery

DOE PAGES

Rzhetsky, Andrey; Foster, Jacob G.; Foster, Ian T.; ...

2015-11-24

Scientists perform a tiny subset of all possible experiments. What characterizes the experiments they choose? What are the consequences of those choices for the pace of scientific discovery? We model scientific knowledge as a network and science as a sequence of experiments designed to gradually uncover it. By analyzing millions of biomedical articles published over 30 y, we find that biomedical scientists pursue conservative research strategies exploring the local neighborhood of central, important molecules. Although such strategies probably serve scientific careers, we show that they slow scientific advance, especially in mature fields, where more risk and less redundant experimentation wouldmore » accelerate discovery of the network. Lastly, we also consider institutional arrangements that could help science pursue these more efficient strategies.« less

Early Stigmatization, PTSD, and Perceived Negative Reactions of Others Predict Subsequent Strategies for Processing Child Sexual Abuse

PubMed Central

Simon, Valerie A.; Feiring, Candice; Cleland, Charles M.

2017-01-01

Objective Trauma processing is central to healthy recovery, but few studies examine how youth process experiences of child sexual abuse (CSA). The current study builds on our prior work identifying individual differences in CSA processing strategies (i.e., Constructive, Absorbed, Avoidant) to examine whether abuse stigmatization, PTSD symptoms, and negative reactions from others experienced during the year after abuse discovery were associated with subsequent CSA processing strategies. Method Participants included 160 ethnically diverse youth (8−15 years, 73% female) with confirmed cases of CSA. Predictors were measured at abuse discovery (T1) and 1 year later (T2). Individual differences in CSA processing strategies were assessed 6 years after discovery (T3) from participants’ abuse narratives. Results The persistence of abuse stigmatization from T1 to T2 significantly increased the odds of using either an Avoidant or Absorbed (vs. Constructive) strategy at T3. Higher levels of PTSD symptoms at T1 as well as their persistence from T1 to T2 each significantly increased the odds of having an Absorbed versus Constructive strategy. The persistence of perceived negative reactions from others from T1 to T2 increased the odds of an Absorbed versus Avoidant strategy. Effect sizes ranged from medium to large (M d = 0.636). Conclusions Results further validate prior work identifying distinct CSA processing strategies and suggest the persistence of abuse-specific disruptions over the year after abuse discovery may be associated with subsequent problems processing CSA experiences. PMID:28936363

The Biogeography of Putative Microbial Antibiotic Production

PubMed Central

Bryant, Jessica A.; Charkoudian, Louise K.; Docherty, Kathryn M.; Jones, Evan; Kembel, Steven W.; Green, Jessica L.; Bohannan, Brendan J. M.

2015-01-01

Understanding patterns in the distribution and abundance of functional traits across a landscape is of fundamental importance to ecology. Mapping these distributions is particularly challenging for species-rich groups with sparse trait measurement coverage, such as flowering plants, insects, and microorganisms. Here, we use likelihood-based character reconstruction to infer and analyze the spatial distribution of unmeasured traits. We apply this framework to a microbial dataset comprised of 11,732 ketosynthase alpha gene sequences extracted from 144 soil samples from three continents to document the spatial distribution of putative microbial polyketide antibiotic production. Antibiotic production is a key competitive strategy for soil microbial survival and performance. Additionally, novel antibiotic discovery is highly relevant to human health, making natural antibiotic production by soil microorganisms a major target for bioprospecting. Our comparison of trait-based biogeographical patterns to patterns based on taxonomy and phylogeny is relevant to our basic understanding of microbial biogeography as well as the pressing need for new antibiotics. PMID:26102275

Identifying and quantifying heterogeneity in high content analysis: application of heterogeneity indices to drug discovery.

PubMed

Gough, Albert H; Chen, Ning; Shun, Tong Ying; Lezon, Timothy R; Boltz, Robert C; Reese, Celeste E; Wagner, Jacob; Vernetti, Lawrence A; Grandis, Jennifer R; Lee, Adrian V; Stern, Andrew M; Schurdak, Mark E; Taylor, D Lansing

2014-01-01

One of the greatest challenges in biomedical research, drug discovery and diagnostics is understanding how seemingly identical cells can respond differently to perturbagens including drugs for disease treatment. Although heterogeneity has become an accepted characteristic of a population of cells, in drug discovery it is not routinely evaluated or reported. The standard practice for cell-based, high content assays has been to assume a normal distribution and to report a well-to-well average value with a standard deviation. To address this important issue we sought to define a method that could be readily implemented to identify, quantify and characterize heterogeneity in cellular and small organism assays to guide decisions during drug discovery and experimental cell/tissue profiling. Our study revealed that heterogeneity can be effectively identified and quantified with three indices that indicate diversity, non-normality and percent outliers. The indices were evaluated using the induction and inhibition of STAT3 activation in five cell lines where the systems response including sample preparation and instrument performance were well characterized and controlled. These heterogeneity indices provide a standardized method that can easily be integrated into small and large scale screening or profiling projects to guide interpretation of the biology, as well as the development of therapeutics and diagnostics. Understanding the heterogeneity in the response to perturbagens will become a critical factor in designing strategies for the development of therapeutics including targeted polypharmacology.

Search strategy has influenced the discovery rate of human viruses.

PubMed

Rosenberg, Ronald; Johansson, Michael A; Powers, Ann M; Miller, Barry R

2013-08-20

A widely held concern is that the pace of infectious disease emergence has been increasing. We have analyzed the rate of discovery of pathogenic viruses, the preeminent source of newly discovered causes of human disease, from 1897 through 2010. The rate was highest during 1950-1969, after which it moderated. This general picture masks two distinct trends: for arthropod-borne viruses, which comprised 39% of pathogenic viruses, the discovery rate peaked at three per year during 1960-1969, but subsequently fell nearly to zero by 1980; however, the rate of discovery of nonarboviruses remained stable at about two per year from 1950 through 2010. The period of highest arbovirus discovery coincided with a comprehensive program supported by The Rockefeller Foundation of isolating viruses from humans, animals, and arthropod vectors at field stations in Latin America, Africa, and India. The productivity of this strategy illustrates the importance of location, approach, long-term commitment, and sponsorship in the discovery of emerging pathogens.

Learning to Love Your Discovery Tool: Strategies for Integrating a Discovery Tool in Face-to-Face, Synchronous, and Asynchronous Instruction

ERIC Educational Resources Information Center

Fawley, Nancy; Krysak, Nikki

2014-01-01

Some librarians embrace discovery tools while others refuse to use them. This lack of consensus can have consequences for student learning when there is inconsistent use, especially in large-scale instruction programs. The authors surveyed academic librarians whose institutions have a discovery tool and who teach information literacy classes in…

Commentary: Leveraging discovery science to advance child and adolescent psychiatric research--a commentary on Zhao and Castellanos 2016.

PubMed

Mennes, Maarten

2016-03-01

'Big Data' and 'Population Imaging' are becoming integral parts of inspiring research aimed at delineating the biological underpinnings of psychiatric disorders. The scientific strategies currently associated with big data and population imaging are typically embedded in so-called discovery science, thereby pointing to the hypothesis-generating rather than hypothesis-testing nature of discovery science. In this issue, Yihong Zhao and F. Xavier Castellanos provide a compelling overview of strategies for discovery science aimed at progressing our understanding of neuropsychiatric disorders. In particular, they focus on efforts in genetic and neuroimaging research, which, together with extended behavioural testing, form the main pillars of psychopathology research. © 2016 Association for Child and Adolescent Mental Health.

Discovery Learning Strategies in English

ERIC Educational Resources Information Center

Singaravelu, G.

2012-01-01

The study substantiates that the effectiveness of Discovery Learning method in learning English Grammar for the learners at standard V. Discovery Learning is particularly beneficial for any student learning a second language. It promotes peer interaction and development of the language and the learning of concepts with content. Reichert and…

FDR doesn't Tell the Whole Story: Joint Influence of Effect Size and Covariance Structure on the Distribution of the False Discovery Proportions

NASA Technical Reports Server (NTRS)

Feiveson, Alan H.; Ploutz-Snyder, Robert; Fiedler, James

2011-01-01

As part of a 2009 Annals of Statistics paper, Gavrilov, Benjamini, and Sarkar report results of simulations that estimated the false discovery rate (FDR) for equally correlated test statistics using a well-known multiple-test procedure. In our study we estimate the distribution of the false discovery proportion (FDP) for the same procedure under a variety of correlation structures among multiple dependent variables in a MANOVA context. Specifically, we study the mean (the FDR), skewness, kurtosis, and percentiles of the FDP distribution in the case of multiple comparisons that give rise to correlated non-central t-statistics when results at several time periods are being compared to baseline. Even if the FDR achieves its nominal value, other aspects of the distribution of the FDP depend on the interaction between signed effect sizes and correlations among variables, proportion of true nulls, and number of dependent variables. We show examples where the mean FDP (the FDR) is 10% as designed, yet there is a surprising probability of having 30% or more false discoveries. Thus, in a real experiment, the proportion of false discoveries could be quite different from the stipulated FDR.

Architectural Strategies for Enabling Data-Driven Science at Scale

NASA Astrophysics Data System (ADS)

Crichton, D. J.; Law, E. S.; Doyle, R. J.; Little, M. M.

2017-12-01

The analysis of large data collections from NASA or other agencies is often executed through traditional computational and data analysis approaches, which require users to bring data to their desktops and perform local data analysis. Alternatively, data are hauled to large computational environments that provide centralized data analysis via traditional High Performance Computing (HPC). Scientific data archives, however, are not only growing massive, but are also becoming highly distributed. Neither traditional approach provides a good solution for optimizing analysis into the future. Assumptions across the NASA mission and science data lifecycle, which historically assume that all data can be collected, transmitted, processed, and archived, will not scale as more capable instruments stress legacy-based systems. New paradigms are needed to increase the productivity and effectiveness of scientific data analysis. This paradigm must recognize that architectural and analytical choices are interrelated, and must be carefully coordinated in any system that aims to allow efficient, interactive scientific exploration and discovery to exploit massive data collections, from point of collection (e.g., onboard) to analysis and decision support. The most effective approach to analyzing a distributed set of massive data may involve some exploration and iteration, putting a premium on the flexibility afforded by the architectural framework. The framework should enable scientist users to assemble workflows efficiently, manage the uncertainties related to data analysis and inference, and optimize deep-dive analytics to enhance scalability. In many cases, this "data ecosystem" needs to be able to integrate multiple observing assets, ground environments, archives, and analytics, evolving from stewardship of measurements of data to using computational methodologies to better derive insight from the data that may be fused with other sets of data. This presentation will discuss architectural strategies, including a 2015-2016 NASA AIST Study on Big Data, for evolving scientific research towards massively distributed data-driven discovery. It will include example use cases across earth science, planetary science, and other disciplines.

The discovery of medicines for rare diseases

PubMed Central

Swinney, David C; Xia, Shuangluo

2015-01-01

There is a pressing need for new medicines (new molecular entities; NMEs) for rare diseases as few of the 6800 rare diseases (according to the NIH) have approved treatments. Drug discovery strategies for the 102 orphan NMEs approved by the US FDA between 1999 and 2012 were analyzed to learn from past success: 46 NMEs were first in class; 51 were followers; and five were imaging agents. First-in-class medicines were discovered with phenotypic assays (15), target-based approaches (12) and biologic strategies (18). Identification of genetic causes in areas with more basic and translational research such as cancer and in-born errors in metabolism contributed to success regardless of discovery strategy. In conclusion, greater knowledge increases the chance of success and empirical solutions can be effective when knowledge is incomplete. PMID:25068983

Experimental Null Method to Guide the Development of Technical Procedures and to Control False-Positive Discovery in Quantitative Proteomics.

PubMed

Shen, Xiaomeng; Hu, Qiang; Li, Jun; Wang, Jianmin; Qu, Jun

2015-10-02

Comprehensive and accurate evaluation of data quality and false-positive biomarker discovery is critical to direct the method development/optimization for quantitative proteomics, which nonetheless remains challenging largely due to the high complexity and unique features of proteomic data. Here we describe an experimental null (EN) method to address this need. Because the method experimentally measures the null distribution (either technical or biological replicates) using the same proteomic samples, the same procedures and the same batch as the case-vs-contol experiment, it correctly reflects the collective effects of technical variability (e.g., variation/bias in sample preparation, LC-MS analysis, and data processing) and project-specific features (e.g., characteristics of the proteome and biological variation) on the performances of quantitative analysis. To show a proof of concept, we employed the EN method to assess the quantitative accuracy and precision and the ability to quantify subtle ratio changes between groups using different experimental and data-processing approaches and in various cellular and tissue proteomes. It was found that choices of quantitative features, sample size, experimental design, data-processing strategies, and quality of chromatographic separation can profoundly affect quantitative precision and accuracy of label-free quantification. The EN method was also demonstrated as a practical tool to determine the optimal experimental parameters and rational ratio cutoff for reliable protein quantification in specific proteomic experiments, for example, to identify the necessary number of technical/biological replicates per group that affords sufficient power for discovery. Furthermore, we assessed the ability of EN method to estimate levels of false-positives in the discovery of altered proteins, using two concocted sample sets mimicking proteomic profiling using technical and biological replicates, respectively, where the true-positives/negatives are known and span a wide concentration range. It was observed that the EN method correctly reflects the null distribution in a proteomic system and accurately measures false altered proteins discovery rate (FADR). In summary, the EN method provides a straightforward, practical, and accurate alternative to statistics-based approaches for the development and evaluation of proteomic experiments and can be universally adapted to various types of quantitative techniques.

Petroleum-resource appraisal and discovery rate forecasting in partially explored regions

USGS Publications Warehouse

Drew, Lawrence J.; Schuenemeyer, J.H.; Root, David H.; Attanasi, E.D.

1980-01-01

PART A: A model of the discovery process can be used to predict the size distribution of future petroleum discoveries in partially explored basins. The parameters of the model are estimated directly from the historical drilling record, rather than being determined by assumptions or analogies. The model is based on the concept of the area of influence of a drill hole, which states that the area of a basin exhausted by a drill hole varies with the size and shape of targets in the basin and with the density of previously drilled wells. It also uses the concept of discovery efficiency, which measures the rate of discovery within several classes of deposit size. The model was tested using 25 years of historical exploration data (1949-74) from the Denver basin. From the trend in the discovery rate (the number of discoveries per unit area exhausted), the discovery efficiencies in each class of deposit size were estimated. Using pre-1956 discovery and drilling data, the model accurately predicted the size distribution of discoveries for the 1956-74 period. PART B: A stochastic model of the discovery process has been developed to predict, using past drilling and discovery data, the distribution of future petroleum deposits in partially explored basins, and the basic mathematical properties of the model have been established. The model has two exogenous parameters, the efficiency of exploration and the effective basin size. The first parameter is the ratio of the probability that an actual exploratory well will make a discovery to the probability that a randomly sited well will make a discovery. The second parameter, the effective basin size, is the area of that part of the basin in which drillers are willing to site wells. Methods for estimating these parameters from locations of past wells and from the sizes and locations of past discoveries were derived, and the properties of estimators of the parameters were studied by simulation. PART C: This study examines the temporal properties and determinants of petroleum exploration for firms operating in the Denver basin. Expectations associated with the favorability of a specific area are modeled by using distributed lag proxy variables (of previous discoveries) and predictions from a discovery process model. In the second part of the study, a discovery process model is linked with a behavioral well-drilling model in order to predict the supply of new reserves. Results of the study indicate that the positive effects of new discoveries on drilling increase for several periods and then diminish to zero within 2? years after the deposit discovery date. Tests of alternative specifications of the argument of the distributed lag function using alternative minimum size classes of deposits produced little change in the model's explanatory power. This result suggests that, once an exploration play is underway, favorable operator expectations are sustained by the quantity of oil found per time period rather than by the discovery of specific size deposits. When predictions of the value of undiscovered deposits (generated from a discovery process model) were substituted for the expectations variable in models used to explain exploration effort, operator behavior was found to be consistent with these predictions. This result suggests that operators, on the average, were efficiently using information contained in the discovery history of the basin in carrying out their exploration plans. Comparison of the two approaches to modeling unobservable operator expectations indicates that the two models produced very similar results. The integration of the behavioral well-drilling model and discovery process model to predict the additions to reserves per unit time was successful only when the quarterly predictions were aggregated to annual values. The accuracy of the aggregated predictions was also found to be reasonably robust to errors in predictions from the behavioral well-drilling equation.

Advancing cancer drug discovery towards more agile development of targeted combination therapies.

PubMed

Carragher, Neil O; Unciti-Broceta, Asier; Cameron, David A

2012-01-01

Current drug-discovery strategies are typically 'target-centric' and are based upon high-throughput screening of large chemical libraries against nominated targets and a selection of lead compounds with optimized 'on-target' potency and selectivity profiles. However, high attrition of targeted agents in clinical development suggest that combinations of targeted agents will be most effective in treating solid tumors if the biological networks that permit cancer cells to subvert monotherapies are identified and retargeted. Conventional drug-discovery and development strategies are suboptimal for the rational design and development of novel drug combinations. In this article, we highlight a series of emerging technologies supporting a less reductionist, more agile, drug-discovery and development approach for the rational design, validation, prioritization and clinical development of novel drug combinations.

Discovery of a phosphor for light emitting diode applications and its structural determination, Ba(Si,Al)5(O,N)8:Eu2+.

PubMed

Park, Woon Bae; Singh, Satendra Pal; Sohn, Kee-Sun

2014-02-12

Most of the novel phosphors that appear in the literature are either a variant of well-known materials or a hybrid material consisting of well-known materials. This situation has actually led to intellectual property (IP) complications in industry and several lawsuits have been the result. Therefore, the definition of a novel phosphor for use in light-emitting diodes should be clarified. A recent trend in phosphor-related IP applications has been to focus on the novel crystallographic structure, so that a slight composition variance and/or the hybrid of a well-known material would not qualify from either a scientific or an industrial point of view. In our previous studies, we employed a systematic materials discovery strategy combining heuristics optimization and a high-throughput process to secure the discovery of genuinely novel and brilliant phosphors that would be immediately ready for use in light emitting diodes. Despite such an achievement, this strategy requires further refinement to prove its versatility under any circumstance. To accomplish such demands, we improved our discovery strategy by incorporating an elitism-involved nondominated sorting genetic algorithm (NSGA-II) that would guarantee the discovery of truly novel phosphors in the present investigation. Using the improved discovery strategy, we discovered an Eu(2+)-doped AB5X8 (A = Sr or Ba, B = Si and Al, X = O and N) phosphor in an orthorhombic structure (A21am) with lattice parameters a = 9.48461(3) Å, b = 13.47194(6) Å, c = 5.77323(2) Å, α = β = γ = 90°, which cannot be found in any of the existing inorganic compound databases.

[MODY type diabetes: overview and recent findings].

PubMed

Ben Khelifa, Souhaïra; Barboura, Ilhem; Dandana, Azza; Ferchichi, Selima; Miled, Abdelhedi

2011-01-01

We present an update of knowledge on diabetes MODY (maturity onset diabetes of the young), including the recent molecular discoveries, and new diagnostic strategies. Considerable progress has been made in understanding the different molecular abnormalities that cause MODY and the phenotypic consequences resulting therefrom. MODY diabetes is very heterogeneous and is the most common form of monogenic diabetes. Its distribution is worldwide. MODY is an autosomal dominant diabetes mellitus, nonketotic and occurs at an early age (usually before 25 years). To date, at least seven genes are associated with MODY, with frequencies that differ from one population to another. Both 2 and 3 subtypes predominate, while other subtypes (1, 4, 5, 6 and 7) concern only a few families. Since its discovery in the sixties, studies have succeeded to fully clarify the epidemiological, molecular and clinical diagnosis of each subtype, to provide better care for patients. However, the subject of MODY has not yet revealed all its secrets. Indeed, it remains to identify other genes that are associated with MODY X.

Fragment-based approaches to anti-HIV drug discovery: state of the art and future opportunities.

PubMed

Huang, Boshi; Kang, Dongwei; Zhan, Peng; Liu, Xinyong

2015-12-01

The search for additional drugs to treat HIV infection is a continuing effort due to the emergence and spread of HIV strains resistant to nearly all current drugs. The recent literature reveals that fragment-based drug design/discovery (FBDD) has become an effective alternative to conventional high-throughput screening strategies for drug discovery. In this critical review, the authors describe the state of the art in FBDD strategies for the discovery of anti-HIV drug-like compounds. The article focuses on fragment screening techniques, direct fragment-based design and early hit-to-lead progress. Rapid progress in biophysical detection and in silico techniques has greatly aided the application of FBDD to discover candidate agents directed at a variety of anti-HIV targets. Growing evidence suggests that structural insights on key proteins in the HIV life cycle can be applied in the early phase of drug discovery campaigns, providing valuable information on the binding modes and efficiently prompting fragment hit-to-lead progression. The combination of structural insights with improved methodologies for FBDD, including the privileged fragment-based reconstruction approach, fragment hybridization based on crystallographic overlays, fragment growth exploiting dynamic combinatorial chemistry, and high-speed fragment assembly via diversity-oriented synthesis followed by in situ screening, offers the possibility of more efficient and rapid discovery of novel drugs for HIV-1 prevention or treatment. Though the use of FBDD in anti-HIV drug discovery is still in its infancy, it is anticipated that anti-HIV agents developed via fragment-based strategies will be introduced into the clinic in the future.

Applications of SHAPES screening in drug discovery.

PubMed

Lepre, Christopher A; Peng, Jeffrey; Fejzo, Jasna; Abdul-Manan, Norzehan; Pocas, Jennifer; Jacobs, Marc; Xie, Xiaoling; Moore, Jonathan M

2002-12-01

The SHAPES strategy combines nuclear magnetic resonance (NMR) screening of a library of small drug-like molecules with a variety of complementary methods, such as virtual screening, high throughput enzymatic assays, combinatorial chemistry, X-ray crystallography, and molecular modeling, in a directed search for new medicinal chemistry leads. In the past few years, the SHAPES strategy has found widespread utility in pharmaceutical research. To illustrate a variety of different implementations of the method, we will focus in this review on recent applications of the SHAPES strategy in several drug discovery programs at Vertex Pharmaceuticals.

Mitigating risk in academic preclinical drug discovery.

PubMed

Dahlin, Jayme L; Inglese, James; Walters, Michael A

2015-04-01

The number of academic drug discovery centres has grown considerably in recent years, providing new opportunities to couple the curiosity-driven research culture in academia with rigorous preclinical drug discovery practices used in industry. To fully realize the potential of these opportunities, it is important that academic researchers understand the risks inherent in preclinical drug discovery, and that translational research programmes are effectively organized and supported at an institutional level. In this article, we discuss strategies to mitigate risks in several key aspects of preclinical drug discovery at academic drug discovery centres, including organization, target selection, assay design, medicinal chemistry and preclinical pharmacology.

A Perspective on Implementing a Quantitative Systems Pharmacology Platform for Drug Discovery and the Advancement of Personalized Medicine

PubMed Central

Stern, Andrew M.; Schurdak, Mark E.; Bahar, Ivet; Berg, Jeremy M.; Taylor, D. Lansing

2016-01-01

Drug candidates exhibiting well-defined pharmacokinetic and pharmacodynamic profiles that are otherwise safe often fail to demonstrate proof-of-concept in phase II and III trials. Innovation in drug discovery and development has been identified as a critical need for improving the efficiency of drug discovery, especially through collaborations between academia, government agencies, and industry. To address the innovation challenge, we describe a comprehensive, unbiased, integrated, and iterative quantitative systems pharmacology (QSP)–driven drug discovery and development strategy and platform that we have implemented at the University of Pittsburgh Drug Discovery Institute. Intrinsic to QSP is its integrated use of multiscale experimental and computational methods to identify mechanisms of disease progression and to test predicted therapeutic strategies likely to achieve clinical validation for appropriate subpopulations of patients. The QSP platform can address biological heterogeneity and anticipate the evolution of resistance mechanisms, which are major challenges for drug development. The implementation of this platform is dedicated to gaining an understanding of mechanism(s) of disease progression to enable the identification of novel therapeutic strategies as well as repurposing drugs. The QSP platform will help promote the paradigm shift from reactive population-based medicine to proactive personalized medicine by focusing on the patient as the starting and the end point. PMID:26962875

Targeting α-synuclein oligomers by protein-fragment complementation for drug discovery in synucleinopathies.

PubMed

Moussaud, Simon; Malany, Siobhan; Mehta, Alka; Vasile, Stefan; Smith, Layton H; McLean, Pamela J

2015-05-01

Reducing the burden of α-synuclein oligomeric species represents a promising approach for disease-modifying therapies against synucleinopathies such as Parkinson's disease and dementia with Lewy bodies. However, the lack of efficient drug discovery strategies that specifically target α-synuclein oligomers has been a limitation to drug discovery programs. Here we describe an innovative strategy that harnesses the power of bimolecular protein-fragment complementation to monitor synuclein-synuclein interactions. We have developed two robust models to monitor α-synuclein oligomerization by generating novel stable cell lines expressing α-synuclein fusion proteins for either fluorescent or bioluminescent protein-fragment complementation under the tetracycline-controlled transcriptional activation system. A pilot screen was performed resulting in the identification of two potential hits, a p38 MAPK inhibitor and a casein kinase 2 inhibitor, thereby demonstrating the suitability of our protein-fragment complementation assay for the measurement of α-synuclein oligomerization in living cells at high throughput. The application of the strategy described herein to monitor α-synuclein oligomer formation in living cells with high throughput will facilitate drug discovery efforts for disease-modifying therapies against synucleinopathies and other proteinopathies.

Therapeutic Approaches to Genetic Ion Channelopathies and Perspectives in Drug Discovery

PubMed Central

Imbrici, Paola; Liantonio, Antonella; Camerino, Giulia M.; De Bellis, Michela; Camerino, Claudia; Mele, Antonietta; Giustino, Arcangela; Pierno, Sabata; De Luca, Annamaria; Tricarico, Domenico; Desaphy, Jean-Francois; Conte, Diana

2016-01-01

In the human genome more than 400 genes encode ion channels, which are transmembrane proteins mediating ion fluxes across membranes. Being expressed in all cell types, they are involved in almost all physiological processes, including sense perception, neurotransmission, muscle contraction, secretion, immune response, cell proliferation, and differentiation. Due to the widespread tissue distribution of ion channels and their physiological functions, mutations in genes encoding ion channel subunits, or their interacting proteins, are responsible for inherited ion channelopathies. These diseases can range from common to very rare disorders and their severity can be mild, disabling, or life-threatening. In spite of this, ion channels are the primary target of only about 5% of the marketed drugs suggesting their potential in drug discovery. The current review summarizes the therapeutic management of the principal ion channelopathies of central and peripheral nervous system, heart, kidney, bone, skeletal muscle and pancreas, resulting from mutations in calcium, sodium, potassium, and chloride ion channels. For most channelopathies the therapy is mainly empirical and symptomatic, often limited by lack of efficacy and tolerability for a significant number of patients. Other channelopathies can exploit ion channel targeted drugs, such as marketed sodium channel blockers. Developing new and more specific therapeutic approaches is therefore required. To this aim, a major advancement in the pharmacotherapy of channelopathies has been the discovery that ion channel mutations lead to change in biophysics that can in turn specifically modify the sensitivity to drugs: this opens the way to a pharmacogenetics strategy, allowing the development of a personalized therapy with increased efficacy and reduced side effects. In addition, the identification of disease modifiers in ion channelopathies appears an alternative strategy to discover novel druggable targets. PMID:27242528

Therapeutic Approaches to Genetic Ion Channelopathies and Perspectives in Drug Discovery.

PubMed

Imbrici, Paola; Liantonio, Antonella; Camerino, Giulia M; De Bellis, Michela; Camerino, Claudia; Mele, Antonietta; Giustino, Arcangela; Pierno, Sabata; De Luca, Annamaria; Tricarico, Domenico; Desaphy, Jean-Francois; Conte, Diana

2016-01-01

In the human genome more than 400 genes encode ion channels, which are transmembrane proteins mediating ion fluxes across membranes. Being expressed in all cell types, they are involved in almost all physiological processes, including sense perception, neurotransmission, muscle contraction, secretion, immune response, cell proliferation, and differentiation. Due to the widespread tissue distribution of ion channels and their physiological functions, mutations in genes encoding ion channel subunits, or their interacting proteins, are responsible for inherited ion channelopathies. These diseases can range from common to very rare disorders and their severity can be mild, disabling, or life-threatening. In spite of this, ion channels are the primary target of only about 5% of the marketed drugs suggesting their potential in drug discovery. The current review summarizes the therapeutic management of the principal ion channelopathies of central and peripheral nervous system, heart, kidney, bone, skeletal muscle and pancreas, resulting from mutations in calcium, sodium, potassium, and chloride ion channels. For most channelopathies the therapy is mainly empirical and symptomatic, often limited by lack of efficacy and tolerability for a significant number of patients. Other channelopathies can exploit ion channel targeted drugs, such as marketed sodium channel blockers. Developing new and more specific therapeutic approaches is therefore required. To this aim, a major advancement in the pharmacotherapy of channelopathies has been the discovery that ion channel mutations lead to change in biophysics that can in turn specifically modify the sensitivity to drugs: this opens the way to a pharmacogenetics strategy, allowing the development of a personalized therapy with increased efficacy and reduced side effects. In addition, the identification of disease modifiers in ion channelopathies appears an alternative strategy to discover novel druggable targets.

Effects of Discovery Learning and Student Assessment on Academic Success

ERIC Educational Resources Information Center

Suphi, Nilgün; Yaratan, Hüseyin

2016-01-01

In this study the effect of Discovery Learning and course evaluation based on Bloom's Taxonomy on the academic success of undergraduate students in Northern Cyprus was investigated. One demographic questionnaire was distributed to 829 students and two questionnaires were distributed to these students' instructors in order to collect information on…

Identifying and Quantifying Heterogeneity in High Content Analysis: Application of Heterogeneity Indices to Drug Discovery

PubMed Central

Gough, Albert H.; Chen, Ning; Shun, Tong Ying; Lezon, Timothy R.; Boltz, Robert C.; Reese, Celeste E.; Wagner, Jacob; Vernetti, Lawrence A.; Grandis, Jennifer R.; Lee, Adrian V.; Stern, Andrew M.; Schurdak, Mark E.; Taylor, D. Lansing

2014-01-01

One of the greatest challenges in biomedical research, drug discovery and diagnostics is understanding how seemingly identical cells can respond differently to perturbagens including drugs for disease treatment. Although heterogeneity has become an accepted characteristic of a population of cells, in drug discovery it is not routinely evaluated or reported. The standard practice for cell-based, high content assays has been to assume a normal distribution and to report a well-to-well average value with a standard deviation. To address this important issue we sought to define a method that could be readily implemented to identify, quantify and characterize heterogeneity in cellular and small organism assays to guide decisions during drug discovery and experimental cell/tissue profiling. Our study revealed that heterogeneity can be effectively identified and quantified with three indices that indicate diversity, non-normality and percent outliers. The indices were evaluated using the induction and inhibition of STAT3 activation in five cell lines where the systems response including sample preparation and instrument performance were well characterized and controlled. These heterogeneity indices provide a standardized method that can easily be integrated into small and large scale screening or profiling projects to guide interpretation of the biology, as well as the development of therapeutics and diagnostics. Understanding the heterogeneity in the response to perturbagens will become a critical factor in designing strategies for the development of therapeutics including targeted polypharmacology. PMID:25036749

Scaffold Repurposing of Old Drugs Towards New Cancer Drug Discovery.

PubMed

Chen, Haijun; Wu, Jianlei; Gao, Yu; Chen, Haiying; Zhou, Jia

2016-01-01

As commented by the Nobelist James Black that "The most fruitful basis of the discovery of a new drug is to start with an old drug", drug repurposing represents an attractive drug discovery strategy. Despite the success of several repurposed drugs on the market, the ultimate therapeutic potential of a large number of non-cancer drugs is hindered during their repositioning due to various issues including the limited efficacy and intellectual property. With the increasing knowledge about the pharmacological properties and newly identified targets, the scaffolds of the old drugs emerge as a great treasure-trove towards new cancer drug discovery. In this review, we summarize the recent advances in the development of novel small molecules for cancer therapy by scaffold repurposing with highlighted examples. The relevant strategies, advantages, challenges and future research directions associated with this approach are also discussed.

Child Predictors of Learning to Control Variables via Instruction or Self-Discovery

ERIC Educational Resources Information Center

Wagensveld, Barbara; Segers, Eliane; Kleemans, Tijs; Verhoeven, Ludo

2015-01-01

We examined the role child factors on the acquisition and transfer of learning the control of variables strategy (CVS) via instruction or self-discovery. Seventy-six fourth graders and 43 sixth graders were randomly assigned to a group receiving direct CVS instruction or a discovery learning group. Prior to the intervention, cognitive, scientific,…

Teaching Slope of a Line Using the Graphing Calculator as a Tool for Discovery Learning

ERIC Educational Resources Information Center

Nichols, Fiona Costello

2012-01-01

Discovery learning is one of the instructional strategies sometimes used to teach Algebra I. However, little research is available that includes investigation of the effects of incorporating the graphing calculator technology with discovery learning. This study was initiated to investigate two instructional approaches for teaching slope of a line…

Computational drug discovery

PubMed Central

Ou-Yang, Si-sheng; Lu, Jun-yan; Kong, Xiang-qian; Liang, Zhong-jie; Luo, Cheng; Jiang, Hualiang

2012-01-01

Computational drug discovery is an effective strategy for accelerating and economizing drug discovery and development process. Because of the dramatic increase in the availability of biological macromolecule and small molecule information, the applicability of computational drug discovery has been extended and broadly applied to nearly every stage in the drug discovery and development workflow, including target identification and validation, lead discovery and optimization and preclinical tests. Over the past decades, computational drug discovery methods such as molecular docking, pharmacophore modeling and mapping, de novo design, molecular similarity calculation and sequence-based virtual screening have been greatly improved. In this review, we present an overview of these important computational methods, platforms and successful applications in this field. PMID:22922346

Natural products and drug discovery: a survey of stakeholders in industry and academia.

PubMed

Amirkia, Vafa; Heinrich, Michael

2015-01-01

In recent decades, natural products have undisputedly played a leading role in the development of novel medicines. Yet, trends in the pharmaceutical industry at the level of research investments indicate that natural product research is neither prioritized nor perceived as fruitful in drug discovery programmes as compared with incremental structural modifications and large volume HTS screening of synthetics. We seek to understand this phenomenon through insights from highly experienced natural product experts in industry and academia. We conducted a survey including a series of qualitative and quantitative questions related to current insights and prospective developments in natural product drug development. The survey was completed by a cross-section of 52 respondents in industry and academia. One recurrent theme is the dissonance between the perceived high potential of NP as drug leads among individuals and the survey participants' assessment of the overall industry and/or company level strategies and their success. The study's industry and academic respondents did not perceive current discovery efforts as more effective as compared with previous decades, yet industry contacts perceived higher hit rates in HTS efforts as compared with academic respondents. Surprisingly, many industry contacts were highly critical to prevalent company and industry-wide drug discovery strategies indicating a high level of dissatisfaction within the industry. These findings support the notion that there is an increasing gap in perception between the effectiveness of well established, commercially widespread drug discovery strategies between those working in industry and academic experts. This research seeks to shed light on this gap and aid in furthering natural product discovery endeavors through an analysis of current bottlenecks in industry drug discovery programmes.

Streptomyces species: Ideal chassis for natural product discovery and overproduction.

PubMed

Liu, Ran; Deng, Zixin; Liu, Tiangang

2018-05-28

There is considerable interest in mining organisms for new natural products (NPs) and in improving methods to overproduce valuable NPs. Because of the rapid development of tools and strategies for metabolic engineering and the markedly increased knowledge of the biosynthetic pathways and genetics of NP-producing organisms, genome mining and overproduction of NPs can be dramatically accelerated. In particular, Streptomyces species have been proposed as suitable chassis organisms for NP discovery and overproduction because of their many unique characteristics not shared with yeast, Escherichia coli, or other microorganisms. In this review, we summarize the methods for genome sequencing, gene cluster prediction, and gene editing in Streptomyces, as well as metabolic engineering strategies for NP overproduction and approaches for generating new products. Finally, two strategies for utilizing Streptomyces as the chassis for NP discovery and overproduction are emphasized. Copyright © 2018 International Metabolic Engineering Society. Published by Elsevier Inc. All rights reserved.

Equation Discovery for Model Identification in Respiratory Mechanics of the Mechanically Ventilated Human Lung

NASA Astrophysics Data System (ADS)

Ganzert, Steven; Guttmann, Josef; Steinmann, Daniel; Kramer, Stefan

Lung protective ventilation strategies reduce the risk of ventilator associated lung injury. To develop such strategies, knowledge about mechanical properties of the mechanically ventilated human lung is essential. This study was designed to develop an equation discovery system to identify mathematical models of the respiratory system in time-series data obtained from mechanically ventilated patients. Two techniques were combined: (i) the usage of declarative bias to reduce search space complexity and inherently providing the processing of background knowledge. (ii) A newly developed heuristic for traversing the hypothesis space with a greedy, randomized strategy analogical to the GSAT algorithm. In 96.8% of all runs the applied equation discovery system was capable to detect the well-established equation of motion model of the respiratory system in the provided data. We see the potential of this semi-automatic approach to detect more complex mathematical descriptions of the respiratory system from respiratory data.

Mitigating risk in academic preclinical drug discovery

PubMed Central

Dahlin, Jayme L.; Inglese, James; Walters, Michael A.

2018-01-01

The number of academic drug discovery centres has grown considerably in recent years, providing new opportunities to couple the curiosity-driven research culture in academia with rigorous preclinical drug discovery practices used in industry. To fully realize the potential of these opportunities, it is important that academic researchers understand the risks inherent in preclinical drug discovery, and that translational research programmes are effectively organized and supported at an institutional level. In this article, we discuss strategies to mitigate risks in several key aspects of preclinical drug discovery at academic drug discovery centres, including organization, target selection, assay design, medicinal chemistry and preclinical pharmacology. PMID:25829283

Is there a best strategy for drug discovery?--SMR Meeting. 13 March 2003, London, UK.

PubMed

Lunec, Anna

2003-05-01

This gathering of members from academia and industry allowed the sharing of ideas and techniques or the acceleration of drug discovery, and it was clear that there is a need for a more streamlined approach to discovery and development. Clearly, new technologies will aid in the discovery process, but the abilities of the human brain to analyze and interpret data should not be overlooked, as many discoveries have been made by chance or as the result of a hunch, and it would be a shame if the advent of artificial intelligence quashed that inquisitive aspect of drug discovery.

Shared strategies for β-lactam catabolism in the soil microbiome.

PubMed

Crofts, Terence S; Wang, Bin; Spivak, Aaron; Gianoulis, Tara A; Forsberg, Kevin J; Gibson, Molly K; Johnsky, Lauren A; Broomall, Stacey M; Rosenzweig, C Nicole; Skowronski, Evan W; Gibbons, Henry S; Sommer, Morten O A; Dantas, Gautam

2018-06-01

The soil microbiome can produce, resist, or degrade antibiotics and even catabolize them. While resistance genes are widely distributed in the soil, there is a dearth of knowledge concerning antibiotic catabolism. Here we describe a pathway for penicillin catabolism in four isolates. Genomic and transcriptomic sequencing revealed β-lactamase, amidase, and phenylacetic acid catabolon upregulation. Knocking out part of the phenylacetic acid catabolon or an apparent penicillin utilization operon (put) resulted in loss of penicillin catabolism in one isolate. A hydrolase from the put operon was found to degrade in vitro benzylpenicilloic acid, the β-lactamase penicillin product. To test the generality of this strategy, an Escherichia coli strain was engineered to co-express a β-lactamase and a penicillin amidase or the put operon, enabling it to grow using penicillin or benzylpenicilloic acid, respectively. Elucidation of additional pathways may allow bioremediation of antibiotic-contaminated soils and discovery of antibiotic-remodeling enzymes with industrial utility.

Rational Improvement of Molar Absorptivity Guided by Oscillator Strength: A Case Study with Furoindolizine-Based Core Skeleton.

PubMed

Lee, Youngjun; Jo, Ala; Park, Seung Bum

2015-12-21

The rational improvement of photophysical properties can be highly valuable for the discovery of novel organic fluorophores. Using our new design strategy guided by the oscillator strength, we developed a series of full-color-tunable furoindolizine analogs with improved molar absorptivity through the fusion of a furan ring into the indolizine-based Seoul fluorophore. The excellent correlation between the computable values (oscillator strength and theoretical S0 -S1 energy gap) and photophysical properties (molar absorptivity and emission wavelength) confirmed the effectualness of our design strategy. © 2015 The Authors. Published by Wiley-VCH Verlag GmbH & Co. KGaA. This is an open access article under the terms of the Creative Commons Attribution Non-Commercial NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

Neoadjuvant trials in ER+ breast cancer: A tool for acceleration of drug development and discovery

PubMed Central

Guerrero-Zotano, Angel L.; Arteaga, Carlos L.

2017-01-01

Neoadjuvant therapy trials offer an excellent strategy for drug development and discovery in breast cancer, particularly in triple negative and HER2-overexpressing subtypes, where pathologic complete response is a good surrogate of long term patient benefit. For estrogen receptor (ER)-positive breast cancers, however, use of this strategy has been challenging because of the lack of validated surrogates of long term efficacy and the overall good prognosis of the majority of patients with this cancer subtype. We review below the clinical benefits of neodjuvant endocrine therapy for ER+/HER2-negative breast cancer, its use and limitations for drug development, prioritization of adjuvant and metastatic trials, and biomarker discovery. PMID:28495849

Fragment-based drug discovery as alternative strategy to the drug development for neglected diseases.

PubMed

Mello, Juliana da Fonseca Rezende E; Gomes, Renan Augusto; Vital-Fujii, Drielli Gomes; Ferreira, Glaucio Monteiro; Trossini, Gustavo Henrique Goulart

2017-12-01

Neglected diseases (NDs) affect large populations and almost whole continents, representing 12% of the global health burden. In contrast, the treatment available today is limited and sometimes ineffective. Under this scenery, the Fragment-Based Drug Discovery emerged as one of the most promising alternatives to the traditional methods of drug development. This method allows achieving new lead compounds with smaller size of fragment libraries. Even with the wide Fragment-Based Drug Discovery success resulting in new effective therapeutic agents against different diseases, until this moment few studies have been applied this approach for NDs area. In this article, we discuss the basic Fragment-Based Drug Discovery process, brief successful ideas of general applications and show a landscape of its use in NDs, encouraging the implementation of this strategy as an interesting way to optimize the development of new drugs to NDs. © 2017 John Wiley & Sons A/S.

A Perspective on Implementing a Quantitative Systems Pharmacology Platform for Drug Discovery and the Advancement of Personalized Medicine.

PubMed

Stern, Andrew M; Schurdak, Mark E; Bahar, Ivet; Berg, Jeremy M; Taylor, D Lansing

2016-07-01

Drug candidates exhibiting well-defined pharmacokinetic and pharmacodynamic profiles that are otherwise safe often fail to demonstrate proof-of-concept in phase II and III trials. Innovation in drug discovery and development has been identified as a critical need for improving the efficiency of drug discovery, especially through collaborations between academia, government agencies, and industry. To address the innovation challenge, we describe a comprehensive, unbiased, integrated, and iterative quantitative systems pharmacology (QSP)-driven drug discovery and development strategy and platform that we have implemented at the University of Pittsburgh Drug Discovery Institute. Intrinsic to QSP is its integrated use of multiscale experimental and computational methods to identify mechanisms of disease progression and to test predicted therapeutic strategies likely to achieve clinical validation for appropriate subpopulations of patients. The QSP platform can address biological heterogeneity and anticipate the evolution of resistance mechanisms, which are major challenges for drug development. The implementation of this platform is dedicated to gaining an understanding of mechanism(s) of disease progression to enable the identification of novel therapeutic strategies as well as repurposing drugs. The QSP platform will help promote the paradigm shift from reactive population-based medicine to proactive personalized medicine by focusing on the patient as the starting and the end point. © 2016 Society for Laboratory Automation and Screening.

Service Discovery Oriented Management System Construction Method

NASA Astrophysics Data System (ADS)

Li, Huawei; Ren, Ying

2017-10-01

In order to solve the problem that there is no uniform method for design service quality management system in large-scale complex service environment, this paper proposes a distributed service-oriented discovery management system construction method. Three measurement functions are proposed to compute nearest neighbor user similarity at different levels. At present in view of the low efficiency of service quality management systems, three solutions are proposed to improve the efficiency of the system. Finally, the key technologies of distributed service quality management system based on service discovery are summarized through the factor addition and subtraction of quantitative experiment.

Marine Bacterial and Archaeal Ion-Pumping Rhodopsins: Genetic Diversity, Physiology, and Ecology

PubMed Central

DeLong, Edward F.; Béjà, Oded; González, José M.; Pedrós-Alió, Carlos

2016-01-01

SUMMARY The recognition of a new family of rhodopsins in marine planktonic bacteria, proton-pumping proteorhodopsin, expanded the known phylogenetic range, environmental distribution, and sequence diversity of retinylidene photoproteins. At the time of this discovery, microbial ion-pumping rhodopsins were known solely in haloarchaea inhabiting extreme hypersaline environments. Shortly thereafter, proteorhodopsins and other light-activated energy-generating rhodopsins were recognized to be widespread among marine bacteria. The ubiquity of marine rhodopsin photosystems now challenges prior understanding of the nature and contributions of “heterotrophic” bacteria to biogeochemical carbon cycling and energy fluxes. Subsequent investigations have focused on the biophysics and biochemistry of these novel microbial rhodopsins, their distribution across the tree of life, evolutionary trajectories, and functional expression in nature. Later discoveries included the identification of proteorhodopsin genes in all three domains of life, the spectral tuning of rhodopsin variants to wavelengths prevailing in the sea, variable light-activated ion-pumping specificities among bacterial rhodopsin variants, and the widespread lateral gene transfer of biosynthetic genes for bacterial rhodopsins and their associated photopigments. Heterologous expression experiments with marine rhodopsin genes (and associated retinal chromophore genes) provided early evidence that light energy harvested by rhodopsins could be harnessed to provide biochemical energy. Importantly, some studies with native marine bacteria show that rhodopsin-containing bacteria use light to enhance growth or promote survival during starvation. We infer from the distribution of rhodopsin genes in diverse genomic contexts that different marine bacteria probably use rhodopsins to support light-dependent fitness strategies somewhere between these two extremes. PMID:27630250

Accelerating Chemical Discovery with Machine Learning: Simulated Evolution of Spin Crossover Complexes with an Artificial Neural Network.

PubMed

Janet, Jon Paul; Chan, Lydia; Kulik, Heather J

2018-03-01

Machine learning (ML) has emerged as a powerful complement to simulation for materials discovery by reducing time for evaluation of energies and properties at accuracy competitive with first-principles methods. We use genetic algorithm (GA) optimization to discover unconventional spin-crossover complexes in combination with efficient scoring from an artificial neural network (ANN) that predicts spin-state splitting of inorganic complexes. We explore a compound space of over 5600 candidate materials derived from eight metal/oxidation state combinations and a 32-ligand pool. We introduce a strategy for error-aware ML-driven discovery by limiting how far the GA travels away from the nearest ANN training points while maximizing property (i.e., spin-splitting) fitness, leading to discovery of 80% of the leads from full chemical space enumeration. Over a 51-complex subset, average unsigned errors (4.5 kcal/mol) are close to the ANN's baseline 3 kcal/mol error. By obtaining leads from the trained ANN within seconds rather than days from a DFT-driven GA, this strategy demonstrates the power of ML for accelerating inorganic material discovery.

Robustness of disaggregate oil and gas discovery forecasting models

USGS Publications Warehouse

Attanasi, E.D.; Schuenemeyer, J.H.

1989-01-01

The trend in forecasting oil and gas discoveries has been to develop and use models that allow forecasts of the size distribution of future discoveries. From such forecasts, exploration and development costs can more readily be computed. Two classes of these forecasting models are the Arps-Roberts type models and the 'creaming method' models. This paper examines the robustness of the forecasts made by these models when the historical data on which the models are based have been subject to economic upheavals or when historical discovery data are aggregated from areas having widely differing economic structures. Model performance is examined in the context of forecasting discoveries for offshore Texas State and Federal areas. The analysis shows how the model forecasts are limited by information contained in the historical discovery data. Because the Arps-Roberts type models require more regularity in discovery sequence than the creaming models, prior information had to be introduced into the Arps-Roberts models to accommodate the influence of economic changes. The creaming methods captured the overall decline in discovery size but did not easily allow introduction of exogenous information to compensate for incomplete historical data. Moreover, the predictive log normal distribution associated with the creaming model methods appears to understate the importance of the potential contribution of small fields. ?? 1989.

Bose-Einstein condensates form in heuristics learned by ciliates deciding to signal 'social' commitments.

PubMed

Clark, Kevin B

2010-03-01

Fringe quantum biology theories often adopt the concept of Bose-Einstein condensation when explaining how consciousness, emotion, perception, learning, and reasoning emerge from operations of intact animal nervous systems and other computational media. However, controversial empirical evidence and mathematical formalism concerning decoherence rates of bioprocesses keep these frameworks from satisfactorily accounting for the physical nature of cognitive-like events. This study, inspired by the discovery that preferential attachment rules computed by complex technological networks obey Bose-Einstein statistics, is the first rigorous attempt to examine whether analogues of Bose-Einstein condensation precipitate learned decision making in live biological systems as bioenergetics optimization predicts. By exploiting the ciliate Spirostomum ambiguum's capacity to learn and store behavioral strategies advertising mating availability into heuristics of topologically invariant computational networks, three distinct phases of strategy use were found to map onto statistical distributions described by Bose-Einstein, Fermi-Dirac, and classical Maxwell-Boltzmann behavior. Ciliates that sensitized or habituated signaling patterns to emit brief periods of either deceptive 'harder-to-get' or altruistic 'easier-to-get' serial escape reactions began testing condensed on initially perceived fittest 'courting' solutions. When these ciliates switched from their first strategy choices, Bose-Einstein condensation of strategy use abruptly dissipated into a Maxwell-Boltzmann computational phase no longer dominated by a single fittest strategy. Recursive trial-and-error strategy searches annealed strategy use back into a condensed phase consistent with performance optimization. 'Social' decisions performed by ciliates showing no nonassociative learning were largely governed by Fermi-Dirac statistics, resulting in degenerate distributions of strategy choices. These findings corroborate previous work demonstrating ciliates with improving expertise search grouped 'courting' assurances at quantum efficiencies and verify efficient processing by primitive 'social' intelligences involves network forms of Bose-Einstein condensation coupled to preceding thermodynamic-sensitive computational phases. 2009 Elsevier Ireland Ltd. All rights reserved.

Computer-Aided Drug Design in Epigenetics

NASA Astrophysics Data System (ADS)

Lu, Wenchao; Zhang, Rukang; Jiang, Hao; Zhang, Huimin; Luo, Cheng

2018-03-01

Epigenetic dysfunction has been widely implicated in several diseases especially cancers thus highlights the therapeutic potential for chemical interventions in this field. With rapid development of computational methodologies and high-performance computational resources, computer-aided drug design has emerged as a promising strategy to speed up epigenetic drug discovery. Herein, we make a brief overview of major computational methods reported in the literature including druggability prediction, virtual screening, homology modeling, scaffold hopping, pharmacophore modeling, molecular dynamics simulations, quantum chemistry calculation and 3D quantitative structure activity relationship that have been successfully applied in the design and discovery of epi-drugs and epi-probes. Finally, we discuss about major limitations of current virtual drug design strategies in epigenetics drug discovery and future directions in this field.

Computer-Aided Drug Design in Epigenetics

PubMed Central

Lu, Wenchao; Zhang, Rukang; Jiang, Hao; Zhang, Huimin; Luo, Cheng

2018-01-01

Epigenetic dysfunction has been widely implicated in several diseases especially cancers thus highlights the therapeutic potential for chemical interventions in this field. With rapid development of computational methodologies and high-performance computational resources, computer-aided drug design has emerged as a promising strategy to speed up epigenetic drug discovery. Herein, we make a brief overview of major computational methods reported in the literature including druggability prediction, virtual screening, homology modeling, scaffold hopping, pharmacophore modeling, molecular dynamics simulations, quantum chemistry calculation, and 3D quantitative structure activity relationship that have been successfully applied in the design and discovery of epi-drugs and epi-probes. Finally, we discuss about major limitations of current virtual drug design strategies in epigenetics drug discovery and future directions in this field. PMID:29594101

Discovery of 2-Pyridinone Aminals: A Prodrug Strategy to Advance a Second Generation of HIV-1 Integrase Strand Transfer Inhibitors

DOE Office of Scientific and Technical Information (OSTI.GOV)

Raheem, Izzat T.; Walji, Abbas M.; Klein, Daniel

The search for new molecular constructs that resemble the critical two-metal binding pharmacophore required for HIV integrase strand transfer inhibition represents a vibrant area of research within drug discovery. Here we present the discovery of a new class of HIV integrase strand transfer inhibitors based on the 2-pyridinone core of MK-0536. These efforts led to the identification of two lead compounds with excellent antiviral activity and preclinical pharmacokinetic profiles to support a once-daily human dose prediction. Dose escalating PK studies in dog revealed significant issues with limited oral absorption and required an innovative prodrug strategy to enhance the high-dose plasmamore » exposures of the parent molecules.« less

Personal discovery in diabetes self-management: Discovering cause and effect using self-monitoring data

PubMed Central

Mamykina, Lena; Heitkemper, Elizabeth M.; Smaldone, Arlene M.; Kukafka, Rita; Cole-Lewis, Heather J.; Davidson, Patricia G.; Mynatt, Elizabeth D.; Cassells, Andrea; Tobin, Jonathan N.; Hripcsak, George

2017-01-01

Objective To outline new design directions for informatics solutions that facilitate personal discovery with self-monitoring data. We investigate this question in the context of chronic disease self-management with the focus on type 2 diabetes. Materials and methods We conducted an observational qualitative study of discovery with personal data among adults attending a diabetes self-management education (DSME) program that utilized a discovery-based curriculum. The study included observations of class sessions, and interviews and focus groups with the educator and attendees of the program (n = 14). Results The main discovery in diabetes self-management evolved around discovering patterns of association between characteristics of individuals’ activities and changes in their blood glucose levels that the participants referred to as “cause and effect”. This discovery empowered individuals to actively engage in self-management and provided a desired flexibility in selection of personalized self-management strategies. We show that discovery of cause and effect involves four essential phases: (1) feature selection, (2) hypothesis generation, (3) feature evaluation, and (4) goal specification. Further, we identify opportunities to support discovery at each stage with informatics and data visualization solutions by providing assistance with: (1) active manipulation of collected data (e.g., grouping, filtering and side-by-side inspection), (2) hypotheses formulation (e.g., using natural language statements or constructing visual queries), (3) inference evaluation (e.g., through aggregation and visual comparison, and statistical analysis of associations), and (4) translation of discoveries into actionable goals (e.g., tailored selection from computable knowledge sources of effective diabetes self-management behaviors). Discussion The study suggests that discovery of cause and effect in diabetes can be a powerful approach to helping individuals to improve their self-management strategies, and that self-monitoring data can serve as a driving engine for personal discovery that may lead to sustainable behavior changes. Conclusions Enabling personal discovery is a promising new approach to enhancing chronic disease self-management with informatics interventions. PMID:28974460

Personal discovery in diabetes self-management: Discovering cause and effect using self-monitoring data.

PubMed

Mamykina, Lena; Heitkemper, Elizabeth M; Smaldone, Arlene M; Kukafka, Rita; Cole-Lewis, Heather J; Davidson, Patricia G; Mynatt, Elizabeth D; Cassells, Andrea; Tobin, Jonathan N; Hripcsak, George

2017-12-01

To outline new design directions for informatics solutions that facilitate personal discovery with self-monitoring data. We investigate this question in the context of chronic disease self-management with the focus on type 2 diabetes. We conducted an observational qualitative study of discovery with personal data among adults attending a diabetes self-management education (DSME) program that utilized a discovery-based curriculum. The study included observations of class sessions, and interviews and focus groups with the educator and attendees of the program (n = 14). The main discovery in diabetes self-management evolved around discovering patterns of association between characteristics of individuals' activities and changes in their blood glucose levels that the participants referred to as "cause and effect". This discovery empowered individuals to actively engage in self-management and provided a desired flexibility in selection of personalized self-management strategies. We show that discovery of cause and effect involves four essential phases: (1) feature selection, (2) hypothesis generation, (3) feature evaluation, and (4) goal specification. Further, we identify opportunities to support discovery at each stage with informatics and data visualization solutions by providing assistance with: (1) active manipulation of collected data (e.g., grouping, filtering and side-by-side inspection), (2) hypotheses formulation (e.g., using natural language statements or constructing visual queries), (3) inference evaluation (e.g., through aggregation and visual comparison, and statistical analysis of associations), and (4) translation of discoveries into actionable goals (e.g., tailored selection from computable knowledge sources of effective diabetes self-management behaviors). The study suggests that discovery of cause and effect in diabetes can be a powerful approach to helping individuals to improve their self-management strategies, and that self-monitoring data can serve as a driving engine for personal discovery that may lead to sustainable behavior changes. Enabling personal discovery is a promising new approach to enhancing chronic disease self-management with informatics interventions. Copyright © 2017 Elsevier Inc. All rights reserved.

Inhibiting the Epidermal Growth Factor Receptor | Center for Cancer Research

Cancer.gov

The Epidermal Growth Factor Receptor (EGFR) is a widely distributed cell surface receptor that responds to several extracellular signaling molecules through an intracellular tyrosine kinase, which phosphorylates target enzymes to trigger a downstream molecular cascade. Since the discovery that EGFR mutations and amplifications are critical in a number of cancers, efforts have been under way to develop and use targeted EGFR inhibitors. These efforts have met with some spectacular successes, but many patients have not responded as expected, have subsequently developed drug-resistant tumors, or have suffered serious side effects from the therapies to date. CCR Investigators are studying EGFR from multiple vantage points with the goal of developing even better strategies to defeat EGFR-related cancers.

Promoting discovery and access to real time observations produced by regional coastal ocean observing systems

NASA Astrophysics Data System (ADS)

Anderson, D. M.; Snowden, D. P.; Bochenek, R.; Bickel, A.

2015-12-01

In the U.S. coastal waters, a network of eleven regional coastal ocean observing systems support real-time coastal and ocean observing. The platforms supported and variables acquired are diverse, ranging from current sensing high frequency (HF) radar to autonomous gliders. The system incorporates data produced by other networks and experimental systems, further increasing the breadth of the collection. Strategies promoted by the U.S. Integrated Ocean Observing System (IOOS) ensure these data are not lost at sea. Every data set deserves a description. ISO and FGDC compliant metadata enables catalog interoperability and record-sharing. Extensive use of netCDF with the Climate and Forecast convention (identifying both metadata and a structured format) is shown to be a powerful strategy to promote discovery, interoperability, and re-use of the data. To integrate specialized data which are often obscure, quality control protocols are being developed to homogenize the QC and make these data more integrate-able. Data Assembly Centers have been established to integrate some specialized streams including gliders, animal telemetry, and HF radar. Subsets of data that are ingested into the National Data Buoy Center are also routed to the Global Telecommunications System (GTS) of the World Meteorological Organization to assure wide international distribution. From the GTS, data are assimilated into now-cast and forecast models, fed to other observing systems, and used to support observation-based decision making such as forecasts, warnings, and alerts. For a few years apps were a popular way to deliver these real-time data streams to phones and tablets. Responsive and adaptive web sites are an emerging flexible strategy to provide access to the regional coastal ocean observations.

Methods and apparatus for distributed resource discovery using examples

NASA Technical Reports Server (NTRS)

Chang, Yuan-Chi (Inventor); Li, Chung-Sheng (Inventor); Smith, John Richard (Inventor); Hill, Matthew L. (Inventor); Bergman, Lawrence David (Inventor); Castelli, Vittorio (Inventor)

2005-01-01

Distributed resource discovery is an essential step for information retrieval and/or providing information services. This step is usually used for determining the location of an information or data repository which has relevant information. The most fundamental challenge is the usual lack of semantic interoperability of the requested resource. In accordance with the invention, a method is disclosed where distributed repositories achieve semantic interoperability through the exchange of examples and, optionally, classifiers. The outcome of the inventive method can be used to determine whether common labels are referring to the same semantic meaning.

Choosing experiments to accelerate collective discovery

PubMed Central

Rzhetsky, Andrey; Foster, Jacob G.; Foster, Ian T.

2015-01-01

A scientist’s choice of research problem affects his or her personal career trajectory. Scientists’ combined choices affect the direction and efficiency of scientific discovery as a whole. In this paper, we infer preferences that shape problem selection from patterns of published findings and then quantify their efficiency. We represent research problems as links between scientific entities in a knowledge network. We then build a generative model of discovery informed by qualitative research on scientific problem selection. We map salient features from this literature to key network properties: an entity’s importance corresponds to its degree centrality, and a problem’s difficulty corresponds to the network distance it spans. Drawing on millions of papers and patents published over 30 years, we use this model to infer the typical research strategy used to explore chemical relationships in biomedicine. This strategy generates conservative research choices focused on building up knowledge around important molecules. These choices become more conservative over time. The observed strategy is efficient for initial exploration of the network and supports scientific careers that require steady output, but is inefficient for science as a whole. Through supercomputer experiments on a sample of the network, we study thousands of alternatives and identify strategies much more efficient at exploring mature knowledge networks. We find that increased risk-taking and the publication of experimental failures would substantially improve the speed of discovery. We consider institutional shifts in grant making, evaluation, and publication that would help realize these efficiencies. PMID:26554009

Strategy of Daiichi Sankyo discovery research in oncology.

PubMed

Akahane, Kouichi; Hirokawa, Kazunori

2014-02-01

We would like to introduce Daiichi Sankyo's approach to developing cancer targeted medicines with special reference to the drug discovery strategy, global discovery activities and external research collaboration leading to generation of innovative drugs for cancer patients. We are developing 14 clinical projects for cancer treatment and three of them have been previously approved. These are mostly targeted for growth and survival signals of cancer cells. To overcome the drug resistance mechanism derived from the heterogeneous nature of cancer, we are developing selective inhibitors in three major clusters of signal pathways which may allow future rational combinations of oncology products. In addition to the main research facility in Japan, research sites in the EU and the USA provide us with different technical expertise and diversified ideas of drug discovery. To access novel drug targets, we are facilitating research collaboration with leading academia and successful cancer research scientists. In conclusion, we intend to focus more on developing innovative personalized medicines for better treatment of cancer.

Drug Repositioning for Effective Prostate Cancer Treatment.

PubMed

Turanli, Beste; Grøtli, Morten; Boren, Jan; Nielsen, Jens; Uhlen, Mathias; Arga, Kazim Y; Mardinoglu, Adil

2018-01-01

Drug repositioning has gained attention from both academia and pharmaceutical companies as an auxiliary process to conventional drug discovery. Chemotherapeutic agents have notorious adverse effects that drastically reduce the life quality of cancer patients so drug repositioning is a promising strategy to identify non-cancer drugs which have anti-cancer activity as well as tolerable adverse effects for human health. There are various strategies for discovery and validation of repurposed drugs. In this review, 25 repurposed drug candidates are presented as result of different strategies, 15 of which are already under clinical investigation for treatment of prostate cancer (PCa). To date, zoledronic acid is the only repurposed, clinically used, and approved non-cancer drug for PCa. Anti-cancer activities of existing drugs presented in this review cover diverse and also known mechanisms such as inhibition of mTOR and VEGFR2 signaling, inhibition of PI3K/Akt signaling, COX and selective COX-2 inhibition, NF-κB inhibition, Wnt/β-Catenin pathway inhibition, DNMT1 inhibition, and GSK-3β inhibition. In addition to monotherapy option, combination therapy with current anti-cancer drugs may also increase drug efficacy and reduce adverse effects. Thus, drug repositioning may become a key approach for drug discovery in terms of time- and cost-efficiency comparing to conventional drug discovery and development process.

Neoclassic drug discovery: the case for lead generation using phenotypic and functional approaches.

PubMed

Lee, Jonathan A; Berg, Ellen L

2013-12-01

Innovation and new molecular entity production by the pharmaceutical industry has been below expectations. Surprisingly, more first-in-class small-molecule drugs approved by the U.S. Food and Drug Administration (FDA) between 1999 and 2008 were identified by functional phenotypic lead generation strategies reminiscent of pre-genomics pharmacology than contemporary molecular targeted strategies that encompass the vast majority of lead generation efforts. This observation, in conjunction with the difficulty in validating molecular targets for drug discovery, has diminished the impact of the "genomics revolution" and has led to a growing grassroots movement and now broader trend in pharma to reconsider the use of modern physiology-based or phenotypic drug discovery (PDD) strategies. This "From the Guest Editors" column provides an introduction and overview of the two-part special issues of Journal of Biomolecular Screening on PDD. Terminology and the business case for use of PDD are defined. Key issues such as assay performance, chemical optimization, target identification, and challenges to the organization and implementation of PDD are discussed. Possible solutions for these challenges and a new neoclassic vision for PDD that combines phenotypic and functional approaches with technology innovations resulting from the genomics-driven era of target-based drug discovery (TDD) are also described. Finally, an overview of the manuscripts in this special edition is provided.

15 years of zebrafish chemical screening

PubMed Central

Rennekamp, Andrew J.; Peterson, Randall T.

2015-01-01

In 2000, the first chemical screen using living zebrafish in a multi-well plate was reported. Since then, more than 60 additional screens have been published describing whole-organism drug and pathway discovery projects in zebrafish. To investigate the scope of the work reported in the last 14 years and to identify trends in the field, we analyzed the discovery strategies of 64 primary research articles from the literature. We found that zebrafish screens have expanded beyond the use of developmental phenotypes to include behavioral, cardiac, metabolic, proliferative and regenerative endpoints. Additionally, many creative strategies have been used to uncover the mechanisms of action of new small molecules including chemical phenocopy, genetic phenocopy, mutant rescue, and spatial localization strategies. PMID:25461724

Stabilization of protein-protein interactions in drug discovery.

PubMed

Andrei, Sebastian A; Sijbesma, Eline; Hann, Michael; Davis, Jeremy; O'Mahony, Gavin; Perry, Matthew W D; Karawajczyk, Anna; Eickhoff, Jan; Brunsveld, Luc; Doveston, Richard G; Milroy, Lech-Gustav; Ottmann, Christian

2017-09-01

PPIs are involved in every disease and specific modulation of these PPIs with small molecules would significantly improve our prospects of developing therapeutic agents. Both industry and academia have engaged in the identification and use of PPI inhibitors. However in comparison, the opposite strategy of employing small-molecule stabilizers of PPIs is underrepresented in drug discovery. Areas covered: PPI stabilization has not been exploited in a systematic manner. Rather, this concept validated by a number of therapeutically used natural products like rapamycin and paclitaxel has been shown retrospectively to be the basis of the activity of synthetic molecules originating from drug discovery projects among them lenalidomide and tafamidis. Here, the authors cover the growing number of synthetic small-molecule PPI stabilizers to advocate for a stronger consideration of this as a drug discovery approach. Expert opinion: Both the natural products and the growing number of synthetic molecules show that PPI stabilization is a viable strategy for drug discovery. There is certainly a significant challenge to adapt compound libraries, screening techniques and downstream methodologies to identify, characterize and optimize PPI stabilizers, but the examples of molecules reviewed here in our opinion justify these efforts.

Radiation Detection Material Discovery Initiative at PNNL

NASA Astrophysics Data System (ADS)

Milbrath, Brian

2006-05-01

Today's security threats are being met with 30-year old radiation technology. Discovery of new radiation detection materials is currently a slow and Edisonian process. With heightened concerns over nuclear proliferation, terrorism and unconventional warfare, an alternative strategy for identification and development of potential radiation detection materials must be adopted. Through the Radiation Detection Materials Discovery Initiative, PNNL focuses on the science-based discovery of next generation materials for radiation detection by addressing three ``grand challenges'': fundamental understanding of radiation detection, identification of new materials, and accelerating the discovery process. The new initiative has eight projects addressing these challenges, which will be described, including early work, paths forward and the opportunities for collaboration.

Rediscovering Medicinal Plants' Potential with OMICS: Microsatellite Survey in Expressed Sequence Tags of Eleven Traditional Plants with Potent Antidiabetic Properties

PubMed Central

Sahu, Jagajjit; Sen, Priyabrata; Choudhury, Manabendra Dutta; Dehury, Budheswar; Barooah, Madhumita; Modi, Mahendra Kumar

2014-01-01

Abstract Herbal medicines and traditionally used medicinal plants present an untapped potential for novel molecular target discovery using systems science and OMICS biotechnology driven strategies. Since up to 40% of the world's poor people have no access to government health services, traditional and folk medicines are often the only therapeutics available to them. In this vein, North East (NE) India is recognized for its rich bioresources. As part of the Indo-Burma hotspot, it is regarded as an epicenter of biodiversity for several plants having myriad traditional uses, including medicinal use. However, the improvement of these valuable bioresources through molecular breeding strategies, for example, using genic microsatellites or Simple Sequence Repeats (SSRs) or Expressed Sequence Tags (ESTs)-derived SSRs has not been fully utilized in large scale to date. In this study, we identified a total of 47,700 microsatellites from 109,609 ESTs of 11 medicinal plants (pineapple, papaya, noyontara, bitter orange, bermuda brass, ratalu, barbados nut, mango, mulberry, lotus, and guduchi) having proven antidiabetic properties. A total of 58,159 primer pairs were designed for the non-redundant 8060 SSR-positive ESTs and putative functions were assigned to 4483 unique contigs. Among the identified microsatellites, excluding mononucleotide repeats, di-/trinucleotides are predominant, among which repeat motifs of AG/CT and AAG/CTT were most abundant. Similarity search of SSR containing ESTs and antidiabetic gene sequences revealed 11 microsatellites linked to antidiabetic genes in five plants. GO term enrichment analysis revealed a total of 80 enriched GO terms widely distributed in 53 biological processes, 17 molecular functions, and 10 cellular components associated with the 11 markers. The present study therefore provides concrete insights into the frequency and distribution of SSRs in important medicinal resources. The microsatellite markers reported here markedly add to the genetic stock for cross transferability in these plants and the literature on biomarkers and novel drug discovery for common chronic diseases such as diabetes. PMID:24802971

Rediscovering medicinal plants' potential with OMICS: microsatellite survey in expressed sequence tags of eleven traditional plants with potent antidiabetic properties.

PubMed

Sahu, Jagajjit; Sen, Priyabrata; Choudhury, Manabendra Dutta; Dehury, Budheswar; Barooah, Madhumita; Modi, Mahendra Kumar; Talukdar, Anupam Das

2014-05-01

Herbal medicines and traditionally used medicinal plants present an untapped potential for novel molecular target discovery using systems science and OMICS biotechnology driven strategies. Since up to 40% of the world's poor people have no access to government health services, traditional and folk medicines are often the only therapeutics available to them. In this vein, North East (NE) India is recognized for its rich bioresources. As part of the Indo-Burma hotspot, it is regarded as an epicenter of biodiversity for several plants having myriad traditional uses, including medicinal use. However, the improvement of these valuable bioresources through molecular breeding strategies, for example, using genic microsatellites or Simple Sequence Repeats (SSRs) or Expressed Sequence Tags (ESTs)-derived SSRs has not been fully utilized in large scale to date. In this study, we identified a total of 47,700 microsatellites from 109,609 ESTs of 11 medicinal plants (pineapple, papaya, noyontara, bitter orange, bermuda brass, ratalu, barbados nut, mango, mulberry, lotus, and guduchi) having proven antidiabetic properties. A total of 58,159 primer pairs were designed for the non-redundant 8060 SSR-positive ESTs and putative functions were assigned to 4483 unique contigs. Among the identified microsatellites, excluding mononucleotide repeats, di-/trinucleotides are predominant, among which repeat motifs of AG/CT and AAG/CTT were most abundant. Similarity search of SSR containing ESTs and antidiabetic gene sequences revealed 11 microsatellites linked to antidiabetic genes in five plants. GO term enrichment analysis revealed a total of 80 enriched GO terms widely distributed in 53 biological processes, 17 molecular functions, and 10 cellular components associated with the 11 markers. The present study therefore provides concrete insights into the frequency and distribution of SSRs in important medicinal resources. The microsatellite markers reported here markedly add to the genetic stock for cross transferability in these plants and the literature on biomarkers and novel drug discovery for common chronic diseases such as diabetes.

A new stem-neopterygian fish from the Middle Triassic of China shows the earliest over-water gliding strategy of the vertebrates.

PubMed

Xu, Guang-Hui; Zhao, Li-Jun; Gao, Ke-Qin; Wu, Fei-Xiang

2013-01-07

Flying fishes are extraordinary aquatic vertebrates capable of gliding great distances over water by exploiting their enlarged pectoral fins and asymmetrical caudal fin. Some 50 species of extant flying fishes are classified in the Exocoetidae (Neopterygii: Teleostei), which have a fossil record no older than the Eocene. The Thoracopteridae is the only pre-Cenozoic group of non-teleosts that shows an array of features associated with the capability of over-water gliding. Until recently, however, the fossil record of the Thoracopteridae has been limited to the Upper Triassic of Austria and Italy. Here, we report the discovery of exceptionally well-preserved fossils of a new thoracopterid flying fish from the Middle Triassic of China, which represents the earliest evidence of an over-water gliding strategy in vertebrates. The results of a phylogenetic analysis resolve the Thoracopteridae as a stem-group of the Neopterygii that is more crown-ward than the Peltopleuriformes, yet more basal than the Luganoiiformes. As the first record of the Thoracopteride in Asia, this new discovery extends the geographical distribution of this group from the western to eastern rim of the Palaeotethys Ocean, providing new evidence to support the Triassic biological exchanges between Europe and southern China. Additionally, the Middle Triassic date of the new thoracopterid supports the hypothesis that the re-establishment of marine ecosystems after end-Permian mass extinction is more rapid than previously thought.

A new stem-neopterygian fish from the Middle Triassic of China shows the earliest over-water gliding strategy of the vertebrates

PubMed Central

Xu, Guang-Hui; Zhao, Li-Jun; Gao, Ke-Qin; Wu, Fei-Xiang

2013-01-01

Flying fishes are extraordinary aquatic vertebrates capable of gliding great distances over water by exploiting their enlarged pectoral fins and asymmetrical caudal fin. Some 50 species of extant flying fishes are classified in the Exocoetidae (Neopterygii: Teleostei), which have a fossil record no older than the Eocene. The Thoracopteridae is the only pre-Cenozoic group of non-teleosts that shows an array of features associated with the capability of over-water gliding. Until recently, however, the fossil record of the Thoracopteridae has been limited to the Upper Triassic of Austria and Italy. Here, we report the discovery of exceptionally well-preserved fossils of a new thoracopterid flying fish from the Middle Triassic of China, which represents the earliest evidence of an over-water gliding strategy in vertebrates. The results of a phylogenetic analysis resolve the Thoracopteridae as a stem-group of the Neopterygii that is more crown-ward than the Peltopleuriformes, yet more basal than the Luganoiiformes. As the first record of the Thoracopteride in Asia, this new discovery extends the geographical distribution of this group from the western to eastern rim of the Palaeotethys Ocean, providing new evidence to support the Triassic biological exchanges between Europe and southern China. Additionally, the Middle Triassic date of the new thoracopterid supports the hypothesis that the re-establishment of marine ecosystems after end-Permian mass extinction is more rapid than previously thought. PMID:23118437

Distributed Drug Discovery, Part 3: Using D3 Methodology to Synthesize Analogs of an Anti-Melanoma Compound

PubMed Central

2008-01-01

For the successful implementation of Distributed Drug Discovery (D3) (outlined in the accompanying Perspective), students, in the course of their educational laboratories, must be able to reproducibly make new, high quality, molecules with potential for biological activity. This article reports the successful achievement of this goal. Using previously rehearsed alkylating agents, students in a second semester organic chemistry laboratory performed a solid-phase combinatorial chemistry experiment in which they made 38 new analogs of the most potent member of a class of antimelanoma compounds. All compounds were made in duplicate, purified by silica gel chromatography, and characterized by NMR and LC/MS. As a continuing part of the Distributed Drug Discovery program, a virtual D3 catalog based on this work was then enumerated and is made freely available to the global scientific community. PMID:19105723

Research & market strategy: how choice of drug discovery approach can affect market position.

PubMed

Sams-Dodd, Frank

2007-04-01

In principal, drug discovery approaches can be grouped into target- and function-based, with the respective aims of developing either a target-selective drug or a drug that produces a specific biological effect irrespective of its mode of action. Most analyses of drug discovery approaches focus on productivity, whereas the strategic implications of the choice of drug discovery approach on market position and ability to maintain market exclusivity are rarely considered. However, a comparison of approaches from the perspective of market position indicates that the functional approach is superior for the development of novel, innovative treatments.

Discovery of Non-random Spatial Distribution of Impacts in the Stardust Cometary Collector

NASA Technical Reports Server (NTRS)

Horz, Friedrich; Westphal, Andrew J.; Gainsforth, Zack; Borg, Janet; Djouadi, Zahia; Bridges, John; Franchi, Ian; Brownlee, Donald E.; Cheng. Andrew F.; Clark, Benton C.;

Apprenticeships, Collaboration and Scientific Discovery in Academic Field Studies

ERIC Educational Resources Information Center

Madden, Derek Scott; Grayson, Diane J.; Madden, Erinn H.; Milewski, Antoni V.; Snyder, Cathy Ann

2012-01-01

Teachers may use apprenticeships and collaboration as instructional strategies that help students to make authentic scientific discoveries as they work as amateur researchers in academic field studies. This concept was examined with 643 students, ages 14-72, who became proficient at field research through cognitive apprenticeships with the…

Implementing the Army NetCentric Data Strategy in a ServiceOriented Environment

DTIC Science & Technology

2009-04-23

a Data Subscriptionc c e s s Federated Search Data Search D a t a A b s t r a c t i o n Adapter Configuration Adapter Data Service D a t a S e r...across t e enterpr se.  • Patterns • Search • Status • Receive – Services • Federated   Search • Artifact Discovery • Data Discovery 17 Data Discovery

Distributed Load Shedding over Directed Communication Networks with Time Delays

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, Tao; Wu, Di

When generation is insufficient to support all loads under emergencies, effective and efficient load shedding needs to be deployed in order to maintain the supply-demand balance. This paper presents a distributed load shedding algorithm, which makes efficient decision based on the discovered global information. In the global information discovery process, each load only communicates with its neighboring load via directed communication links possibly with arbitrarily large but bounded time varying communication delays. We propose a novel distributed information discovery algorithm based on ratio consensus. Simulation results are used to validate the proposed method.

Optimizing Oral Bioavailability in Drug Discovery: An Overview of Design and Testing Strategies and Formulation Options.

PubMed

Aungst, Bruce J

2017-04-01

For discovery teams working toward new, orally administered therapeutic agents, one requirement is to attain adequate systemic exposure after oral dosing, which is best accomplished when oral bioavailability is optimized. This report summarizes the bioavailability challenges currently faced in drug discovery, and the design and testing methods and strategies currently utilized to address the challenges. Profiling of discovery compounds usually includes separate assessments of solubility, permeability, and susceptibility to first-pass metabolism, which are the 3 most likely contributors to incomplete oral bioavailability. An initial assessment of absorption potential may be made computationally, and high throughput in vitro assays are typically performed to prioritize compounds for in vivo studies. The initial pharmacokinetic study is a critical decision point in compound evaluation, and the importance of the effect the dosing vehicle or formulation can have on oral bioavailability, especially for poorly water soluble compounds, is emphasized. Dosing vehicles and bioavailability-enabling formulations that can be used for discovery and preclinical studies are described. Optimizing oral bioavailability within a chemical series or for a lead compound requires identification of the barrier limiting bioavailability, and methods used for this purpose are outlined. Finally, a few key guidelines are offered for consideration when facing the challenges of optimizing oral bioavailability in drug discovery. Copyright © 2017 American Pharmacists Association®. Published by Elsevier Inc. All rights reserved.

New nitrogen uptake strategy: specialized snow roots.

PubMed

Onipchenko, Vladimir G; Makarov, Mikhail I; van Logtestijn, Richard S P; Ivanov, Viktor B; Akhmetzhanova, Assem A; Tekeev, Dzhamal K; Ermak, Anton A; Salpagarova, Fatima S; Kozhevnikova, Anna D; Cornelissen, Johannes H C

2009-08-01

The evolution of plants has yielded a wealth of adaptations for the acquisition of key mineral nutrients. These include the structure, physiology and positioning of root systems. We report the discovery of specialized snow roots as a plant strategy to cope with the very short season for nutrient uptake and growth in alpine snow-beds, i.e. patches in the landscape that remain snow-covered well into the summer. We provide anatomical, chemical and experimental (15)N isotope tracking evidence that the Caucasian snow-bed plant Corydalis conorhiza forms extensive networks of specialized above-ground roots, which grow against gravity to acquire nitrogen directly from within snow packs. Snow roots capture nitrogen that would otherwise partly run off down-slope over a frozen surface, thereby helping to nourish these alpine ecosystems. Climate warming is changing and will change mountain snow regimes, while large-scale anthropogenic N deposition has increased snow N contents. These global changes are likely to impact on the distribution, abundance and functional significance of snow roots.

Explorative solid-phase extraction (E-SPE) for accelerated microbial natural product discovery, dereplication, and purification.

PubMed

Månsson, Maria; Phipps, Richard K; Gram, Lone; Munro, Murray H G; Larsen, Thomas O; Nielsen, Kristian F

2010-06-25

Microbial natural products (NP) cover a high chemical diversity, and in consequence extracts from microorganisms are often complex to analyze and purify. A distribution analysis of calculated pK(a) values from the 34390 records in Antibase2008 revealed that within pH 2-11, 44% of all included compounds had an acidic functionality, 17% a basic functionality, and 9% both. This showed a great potential for using ion-exchange chromatography as an integral part of the separation procedure, orthogonal to the classic reversed-phase strategy. Thus, we investigated the use of an "explorative solid-phase extraction" (E-SPE) protocol using SAX, Oasis MAX, SCX, and LH-20 columns for targeted exploitation of chemical functionalities. E-SPE provides a minimum of fractions (15) for chemical and biological analyses and implicates development into a preparative scale methodology. Overall, this allows fast extract prioritization, easier dereplication, mapping of biological activities, and formulation of a purification strategy.

Exome sequencing of extreme phenotypes identifies DCTN4 as a modifier of chronic Pseudomonas aeruginosa infection in cystic fibrosis.

PubMed

Emond, Mary J; Louie, Tin; Emerson, Julia; Zhao, Wei; Mathias, Rasika A; Knowles, Michael R; Wright, Fred A; Rieder, Mark J; Tabor, Holly K; Nickerson, Deborah A; Barnes, Kathleen C; Gibson, Ronald L; Bamshad, Michael J

2012-07-08

Exome sequencing has become a powerful and effective strategy for the discovery of genes underlying Mendelian disorders. However, use of exome sequencing to identify variants associated with complex traits has been more challenging, partly because the sample sizes needed for adequate power may be very large. One strategy to increase efficiency is to sequence individuals who are at both ends of a phenotype distribution (those with extreme phenotypes). Because the frequency of alleles that contribute to the trait are enriched in one or both phenotype extremes, a modest sample size can potentially be used to identify novel candidate genes and/or alleles. As part of the National Heart, Lung, and Blood Institute (NHLBI) Exome Sequencing Project (ESP), we used an extreme phenotype study design to discover that variants in DCTN4, encoding a dynactin protein, are associated with time to first P. aeruginosa airway infection, chronic P. aeruginosa infection and mucoid P. aeruginosa in individuals with cystic fibrosis.

Genomic Medicine Without Borders: Which Strategies Should Developing Countries Employ to Invest in Precision Medicine? A New "Fast-Second Winner" Strategy.

PubMed

Mitropoulos, Konstantinos; Cooper, David N; Mitropoulou, Christina; Agathos, Spiros; Reichardt, Jürgen K V; Al-Maskari, Fatima; Chantratita, Wasun; Wonkam, Ambroise; Dandara, Collet; Katsila, Theodora; Lopez-Correa, Catalina; Ali, Bassam R; Patrinos, George P

2017-11-01

Genomic medicine has greatly matured in terms of its technical capabilities, but the diffusion of genomic innovations worldwide faces significant barriers beyond mere access to technology. New global development strategies are sorely needed for biotechnologies such as genomics and their applications toward precision medicine without borders. Moreover, diffusion of genomic medicine globally cannot adhere to a "one-size-fits-all-countries" development strategy, in the same way that drug treatments should be customized. This begs a timely, difficult but crucial question: How should developing countries, and the resource-limited regions of developed countries, invest in genomic medicine? Although a full-scale investment in infrastructure from discovery to the translational implementation of genomic science is ideal, this may not always be feasible in all countries at all times. A simple "transplantation of genomics" from developed to developing countries is unlikely to be feasible. Nor should developing countries be seen as simple recipients and beneficiaries of genomic medicine developed elsewhere because important advances in genomic medicine have materialized in developing countries as well. There are several noteworthy examples of genomic medicine success stories involving resource-limited settings that are contextualized and described in this global genomic medicine innovation analysis. In addition, we outline here a new long-term development strategy for global genomic medicine in a way that recognizes the individual country's pressing public health priorities and disease burdens. We term this approach the "Fast-Second Winner" model of innovation that supports innovation commencing not only "upstream" of discovery science but also "mid-stream," building on emerging highly promising biomarker and diagnostic candidates from the global science discovery pipeline, based on the unique needs of each country. A mid-stream entry into innovation can enhance collective learning from other innovators' mistakes upstream in discovery science and boost the probability of success for translation and implementation when resources are limited. This à la carte model of global innovation and development strategy offers multiple entry points into the global genomics innovation ecosystem for developing countries, whether or not extensive and expensive discovery infrastructures are already in place. Ultimately, broadening our thinking beyond the linear model of innovation will help us to enable the vision and practice of genomics without borders in both developed and resource-limited settings.

From leptin to other adipokines in health and disease: facts and expectations at the beginning of the 21st century.

PubMed

Blüher, Matthias; Mantzoros, Christos S

2015-01-01

This year marks the 20th anniversary of the discovery of leptin, which has tremendously stimulated translational obesity research. The discovery of leptin has led to realizations that have established adipose tissue as an endocrine organ, secreting bioactive molecules including hormones now termed adipokines. Through adipokines, the adipose tissue influences the regulation of several important physiological functions including but not limited to appetite, satiety, energy expenditure, activity, insulin sensitivity and secretion, glucose and lipid metabolism, fat distribution, endothelial function, hemostasis, blood pressure, neuroendocrine regulation, and function of the immune system. Adipokines have a great potential for clinical use as potential therapeutics for obesity, obesity related metabolic, cardiovascular and other diseases. After 20 years of intense research efforts, recombinant leptin and the leptin analog metreleptin are already available for the treatment of congenital leptin deficiency and lipodystrophy. Other adipokines are also emerging as promising candidates for urgently needed novel pharmacological treatment strategies not only in obesity but also other disease states associated with and influenced by adipose tissue size and activity. In addition, prediction of reduced type 2 diabetes risk by high circulating adiponectin concentrations suggests that adipokines have the potential to be used as biomarkers for individual treatment success and disease progression, to monitor clinical responses and to identify non-responders to anti-obesity interventions. With the growing number of adipokines there is an increasing need to define their function, molecular targets and translational potential for the treatment of obesity and other diseases. In this review we present research data on adipose tissue secreted hormones, the discovery of which followed the discovery of leptin 20 years ago pointing to future research directions to unravel mechanisms of action for adipokines. Copyright © 2015 Elsevier Inc. All rights reserved.

Lowering the barriers for accessing distributed geospatial big data to advance spatial data science: the PolarHub solution

NASA Astrophysics Data System (ADS)

Li, W.

2017-12-01

Data is the crux of science. The widespread availability of big data today is of particular importance for fostering new forms of geospatial innovation. This paper reports a state-of-the-art solution that addresses a key cyberinfrastructure research problem—providing ready access to big, distributed geospatial data resources on the Web. We first formulate this data-access problem and introduce its indispensable elements, including identifying the cyber-location, space and time coverage, theme, and quality of the dataset. We then propose strategies to tackle each data-access issue and make the data more discoverable and usable for geospatial data users and decision makers. Among these strategies is large-scale web crawling as a key technique to support automatic collection of online geospatial data that are highly distributed, intrinsically heterogeneous, and known to be dynamic. To better understand the content and scientific meanings of the data, methods including space-time filtering, ontology-based thematic classification, and service quality evaluation are incorporated. To serve a broad scientific user community, these techniques are integrated into an operational data crawling system, PolarHub, which is also an important cyberinfrastructure building block to support effective data discovery. A series of experiments were conducted to demonstrate the outstanding performance of the PolarHub system. We expect this work to contribute significantly in building the theoretical and methodological foundation for data-driven geography and the emerging spatial data science.

Churchill: an ultra-fast, deterministic, highly scalable and balanced parallelization strategy for the discovery of human genetic variation in clinical and population-scale genomics.

PubMed

Kelly, Benjamin J; Fitch, James R; Hu, Yangqiu; Corsmeier, Donald J; Zhong, Huachun; Wetzel, Amy N; Nordquist, Russell D; Newsom, David L; White, Peter

2015-01-20

While advances in genome sequencing technology make population-scale genomics a possibility, current approaches for analysis of these data rely upon parallelization strategies that have limited scalability, complex implementation and lack reproducibility. Churchill, a balanced regional parallelization strategy, overcomes these challenges, fully automating the multiple steps required to go from raw sequencing reads to variant discovery. Through implementation of novel deterministic parallelization techniques, Churchill allows computationally efficient analysis of a high-depth whole genome sample in less than two hours. The method is highly scalable, enabling full analysis of the 1000 Genomes raw sequence dataset in a week using cloud resources. http://churchill.nchri.org/.

Trellis Tone Modulation Multiple-Access for Peer Discovery in D2D Networks

PubMed Central

Lim, Chiwoo; Kim, Sang-Hyo

2018-01-01

In this paper, a new non-orthogonal multiple-access scheme, trellis tone modulation multiple-access (TTMMA), is proposed for peer discovery of distributed device-to-device (D2D) communication. The range and capacity of discovery are important performance metrics in peer discovery. The proposed trellis tone modulation uses single-tone transmission and achieves a long discovery range due to its low Peak-to-Average Power Ratio (PAPR). The TTMMA also exploits non-orthogonal resource assignment to increase the discovery capacity. For the multi-user detection of superposed multiple-access signals, a message-passing algorithm with supplementary schemes are proposed. With TTMMA and its message-passing demodulation, approximately 1.5 times the number of devices are discovered compared to the conventional frequency division multiple-access (FDMA)-based discovery. PMID:29673167

Trellis Tone Modulation Multiple-Access for Peer Discovery in D2D Networks.

PubMed

Lim, Chiwoo; Jang, Min; Kim, Sang-Hyo

2018-04-17

In this paper, a new non-orthogonal multiple-access scheme, trellis tone modulation multiple-access (TTMMA), is proposed for peer discovery of distributed device-to-device (D2D) communication. The range and capacity of discovery are important performance metrics in peer discovery. The proposed trellis tone modulation uses single-tone transmission and achieves a long discovery range due to its low Peak-to-Average Power Ratio (PAPR). The TTMMA also exploits non-orthogonal resource assignment to increase the discovery capacity. For the multi-user detection of superposed multiple-access signals, a message-passing algorithm with supplementary schemes are proposed. With TTMMA and its message-passing demodulation, approximately 1.5 times the number of devices are discovered compared to the conventional frequency division multiple-access (FDMA)-based discovery.

A Control Strategy for High-Performance Macromolecular Materials

DTIC Science & Technology

2007-01-04

None as of this date. Potential transitions with Moldflow Corporation, Boston, MA. New Discoveries None as of this date. Contract FA9550-06-C-0017, Final Technical Report, Submitted by Nonlinear Control Strategies, Inc.

Renaissance in Antibiotic Discovery: Some Novel Approaches for Finding Drugs to Treat Bad Bugs.

PubMed

Gadakh, Bharat; Van Aerschot, Arthur

2015-01-01

With the alarming resistance to currently used antibiotics, there is a serious worldwide threat to public health. Therefore, there is an urgent need to search for new antibiotics or new cellular targets which are essential for survival of the pathogens. However, during the past 50 years, only two new classes of antibiotics (oxazolidinone and lipopeptides) have reached the clinic. This suggests that the success rate in discovering new/novel antibiotics using conventional approaches is limited and that we must reconsider our antibiotic discovery approaches. While many new strategies are being pursued lately, this review primarily focuses only on a few of these novel/new approaches for antibiotic discovery. These include structure-based drug design (SBDD), the genomic approach, anti-virulence strategy, targeting nonmultiplying bacteria and the use of bacteriophages. In general, recent advancements in nuclear magnetic resonance, Xcrystallography, and genomic evolution have significant impact on antibacterial drug research. This review therefore aims to discuss recent strategies in searching new antibacterial agents making use of these technical novelties, their advantages, disadvantages and limitations.

Dominie: Teaching and Assessment Strategies. CAL Research Group Technical Report No. 74.

ERIC Educational Resources Information Center

Spensley, Fiona; Elsom-Cook, Mark

This document outlines the strategies that are used for teaching and assessment in Dominie, an intelligent tutoring system designed to enable the user to operate a computer interface independently. Eight interaction modes are described in detail: four teaching strategies (cognitive apprenticeship, successive refinement, discovery learning, and…

Nanoparticle-mediated drug delivery for treating melanoma

PubMed Central

Mundra, Vaibhav; Li, Wei; Mahato, Ram I

2015-01-01

Melanoma originated from melanocytes is the most aggressive type of skin cancer with limited treatment options. New targeted therapeutic options with the discovery of BRAF and MEK inhibitors have shown significant survival benefits. Despite the recent progress, development of chemoresistance and systemic toxicity remains a challenge for treating metastatic melanoma. While the response from the first line of treatment against melanoma using dacarbazine remains only 5–10%, the prolonged use of targeted therapy against mutated oncogene BRAF develops chemoresistance. In this review, we will discuss the nanoparticle-based strategies for encapsulation and conjugation of drugs to the polymer for maximizing their tumor distribution through enhanced permeability and retention effect. We will also highlight photodynamic therapy and design of melanoma-targeted nanoparticles. PMID:26244818

A Statistical Selection Strategy for Normalization Procedures in LC-MS Proteomics Experiments through Dataset Dependent Ranking of Normalization Scaling Factors

DOE Office of Scientific and Technical Information (OSTI.GOV)

Webb-Robertson, Bobbie-Jo M.; Matzke, Melissa M.; Jacobs, Jon M.

2011-12-01

Quantification of LC-MS peak intensities assigned during peptide identification in a typical comparative proteomics experiment will deviate from run-to-run of the instrument due to both technical and biological variation. Thus, normalization of peak intensities across a LC-MS proteomics dataset is a fundamental step in pre-processing. However, the downstream analysis of LC-MS proteomics data can be dramatically affected by the normalization method selected . Current normalization procedures for LC-MS proteomics data are presented in the context of normalization values derived from subsets of the full collection of identified peptides. The distribution of these normalization values is unknown a priori. If theymore » are not independent from the biological factors associated with the experiment the normalization process can introduce bias into the data, which will affect downstream statistical biomarker discovery. We present a novel approach to evaluate normalization strategies, where a normalization strategy includes the peptide selection component associated with the derivation of normalization values. Our approach evaluates the effect of normalization on the between-group variance structure in order to identify candidate normalization strategies that improve the structure of the data without introducing bias into the normalized peak intensities.« less

PharMillenium '99--the second world pharmaceutical congress and exhibition. Accelerating the pipeline: from drug discovery to market. 1-3 February 1999, Washington DC, USA.

PubMed

Fernandes, M

1999-04-01

This highly interactive meeting effectively covered critical issues on every transaction from drug discovery through to development and commercialization. The program included company-specific descriptions of new discovery products, together with seminars by clinical research and site management organizations on the acceleration of development, pharmaco-economics, branding of products, direct-to-consumer advertising, global marketing, management, information technology and business strategy. There were approximately 50 sessions covered by 70 speakers.

Quantitative Analysis of Tissue Samples by Combining iTRAQ Isobaric Labeling with Selected/Multiple Reaction Monitoring (SRM/MRM).

PubMed

Narumi, Ryohei; Tomonaga, Takeshi

2016-01-01

Mass spectrometry-based phosphoproteomics is an indispensible technique used in the discovery and quantification of phosphorylation events on proteins in biological samples. The application of this technique to tissue samples is especially useful for the discovery of biomarkers as well as biological studies. We herein describe the application of a large-scale phosphoproteome analysis and SRM/MRM-based quantitation to develop a strategy for the systematic discovery and validation of biomarkers using tissue samples.

Space Science Enterprise Strategy

NASA Technical Reports Server (NTRS)

2003-01-01

The 2003 Space Science Enterprise Strategy represents the efforts of hundreds of scientists, staff, and educators, as well as collaboration with the other NASA Enterprises. It reveals the progress we have made, our plans for the near future, and our opportunity to support the Agency's Mission to "explore the universe and search for life." Space science has made spectacular advances in the recent past, from the first baby pictures of the universe to the discovery of water ice on Mars. Each new discovery impels us to ask new questions or regard old ones in new ways. How did the universe begin? How did life arise? Are we alone? These questions continue to inspire all of us to keep exploring and searching. And, as we get closer to answers, we will continue to share our findings with the science community, educators, and the public as broadly and as rapidly as possible. In this Strategy, you will find science objectives that define NASA's quest for discovery. You will also find the framework of programs, such as flight missions and ground-based research, that will enable us to achieve these objectives. This Strategy is founded on recommendations from the community, as well as lessons learned from past programs, and maps the stepping-stones to the future of space science.

Open innovation for phenotypic drug discovery: The PD2 assay panel.

PubMed

Lee, Jonathan A; Chu, Shaoyou; Willard, Francis S; Cox, Karen L; Sells Galvin, Rachelle J; Peery, Robert B; Oliver, Sarah E; Oler, Jennifer; Meredith, Tamika D; Heidler, Steven A; Gough, Wendy H; Husain, Saba; Palkowitz, Alan D; Moxham, Christopher M

2011-07-01

Phenotypic lead generation strategies seek to identify compounds that modulate complex, physiologically relevant systems, an approach that is complementary to traditional, target-directed strategies. Unlike gene-specific assays, phenotypic assays interrogate multiple molecular targets and signaling pathways in a target "agnostic" fashion, which may reveal novel functions for well-studied proteins and discover new pathways of therapeutic value. Significantly, existing compound libraries may not have sufficient chemical diversity to fully leverage a phenotypic strategy. To address this issue, Eli Lilly and Company launched the Phenotypic Drug Discovery Initiative (PD(2)), a model of open innovation whereby external research groups can submit compounds for testing in a panel of Lilly phenotypic assays. This communication describes the statistical validation, operations, and initial screening results from the first PD(2) assay panel. Analysis of PD(2) submissions indicates that chemical diversity from open source collaborations complements internal sources. Screening results for the first 4691 compounds submitted to PD(2) have confirmed hit rates from 1.6% to 10%, with the majority of active compounds exhibiting acceptable potency and selectivity. Phenotypic lead generation strategies, in conjunction with novel chemical diversity obtained via open-source initiatives such as PD(2), may provide a means to identify compounds that modulate biology by novel mechanisms and expand the innovation potential of drug discovery.

Novel Approaches to Pulmonary Arterial Hypertension Drug Discovery

PubMed Central

Sung, Yon K.; Yuan, Ke; de Jesus Perez, Vinicio A.

2016-01-01

Introduction Pulmonary arterial hypertension (PAH) is a rare disorder associated with abnormally elevated pulmonary pressures that, if untreated, leads to right heart failure and premature death. The goal of drug development for PAH is to develop effective therapies that halt, or ideally, reverse the obliterative vasculopathy that results in vessel loss and obstruction of blood flow to the lungs. Areas Covered This review summarizes the current approach to candidate discovery in PAH and discusses the currently available drug discovery methods that should be implemented to prioritize targets and obtain a comprehensive pharmacological profile of promising compounds with well-defined mechanisms. Expert opinion To improve the successful identification of leading drug candidates, it is necessary that traditional pre-clinical studies are combined with drug screening strategies that maximize the characterization of biological activity and identify relevant off-target effects that could hinder the clinical efficacy of the compound when tested in human subjects. A successful drug discovery strategy in PAH will require collaboration of clinician scientists with medicinal chemists and pharmacologists who can identify compounds with an adequate safety profile and biological activity against relevant disease mechanisms. PMID:26901465

The early bird gets the worm: foraging strategies of wild songbirds lead to the early discovery of food sources

PubMed Central

Farine, Damien R.; Lang, Stephen D. J.

2013-01-01

Animals need to manage the combined risks of predation and starvation in order to survive. Theoretical and empirical studies have shown that individuals can reduce predation risk by delaying feeding (and hence fat storage) until late afternoon. However, little is known about how individuals manage the opposing pressures of resource uncertainty and predation risks. We suggest that individuals should follow a two-part strategy: prioritizing the discovery of food early in the day and exploiting the best patch late in the day. Using automated data loggers, we tested whether a temporal component exists in the discovery of novel foraging locations by individuals in a mixed-species foraging guild. We found that food deployed in the morning was discovered significantly more often than food deployed in the afternoon. Based on the diurnal activity patterns in this population, overall rates of new arrivals were also significantly higher than expected in the morning and significantly lower than expected in the afternoon. These results align with our predictions of a shift from patch discovery to exploitation over the course of the day. PMID:24108676

The Localized Discovery and Recovery for Query Packet Losses in Wireless Sensor Networks with Distributed Detector Clusters

PubMed Central

Teng, Rui; Leibnitz, Kenji; Miura, Ryu

2013-01-01

An essential application of wireless sensor networks is to successfully respond to user queries. Query packet losses occur in the query dissemination due to wireless communication problems such as interference, multipath fading, packet collisions, etc. The losses of query messages at sensor nodes result in the failure of sensor nodes reporting the requested data. Hence, the reliable and successful dissemination of query messages to sensor nodes is a non-trivial problem. The target of this paper is to enable highly successful query delivery to sensor nodes by localized and energy-efficient discovery, and recovery of query losses. We adopt local and collective cooperation among sensor nodes to increase the success rate of distributed discoveries and recoveries. To enable the scalability in the operations of discoveries and recoveries, we employ a distributed name resolution mechanism at each sensor node to allow sensor nodes to self-detect the correlated queries and query losses, and then efficiently locally respond to the query losses. We prove that the collective discovery of query losses has a high impact on the success of query dissemination and reveal that scalability can be achieved by using the proposed approach. We further study the novel features of the cooperation and competition in the collective recovery at PHY and MAC layers, and show that the appropriate number of detectors can achieve optimal successful recovery rate. We evaluate the proposed approach with both mathematical analyses and computer simulations. The proposed approach enables a high rate of successful delivery of query messages and it results in short route lengths to recover from query losses. The proposed approach is scalable and operates in a fully distributed manner. PMID:23748172

The war against influenza: discovery and development of sialidase inhibitors.

PubMed

von Itzstein, Mark

2007-12-01

The threat of a major human influenza pandemic, in particular from highly aggressive strains such as avian H5N1, has emphasized the need for therapeutic strategies to combat these pathogens. At present, two inhibitors of sialidase (also known as neuraminidase), a viral enzyme that has a key role in the life cycle of influenza viruses, would be the mainstay of pharmacological strategies in the event of such a pandemic. This article provides a historical perspective on the discovery and development of these drugs--zanamivir and oseltamivir--and highlights the value of structure-based drug design in this process.

A Virtual Bioinformatics Knowledge Environment for Early Cancer Detection

NASA Technical Reports Server (NTRS)

Crichton, Daniel; Srivastava, Sudhir; Johnsey, Donald

2003-01-01

Discovery of disease biomarkers for cancer is a leading focus of early detection. The National Cancer Institute created a network of collaborating institutions focused on the discovery and validation of cancer biomarkers called the Early Detection Research Network (EDRN). Informatics plays a key role in enabling a virtual knowledge environment that provides scientists real time access to distributed data sets located at research institutions across the nation. The distributed and heterogeneous nature of the collaboration makes data sharing across institutions very difficult. EDRN has developed a comprehensive informatics effort focused on developing a national infrastructure enabling seamless access, sharing and discovery of science data resources across all EDRN sites. This paper will discuss the EDRN knowledge system architecture, its objectives and its accomplishments.

Antisense oligonucleotide technologies in drug discovery.

PubMed

Aboul-Fadl, Tarek

2006-09-01

The principle of antisense oligonucleotide (AS-OD) technologies is based on the specific inhibition of unwanted gene expression by blocking mRNA activity. It has long appeared to be an ideal strategy to leverage new genomic knowledge for drug discovery and development. In recent years, AS-OD technologies have been widely used as potent and promising tools for this purpose. There is a rapid increase in the number of antisense molecules progressing in clinical trials. AS-OD technologies provide a simple and efficient approach for drug discovery and development and are expected to become a reality in the near future. This editorial describes the established and emerging AS-OD technologies in drug discovery.

Interrogating the relationship between rat in vivo tissue distribution and drug property data for >200 structurally unrelated molecules

PubMed Central

Harrell, Andrew W; Sychterz, Caroline; Ho, May Y; Weber, Andrew; Valko, Klara; Negash, Kitaw

2015-01-01

The ability to explain distribution patterns from drug physicochemical properties and binding characteristics has been explored for more than 200 compounds by interrogating data from quantitative whole body autoradiography studies (QWBA). These in vivo outcomes have been compared to in silico and in vitro drug property data to determine the most influential properties governing drug distribution. Consistent with current knowledge, in vivo distribution was most influenced by ionization state and lipophilicity which in turn affected phospholipid and plasma protein binding. Basic and neutral molecules were generally better distributed than acidic counterparts demonstrating weaker plasma protein and stronger phospholipid binding. The influence of phospholipid binding was particularly evident in tissues with high phospholipid content like spleen and lung. Conversely, poorer distribution of acidic drugs was associated with stronger plasma protein and weaker phospholipid binding. The distribution of a proportion of acidic drugs was enhanced, however, in tissues known to express anionic uptake transporters such as the liver and kidney. Greatest distribution was observed into melanin containing tissues of the eye, most likely due to melanin binding. Basic molecules were consistently better distributed into parts of the eye and skin containing melanin than those without. The data, therefore, suggest that drug binding to macromolecules strongly influences the distribution of total drug for a large proportion of molecules in most tissues. Reducing lipophilicity, a strategy often used in discovery to optimize pharmacokinetic properties such as absorption and clearance, also decreased the influence of nonspecific binding on drug distribution. PMID:26516585

Flow Cytometry: Impact on Early Drug Discovery.

PubMed

Edwards, Bruce S; Sklar, Larry A

2015-07-01

Modern flow cytometers can make optical measurements of 10 or more parameters per cell at tens of thousands of cells per second and more than five orders of magnitude dynamic range. Although flow cytometry is used in most drug discovery stages, "sip-and-spit" sampling technology has restricted it to low-sample-throughput applications. The advent of HyperCyt sampling technology has recently made possible primary screening applications in which tens of thousands of compounds are analyzed per day. Target-multiplexing methodologies in combination with extended multiparameter analyses enable profiling of lead candidates early in the discovery process, when the greatest numbers of candidates are available for evaluation. The ability to sample small volumes with negligible waste reduces reagent costs, compound usage, and consumption of cells. Improved compound library formatting strategies can further extend primary screening opportunities when samples are scarce. Dozens of targets have been screened in 384- and 1536-well assay formats, predominantly in academic screening lab settings. In concert with commercial platform evolution and trending drug discovery strategies, HyperCyt-based systems are now finding their way into mainstream screening labs. Recent advances in flow-based imaging, mass spectrometry, and parallel sample processing promise dramatically expanded single-cell profiling capabilities to bolster systems-level approaches to drug discovery. © 2015 Society for Laboratory Automation and Screening.

Flow Cytometry: Impact On Early Drug Discovery

PubMed Central

Edwards, Bruce S.; Sklar, Larry A.

2015-01-01

Summary Modern flow cytometers can make optical measurements of 10 or more parameters per cell at tens-of-thousands of cells per second and over five orders of magnitude dynamic range. Although flow cytometry is used in most drug discovery stages, “sip-and-spit” sampling technology has restricted it to low sample throughput applications. The advent of HyperCyt sampling technology has recently made possible primary screening applications in which tens-of-thousands of compounds are analyzed per day. Target-multiplexing methodologies in combination with extended multi-parameter analyses enable profiling of lead candidates early in the discovery process, when the greatest numbers of candidates are available for evaluation. The ability to sample small volumes with negligible waste reduces reagent costs, compound usage and consumption of cells. Improved compound library formatting strategies can further extend primary screening opportunities when samples are scarce. Dozens of targets have been screened in 384- and 1536-well assay formats, predominantly in academic screening lab settings. In concert with commercial platform evolution and trending drug discovery strategies, HyperCyt-based systems are now finding their way into mainstream screening labs. Recent advances in flow-based imaging, mass spectrometry and parallel sample processing promise dramatically expanded single cell profiling capabilities to bolster systems level approaches to drug discovery. PMID:25805180

Detailed view inside the aft fuselage of the Orbiter Discovery ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

Detailed view inside the aft fuselage of the Orbiter Discovery showing the network of supply, distribution and feed lines to deliver fuel, oxidizer and other vital gasses and fluids to the Space Shuttle Main Engines (SSMEs). This photograph was taken in the Orbiter Processing Facility at the Kennedy Space Center. - Space Transportation System, Orbiter Discovery (OV-103), Lyndon B. Johnson Space Center, 2101 NASA Parkway, Houston, Harris County, TX

Drug discovery of neurodegenerative disease through network pharmacology approach in herbs.

PubMed

Ke, Zhipeng; Zhang, Xinzhuang; Cao, Zeyu; Ding, Yue; Li, Na; Cao, Liang; Wang, Tuanjie; Zhang, Chenfeng; Ding, Gang; Wang, Zhenzhong; Xu, Xiaojie; Xiao, Wei

2016-03-01

Neurodegenerative diseases, referring to as the progressive loss of structure and function of neurons, constitute one of the major challenges of modern medicine. Traditional Chinese herbs have been used as a major preventive and therapeutic strategy against disease for thousands years. The numerous species of medicinal herbs and Traditional Chinese Medicine (TCM) compound formulas in nervous system disease therapy make it a large chemical resource library for drug discovery. In this work, we collected 7362 kinds of herbs and 58,147 Traditional Chinese medicinal compounds (Tcmcs). The predicted active compounds in herbs have good oral bioavailability and central nervous system (CNS) permeability. The molecular docking and network analysis were employed to analyze the effects of herbs on neurodegenerative diseases. In order to evaluate the predicted efficacy of herbs, automated text mining was utilized to exhaustively search in PubMed by some related keywords. After that, receiver operator characteristic (ROC) curves was used to estimate the accuracy of predictions. Our study suggested that most herbs were distributed in family of Asteraceae, Fabaceae, Lamiaceae and Apocynaceae. The predictive model yielded good sensitivity and specificity with the AUC values above 0.800. At last, 504 kinds of herbs were obtained by using the optimal cutoff values in ROC curves. These 504 herbs would be the most potential herb resources for neurodegenerative diseases treatment. This study would give us an opportunity to use these herbs as a chemical resource library for drug discovery of anti-neurodegenerative disease. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

Brazil: An emerging partner in drug R&D.

PubMed

Rodrigues, Debora G

2009-08-01

With the need for innovation in drug discovery and development and changes to patent laws that are enabling greater IP protection, many pharmaceutical companies are pursuing international cooperation agreements with foreign companies as part of a global development strategy to enhance product pipelines. Brazil, the largest pharmaceutical market in Latin America, has improved its infrastructure, scientific and technological capabilities and has created a sustainable strategy to promote drug discovery research activities. Positive economic growth, a stable political structure, expanding patient populations an increasing governmental, private and foreign investments are creating a new landscape for drug R&D in the country. As Brazilian-based pharmaceutical companies become further established, new opportunities for partnerships and collaborative alliances are becoming available for the drug discovery process, as well as for co-manufacturing and co-marketing efforts. This feature review provides an overview of the Brazilian pharmaceutical market and discusses current opportunities, emerging trends and challenges for this expanding market.

The role of fragment-based and computational methods in polypharmacology.

PubMed

Bottegoni, Giovanni; Favia, Angelo D; Recanatini, Maurizio; Cavalli, Andrea

2012-01-01

Polypharmacology-based strategies are gaining increased attention as a novel approach to obtaining potentially innovative medicines for multifactorial diseases. However, some within the pharmaceutical community have resisted these strategies because they can be resource-hungry in the early stages of the drug discovery process. Here, we report on fragment-based and computational methods that might accelerate and optimize the discovery of multitarget drugs. In particular, we illustrate that fragment-based approaches can be particularly suited for polypharmacology, owing to the inherent promiscuous nature of fragments. In parallel, we explain how computer-assisted protocols can provide invaluable insights into how to unveil compounds theoretically able to bind to more than one protein. Furthermore, several pragmatic aspects related to the use of these approaches are covered, thus offering the reader practical insights on multitarget-oriented drug discovery projects. Copyright © 2011 Elsevier Ltd. All rights reserved.

Active Learning Strategies and Assessment in World Geography Classes

ERIC Educational Resources Information Center

Klein, Phil

2003-01-01

Active learning strategies include a variety of methods, such as inquiry and discovery, in which students are actively engaged in the learning process. This article describes several strategies that can be used in secondary-or college-level world geography courses. The goal of these activities is to foster development of a spatial perspective in…

Microfluidic Devices for Automation of Assays on Drosophila Melanogaster for Applications in Drug Discovery and Biological Studies.

PubMed

Ghaemi, Reza; Selvaganapathy, Ponnambalam R

Drug discovery is a long and expensive process, which usually takes 12-15 years and could cost up to ~$1 billion. Conventional drug discovery process starts with high throughput screening and selection of drug candidates that bind to specific target associated with a disease condition. However, this process does not consider whether the chosen candidate is optimal not only for binding but also for ease of administration, distribution in the body, effect of metabolism and associated toxicity if any. A holistic approach, using model organisms early in the drug discovery process to select drug candidates that are optimal not only in binding but also suitable for administration, distribution and are not toxic is now considered as a viable way for lowering the cost and time associated with the drug discovery process. However, the conventional drug discovery assays using Drosophila are manual and required skill operator, which makes them expensive and not suitable for high-throughput screening. Recently, microfluidics has been used to automate many of the operations (e.g. sorting, positioning, drug delivery) associated with the Drosophila drug discovery assays and thereby increase their throughput. This review highlights recent microfluidic devices that have been developed for Drosophila assays with primary application towards drug discovery for human diseases. The microfluidic devices that have been reviewed in this paper are categorized based on the stage of the Drosophila that have been used. In each category, the microfluidic technologies behind each device are described and their potential biological applications are discussed.

Mass spectrometry-based biomarker discovery: toward a global proteome index of individuality.

PubMed

Hawkridge, Adam M; Muddiman, David C

2009-01-01

Biomarker discovery and proteomics have become synonymous with mass spectrometry in recent years. Although this conflation is an injustice to the many essential biomolecular techniques widely used in biomarker-discovery platforms, it underscores the power and potential of contemporary mass spectrometry. Numerous novel and powerful technologies have been developed around mass spectrometry, proteomics, and biomarker discovery over the past 20 years to globally study complex proteomes (e.g., plasma). However, very few large-scale longitudinal studies have been carried out using these platforms to establish the analytical variability relative to true biological variability. The purpose of this review is not to cover exhaustively the applications of mass spectrometry to biomarker discovery, but rather to discuss the analytical methods and strategies that have been developed for mass spectrometry-based biomarker-discovery platforms and to place them in the context of the many challenges and opportunities yet to be addressed.

Essential Skills and Knowledge for Troubleshooting E-Resources Access Issues in a Web-Scale Discovery Environment

ERIC Educational Resources Information Center

Carter, Sunshine; Traill, Stacie

2017-01-01

Electronic resource access troubleshooting is familiar work in most libraries. The added complexity introduced when a library implements a web-scale discovery service, however, creates a strong need for well-organized, rigorous training to enable troubleshooting staff to provide the best service possible. This article outlines strategies, tools,…

A Framework for Seamless Interoperation of Heterogeneous Distributed Software Components

DTIC Science & Technology

2005-05-01

interoperability, b) distributed resource discovery, and c) validation of quality requirements. Principles and prototypical systems were created to demonstrate the successful completion of the research.

Adverse Drug Event Discovery Using Biomedical Literature: A Big Data Neural Network Adventure

PubMed Central

Badger, Jonathan; LaRose, Eric; Shirzadi, Ehsan; Mahnke, Andrea; Mayer, John; Ye, Zhan; Page, David; Peissig, Peggy

2017-01-01

Background The study of adverse drug events (ADEs) is a tenured topic in medical literature. In recent years, increasing numbers of scientific articles and health-related social media posts have been generated and shared daily, albeit with very limited use for ADE study and with little known about the content with respect to ADEs. Objective The aim of this study was to develop a big data analytics strategy that mines the content of scientific articles and health-related Web-based social media to detect and identify ADEs. Methods We analyzed the following two data sources: (1) biomedical articles and (2) health-related social media blog posts. We developed an intelligent and scalable text mining solution on big data infrastructures composed of Apache Spark, natural language processing, and machine learning. This was combined with an Elasticsearch No-SQL distributed database to explore and visualize ADEs. Results The accuracy, precision, recall, and area under receiver operating characteristic of the system were 92.7%, 93.6%, 93.0%, and 0.905, respectively, and showed better results in comparison with traditional approaches in the literature. This work not only detected and classified ADE sentences from big data biomedical literature but also scientifically visualized ADE interactions. Conclusions To the best of our knowledge, this work is the first to investigate a big data machine learning strategy for ADE discovery on massive datasets downloaded from PubMed Central and social media. This contribution illustrates possible capacities in big data biomedical text analysis using advanced computational methods with real-time update from new data published on a daily basis. PMID:29222076

Intelligent services for discovery of complex geospatial features from remote sensing imagery

NASA Astrophysics Data System (ADS)

Yue, Peng; Di, Liping; Wei, Yaxing; Han, Weiguo

2013-09-01

Remote sensing imagery has been commonly used by intelligence analysts to discover geospatial features, including complex ones. The overwhelming volume of routine image acquisition requires automated methods or systems for feature discovery instead of manual image interpretation. The methods of extraction of elementary ground features such as buildings and roads from remote sensing imagery have been studied extensively. The discovery of complex geospatial features, however, is still rather understudied. A complex feature, such as a Weapon of Mass Destruction (WMD) proliferation facility, is spatially composed of elementary features (e.g., buildings for hosting fuel concentration machines, cooling towers, transportation roads, and fences). Such spatial semantics, together with thematic semantics of feature types, can be used to discover complex geospatial features. This paper proposes a workflow-based approach for discovery of complex geospatial features that uses geospatial semantics and services. The elementary features extracted from imagery are archived in distributed Web Feature Services (WFSs) and discoverable from a catalogue service. Using spatial semantics among elementary features and thematic semantics among feature types, workflow-based service chains can be constructed to locate semantically-related complex features in imagery. The workflows are reusable and can provide on-demand discovery of complex features in a distributed environment.

Enabling drug discovery project decisions with integrated computational chemistry and informatics

NASA Astrophysics Data System (ADS)

Tsui, Vickie; Ortwine, Daniel F.; Blaney, Jeffrey M.

2017-03-01

Computational chemistry/informatics scientists and software engineers in Genentech Small Molecule Drug Discovery collaborate with experimental scientists in a therapeutic project-centric environment. Our mission is to enable and improve pre-clinical drug discovery design and decisions. Our goal is to deliver timely data, analysis, and modeling to our therapeutic project teams using best-in-class software tools. We describe our strategy, the organization of our group, and our approaches to reach this goal. We conclude with a summary of the interdisciplinary skills required for computational scientists and recommendations for their training.

Surveillance theory applied to virus detection: a case for targeted discovery

USGS Publications Warehouse

Bogich, Tiffany L.; Anthony, Simon J.; Nichols, James D.

2013-01-01

Virus detection and mathematical modeling have gone through rapid developments in the past decade. Both offer new insights into the epidemiology of infectious disease and characterization of future risk; however, modeling has not yet been applied to designing the best surveillance strategies for viral and pathogen discovery. We review recent developments and propose methods to integrate viral and pathogen discovery and mathematical modeling through optimal surveillance theory, arguing for a more targeted approach to novel virus detection guided by the principles of adaptive management and structured decision-making.

Avoiding false discoveries in association studies.

PubMed

Sabatti, Chiara

2007-01-01

We consider the problem of controlling false discoveries in association studies. We assume that the design of the study is adequate so that the "false discoveries" are potentially only because of random chance, not to confounding or other flaws. Under this premise, we review the statistical framework for hypothesis testing and correction for multiple comparisons. We consider in detail the currently accepted strategies in linkage analysis. We then examine the underlying similarities and differences between linkage and association studies and document some of the most recent methodological developments for association mapping.

Genomics and transcriptomics in drug discovery.

PubMed

Dopazo, Joaquin

2014-02-01

The popularization of genomic high-throughput technologies is causing a revolution in biomedical research and, particularly, is transforming the field of drug discovery. Systems biology offers a framework to understand the extensive human genetic heterogeneity revealed by genomic sequencing in the context of the network of functional, regulatory and physical protein-drug interactions. Thus, approaches to find biomarkers and therapeutic targets will have to take into account the complex system nature of the relationships of the proteins with the disease. Pharmaceutical companies will have to reorient their drug discovery strategies considering the human genetic heterogeneity. Consequently, modeling and computational data analysis will have an increasingly important role in drug discovery. Copyright © 2013 Elsevier Ltd. All rights reserved.

Novel dual small-molecule HIV inhibitors: scaffolds and discovery strategies.

PubMed

Song, Anran; Yu, Haiqing; Wang, Changyuan; Zhu, Xingqi; Liu, Kexin; Ma, Xiaodong

2015-01-01

Searching for safe and effective treatments for HIV infection is still a great challenge worldwide in spite of the 27 marketed anti-HIV drugs and the powerful highly active antiretroviral therapy (HAART). As a promising prospect for generation of new HIV therapy drugs, multiple ligands (MDLs) were greatly focused on recently due to their lower toxicity, simplified dosing and patient adherence than single-target drugs. Till now, by disrupting two active sites or steps of HIV replications, a number of HIV dual inhibitors, such as CD4-gssucap120 inhibitors, CXCR4-gp20 inhibitors, RT-CXCR4 inhibitors, RT-protease inhibitors, RT-integrase inhibitors, and RTassociated functions inhibitors have been identified. Generally, these dual inhibitors were discovered mainly through screening approaches and design strategies. Of these compounds, the molecules bearing small skeletons exhibited strong anti-HIV activity and aroused great attention recently. Reviewing the progress of the dual small-molecule HIV inhibitors from the point of view of their scaffolds and discovery strategies will provide valuable information for producing more effective anti-HIV drugs. In this regard, novel dual small-molecule HIV inhibitors were illustrated, and their discovery paradigms as the major contents were also summarized in this manuscript.

From Mollusks to Medicine: A Venomics Approach for the Discovery and Characterization of Therapeutics from Terebridae Peptide Toxins.

PubMed

Verdes, Aida; Anand, Prachi; Gorson, Juliette; Jannetti, Stephen; Kelly, Patrick; Leffler, Abba; Simpson, Danny; Ramrattan, Girish; Holford, Mandë

2016-04-19

Animal venoms comprise a diversity of peptide toxins that manipulate molecular targets such as ion channels and receptors, making venom peptides attractive candidates for the development of therapeutics to benefit human health. However, identifying bioactive venom peptides remains a significant challenge. In this review we describe our particular venomics strategy for the discovery, characterization, and optimization of Terebridae venom peptides, teretoxins. Our strategy reflects the scientific path from mollusks to medicine in an integrative sequential approach with the following steps: (1) delimitation of venomous Terebridae lineages through taxonomic and phylogenetic analyses; (2) identification and classification of putative teretoxins through omics methodologies, including genomics, transcriptomics, and proteomics; (3) chemical and recombinant synthesis of promising peptide toxins; (4) structural characterization through experimental and computational methods; (5) determination of teretoxin bioactivity and molecular function through biological assays and computational modeling; (6) optimization of peptide toxin affinity and selectivity to molecular target; and (7) development of strategies for effective delivery of venom peptide therapeutics. While our research focuses on terebrids, the venomics approach outlined here can be applied to the discovery and characterization of peptide toxins from any venomous taxa.

Strategies to potentiate antimicrobial photoinactivation by overcoming resistant phenotypes†

PubMed Central

Vera, D. Mariano A.; Haynes, Mark H; Ball, Anthony R.; Dai, D. Tianhong; Astrakas, Christos; Kelso, Michael J; Hamblin, Michael R; Tegos, George P.

2012-01-01

Conventional antimicrobial strategies have become increasingly ineffective due to the emergence of multidrug resistance among pathogenic microorganisms. The need to overcome these deficiencies has triggered the exploration of alternative treatments and unconventional approaches towards controlling microbial infections. Photodynamic therapy was originally established as an anti-cancer modality and is currently used in the treatment of age related macular degeneration. The concept of photodynamic inactivation requires cell exposure to light energy, typically wavelengths in the visible region that causes the excitation of photosensitizer molecules either exogenous or endogenous, which results in the production of reactive oxygen species. ROS produce cell inactivation and death through modification of intracellular components. The versatile characteristics of PDT prompted its investigation as an anti-infective discovery platform. Advances in understanding of microbial physiology have shed light on a series of pathways, and phenotypes that serve as putative targets for antimicrobial drug discovery. Investigations of these phenotypic elements in concert with PDT have been reported focused on multidrug efflux systems, biofilms, virulence and pathogenesis determinants. In many instances the results are promising but only preliminary and require further investigation. This review discusses the different antimicrobial PDT strategies and highlights the need for highly informative and comprehensive discovery approaches. PMID:22242675

Characterizing Listener Engagement with Popular Songs Using Large-Scale Music Discovery Data

PubMed Central

Kaneshiro, Blair; Ruan, Feng; Baker, Casey W.; Berger, Jonathan

2017-01-01

Music discovery in everyday situations has been facilitated in recent years by audio content recognition services such as Shazam. The widespread use of such services has produced a wealth of user data, specifying where and when a global audience takes action to learn more about music playing around them. Here, we analyze a large collection of Shazam queries of popular songs to study the relationship between the timing of queries and corresponding musical content. Our results reveal that the distribution of queries varies over the course of a song, and that salient musical events drive an increase in queries during a song. Furthermore, we find that the distribution of queries at the time of a song's release differs from the distribution following a song's peak and subsequent decline in popularity, possibly reflecting an evolution of user intent over the “life cycle” of a song. Finally, we derive insights into the data size needed to achieve consistent query distributions for individual songs. The combined findings of this study suggest that music discovery behavior, and other facets of the human experience of music, can be studied quantitatively using large-scale industrial data. PMID:28386241

Characterizing Listener Engagement with Popular Songs Using Large-Scale Music Discovery Data.

PubMed

Kaneshiro, Blair; Ruan, Feng; Baker, Casey W; Berger, Jonathan

2017-01-01

Music discovery in everyday situations has been facilitated in recent years by audio content recognition services such as Shazam. The widespread use of such services has produced a wealth of user data, specifying where and when a global audience takes action to learn more about music playing around them. Here, we analyze a large collection of Shazam queries of popular songs to study the relationship between the timing of queries and corresponding musical content. Our results reveal that the distribution of queries varies over the course of a song, and that salient musical events drive an increase in queries during a song. Furthermore, we find that the distribution of queries at the time of a song's release differs from the distribution following a song's peak and subsequent decline in popularity, possibly reflecting an evolution of user intent over the "life cycle" of a song. Finally, we derive insights into the data size needed to achieve consistent query distributions for individual songs. The combined findings of this study suggest that music discovery behavior, and other facets of the human experience of music, can be studied quantitatively using large-scale industrial data.

Gene Discovery of Characteristic Metabolic Pathways in the Tea Plant (Camellia sinensis) Using ‘Omics’-Based Network Approaches: A Future Perspective

PubMed Central

Zhang, Shihua; Zhang, Liang; Tai, Yuling; Wang, Xuewen; Ho, Chi-Tang; Wan, Xiaochun

2018-01-01

Characteristic secondary metabolites, including flavonoids, theanine and caffeine, in the tea plant (Camellia sinensis) are the primary sources of the rich flavors, fresh taste, and health benefits of tea. The decoding of genes involved in these characteristic components is still significantly lagging, which lays an obstacle for applied genetic improvement and metabolic engineering. With the popularity of high-throughout transcriptomics and metabolomics, ‘omics’-based network approaches, such as gene co-expression network and gene-to-metabolite network, have emerged as powerful tools for gene discovery of plant-specialized (secondary) metabolism. Thus, it is pivotal to summarize and introduce such system-based strategies in facilitating gene identification of characteristic metabolic pathways in the tea plant (or other plants). In this review, we describe recent advances in transcriptomics and metabolomics for transcript and metabolite profiling, and highlight ‘omics’-based network strategies using successful examples in model and non-model plants. Further, we summarize recent progress in ‘omics’ analysis for gene identification of characteristic metabolites in the tea plant. Limitations of the current strategies are discussed by comparison with ‘omics’-based network approaches. Finally, we demonstrate the potential of introducing such network strategies in the tea plant, with a prospects ending for a promising network discovery of characteristic metabolite genes in the tea plant. PMID:29915604

AM: An Artificial Intelligence Approach to Discovery in Mathematics as Heuristic Search

DTIC Science & Technology

1976-07-01

Artificial Intelligence Approach to Discovery in Mathematics as Heuristic Search by Douglas B. Len-t APPROVED FOR PUBLIC RELEASE; DISTRIBUTION IS UNLIMITED (A...570 AM: An Artificial Intelligence Approach to Discovery in Mathematics as Heuristic Search by Douglas B. Lenat ABSTRACT A program, called "AM", is...While AM’s " approach " to empirical research may be used in other scientific domains, the main limitation (reliance on hindsight) will probably recur

Distributed data mining on grids: services, tools, and applications.

PubMed

Cannataro, Mario; Congiusta, Antonio; Pugliese, Andrea; Talia, Domenico; Trunfio, Paolo

2004-12-01

Data mining algorithms are widely used today for the analysis of large corporate and scientific datasets stored in databases and data archives. Industry, science, and commerce fields often need to analyze very large datasets maintained over geographically distributed sites by using the computational power of distributed and parallel systems. The grid can play a significant role in providing an effective computational support for distributed knowledge discovery applications. For the development of data mining applications on grids we designed a system called Knowledge Grid. This paper describes the Knowledge Grid framework and presents the toolset provided by the Knowledge Grid for implementing distributed knowledge discovery. The paper discusses how to design and implement data mining applications by using the Knowledge Grid tools starting from searching grid resources, composing software and data components, and executing the resulting data mining process on a grid. Some performance results are also discussed.

Intelligent resource discovery using ontology-based resource profiles

NASA Technical Reports Server (NTRS)

Hughes, J. Steven; Crichton, Dan; Kelly, Sean; Crichton, Jerry; Tran, Thuy

2004-01-01

Successful resource discovery across heterogeneous repositories is strongly dependent on the semantic and syntactic homogeneity of the associated resource descriptions. Ideally, resource descriptions are easily extracted from pre-existing standardized sources, expressed using standard syntactic and semantic structures, and managed and accessed within a distributed, flexible, and scaleable software framework.

PolarHub: A Global Hub for Polar Data Discovery

NASA Astrophysics Data System (ADS)

Li, W.

2014-12-01

This paper reports the outcome of a NSF project in developing a large-scale web crawler PolarHub to discover automatically the distributed polar dataset in the format of OGC web services (OWS) in the cyberspace. PolarHub is a machine robot; its goal is to visit as many webpages as possible to find those containing information about polar OWS, extract this information and store it into the backend data repository. This is a very challenging task given huge data volume of webpages on the Web. Three unique features was introduced in PolarHub to make it distinctive from earlier crawler solutions: (1) a multi-task, multi-user, multi-thread support to the crawling tasks; (2) an extensive use of thread pool and Data Access Object (DAO) design patterns to separate persistent data storage and business logic to achieve high extendibility of the crawler tool; (3) a pattern-matching based customizable crawling algorithm to support discovery of multi-type geospatial web services; and (4) a universal and portable client-server communication mechanism combining a server-push and client pull strategies for enhanced asynchronous processing. A series of experiments were conducted to identify the impact of crawling parameters to the overall system performance. The geographical distribution pattern of all PolarHub identified services is also demonstrated. We expect this work to make a major contribution to the field of geospatial information retrieval and geospatial interoperability, to bridge the gap between data provider and data consumer, and to accelerate polar science by enhancing the accessibility and reusability of adequate polar data.

The contribution of 700,000 ORF sequence tags to the definition of the human transcriptome

PubMed Central

Camargo, Anamaria A.; Samaia, Helena P. B.; Dias-Neto, Emmanuel; Simão, Daniel F.; Migotto, Italo A.; Briones, Marcelo R. S.; Costa, Fernando F.; Aparecida Nagai, Maria; Verjovski-Almeida, Sergio; Zago, Marco A.; Andrade, Luis Eduardo C.; Carrer, Helaine; El-Dorry, Hamza F. A.; Espreafico, Enilza M.; Habr-Gama, Angelita; Giannella-Neto, Daniel; Goldman, Gustavo H.; Gruber, Arthur; Hackel, Christine; Kimura, Edna T.; Maciel, Rui M. B.; Marie, Suely K. N.; Martins, Elizabeth A. L.; Nóbrega, Marina P.; Paçó-Larson, Maria Luisa; Pardini, Maria Inês M. C.; Pereira, Gonçalo G.; Pesquero, João Bosco; Rodrigues, Vanderlei; Rogatto, Silvia R.; da Silva, Ismael D. C. G.; Sogayar, Mari C.; Sonati, Maria de Fátima; Tajara, Eloiza H.; Valentini, Sandro R.; Alberto, Fernando L.; Amaral, Maria Elisabete J.; Aneas, Ivy; Arnaldi, Liliane A. T.; de Assis, Angela M.; Bengtson, Mário Henrique; Bergamo, Nadia Aparecida; Bombonato, Vanessa; de Camargo, Maria E. R.; Canevari, Renata A.; Carraro, Dirce M.; Cerutti, Janete M.; Corrêa, Maria Lucia C.; Corrêa, Rosana F. R.; Costa, Maria Cristina R.; Curcio, Cyntia; Hokama, Paula O. M.; Ferreira, Ari J. S.; Furuzawa, Gilberto K.; Gushiken, Tsieko; Ho, Paulo L.; Kimura, Elza; Krieger, José E.; Leite, Luciana C. C.; Majumder, Paromita; Marins, Mozart; Marques, Everaldo R.; Melo, Analy S. A.; Melo, Monica; Mestriner, Carlos Alberto; Miracca, Elisabete C.; Miranda, Daniela C.; Nascimento, Ana Lucia T. O.; Nóbrega, Francisco G.; Ojopi, Élida P. B.; Pandolfi, José Rodrigo C.; Pessoa, Luciana G.; Prevedel, Aline C.; Rahal, Paula; Rainho, Claudia A.; Reis, Eduardo M. R.; Ribeiro, Marcelo L.; da Rós, Nancy; de Sá, Renata G.; Sales, Magaly M.; Sant'anna, Simone Cristina; dos Santos, Mariana L.; da Silva, Aline M.; da Silva, Neusa P.; Silva, Wilson A.; da Silveira, Rosana A.; Sousa, Josane F.; Stecconi, Daniella; Tsukumo, Fernando; Valente, Valéria; Soares, Fernando; Moreira, Eloisa S.; Nunes, Diana N.; Correa, Ricardo G.; Zalcberg, Heloisa; Carvalho, Alex F.; Reis, Luis F. L.; Brentani, Ricardo R.; Simpson, Andrew J. G.; de Souza, Sandro J.

2001-01-01

Open reading frame expressed sequences tags (ORESTES) differ from conventional ESTs by providing sequence data from the central protein coding portion of transcripts. We generated a total of 696,745 ORESTES sequences from 24 human tissues and used a subset of the data that correspond to a set of 15,095 full-length mRNAs as a means of assessing the efficiency of the strategy and its potential contribution to the definition of the human transcriptome. We estimate that ORESTES sampled over 80% of all highly and moderately expressed, and between 40% and 50% of rarely expressed, human genes. In our most thoroughly sequenced tissue, the breast, the 130,000 ORESTES generated are derived from transcripts from an estimated 70% of all genes expressed in that tissue, with an equally efficient representation of both highly and poorly expressed genes. In this respect, we find that the capacity of the ORESTES strategy both for gene discovery and shotgun transcript sequence generation significantly exceeds that of conventional ESTs. The distribution of ORESTES is such that many human transcripts are now represented by a scaffold of partial sequences distributed along the length of each gene product. The experimental joining of the scaffold components, by reverse transcription–PCR, represents a direct route to transcript finishing that may represent a useful alternative to full-length cDNA cloning. PMID:11593022

The contribution of 700,000 ORF sequence tags to the definition of the human transcriptome.

PubMed

Camargo, A A; Samaia, H P; Dias-Neto, E; Simão, D F; Migotto, I A; Briones, M R; Costa, F F; Nagai, M A; Verjovski-Almeida, S; Zago, M A; Andrade, L E; Carrer, H; El-Dorry, H F; Espreafico, E M; Habr-Gama, A; Giannella-Neto, D; Goldman, G H; Gruber, A; Hackel, C; Kimura, E T; Maciel, R M; Marie, S K; Martins, E A; Nobrega, M P; Paco-Larson, M L; Pardini, M I; Pereira, G G; Pesquero, J B; Rodrigues, V; Rogatto, S R; da Silva, I D; Sogayar, M C; Sonati, M F; Tajara, E H; Valentini, S R; Alberto, F L; Amaral, M E; Aneas, I; Arnaldi, L A; de Assis, A M; Bengtson, M H; Bergamo, N A; Bombonato, V; de Camargo, M E; Canevari, R A; Carraro, D M; Cerutti, J M; Correa, M L; Correa, R F; Costa, M C; Curcio, C; Hokama, P O; Ferreira, A J; Furuzawa, G K; Gushiken, T; Ho, P L; Kimura, E; Krieger, J E; Leite, L C; Majumder, P; Marins, M; Marques, E R; Melo, A S; Melo, M B; Mestriner, C A; Miracca, E C; Miranda, D C; Nascimento, A L; Nobrega, F G; Ojopi, E P; Pandolfi, J R; Pessoa, L G; Prevedel, A C; Rahal, P; Rainho, C A; Reis, E M; Ribeiro, M L; da Ros, N; de Sa, R G; Sales, M M; Sant'anna, S C; dos Santos, M L; da Silva, A M; da Silva, N P; Silva, W A; da Silveira, R A; Sousa, J F; Stecconi, D; Tsukumo, F; Valente, V; Soares, F; Moreira, E S; Nunes, D N; Correa, R G; Zalcberg, H; Carvalho, A F; Reis, L F; Brentani, R R; Simpson, A J; de Souza, S J; Melo, M

2001-10-09

Open reading frame expressed sequences tags (ORESTES) differ from conventional ESTs by providing sequence data from the central protein coding portion of transcripts. We generated a total of 696,745 ORESTES sequences from 24 human tissues and used a subset of the data that correspond to a set of 15,095 full-length mRNAs as a means of assessing the efficiency of the strategy and its potential contribution to the definition of the human transcriptome. We estimate that ORESTES sampled over 80% of all highly and moderately expressed, and between 40% and 50% of rarely expressed, human genes. In our most thoroughly sequenced tissue, the breast, the 130,000 ORESTES generated are derived from transcripts from an estimated 70% of all genes expressed in that tissue, with an equally efficient representation of both highly and poorly expressed genes. In this respect, we find that the capacity of the ORESTES strategy both for gene discovery and shotgun transcript sequence generation significantly exceeds that of conventional ESTs. The distribution of ORESTES is such that many human transcripts are now represented by a scaffold of partial sequences distributed along the length of each gene product. The experimental joining of the scaffold components, by reverse transcription-PCR, represents a direct route to transcript finishing that may represent a useful alternative to full-length cDNA cloning.

The Tuberculosis Drug Discovery and Development Pipeline and Emerging Drug Targets

PubMed Central

Mdluli, Khisimuzi; Kaneko, Takushi; Upton, Anna

2015-01-01

The recent accelerated approval for use in extensively drug-resistant and multidrug-resistant-tuberculosis (MDR-TB) of two first-in-class TB drugs, bedaquiline and delamanid, has reinvigorated the TB drug discovery and development field. However, although several promising clinical development programs are ongoing to evaluate new TB drugs and regimens, the number of novel series represented is few. The global early-development pipeline is also woefully thin. To have a chance of achieving the goal of better, shorter, safer TB drug regimens with utility against drug-sensitive and drug-resistant disease, a robust and diverse global TB drug discovery pipeline is key, including innovative approaches that make use of recently acquired knowledge on the biology of TB. Fortunately, drug discovery for TB has resurged in recent years, generating compounds with varying potential for progression into developable leads. In parallel, advances have been made in understanding TB pathogenesis. It is now possible to apply the lessons learned from recent TB hit generation efforts and newly validated TB drug targets to generate the next wave of TB drug leads. Use of currently underexploited sources of chemical matter and lead-optimization strategies may also improve the efficiency of future TB drug discovery. Novel TB drug regimens with shorter treatment durations must target all subpopulations of Mycobacterium tuberculosis existing in an infection, including those responsible for the protracted TB treatment duration. This review summarizes the current TB drug development pipeline and proposes strategies for generating improved hits and leads in the discovery phase that could help achieve this goal. PMID:25635061

Is Open Science the Future of Drug Development?

PubMed

Shaw, Daniel L

2017-03-01

Traditional drug development models are widely perceived as opaque and inefficient, with the cost of research and development continuing to rise even as production of new drugs stays constant. Searching for strategies to improve the drug discovery process, the biomedical research field has begun to embrace open strategies. The resulting changes are starting to reshape the industry. Open science-an umbrella term for diverse strategies that seek external input and public engagement-has become an essential tool with researchers, who are increasingly turning to collaboration, crowdsourcing, data sharing, and open sourcing to tackle some of the most pressing problems in medicine. Notable examples of such open drug development include initiatives formed around malaria and tropical disease. Open practices have found their way into the drug discovery process, from target identification and compound screening to clinical trials. This perspective argues that while open science poses some risks-which include the management of collaboration and the protection of proprietary data-these strategies are, in many cases, the more efficient and ethical way to conduct biomedical research.

Target-decoy Based False Discovery Rate Estimation for Large-scale Metabolite Identification.

PubMed

Wang, Xusheng; Jones, Drew R; Shaw, Timothy I; Cho, Ji-Hoon; Wang, Yuanyuan; Tan, Haiyan; Xie, Boer; Zhou, Suiping; Li, Yuxin; Peng, Junmin

2018-05-23

Metabolite identification is a crucial step in mass spectrometry (MS)-based metabolomics. However, it is still challenging to assess the confidence of assigned metabolites. In this study, we report a novel method for estimating false discovery rate (FDR) of metabolite assignment with a target-decoy strategy, in which the decoys are generated through violating the octet rule of chemistry by adding small odd numbers of hydrogen atoms. The target-decoy strategy was integrated into JUMPm, an automated metabolite identification pipeline for large-scale MS analysis, and was also evaluated with two other metabolomics tools, mzMatch and mzMine 2. The reliability of FDR calculation was examined by false datasets, which were simulated by altering MS1 or MS2 spectra. Finally, we used the JUMPm pipeline coupled with the target-decoy strategy to process unlabeled and stable-isotope labeled metabolomic datasets. The results demonstrate that the target-decoy strategy is a simple and effective method for evaluating the confidence of high-throughput metabolite identification.

Discovery of Novel Drugs to Improve Bone Health in Neurofibromatosis Type 1: The Wnt/Beta-Catenin Pathway in Fracture Repair and Pseudarthrosis

DTIC Science & Technology

2015-08-01

AWARD NUMBER: W81XWH-13-1-0113 TITLE: Discovery of Novel Drugs To Improve Bone Health in Neurofibromatosis Type 1: The Wnt/Beta-Catenin...Discovery of Novel Drugs To Improve Bone Health in Neurofibromatosis Type 1: The Wnt/Beta-Catenin Pathway in Fracture Repair and Pseudarthrosis 5a...AVAILABILITY STATEMENT Approved for Public Release; Distribution Unlimited 13. SUPPLEMENTARY NOTES 14. ABSTRACT Patients with Neurofibromatosis (NF1

The re-emergence of natural products for drug discovery in the genomics era.

PubMed

Harvey, Alan L; Edrada-Ebel, RuAngelie; Quinn, Ronald J

2015-02-01

Natural products have been a rich source of compounds for drug discovery. However, their use has diminished in the past two decades, in part because of technical barriers to screening natural products in high-throughput assays against molecular targets. Here, we review strategies for natural product screening that harness the recent technical advances that have reduced these barriers. We also assess the use of genomic and metabolomic approaches to augment traditional methods of studying natural products, and highlight recent examples of natural products in antimicrobial drug discovery and as inhibitors of protein-protein interactions. The growing appreciation of functional assays and phenotypic screens may further contribute to a revival of interest in natural products for drug discovery.

A unified approach to computational drug discovery.

PubMed

Tseng, Chih-Yuan; Tuszynski, Jack

2015-11-01

It has been reported that a slowdown in the development of new medical therapies is affecting clinical outcomes. The FDA has thus initiated the Critical Path Initiative project investigating better approaches. We review the current strategies in drug discovery and focus on the advantages of the maximum entropy method being introduced in this area. The maximum entropy principle is derived from statistical thermodynamics and has been demonstrated to be an inductive inference tool. We propose a unified method to drug discovery that hinges on robust information processing using entropic inductive inference. Increasingly, applications of maximum entropy in drug discovery employ this unified approach and demonstrate the usefulness of the concept in the area of pharmaceutical sciences. Copyright © 2015. Published by Elsevier Ltd.

WebMOTIFS: automated discovery, filtering and scoring of DNA sequence motifs using multiple programs and Bayesian approaches

PubMed Central

Romer, Katherine A.; Kayombya, Guy-Richard; Fraenkel, Ernest

2007-01-01

WebMOTIFS provides a web interface that facilitates the discovery and analysis of DNA-sequence motifs. Several studies have shown that the accuracy of motif discovery can be significantly improved by using multiple de novo motif discovery programs and using randomized control calculations to identify the most significant motifs or by using Bayesian approaches. WebMOTIFS makes it easy to apply these strategies. Using a single submission form, users can run several motif discovery programs and score, cluster and visualize the results. In addition, the Bayesian motif discovery program THEME can be used to determine the class of transcription factors that is most likely to regulate a set of sequences. Input can be provided as a list of gene or probe identifiers. Used with the default settings, WebMOTIFS accurately identifies biologically relevant motifs from diverse data in several species. WebMOTIFS is freely available at http://fraenkel.mit.edu/webmotifs. PMID:17584794

Viral Determinants and Vector Competence of Zika Virus Transmission.

PubMed

Tham, Hong-Wai; Balasubramaniam, Vinod; Ooi, Man K; Chew, Miaw-Fang

2018-01-01

Zika virus (ZIKV) has emerged as a new global health threat. Since its first discovery in Zika forest in Uganda, this virus has been isolated from several mosquito species, including Aedes aegypti and Aedes albopictus . The geographical distribution of these mosquito species across tropical and subtropical regions has led to several outbreaks, including the recent pandemic in Brazil, followed by the Pacific islands and other areas of North and South America. This has gained attention of the scientific community to elucidate the epidemiology and transmission of ZIKV. Despite its strong attention on clinical aspects for healthcare professionals, the relationships between ZIKV and its principal vectors, A. aegypti and A. albopictus , have not gained substantial interest in the scientific research community. As such, this review aims to summarize the current knowledge on ZIKV tropism and some important mechanisms which may be employed by the virus for effective strategies on viral survival in mosquitoes. In addition, this review identifies the areas of research that should be placed attention to, for which to be exploited for novel mosquito control strategies.

Viral Determinants and Vector Competence of Zika Virus Transmission

PubMed Central

Tham, Hong-Wai; Balasubramaniam, Vinod; Ooi, Man K.; Chew, Miaw-Fang

2018-01-01

Zika virus (ZIKV) has emerged as a new global health threat. Since its first discovery in Zika forest in Uganda, this virus has been isolated from several mosquito species, including Aedes aegypti and Aedes albopictus. The geographical distribution of these mosquito species across tropical and subtropical regions has led to several outbreaks, including the recent pandemic in Brazil, followed by the Pacific islands and other areas of North and South America. This has gained attention of the scientific community to elucidate the epidemiology and transmission of ZIKV. Despite its strong attention on clinical aspects for healthcare professionals, the relationships between ZIKV and its principal vectors, A. aegypti and A. albopictus, have not gained substantial interest in the scientific research community. As such, this review aims to summarize the current knowledge on ZIKV tropism and some important mechanisms which may be employed by the virus for effective strategies on viral survival in mosquitoes. In addition, this review identifies the areas of research that should be placed attention to, for which to be exploited for novel mosquito control strategies. PMID:29875751

From Protein Structure to Small-Molecules: Recent Advances and Applications to Fragment-Based Drug Discovery.

PubMed

Ferreira, Leonardo G; Andricopulo, Adriano D

2017-01-01

Fragment-based drug discovery (FBDD) is a broadly used strategy in structure-guided ligand design, whereby low-molecular weight hits move from lead-like to drug-like compounds. Over the past 15 years, an increasingly important role of the integration of these strategies into industrial and academic research platforms has been successfully established, allowing outstanding contributions to drug discovery. One important factor for the current prominence of FBDD is the better coverage of the chemical space provided by fragment-like libraries. The development of the field relies on two features: (i) the growing number of structurally characterized drug targets and (ii) the enormous chemical diversity available for experimental and virtual screenings. Indeed, fragment-based campaigns have contributed to address major challenges in lead optimization, such as the appropriate physicochemical profile of clinical candidates. This perspective paper outlines the usefulness and applications of FBDD approaches in medicinal chemistry and drug design. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Chronicles in drug discovery.

PubMed

Davies, Shelley L; Ferrer, Elisa; Moral, Maria Angels

2006-06-01

Chronicles in Drug Discovery features special interest reports on advances in drug discovery. This month we highlight new options to prevent oral mucositis, a treatment-limiting adverse effect of chemotherapy. Studies are currently focusing on mechanism-based therapies to prevent or repair DNA damage to epithelial and submucosal cells and the cascade or events that follow to cause tissue damage or analgesics to ease the associated oral cavity pain. Therapeutic limitations also exist for the use of the highly effective antibiotic gentamicin, as it evokes acute renal failure. Mechanistic investigations have shed some light on potential targets: the kallikreins, peroxynitrite-related pathways, superoxide production and the accumulation of aminoglycosides. New antibiotic strategies for trachoma, the leading cause of preventable blindness, are also explored along with studies to aid the development of vaccine candidates. Finally, we discuss the utility of allosteric-potentiating ligands to modulate nicotinic acetylcholine receptors, mimicking the reward/addictive effects of nicotine, as potential strategies for smoking cessation. (c) 2006 Prous Science. All rights reserved.

New strategy for drug discovery by large-scale association analysis of molecular networks of different species.

PubMed

Zhang, Bo; Fu, Yingxue; Huang, Chao; Zheng, Chunli; Wu, Ziyin; Zhang, Wenjuan; Yang, Xiaoyan; Gong, Fukai; Li, Yuerong; Chen, Xiaoyu; Gao, Shuo; Chen, Xuetong; Li, Yan; Lu, Aiping; Wang, Yonghua

2016-02-25

The development of modern omics technology has not significantly improved the efficiency of drug development. Rather precise and targeted drug discovery remains unsolved. Here a large-scale cross-species molecular network association (CSMNA) approach for targeted drug screening from natural sources is presented. The algorithm integrates molecular network omics data from humans and 267 plants and microbes, establishing the biological relationships between them and extracting evolutionarily convergent chemicals. This technique allows the researcher to assess targeted drugs for specific human diseases based on specific plant or microbe pathways. In a perspective validation, connections between the plant Halliwell-Asada (HA) cycle and the human Nrf2-ARE pathway were verified and the manner by which the HA cycle molecules act on the human Nrf2-ARE pathway as antioxidants was determined. This shows the potential applicability of this approach in drug discovery. The current method integrates disparate evolutionary species into chemico-biologically coherent circuits, suggesting a new cross-species omics analysis strategy for rational drug development.

Metabolic Clustering Analysis as a Strategy for Compound Selection in the Drug Discovery Pipeline for Leishmaniasis.

PubMed

Armitage, Emily G; Godzien, Joanna; Peña, Imanol; López-Gonzálvez, Ángeles; Angulo, Santiago; Gradillas, Ana; Alonso-Herranz, Vanesa; Martín, Julio; Fiandor, Jose M; Barrett, Michael P; Gabarro, Raquel; Barbas, Coral

2018-05-18

A lack of viable hits, increasing resistance, and limited knowledge on mode of action is hindering drug discovery for many diseases. To optimize prioritization and accelerate the discovery process, a strategy to cluster compounds based on more than chemical structure is required. We show the power of metabolomics in comparing effects on metabolism of 28 different candidate treatments for Leishmaniasis (25 from the GSK Leishmania box, two analogues of Leishmania box series, and amphotericin B as a gold standard treatment), tested in the axenic amastigote form of Leishmania donovani. Capillary electrophoresis-mass spectrometry was applied to identify the metabolic profile of Leishmania donovani, and principal components analysis was used to cluster compounds on potential mode of action, offering a medium throughput screening approach in drug selection/prioritization. The comprehensive and sensitive nature of the data has also made detailed effects of each compound obtainable, providing a resource to assist in further mechanistic studies and prioritization of these compounds for the development of new antileishmanial drugs.

Reception Learning and Self-Discovery Learning in Histology: Students' Perceptions and Their Implications for Assessing the Effectiveness of Different Learning Modalities

ERIC Educational Resources Information Center

Campos-Sanchez, Antonio; Martin-Piedra, Miguel-Angel; Carriel, Victor; Gonzalez-Andrades, Miguel; Garzon, Ingrid; Sanchez-Quevedo, Maria-Carmen; Alaminos, Miguel

2012-01-01

Two questionnaires were used to investigate students' perceptions of their motivation to opt for reception learning (RL) or self-discovery learning (SDL) in histology and their choices of complementary learning strategies (CLS). The results demonstrated that the motivation to attend RL sessions was higher than the motivation to attend SDL to gain…

Computational neuropharmacology: dynamical approaches in drug discovery.

PubMed

Aradi, Ildiko; Erdi, Péter

2006-05-01

Computational approaches that adopt dynamical models are widely accepted in basic and clinical neuroscience research as indispensable tools with which to understand normal and pathological neuronal mechanisms. Although computer-aided techniques have been used in pharmaceutical research (e.g. in structure- and ligand-based drug design), the power of dynamical models has not yet been exploited in drug discovery. We suggest that dynamical system theory and computational neuroscience--integrated with well-established, conventional molecular and electrophysiological methods--offer a broad perspective in drug discovery and in the search for novel targets and strategies for the treatment of neurological and psychiatric diseases.

Developing a distributed HTML5-based search engine for geospatial resource discovery

NASA Astrophysics Data System (ADS)

ZHOU, N.; XIA, J.; Nebert, D.; Yang, C.; Gui, Z.; Liu, K.

2013-12-01

With explosive growth of data, Geospatial Cyberinfrastructure(GCI) components are developed to manage geospatial resources, such as data discovery and data publishing. However, the efficiency of geospatial resources discovery is still challenging in that: (1) existing GCIs are usually developed for users of specific domains. Users may have to visit a number of GCIs to find appropriate resources; (2) The complexity of decentralized network environment usually results in slow response and pool user experience; (3) Users who use different browsers and devices may have very different user experiences because of the diversity of front-end platforms (e.g. Silverlight, Flash or HTML). To address these issues, we developed a distributed and HTML5-based search engine. Specifically, (1)the search engine adopts a brokering approach to retrieve geospatial metadata from various and distributed GCIs; (2) the asynchronous record retrieval mode enhances the search performance and user interactivity; (3) the search engine based on HTML5 is able to provide unified access capabilities for users with different devices (e.g. tablet and smartphone).

Distributed Drug Discovery, Part 2: Global Rehearsal of Alkylating Agents for the Synthesis of Resin-Bound Unnatural Amino Acids and Virtual D3 Catalog Construction

PubMed Central

2008-01-01

Distributed Drug Discovery (D3) proposes solving large drug discovery problems by breaking them into smaller units for processing at multiple sites. A key component of the synthetic and computational stages of D3 is the global rehearsal of prospective reagents and their subsequent use in the creation of virtual catalogs of molecules accessible by simple, inexpensive combinatorial chemistry. The first section of this article documents the feasibility of the synthetic component of Distributed Drug Discovery. Twenty-four alkylating agents were rehearsed in the United States, Poland, Russia, and Spain, for their utility in the synthesis of resin-bound unnatural amino acids 1, key intermediates in many combinatorial chemistry procedures. This global reagent rehearsal, coupled to virtual library generation, increases the likelihood that any member of that virtual library can be made. It facilitates the realistic integration of worldwide virtual D3 catalog computational analysis with synthesis. The second part of this article describes the creation of the first virtual D3 catalog. It reports the enumeration of 24 416 acylated unnatural amino acids 5, assembled from lists of either rehearsed or well-precedented alkylating and acylating reagents, and describes how the resulting catalog can be freely accessed, searched, and downloaded by the scientific community. PMID:19105725

Modular, Antibody-free Time-Resolved LRET Kinase Assay Enabled by Quantum Dots and Tb3+-sensitizing Peptides

NASA Astrophysics Data System (ADS)

Cui, Wei; Parker, Laurie L.

2016-07-01

Fluorescent drug screening assays are essential for tyrosine kinase inhibitor discovery. Here we demonstrate a flexible, antibody-free TR-LRET kinase assay strategy that is enabled by the combination of streptavidin-coated quantum dot (QD) acceptors and biotinylated, Tb3+ sensitizing peptide donors. By exploiting the spectral features of Tb3+ and QD, and the high binding affinity of the streptavidin-biotin interaction, we achieved multiplexed detection of kinase activity in a modular fashion without requiring additional covalent labeling of each peptide substrate. This strategy is compatible with high-throughput screening, and should be adaptable to the rapidly changing workflows and targets involved in kinase inhibitor discovery.

Refining the chemical toolbox to be fit for educational and practical purpose for drug discovery in the 21st Century.

PubMed

Lolli, Marco; Narramore, Sarah; Fishwick, Colin W G; Pors, Klaus

2015-08-01

We live in a time where exploration and generation of new knowledge is occurring on a colossal scale. Medicinal chemists have traditionally taken key roles in drug discovery; however, the many unmet medical demands in the healthcare sector emphasise the need to evolve the medicinal chemistry discipline. To rise to the challenges in the 21st Century there is a necessity to refine the chemical toolbox for educational and practical reasons. This review proposes modern strategies that are beneficial to teaching in academia but are also important reminders of strategies that can potentially lead to better drugs. Copyright © 2015 Elsevier Ltd. All rights reserved.

Fragment Based Strategies for Discovery of Novel HIV-1 Reverse Transcriptase and Integrase Inhibitors.

PubMed

Latham, Catherine F; La, Jennifer; Tinetti, Ricky N; Chalmers, David K; Tachedjian, Gilda

2016-01-01

Human immunodeficiency virus (HIV) remains a global health problem. While combined antiretroviral therapy has been successful in controlling the virus in patients, HIV can develop resistance to drugs used for treatment, rendering available drugs less effective and limiting treatment options. Initiatives to find novel drugs for HIV treatment are ongoing, although traditional drug design approaches often focus on known binding sites for inhibition of established drug targets like reverse transcriptase and integrase. These approaches tend towards generating more inhibitors in the same drug classes already used in the clinic. Lack of diversity in antiretroviral drug classes can result in limited treatment options, as cross-resistance can emerge to a whole drug class in patients treated with only one drug from that class. A fresh approach in the search for new HIV-1 drugs is fragment-based drug discovery (FBDD), a validated strategy for drug discovery based on using smaller libraries of low molecular weight molecules (<300 Da) screened using primarily biophysical assays. FBDD is aimed at not only finding novel drug scaffolds, but also probing the target protein to find new, often allosteric, inhibitory binding sites. Several fragment-based strategies have been successful in identifying novel inhibitory sites or scaffolds for two proven drug targets for HIV-1, reverse transcriptase and integrase. While any FBDD-generated HIV-1 drugs have yet to enter the clinic, recent FBDD initiatives against these two well-characterised HIV-1 targets have reinvigorated antiretroviral drug discovery and the search for novel classes of HIV-1 drugs.

Mass spectrometry-driven drug discovery for development of herbal medicine.

PubMed

Zhang, Aihua; Sun, Hui; Wang, Xijun

2018-05-01

Herbal medicine (HM) has made a major contribution to the drug discovery process with regard to identifying products compounds. Currently, more attention has been focused on drug discovery from natural compounds of HM. Despite the rapid advancement of modern analytical techniques, drug discovery is still a difficult and lengthy process. Fortunately, mass spectrometry (MS) can provide us with useful structural information for drug discovery, has been recognized as a sensitive, rapid, and high-throughput technology for advancing drug discovery from HM in the post-genomic era. It is essential to develop an efficient, high-quality, high-throughput screening method integrated with an MS platform for early screening of candidate drug molecules from natural products. We have developed a new chinmedomics strategy reliant on MS that is capable of capturing the candidate molecules, facilitating their identification of novel chemical structures in the early phase; chinmedomics-guided natural product discovery based on MS may provide an effective tool that addresses challenges in early screening of effective constituents of herbs against disease. This critical review covers the use of MS with related techniques and methodologies for natural product discovery, biomarker identification, and determination of mechanisms of action. It also highlights high-throughput chinmedomics screening methods suitable for lead compound discovery illustrated by recent successes. © 2016 Wiley Periodicals, Inc.

An Automated Peak Identification/Calibration Procedure for High-Dimensional Protein Measures From Mass Spectrometers.

PubMed

Yasui, Yutaka; McLerran, Dale; Adam, Bao-Ling; Winget, Marcy; Thornquist, Mark; Feng, Ziding

2003-01-01

Discovery of "signature" protein profiles that distinguish disease states (eg, malignant, benign, and normal) is a key step towards translating recent advancements in proteomic technologies into clinical utilities. Protein data generated from mass spectrometers are, however, large in size and have complex features due to complexities in both biological specimens and interfering biochemical/physical processes of the measurement procedure. Making sense out of such high-dimensional complex data is challenging and necessitates the use of a systematic data analytic strategy. We propose here a data processing strategy for two major issues in the analysis of such mass-spectrometry-generated proteomic data: (1) separation of protein "signals" from background "noise" in protein intensity measurements and (2) calibration of protein mass/charge measurements across samples. We illustrate the two issues and the utility of the proposed strategy using data from a prostate cancer biomarker discovery project as an example.

Molecular basis of high viscosity in concentrated antibody solutions: Strategies for high concentration drug product development.

PubMed

Tomar, Dheeraj S; Kumar, Sandeep; Singh, Satish K; Goswami, Sumit; Li, Li

2016-01-01

Effective translation of breakthrough discoveries into innovative products in the clinic requires proactive mitigation or elimination of several drug development challenges. These challenges can vary depending upon the type of drug molecule. In the case of therapeutic antibody candidates, a commonly encountered challenge is high viscosity of the concentrated antibody solutions. Concentration-dependent viscosity behaviors of mAbs and other biologic entities may depend on pairwise and higher-order intermolecular interactions, non-native aggregation, and concentration-dependent fluctuations of various antibody regions. This article reviews our current understanding of molecular origins of viscosity behaviors of antibody solutions. We discuss general strategies and guidelines to select low viscosity candidates or optimize lead candidates for lower viscosity at early drug discovery stages. Moreover, strategies for formulation optimization and excipient design are also presented for candidates already in advanced product development stages. Potential future directions for research in this field are also explored.

Qualitative and quantitative mass spectrometry imaging of drugs and metabolites in tissue at therapeutic levels.

PubMed

Sun, Na; Walch, Axel

2013-08-01

Mass spectrometry imaging (MSI) is a rapidly evolving technology that yields qualitative and quantitative distribution maps of small pharmaceutical-active molecules and their metabolites in tissue sections in situ. The simplicity, high sensitivity and ability to provide comprehensive spatial distribution maps of different classes of biomolecules make MSI a valuable tool to complement histopathology for diagnostics and biomarker discovery. In this review, qualitative and quantitative MSI of drugs and metabolites in tissue at therapeutic levels are discussed and the impact of this technique in drug discovery and clinical research is highlighted.

Modeling the Cerebellar Microcircuit: New Strategies for a Long-Standing Issue.

PubMed

D'Angelo, Egidio; Antonietti, Alberto; Casali, Stefano; Casellato, Claudia; Garrido, Jesus A; Luque, Niceto Rafael; Mapelli, Lisa; Masoli, Stefano; Pedrocchi, Alessandra; Prestori, Francesca; Rizza, Martina Francesca; Ros, Eduardo

2016-01-01

The cerebellar microcircuit has been the work bench for theoretical and computational modeling since the beginning of neuroscientific research. The regular neural architecture of the cerebellum inspired different solutions to the long-standing issue of how its circuitry could control motor learning and coordination. Originally, the cerebellar network was modeled using a statistical-topological approach that was later extended by considering the geometrical organization of local microcircuits. However, with the advancement in anatomical and physiological investigations, new discoveries have revealed an unexpected richness of connections, neuronal dynamics and plasticity, calling for a change in modeling strategies, so as to include the multitude of elementary aspects of the network into an integrated and easily updatable computational framework. Recently, biophysically accurate "realistic" models using a bottom-up strategy accounted for both detailed connectivity and neuronal non-linear membrane dynamics. In this perspective review, we will consider the state of the art and discuss how these initial efforts could be further improved. Moreover, we will consider how embodied neurorobotic models including spiking cerebellar networks could help explaining the role and interplay of distributed forms of plasticity. We envisage that realistic modeling, combined with closed-loop simulations, will help to capture the essence of cerebellar computations and could eventually be applied to neurological diseases and neurorobotic control systems.

Modeling the Cerebellar Microcircuit: New Strategies for a Long-Standing Issue

PubMed Central

D’Angelo, Egidio; Antonietti, Alberto; Casali, Stefano; Casellato, Claudia; Garrido, Jesus A.; Luque, Niceto Rafael; Mapelli, Lisa; Masoli, Stefano; Pedrocchi, Alessandra; Prestori, Francesca; Rizza, Martina Francesca; Ros, Eduardo

2016-01-01

The cerebellar microcircuit has been the work bench for theoretical and computational modeling since the beginning of neuroscientific research. The regular neural architecture of the cerebellum inspired different solutions to the long-standing issue of how its circuitry could control motor learning and coordination. Originally, the cerebellar network was modeled using a statistical-topological approach that was later extended by considering the geometrical organization of local microcircuits. However, with the advancement in anatomical and physiological investigations, new discoveries have revealed an unexpected richness of connections, neuronal dynamics and plasticity, calling for a change in modeling strategies, so as to include the multitude of elementary aspects of the network into an integrated and easily updatable computational framework. Recently, biophysically accurate “realistic” models using a bottom-up strategy accounted for both detailed connectivity and neuronal non-linear membrane dynamics. In this perspective review, we will consider the state of the art and discuss how these initial efforts could be further improved. Moreover, we will consider how embodied neurorobotic models including spiking cerebellar networks could help explaining the role and interplay of distributed forms of plasticity. We envisage that realistic modeling, combined with closed-loop simulations, will help to capture the essence of cerebellar computations and could eventually be applied to neurological diseases and neurorobotic control systems. PMID:27458345

Content Management Middleware for the Support of Distributed Teaching

ERIC Educational Resources Information Center

Tsalapatas, Hariklia; Stav, John B.; Kalantzis, Christos

2004-01-01

eCMS is a web-based federated content management system for the support of distributed teaching based on an open, distributed middleware architecture for the publication, discovery, retrieval, and integration of educational material. The infrastructure supports the management of both standalone material and structured courses, as well as the…

A Non-parametric Cutout Index for Robust Evaluation of Identified Proteins*

PubMed Central

Serang, Oliver; Paulo, Joao; Steen, Hanno; Steen, Judith A.

2013-01-01

This paper proposes a novel, automated method for evaluating sets of proteins identified using mass spectrometry. The remaining peptide-spectrum match score distributions of protein sets are compared to an empirical absent peptide-spectrum match score distribution, and a Bayesian non-parametric method reminiscent of the Dirichlet process is presented to accurately perform this comparison. Thus, for a given protein set, the process computes the likelihood that the proteins identified are correctly identified. First, the method is used to evaluate protein sets chosen using different protein-level false discovery rate (FDR) thresholds, assigning each protein set a likelihood. The protein set assigned the highest likelihood is used to choose a non-arbitrary protein-level FDR threshold. Because the method can be used to evaluate any protein identification strategy (and is not limited to mere comparisons of different FDR thresholds), we subsequently use the method to compare and evaluate multiple simple methods for merging peptide evidence over replicate experiments. The general statistical approach can be applied to other types of data (e.g. RNA sequencing) and generalizes to multivariate problems. PMID:23292186

Leveraging ecological theory to guide natural product discovery.

PubMed

Smanski, Michael J; Schlatter, Daniel C; Kinkel, Linda L

2016-03-01

Technological improvements have accelerated natural product (NP) discovery and engineering to the point that systematic genome mining for new molecules is on the horizon. NP biosynthetic potential is not equally distributed across organisms, environments, or microbial life histories, but instead is enriched in a number of prolific clades. Also, NPs are not equally abundant in nature; some are quite common and others markedly rare. Armed with this knowledge, random 'fishing expeditions' for new NPs are increasingly harder to justify. Understanding the ecological and evolutionary pressures that drive the non-uniform distribution of NP biosynthesis provides a rational framework for the targeted isolation of strains enriched in new NP potential. Additionally, ecological theory leads to testable hypotheses regarding the roles of NPs in shaping ecosystems. Here we review several recent strain prioritization practices and discuss the ecological and evolutionary underpinnings for each. Finally, we offer perspectives on leveraging microbial ecology and evolutionary biology for future NP discovery.

Actinomycetes: still a source of novel antibiotics.

PubMed

Genilloud, Olga

2017-10-18

Covering: 2006 to 2017Actinomycetes have been, for decades, one of the most important sources for the discovery of new antibiotics with an important number of drugs and analogs successfully introduced in the market and still used today in clinical practice. The intensive antibacterial discovery effort that generated the large number of highly potent broad-spectrum antibiotics, has seen a dramatic decline in the large pharma industry in the last two decades resulting in a lack of new classes of antibiotics with novel mechanisms of action reaching the clinic. Whereas the decline in the number of new chemical scaffolds and the rediscovery problem of old known molecules has become a hurdle for industrial natural products discovery programs, new actinomycetes compounds and leads have continued to be discovered and developed to the preclinical stages. Actinomycetes are still one of the most important sources of chemical diversity and a reservoir to mine for novel structures that is requiring the integration of diverse disciplines. These can range from novel strategies to isolate species previously not cultivated, innovative whole cell screening approaches and on-site analytical detection and dereplication tools for novel compounds, to in silico biosynthetic predictions from whole gene sequences and novel engineered heterologous expression, that have inspired the isolation of new NPs and shown their potential application in the discovery of novel antibiotics. This review will address the discovery of antibiotics from actinomycetes from two different perspectives including: (1) an update of the most important antibiotics that have only reached the clinical development in the recent years despite their early discovery, and (2) an overview of the most recent classes of antibiotics described from 2006 to 2017 in the framework of the different strategies employed to untap novel compounds previously overlooked with traditional approaches.

Discovery of small molecule inhibitors of the Wnt/β-catenin signaling pathway by targeting β-catenin/Tcf4 interactions.

PubMed

Yan, Maocai; Li, Guanqun; An, Jing

2017-06-01

The Wnt/β-catenin signaling pathway typically shows aberrant activation in various cancer cells, especially colorectal cancer cells. This signaling pathway regulates the expression of a variety of tumor-related proteins, including c-myc and cyclin D1, and plays essential roles in tumorigenesis and in the development of many cancers. Small molecules that block the interactions between β-catenin and Tcf4, a downstream stage of activation of the Wnt/β-catenin signaling pathway, could efficiently cut off this signal transduction and thereby act as a novel class of anticancer drugs. This paper reviews the currently reported inhibitors that target β-catenin/Tcf4 interactions, focusing on the discovery approaches taken in the design of these inhibitors and their bioactivities. A brief perspective is then shared on the future discovery and development of this class of inhibitors. Impact statement This mini-review summarized the current knowledge of inhibitors of interactions of beta-catenin/Tcf4 published to date according to their discovery approaches, and discussed their in vitro and in vivo activities, selectivities, and pharmacokinetic properties. Several reviews presently available now in this field describe modulators of the Wnt/beta-catenin pathway, but are generally focused on the bioactivities of these inhibitors. By contrast, this review focused on the drug discovery approaches taken in identifying these types of inhibitors and provided our perspective on further strategies for future drug discoveries. This review also integrated many recently published and important works on highly selective inhibitors as well as rational drug design. We believe that the findings and strategies summarized in this review have broad implications and will be of interest throughout the biochemical and pharmaceutical research community.

Adverse Drug Event Discovery Using Biomedical Literature: A Big Data Neural Network Adventure.

PubMed

P Tafti, Ahmad; Badger, Jonathan; LaRose, Eric; Shirzadi, Ehsan; Mahnke, Andrea; Mayer, John; Ye, Zhan; Page, David; Peissig, Peggy

2017-12-08

The study of adverse drug events (ADEs) is a tenured topic in medical literature. In recent years, increasing numbers of scientific articles and health-related social media posts have been generated and shared daily, albeit with very limited use for ADE study and with little known about the content with respect to ADEs. The aim of this study was to develop a big data analytics strategy that mines the content of scientific articles and health-related Web-based social media to detect and identify ADEs. We analyzed the following two data sources: (1) biomedical articles and (2) health-related social media blog posts. We developed an intelligent and scalable text mining solution on big data infrastructures composed of Apache Spark, natural language processing, and machine learning. This was combined with an Elasticsearch No-SQL distributed database to explore and visualize ADEs. The accuracy, precision, recall, and area under receiver operating characteristic of the system were 92.7%, 93.6%, 93.0%, and 0.905, respectively, and showed better results in comparison with traditional approaches in the literature. This work not only detected and classified ADE sentences from big data biomedical literature but also scientifically visualized ADE interactions. To the best of our knowledge, this work is the first to investigate a big data machine learning strategy for ADE discovery on massive datasets downloaded from PubMed Central and social media. This contribution illustrates possible capacities in big data biomedical text analysis using advanced computational methods with real-time update from new data published on a daily basis. ©Ahmad P Tafti, Jonathan Badger, Eric LaRose, Ehsan Shirzadi, Andrea Mahnke, John Mayer, Zhan Ye, David Page, Peggy Peissig. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 08.12.2017.

Isomer-specific profiling of N-glycans derived from human serum for potential biomarker discovery in pancreatic cancer.

PubMed

Liu, Yufei; Wang, Chang; Wang, Ran; Wu, Yike; Zhang, Liang; Liu, Bi-Feng; Cheng, Liming; Liu, Xin

2018-06-15

Glycosylation is one of the most important post-translational modifications of protein. Recently, global profiling of human serum glycomics has become a noninvasive method for cancer-related biomarker discovery and many studies have focused on compositional glycan profiling. In contrast, structure-specific glycan profiling may provide more potential biomarkers with higher specificity than compositional profiling. In this work, N-glycans released from human serum were neutralized with methylamine and reduced by ammonia-borane complex prior to profiling using nanoLC-ESI-MS with porous graphitized carbon (PGC) and relative abundances of over 280 isomers were compared between pancreatic cancer (PC) cases (n = 32) and healthy controls (n = 32). Statistical analysis identified 25 specific-isomeric biomarkers with significant differences (p-value < 0.05). ROC and PCA analysis were performed to assess the potential biomarkers which were identified as being significantly altered in cancer. The AUCs of the significantly changed specific-isomers were ranging from 0.712 to 0.949. In addition, with the combination of all potential biomarkers, a higher AUC of 0.976 with sensitivity (93.5%) and specificity (90.6%) was obtained. Overall, the proposed strategy coupled to relative quantitative analysis of isomeric glycans make it possible to discover new biomarkers for the diagnosis of PC. Pancreatic cancer (PC) has a poor prognosis with a five-year survival rate <5%. Therefore, a strategy for accurate diagnosis of PC is indeed required. In this paper, a dual-derivatized strategy for structure-specific glycan profiling has been used and according to our best knowledge, this is the first application of this strategy for PC biomarker discovery, in which the separation, identification and relative quantification of isomeric glycans can be simultaneously obtained. In addition, by in-depth analysis of isomeric glycans, the full description of the stereo- and region- diversity of glycans can also be achieved, which might provide more potential information for PC biomarker discovery. Copyright © 2018 Elsevier B.V. All rights reserved.

In silico mining and PCR-based approaches to transcription factor discovery in non-model plants: gene discovery of the WRKY transcription factors in conifers.

PubMed

Liu, Jun-Jun; Xiang, Yu

2011-01-01

WRKY transcription factors are key regulators of numerous biological processes in plant growth and development, as well as plant responses to abiotic and biotic stresses. Research on biological functions of plant WRKY genes has focused in the past on model plant species or species with largely characterized transcriptomes. However, a variety of non-model plants, such as forest conifers, are essential as feed, biofuel, and wood or for sustainable ecosystems. Identification of WRKY genes in these non-model plants is equally important for understanding the evolutionary and function-adaptive processes of this transcription factor family. Because of limited genomic information, the rarity of regulatory gene mRNAs in transcriptomes, and the sequence divergence to model organism genes, identification of transcription factors in non-model plants using methods similar to those generally used for model plants is difficult. This chapter describes a gene family discovery strategy for identification of WRKY transcription factors in conifers by a combination of in silico-based prediction and PCR-based experimental approaches. Compared to traditional cDNA library screening or EST sequencing at transcriptome scales, this integrated gene discovery strategy provides fast, simple, reliable, and specific methods to unveil the WRKY gene family at both genome and transcriptome levels in non-model plants.

Accessing external innovation in drug discovery and development.

PubMed

Tufféry, Pierre

2015-06-01

A decline in the productivity of the pharmaceutical industry research and development (R&D) pipeline has highlighted the need to reconsider the classical strategies of drug discovery and development, which are based on internal resources, and to identify new means to improve the drug discovery process. Accepting that the combination of internal and external ideas can improve innovation, ways to access external innovation, that is, opening projects to external contributions, have recently been sought. In this review, the authors look at a number of external innovation opportunities. These include increased interactions with academia via academic centers of excellence/innovation centers, better communication on projects using crowdsourcing or social media and new models centered on external providers such as built-to-buy startups or virtual pharmaceutical companies. The buzz for accessing external innovation relies on the pharmaceutical industry's major challenge to improve R&D productivity, a conjuncture favorable to increase interactions with academia and new business models supporting access to external innovation. So far, access to external innovation has mostly been considered during early stages of drug development, and there is room for enhancement. First outcomes suggest that external innovation should become part of drug development in the long term. However, the balance between internal and external developments in drug discovery can vary largely depending on the company strategies.

Strategies for target identification of antimicrobial natural products.

PubMed

Farha, Maya A; Brown, Eric D

2016-05-04

Covering: 2000 to 2015Despite a pervasive decline in natural product research at many pharmaceutical companies over the last two decades, natural products have undeniably been a prolific and unsurpassed source for new lead antibacterial compounds. Due to their inherent complexity, natural extracts face several hurdles in high-throughout discovery programs, including target identification. Target identification and validation is a crucial process for advancing hits through the discovery pipeline, but has remained a major bottleneck. In the case of natural products, extremely low yields and limited compound supply further impede the process. Here, we review the wealth of target identification strategies that have been proposed and implemented for the characterization of novel antibacterials. Traditionally, these have included genomic and biochemical-based approaches, which, in recent years, have been improved with modern-day technology and better honed for natural product discovery. Further, we discuss the more recent innovative approaches for uncovering the target of new antibacterial natural products, which have resulted from modern advances in chemical biology tools. Finally, we present unique screening platforms implemented to streamline the process of target identification. The different innovative methods to respond to the challenge of characterizing the mode of action for antibacterial natural products have cumulatively built useful frameworks that may advocate a renovated interest in natural product drug discovery programs.

Interestingness measures and strategies for mining multi-ontology multi-level association rules from gene ontology annotations for the discovery of new GO relationships.

PubMed

Manda, Prashanti; McCarthy, Fiona; Bridges, Susan M

2013-10-01

The Gene Ontology (GO), a set of three sub-ontologies, is one of the most popular bio-ontologies used for describing gene product characteristics. GO annotation data containing terms from multiple sub-ontologies and at different levels in the ontologies is an important source of implicit relationships between terms from the three sub-ontologies. Data mining techniques such as association rule mining that are tailored to mine from multiple ontologies at multiple levels of abstraction are required for effective knowledge discovery from GO annotation data. We present a data mining approach, Multi-ontology data mining at All Levels (MOAL) that uses the structure and relationships of the GO to mine multi-ontology multi-level association rules. We introduce two interestingness measures: Multi-ontology Support (MOSupport) and Multi-ontology Confidence (MOConfidence) customized to evaluate multi-ontology multi-level association rules. We also describe a variety of post-processing strategies for pruning uninteresting rules. We use publicly available GO annotation data to demonstrate our methods with respect to two applications (1) the discovery of co-annotation suggestions and (2) the discovery of new cross-ontology relationships. Copyright © 2013 The Authors. Published by Elsevier Inc. All rights reserved.

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

PubMed

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.

The path to producing pharmaceuticals from natural products uncovered by academia-from the perspective of a science coordinator.

PubMed

Fujie, Akihiko

2017-01-01

To actualize the invention of all-Japanese medicines, the Department of Innovative Drug Discovery and Development (iD3) in the Japan Agency for Medical Research and Development (AMED) serves as the headquarters for the Drug Discovery Support Network. iD3 assists with creating research strategies for the seeds of medicines discovered by academia and provides technological support, intellectual property management, and aid for applying the seeds through industry-led efforts. In this review, from the perspective of a science coordinator, I will describe the current activities of the drug discovery support network and iD3 as well as the challenges and future developments of pharmaceutical research and development using the natural product drug discovery method.

Rethinking 'academic' drug discovery: the Manchester Institute perspective.

PubMed

Jordan, Allan M; Waddell, Ian D; Ogilvie, Donald J

2015-05-01

The contraction in research within pharma has seen a renaissance in drug discovery within the academic setting. Often, groups grow organically from academic research laboratories, exploiting a particular area of novel biology or new technology. However, increasingly, new groups driven by industrial staff are emerging with demonstrable expertise in the delivery of medicines. As part of a strategic review by Cancer Research UK (CR-UK), the drug discovery team at the Manchester Institute was established to translate novel research from the Manchester cancer research community into drug discovery programmes. From a standing start, we have taken innovative approaches to solve key issues faced by similar groups, such as hit finding and target identification. Herein, we share our lessons learnt and successful strategies. Copyright © 2014 Elsevier Ltd. All rights reserved.

False Discovery Control in Large-Scale Spatial Multiple Testing

PubMed Central

Sun, Wenguang; Reich, Brian J.; Cai, T. Tony; Guindani, Michele; Schwartzman, Armin

2014-01-01

Summary This article develops a unified theoretical and computational framework for false discovery control in multiple testing of spatial signals. We consider both point-wise and cluster-wise spatial analyses, and derive oracle procedures which optimally control the false discovery rate, false discovery exceedance and false cluster rate, respectively. A data-driven finite approximation strategy is developed to mimic the oracle procedures on a continuous spatial domain. Our multiple testing procedures are asymptotically valid and can be effectively implemented using Bayesian computational algorithms for analysis of large spatial data sets. Numerical results show that the proposed procedures lead to more accurate error control and better power performance than conventional methods. We demonstrate our methods for analyzing the time trends in tropospheric ozone in eastern US. PMID:25642138

Virtual drug discovery: beyond computational chemistry?

PubMed

Gilardoni, Francois; Arvanites, Anthony C

2010-02-01

This editorial looks at how a fully integrated structure that performs all aspects in the drug discovery process, under one company, is slowly disappearing. The steps in the drug discovery paradigm have been slowly increasing toward virtuality or outsourcing at various phases of product development in a company's candidate pipeline. Each step in the process, such as target identification and validation and medicinal chemistry, can be managed by scientific teams within a 'virtual' company. Pharmaceutical companies to biotechnology start-ups have been quick in adopting this new research and development business strategy in order to gain flexibility, access the best technologies and technical expertise, and decrease product developmental costs. In today's financial climate, the term virtual drug discovery has an organizational meaning. It represents the next evolutionary step in outsourcing drug development.

Crystal structure of Zika virus NS5 RNA-dependent RNA polymerase.

PubMed

Godoy, Andre S; Lima, Gustavo M A; Oliveira, Ketllyn I Z; Torres, Naiara U; Maluf, Fernando V; Guido, Rafael V C; Oliva, Glaucius

2017-03-27

The current Zika virus (ZIKV) outbreak became a global health threat of complex epidemiology and devastating neurological impacts, therefore requiring urgent efforts towards the development of novel efficacious and safe antiviral drugs. Due to its central role in RNA viral replication, the non-structural protein 5 (NS5) RNA-dependent RNA-polymerase (RdRp) is a prime target for drug discovery. Here we describe the crystal structure of the recombinant ZIKV NS5 RdRp domain at 1.9 Å resolution as a platform for structure-based drug design strategy. The overall structure is similar to other flaviviral homologues. However, the priming loop target site, which is suitable for non-nucleoside polymerase inhibitor design, shows significant differences in comparison with the dengue virus structures, including a tighter pocket and a modified local charge distribution.

Psychiatry as a Clinical Neuroscience Discipline

PubMed Central

Insel, Thomas R.; Quirion, Remi

2006-01-01

One of the fundamental insights emerging from contemporary neuroscience is that mental illnesses are brain disorders. In contrast to classic neurological illnesses that involve discrete brain lesions, mental disorders need to be addressed as disorders of distributed brain systems with symptoms forged by developmental and social experiences. While genomics will be important for revealing risk, and cellular neuroscience should provide targets for novel treatments for these disorders, it is most likely that the tools of systems neuroscience will yield the biomarkers needed to revolutionize psychiatric diagnosis and treatment. This essay considers the discoveries that will be necessary over the next two decades to translate the promise of modern neuroscience into strategies for prevention and cures of mental disorders. To deliver on this spectacular new potential, clinical neuroscience must be integrated into the discipline of psychiatry, thereby transforming current psychiatric training, tools, and practices. PMID:16264165

Comparison of Two Methods Used to Model Shape Parameters of Pareto Distributions

USGS Publications Warehouse

Liu, C.; Charpentier, R.R.; Su, J.

2011-01-01

Two methods are compared for estimating the shape parameters of Pareto field-size (or pool-size) distributions for petroleum resource assessment. Both methods assume mature exploration in which most of the larger fields have been discovered. Both methods use the sizes of larger discovered fields to estimate the numbers and sizes of smaller fields: (1) the tail-truncated method uses a plot of field size versus size rank, and (2) the log-geometric method uses data binned in field-size classes and the ratios of adjacent bin counts. Simulation experiments were conducted using discovered oil and gas pool-size distributions from four petroleum systems in Alberta, Canada and using Pareto distributions generated by Monte Carlo simulation. The estimates of the shape parameters of the Pareto distributions, calculated by both the tail-truncated and log-geometric methods, generally stabilize where discovered pool numbers are greater than 100. However, with fewer than 100 discoveries, these estimates can vary greatly with each new discovery. The estimated shape parameters of the tail-truncated method are more stable and larger than those of the log-geometric method where the number of discovered pools is more than 100. Both methods, however, tend to underestimate the shape parameter. Monte Carlo simulation was also used to create sequences of discovered pool sizes by sampling from a Pareto distribution with a discovery process model using a defined exploration efficiency (in order to show how biased the sampling was in favor of larger fields being discovered first). A higher (more biased) exploration efficiency gives better estimates of the Pareto shape parameters. ?? 2011 International Association for Mathematical Geosciences.

Assessing differential expression in two-color microarrays: a resampling-based empirical Bayes approach.

PubMed

Li, Dongmei; Le Pape, Marc A; Parikh, Nisha I; Chen, Will X; Dye, Timothy D

2013-01-01

Microarrays are widely used for examining differential gene expression, identifying single nucleotide polymorphisms, and detecting methylation loci. Multiple testing methods in microarray data analysis aim at controlling both Type I and Type II error rates; however, real microarray data do not always fit their distribution assumptions. Smyth's ubiquitous parametric method, for example, inadequately accommodates violations of normality assumptions, resulting in inflated Type I error rates. The Significance Analysis of Microarrays, another widely used microarray data analysis method, is based on a permutation test and is robust to non-normally distributed data; however, the Significance Analysis of Microarrays method fold change criteria are problematic, and can critically alter the conclusion of a study, as a result of compositional changes of the control data set in the analysis. We propose a novel approach, combining resampling with empirical Bayes methods: the Resampling-based empirical Bayes Methods. This approach not only reduces false discovery rates for non-normally distributed microarray data, but it is also impervious to fold change threshold since no control data set selection is needed. Through simulation studies, sensitivities, specificities, total rejections, and false discovery rates are compared across the Smyth's parametric method, the Significance Analysis of Microarrays, and the Resampling-based empirical Bayes Methods. Differences in false discovery rates controls between each approach are illustrated through a preterm delivery methylation study. The results show that the Resampling-based empirical Bayes Methods offer significantly higher specificity and lower false discovery rates compared to Smyth's parametric method when data are not normally distributed. The Resampling-based empirical Bayes Methods also offers higher statistical power than the Significance Analysis of Microarrays method when the proportion of significantly differentially expressed genes is large for both normally and non-normally distributed data. Finally, the Resampling-based empirical Bayes Methods are generalizable to next generation sequencing RNA-seq data analysis.

An High Resolution Near-Earth Objects Population Enabling Next-Generation Search Strategies

NASA Technical Reports Server (NTRS)

Tricaico, Pasquale; Beshore, E. C.; Larson, S. M.; Boattini, A.; Williams, G. V.

2010-01-01

Over the past decade, the dedicated search for kilometer-size near-Earth objects (NEOs), potentially hazardous objects (PHOs), and potential Earth impactors has led to a boost in the rate of discoveries of these objects. The catalog of known NEOs is the fundamental ingredient used to develop a model for the NEOs population, either by assessing and correcting for the observational bias (Jedicke et al., 2002), or by evaluating the migration rates from the NEOs source regions (Bottke et al., 2002). The modeled NEOs population is a necessary tool used to track the progress in the search of large NEOs (Jedicke et al., 2003) and to try to predict the distribution of the ones still undiscovered, as well as to study the sky distribution of potential Earth impactors (Chesley & Spahr, 2004). We present a method to model the NEOs population in all six orbital elements, on a finely grained grid, allowing us the design and test of targeted and optimized search strategies. This method relies on the observational data routinely reported to the Minor Planet Center (MPC) by the Catalina Sky Survey (CSS) and by other active NEO surveys over the past decade, to determine on a nightly basis the efficiency in detecting moving objects as a function of observable quantities including apparent magnitude, rate of motion, airmass, and galactic latitude. The cumulative detection probability is then be computed for objects within a small range in orbital elements and absolute magnitude, and the comparison with the number of know NEOs within the same range allows us to model the population. When propagated to the present epoch and projected on the sky plane, this provides the distribution of the missing large NEOs, PHOs, and potential impactors.

U.S. Geological Survey science strategy for highly pathogenic avian influenza in wildlife and the environment (2016–2020)

USGS Publications Warehouse

Harris, M. Camille; Pearce, John M.; Prosser, Diann J.; White, C. LeAnn; Miles, A. Keith; Sleeman, Jonathan M.; Brand, Christopher J.; Cronin, James P.; De La Cruz, Susan; Densmore, Christine L.; Doyle, Thomas W.; Dusek, Robert J.; Fleskes, Joseph P.; Flint, Paul L.; Guala, Gerald F.; Hall, Jeffrey S.; Hubbard, Laura E.; Hunt, Randall J.; Ip, Hon S.; Katz, Rachel A.; Laurent, Kevin W.; Miller, Mark P.; Munn, Mark D.; Ramey, Andy M.; Richards, Kevin D.; Russell, Robin E.; Stokdyk, Joel P.; Takekawa, John Y.; Walsh, Daniel P.

2016-08-18

IntroductionThrough the Science Strategy for Highly Pathogenic Avian Influenza (HPAI) in Wildlife and the Environment, the USGS will assess avian influenza (AI) dynamics in an ecological context to inform decisions made by resource managers and policymakers from the local to national level. Through collection of unbiased scientific information on the ecology of AI viruses and wildlife hosts in a changing world, the U.S. Geological Survey (USGS) will enhance the development of AI forecasting tools and ensure this information is integrated with a quality decision process for managing HPAI.The overall goal of this USGS Science Strategy for HPAI in Wildlife and the Environment goes beyond document­ing the occurrence and distribution of AI viruses in wild birds. The USGS aims to understand the epidemiological processes and environmental factors that influence HPAI distribution and describe the mechanisms of transmission between wild birds and poultry. USGS scientists developed a conceptual model describing the process linking HPAI dispersal in wild waterfowl to the outbreaks in poul­try. This strategy focuses on five long-term science goals, which include:Science Goal 1—Augment the National HPAI Surveillance Plan;Science Goal 2—Determine mechanisms of HPAI disease spread in wildlife and the environment;Science Goal 3—Characterize HPAI viruses circulating in wildlife;Science Goal 4—Understand implications of avian ecol­ogy on HPAI spread; andScience Goal 5—Develop HPAI forecasting and decision-making tools.These goals will help define and describe the processes outlined in the conceptual model with the ultimate goal of facilitating biosecurity and minimizing transfer of diseases across the wildlife-poultry interface. The first four science goals are focused on scientific discovery and the fifth goal is application-based. Decision analyses in the fifth goal will guide prioritization of proposed actions in the first four goals.

Supernovae Discovery Efficiency

NASA Astrophysics Data System (ADS)

John, Colin

2018-01-01

Abstract:We present supernovae (SN) search efficiency measurements for recent Hubble Space Telescope (HST) surveys. Efficiency is a key component to any search, and is important parameter as a correction factor for SN rates. To achieve an accurate value for efficiency, many supernovae need to be discoverable in surveys. This cannot be achieved from real SN only, due to their scarcity, so fake SN are planted. These fake supernovae—with a goal of realism in mind—yield an understanding of efficiency based on position related to other celestial objects, and brightness. To improve realism, we built a more accurate model of supernovae using a point-spread function. The next improvement to realism is planting these objects close to galaxies and of various parameters of brightness, magnitude, local galactic brightness and redshift. Once these are planted, a very accurate SN is visible and discoverable by the searcher. It is very important to find factors that affect this discovery efficiency. Exploring the factors that effect detection yields a more accurate correction factor. Further inquires into efficiency give us a better understanding of image processing, searching techniques and survey strategies, and result in an overall higher likelihood to find these events in future surveys with Hubble, James Webb, and WFIRST telescopes. After efficiency is discovered and refined with many unique surveys, it factors into measurements of SN rates versus redshift. By comparing SN rates vs redshift against the star formation rate we can test models to determine how long star systems take from the point of inception to explosion (delay time distribution). This delay time distribution is compared to SN progenitors models to get an accurate idea of what these stars were like before their deaths.

Emergence of Chinese drug discovery research: impact of hit and lead identification.

PubMed

Zhou, Caihong; Zhou, Yan; Wang, Jia; Zhu, Yue; Deng, Jiejie; Wang, Ming-Wei

2015-03-01

The identification of hits and the generation of viable leads is an early and yet crucial step in drug discovery. In the West, the main players of drug discovery are pharmaceutical and biotechnology companies, while in China, academic institutions remain central in the field of drug discovery. There has been a tremendous amount of investment from the public as well as private sectors to support infrastructure buildup and expertise consolidation relative to drug discovery and development in the past two decades. A large-scale compound library has been established in China, and a series of high-impact discoveries of lead compounds have been made by integrating information obtained from different technology-based strategies. Natural products are a major source in China's drug discovery efforts. Knowledge has been enhanced via disruptive breakthroughs such as the discovery of Boc5 as a nonpeptidic agonist of glucagon-like peptide 1 receptor (GLP-1R), one of the class B G protein-coupled receptors (GPCRs). Most of the original hit identification and lead generation were carried out by academic institutions, including universities and specialized research institutes. The Chinese pharmaceutical industry is gradually transforming itself from manufacturing low-end generics and active pharmaceutical ingredients to inventing new drugs. © 2014 Society for Laboratory Automation and Screening.

Students' Individual Schematization Pathways--Empirical Reconstructions for the Case of Part-of-Part Determination for Fractions

ERIC Educational Resources Information Center

Glade, Matthias; Prediger, Susanne

2017-01-01

According to the design principle of progressive schematization, learning trajectories towards procedural rules can be organized as independent discoveries when the learning arrangement invites the students first to develop models for mathematical concepts and model-based informal strategies; then to explore the strategies and to discover pattern…

Seeing Relationships: Using Spatial Thinking to Teach Science, Mathematics, and Social Studies

ERIC Educational Resources Information Center

Newcombe, Nora S.

2013-01-01

The author discusses four specific strategies for enhancing and supporting the spatial aspects of the science, mathematics, and social studies curricula. However, these four strategies are examples of what can be done, not an exhaustive list. The overarching concept is to embrace the spatial visualizations used for discovery and communication in…

Strategy Shifts Without Impasses: A Computational Model of the Sum-to- Min Transition.

DTIC Science & Technology

1991-09-01

the larger addend to the left hand. Rather, it starts and Gallistel (1978) who found that very young chil- with whichever addend is presented first... Gallistel , C. R. (1978). The child’s the discovery of problem solving strategies. Cognitive understanding of number. Cambridge, MA: Harvard Science

Is Open Science the Future of Drug Development?

PubMed Central

Shaw, Daniel L.

2017-01-01

Traditional drug development models are widely perceived as opaque and inefficient, with the cost of research and development continuing to rise even as production of new drugs stays constant. Searching for strategies to improve the drug discovery process, the biomedical research field has begun to embrace open strategies. The resulting changes are starting to reshape the industry. Open science—an umbrella term for diverse strategies that seek external input and public engagement—has become an essential tool with researchers, who are increasingly turning to collaboration, crowdsourcing, data sharing, and open sourcing to tackle some of the most pressing problems in medicine. Notable examples of such open drug development include initiatives formed around malaria and tropical disease. Open practices have found their way into the drug discovery process, from target identification and compound screening to clinical trials. This perspective argues that while open science poses some risks—which include the management of collaboration and the protection of proprietary data—these strategies are, in many cases, the more efficient and ethical way to conduct biomedical research. PMID:28356902

Finds in Belize document Late Classic Maya salt making and canoe transport

PubMed Central

McKillop, Heather

2005-01-01

How did people in preIndustrial ancient civilizations produce and distribute bulk items, such as salt, needed for everyday use by their large urban populations? This report focuses on the ancient Maya who obtained quantities of salt at cities in the interior of the Yucatan peninsula of Mexico, Belize, and Guatemala in an area where salt is scarce. I report the discovery of 41 Late Classic Maya saltworks (anno Domini 600–900) in Punta Ycacos Lagoon on the south coast of Belize, including one with the first-known ancient Maya canoe paddle. The discoveries add important empirical information for evaluating the extent of surplus salt production and river transport during the height of Late Classic civilization in the southern Maya lowlands. The discovery of the saltworks indicates that there was extensive production and distribution of goods and resources outside the cities in the interior of the Yucatan. The discovery of a wooden canoe paddle from one of the Punta Ycacos saltworks, Ka'k' Naab', ties the production of salt to its inland transport by rivers and documents the importance of canoe trade between the coast and the interior during the Late Classic. Archaeological discovery of multiple saltworks on the Belizean coast represents surplus production of salt destined largely for the inland Peten Maya during their Late Classic peak, underscoring the importance of non-state-controlled workshop production in preIndustrial societies. PMID:15809426

Where to Dig for Fossils: Combining Climate-Envelope, Taphonomy and Discovery Models

PubMed Central

Block, Sebastián; Saltré, Frédérik; Rodríguez-Rey, Marta; Fordham, Damien A.; Unkel, Ingmar; Bradshaw, Corey J. A.

2016-01-01

Fossils represent invaluable data to reconstruct the past history of life, yet fossil-rich sites are often rare and difficult to find. The traditional fossil-hunting approach focuses on small areas and has not yet taken advantage of modelling techniques commonly used in ecology to account for an organism’s past distributions. We propose a new method to assist finding fossils at continental scales based on modelling the past distribution of species, the geological suitability of fossil preservation and the likelihood of fossil discovery in the field, and apply it to several genera of Australian megafauna that went extinct in the Late Quaternary. Our models predicted higher fossil potentials for independent sites than for randomly selected locations (mean Kolmogorov-Smirnov statistic = 0.66). We demonstrate the utility of accounting for the distribution history of fossil taxa when trying to find the most suitable areas to look for fossils. For some genera, the probability of finding fossils based on simple climate-envelope models was higher than the probability based on models incorporating current conditions associated with fossil preservation and discovery as predictors. However, combining the outputs from climate-envelope, preservation, and discovery models resulted in the most accurate predictions of potential fossil sites at a continental scale. We proposed potential areas to discover new fossils of Diprotodon, Zygomaturus, Protemnodon, Thylacoleo, and Genyornis, and provide guidelines on how to apply our approach to assist fossil hunting in other continents and geological settings. PMID:27027874

Where to Dig for Fossils: Combining Climate-Envelope, Taphonomy and Discovery Models.

PubMed

Block, Sebastián; Saltré, Frédérik; Rodríguez-Rey, Marta; Fordham, Damien A; Unkel, Ingmar; Bradshaw, Corey J A

2016-01-01

Fossils represent invaluable data to reconstruct the past history of life, yet fossil-rich sites are often rare and difficult to find. The traditional fossil-hunting approach focuses on small areas and has not yet taken advantage of modelling techniques commonly used in ecology to account for an organism's past distributions. We propose a new method to assist finding fossils at continental scales based on modelling the past distribution of species, the geological suitability of fossil preservation and the likelihood of fossil discovery in the field, and apply it to several genera of Australian megafauna that went extinct in the Late Quaternary. Our models predicted higher fossil potentials for independent sites than for randomly selected locations (mean Kolmogorov-Smirnov statistic = 0.66). We demonstrate the utility of accounting for the distribution history of fossil taxa when trying to find the most suitable areas to look for fossils. For some genera, the probability of finding fossils based on simple climate-envelope models was higher than the probability based on models incorporating current conditions associated with fossil preservation and discovery as predictors. However, combining the outputs from climate-envelope, preservation, and discovery models resulted in the most accurate predictions of potential fossil sites at a continental scale. We proposed potential areas to discover new fossils of Diprotodon, Zygomaturus, Protemnodon, Thylacoleo, and Genyornis, and provide guidelines on how to apply our approach to assist fossil hunting in other continents and geological settings.

A new approach to the rationale discovery of polymeric biomaterials

PubMed Central

Kohn, Joachim; Welsh, William J.; Knight, Doyle

2007-01-01

This paper attempts to illustrate both the need for new approaches to biomaterials discovery as well as the significant promise inherent in the use of combinatorial and computational design strategies. The key observation of this Leading Opinion Paper is that the biomaterials community has been slow to embrace advanced biomaterials discovery tools such as combinatorial methods, high throughput experimentation, and computational modeling in spite of the significant promise shown by these discovery tools in materials science, medicinal chemistry and the pharmaceutical industry. It seems that the complexity of living cells and their interactions with biomaterials has been a conceptual as well as a practical barrier to the use of advanced discovery tools in biomaterials science. However, with the continued increase in computer power, the goal of predicting the biological response of cells in contact with biomaterials surfaces is within reach. Once combinatorial synthesis, high throughput experimentation, and computational modeling are integrated into the biomaterials discovery process, a significant acceleration is possible in the pace of development of improved medical implants, tissue regeneration scaffolds, and gene/drug delivery systems. PMID:17644176

Mathematical modeling for novel cancer drug discovery and development.

PubMed

Zhang, Ping; Brusic, Vladimir

2014-10-01

Mathematical modeling enables: the in silico classification of cancers, the prediction of disease outcomes, optimization of therapy, identification of promising drug targets and prediction of resistance to anticancer drugs. In silico pre-screened drug targets can be validated by a small number of carefully selected experiments. This review discusses the basics of mathematical modeling in cancer drug discovery and development. The topics include in silico discovery of novel molecular drug targets, optimization of immunotherapies, personalized medicine and guiding preclinical and clinical trials. Breast cancer has been used to demonstrate the applications of mathematical modeling in cancer diagnostics, the identification of high-risk population, cancer screening strategies, prediction of tumor growth and guiding cancer treatment. Mathematical models are the key components of the toolkit used in the fight against cancer. The combinatorial complexity of new drugs discovery is enormous, making systematic drug discovery, by experimentation, alone difficult if not impossible. The biggest challenges include seamless integration of growing data, information and knowledge, and making them available for a multiplicity of analyses. Mathematical models are essential for bringing cancer drug discovery into the era of Omics, Big Data and personalized medicine.

Compound annotation with real time cellular activity profiles to improve drug discovery.

PubMed

Fang, Ye

2016-01-01

In the past decade, a range of innovative strategies have been developed to improve the productivity of pharmaceutical research and development. In particular, compound annotation, combined with informatics, has provided unprecedented opportunities for drug discovery. In this review, a literature search from 2000 to 2015 was conducted to provide an overview of the compound annotation approaches currently used in drug discovery. Based on this, a framework related to a compound annotation approach using real-time cellular activity profiles for probe, drug, and biology discovery is proposed. Compound annotation with chemical structure, drug-like properties, bioactivities, genome-wide effects, clinical phenotypes, and textural abstracts has received significant attention in early drug discovery. However, these annotations are mostly associated with endpoint results. Advances in assay techniques have made it possible to obtain real-time cellular activity profiles of drug molecules under different phenotypes, so it is possible to generate compound annotation with real-time cellular activity profiles. Combining compound annotation with informatics, such as similarity analysis, presents a good opportunity to improve the rate of discovery of novel drugs and probes, and enhance our understanding of the underlying biology.

A green protocol for efficient discovery of novel natural compounds: characterization of new ginsenosides from the stems and leaves of Panax ginseng as a case study.

PubMed

Qiu, Shi; Yang, Wen-Zhi; Shi, Xiao-Jian; Yao, Chang-Liang; Yang, Min; Liu, Xuan; Jiang, Bao-Hong; Wu, Wan-Ying; Guo, De-An

2015-09-17

Exploration of new natural compounds is of vital significance for drug discovery and development. The conventional approaches by systematic phytochemical isolation are low-efficiency and consume masses of organic solvent. This study presents an integrated strategy that combines offline comprehensive two-dimensional liquid chromatography, hybrid linear ion-trap/Orbitrap mass spectrometry, and NMR analysis (2D LC/LTQ-Orbitrap-MS/NMR), aimed to establish a green protocol for the efficient discovery of new natural molecules. A comprehensive chemical analysis of the total ginsenosides of stems and leaves of Panax ginseng (SLP), a cardiovascular disease medicine, was performed following this strategy. An offline 2D LC system was constructed with an orthogonality of 0.79 and a practical peak capacity of 11,000. The much greener UHPLC separation and LTQ-Orbitrap-MS detection by data-dependent high-energy C-trap dissociation (HCD)/dynamic exclusion were employed for separation and characterization of ginsenosides from thirteen fractionated SLP samples. Consequently, a total of 646 ginsenosides were characterized, and 427 have not been isolated from the genus of Panax L. The ginsenosides identified from SLP exhibited distinct sapogenin diversity and molecular isomerism. NMR analysis was finally employed to verify and offer complementary structural information to MS-oriented characterization. The established 2D LC/LTQ-Orbitrap-MS/NMR approach outperforms the conventional approaches in respect of significantly improved efficiency, much less use of drug materials and organic solvent. The integrated strategy enables a deep investigation on the therapeutic basis of an herbal medicine, and facilitates new compounds discovery in an efficient and environmentally friendly manner as well. Copyright © 2015 Elsevier B.V. All rights reserved.

Novel Biomarker Discovery for Diagnostic and Therapeutic Strategies in Prostate Cancer

DTIC Science & Technology

2015-06-01

PURPOSE: to identify high affinity aptamers that distinguish between prostate cancers that are likely to remain organ- confined and those with potential to...metastasize. SCOPE: This was a pilot project to generate RNA aptamers that selectively react with a prostate cancer cell line that remains confined... Aptamer -Facilitated Biomarker Discovery (AptaBiD) technology. TASKS AND PROGRESS: (1) Non-metastatic LNCaP-Pro-5 cells, metastasis-prone LNCaP-LN3

Novel Biomarker Discovery for Diagnostic and Therapeutic Strategies in Prostate Cancer

DTIC Science & Technology

2014-03-01

aptamers that distinguish between prostate cancers that are likely to remain organ-confined and those with potential to metastasize, The scope of this...pilot is to generate DNA aptamers that selectively react with a prostate cancer cell line that remains confined to the prostate (LNCaP) vs. a...subpopulation of this cell line that has acquired the ability to metastasize aggressively, employing Cell-Selex and Aptamer -Facilitated Biomarker Discovery

Using Discovery Maps as a Free-Choice Learning Process Can Enhance the Effectiveness of Environmental Education in a Botanical Garden

ERIC Educational Resources Information Center

Yang, Xi; Chen, Jin

2017-01-01

Botanical gardens (BGs) are important agencies that enhance human knowledge and attitude towards flora conservation. By following free-choice learning model, we developed a "Discovery map" and distributed the map to visitors at the Xishuangbanna Tropical Botanical Garden in Yunnan, China. Visitors, who did and did not receive discovery…

Constructing a Graph Database for Semantic Literature-Based Discovery.

PubMed

Hristovski, Dimitar; Kastrin, Andrej; Dinevski, Dejan; Rindflesch, Thomas C

2015-01-01

Literature-based discovery (LBD) generates discoveries, or hypotheses, by combining what is already known in the literature. Potential discoveries have the form of relations between biomedical concepts; for example, a drug may be determined to treat a disease other than the one for which it was intended. LBD views the knowledge in a domain as a network; a set of concepts along with the relations between them. As a starting point, we used SemMedDB, a database of semantic relations between biomedical concepts extracted with SemRep from Medline. SemMedDB is distributed as a MySQL relational database, which has some problems when dealing with network data. We transformed and uploaded SemMedDB into the Neo4j graph database, and implemented the basic LBD discovery algorithms with the Cypher query language. We conclude that storing the data needed for semantic LBD is more natural in a graph database. Also, implementing LBD discovery algorithms is conceptually simpler with a graph query language when compared with standard SQL.

Quantitative proteomics in cardiovascular research: global and targeted strategies

PubMed Central

Shen, Xiaomeng; Young, Rebeccah; Canty, John M.; Qu, Jun

2014-01-01

Extensive technical advances in the past decade have substantially expanded quantitative proteomics in cardiovascular research. This has great promise for elucidating the mechanisms of cardiovascular diseases (CVD) and the discovery of cardiac biomarkers used for diagnosis and treatment evaluation. Global and targeted proteomics are the two major avenues of quantitative proteomics. While global approaches enable unbiased discovery of altered proteins via relative quantification at the proteome level, targeted techniques provide higher sensitivity and accuracy, and are capable of multiplexed absolute quantification in numerous clinical/biological samples. While promising, technical challenges need to be overcome to enable full utilization of these techniques in cardiovascular medicine. Here we discuss recent advances in quantitative proteomics and summarize applications in cardiovascular research with an emphasis on biomarker discovery and elucidating molecular mechanisms of disease. We propose the integration of global and targeted strategies as a high-throughput pipeline for cardiovascular proteomics. Targeted approaches enable rapid, extensive validation of biomarker candidates discovered by global proteomics. These approaches provide a promising alternative to immunoassays and other low-throughput means currently used for limited validation. PMID:24920501

High-throughput and targeted in-depth mass spectrometry-based approaches for biofluid profiling and biomarker discovery.

PubMed

Jimenez, Connie R; Piersma, Sander; Pham, Thang V

2007-12-01

Proteomics aims to create a link between genomic information, biological function and disease through global studies of protein expression, modification and protein-protein interactions. Recent advances in key proteomics tools, such as mass spectrometry (MS) and (bio)informatics, provide tremendous opportunities for biomarker-related clinical applications. In this review, we focus on two complementary MS-based approaches with high potential for the discovery of biomarker patterns and low-abundant candidate biomarkers in biofluids: high-throughput matrix-assisted laser desorption/ionization time-of-flight mass spectroscopy-based methods for peptidome profiling and label-free liquid chromatography-based methods coupled to MS for in-depth profiling of biofluids with a focus on subproteomes, including the low-molecular-weight proteome, carrier-bound proteome and N-linked glycoproteome. The two approaches differ in their aims, throughput and sensitivity. We discuss recent progress and challenges in the analysis of plasma/serum and proximal fluids using these strategies and highlight the potential of liquid chromatography-MS-based proteomics of cancer cell and tumor secretomes for the discovery of candidate blood-based biomarkers. Strategies for candidate validation are also described.

[Drug innovation and reverse thinking].

PubMed

Guo, Zong-ru

2016-03-01

Drug innovation involves an individual molecular operation, and every new molecular entity features a hard-duplicated track of R&D. The transformation from an active compound to a new medicine carries out almost in a chaotic system devoid of regularity and periodic alteration. Since new millennium the dominant position in drug innovation has been occupied by the first-in-class drugs, yet the number of launched follow-on drugs has been distinctly decreased. The innovation of first-in-class drugs is characterized by a high risk throughout the whole process. To achieve initiative and uniqueness of drug discovery, the strategy and method of the inverse thinking might be a feasible way, because the inertial and conformity thinkings in drug discovery normally lead to ensemble with similar drug category. However, the study from the flipside or opposite of things(e.g. targets or effects) brand new routes might be opened. This article is to describe the strategy of reverse thinking in drug discovery by some examples including opioid receptor antagonist eluxadoline, HSP90 activator, h ERG channel agonist, covalent drugs, and ultra-small drugs.

NHS-Esters As Versatile Reactivity-Based Probes for Mapping Proteome-Wide Ligandable Hotspots.

PubMed

Ward, Carl C; Kleinman, Jordan I; Nomura, Daniel K

2017-06-16

Most of the proteome is considered undruggable, oftentimes hindering translational efforts for drug discovery. Identifying previously unknown druggable hotspots in proteins would enable strategies for pharmacologically interrogating these sites with small molecules. Activity-based protein profiling (ABPP) has arisen as a powerful chemoproteomic strategy that uses reactivity-based chemical probes to map reactive, functional, and ligandable hotspots in complex proteomes, which has enabled inhibitor discovery against various therapeutic protein targets. Here, we report an alkyne-functionalized N-hydroxysuccinimide-ester (NHS-ester) as a versatile reactivity-based probe for mapping the reactivity of a wide range of nucleophilic ligandable hotspots, including lysines, serines, threonines, and tyrosines, encompassing active sites, allosteric sites, post-translational modification sites, protein interaction sites, and previously uncharacterized potential binding sites. Surprisingly, we also show that fragment-based NHS-ester ligands can be made to confer selectivity for specific lysine hotspots on specific targets including Dpyd, Aldh2, and Gstt1. We thus put forth NHS-esters as promising reactivity-based probes and chemical scaffolds for covalent ligand discovery.

Evaluation of phylogenetic footprint discovery for predicting bacterial cis-regulatory elements and revealing their evolution.

PubMed

Janky, Rekin's; van Helden, Jacques

2008-01-23

The detection of conserved motifs in promoters of orthologous genes (phylogenetic footprints) has become a common strategy to predict cis-acting regulatory elements. Several software tools are routinely used to raise hypotheses about regulation. However, these tools are generally used as black boxes, with default parameters. A systematic evaluation of optimal parameters for a footprint discovery strategy can bring a sizeable improvement to the predictions. We evaluate the performances of a footprint discovery approach based on the detection of over-represented spaced motifs. This method is particularly suitable for (but not restricted to) Bacteria, since such motifs are typically bound by factors containing a Helix-Turn-Helix domain. We evaluated footprint discovery in 368 Escherichia coli K12 genes with annotated sites, under 40 different combinations of parameters (taxonomical level, background model, organism-specific filtering, operon inference). Motifs are assessed both at the levels of correctness and significance. We further report a detailed analysis of 181 bacterial orthologs of the LexA repressor. Distinct motifs are detected at various taxonomical levels, including the 7 previously characterized taxon-specific motifs. In addition, we highlight a significantly stronger conservation of half-motifs in Actinobacteria, relative to Firmicutes, suggesting an intermediate state in specificity switching between the two Gram-positive phyla, and thereby revealing the on-going evolution of LexA auto-regulation. The footprint discovery method proposed here shows excellent results with E. coli and can readily be extended to predict cis-acting regulatory signals and propose testable hypotheses in bacterial genomes for which nothing is known about regulation.

A lead discovery strategy driven by a comprehensive analysis of proteases in the peptide substrate space

PubMed Central

Sukuru, Sai Chetan K; Nigsch, Florian; Quancard, Jean; Renatus, Martin; Chopra, Rajiv; Brooijmans, Natasja; Mikhailov, Dmitri; Deng, Zhan; Cornett, Allen; Jenkins, Jeremy L; Hommel, Ulrich; Davies, John W; Glick, Meir

2010-01-01

We present here a comprehensive analysis of proteases in the peptide substrate space and demonstrate its applicability for lead discovery. Aligned octapeptide substrates of 498 proteases taken from the MEROPS peptidase database were used for the in silico analysis. A multiple-category naïve Bayes model, trained on the two-dimensional chemical features of the substrates, was able to classify the substrates of 365 (73%) proteases and elucidate statistically significant chemical features for each of their specific substrate positions. The positional awareness of the method allows us to identify the most similar substrate positions between proteases. Our analysis reveals that proteases from different families, based on the traditional classification (aspartic, cysteine, serine, and metallo), could have substrates that differ at the cleavage site (P1–P1′) but are similar away from it. Caspase-3 (cysteine protease) and granzyme B (serine protease) are previously known examples of cross-family neighbors identified by this method. To assess whether peptide substrate similarity between unrelated proteases could reliably translate into the discovery of low molecular weight synthetic inhibitors, a lead discovery strategy was tested on two other cross-family neighbors—namely cathepsin L2 and matrix metallo proteinase 9, and calpain 1 and pepsin A. For both these pairs, a naïve Bayes classifier model trained on inhibitors of one protease could successfully enrich those of its neighbor from a different family and vice versa, indicating that this approach could be prospectively applied to lead discovery for a novel protease target with no known synthetic inhibitors. PMID:20799349

An algorithm of discovering signatures from DNA databases on a computer cluster.

PubMed

Lee, Hsiao Ping; Sheu, Tzu-Fang

2014-10-05

Signatures are short sequences that are unique and not similar to any other sequence in a database that can be used as the basis to identify different species. Even though several signature discovery algorithms have been proposed in the past, these algorithms require the entirety of databases to be loaded in the memory, thus restricting the amount of data that they can process. It makes those algorithms unable to process databases with large amounts of data. Also, those algorithms use sequential models and have slower discovery speeds, meaning that the efficiency can be improved. In this research, we are debuting the utilization of a divide-and-conquer strategy in signature discovery and have proposed a parallel signature discovery algorithm on a computer cluster. The algorithm applies the divide-and-conquer strategy to solve the problem posed to the existing algorithms where they are unable to process large databases and uses a parallel computing mechanism to effectively improve the efficiency of signature discovery. Even when run with just the memory of regular personal computers, the algorithm can still process large databases such as the human whole-genome EST database which were previously unable to be processed by the existing algorithms. The algorithm proposed in this research is not limited by the amount of usable memory and can rapidly find signatures in large databases, making it useful in applications such as Next Generation Sequencing and other large database analysis and processing. The implementation of the proposed algorithm is available at http://www.cs.pu.edu.tw/~fang/DDCSDPrograms/DDCSD.htm.

Network discovery with DCM

PubMed Central

Friston, Karl J.; Li, Baojuan; Daunizeau, Jean; Stephan, Klaas E.

2011-01-01

This paper is about inferring or discovering the functional architecture of distributed systems using Dynamic Causal Modelling (DCM). We describe a scheme that recovers the (dynamic) Bayesian dependency graph (connections in a network) using observed network activity. This network discovery uses Bayesian model selection to identify the sparsity structure (absence of edges or connections) in a graph that best explains observed time-series. The implicit adjacency matrix specifies the form of the network (e.g., cyclic or acyclic) and its graph-theoretical attributes (e.g., degree distribution). The scheme is illustrated using functional magnetic resonance imaging (fMRI) time series to discover functional brain networks. Crucially, it can be applied to experimentally evoked responses (activation studies) or endogenous activity in task-free (resting state) fMRI studies. Unlike conventional approaches to network discovery, DCM permits the analysis of directed and cyclic graphs. Furthermore, it eschews (implausible) Markovian assumptions about the serial independence of random fluctuations. The scheme furnishes a network description of distributed activity in the brain that is optimal in the sense of having the greatest conditional probability, relative to other networks. The networks are characterised in terms of their connectivity or adjacency matrices and conditional distributions over the directed (and reciprocal) effective connectivity between connected nodes or regions. We envisage that this approach will provide a useful complement to current analyses of functional connectivity for both activation and resting-state studies. PMID:21182971

Comparative mass spectrometry-based metabolomics strategies for the investigation of microbial secondary metabolites.

PubMed

Covington, Brett C; McLean, John A; Bachmann, Brian O

2017-01-04

Covering: 2000 to 2016The labor-intensive process of microbial natural product discovery is contingent upon identifying discrete secondary metabolites of interest within complex biological extracts, which contain inventories of all extractable small molecules produced by an organism or consortium. Historically, compound isolation prioritization has been driven by observed biological activity and/or relative metabolite abundance and followed by dereplication via accurate mass analysis. Decades of discovery using variants of these methods has generated the natural pharmacopeia but also contributes to recent high rediscovery rates. However, genomic sequencing reveals substantial untapped potential in previously mined organisms, and can provide useful prescience of potentially new secondary metabolites that ultimately enables isolation. Recently, advances in comparative metabolomics analyses have been coupled to secondary metabolic predictions to accelerate bioactivity and abundance-independent discovery work flows. In this review we will discuss the various analytical and computational techniques that enable MS-based metabolomic applications to natural product discovery and discuss the future prospects for comparative metabolomics in natural product discovery.

Hierarchical virtual screening approaches in small molecule drug discovery.

PubMed

Kumar, Ashutosh; Zhang, Kam Y J

2015-01-01

Virtual screening has played a significant role in the discovery of small molecule inhibitors of therapeutic targets in last two decades. Various ligand and structure-based virtual screening approaches are employed to identify small molecule ligands for proteins of interest. These approaches are often combined in either hierarchical or parallel manner to take advantage of the strength and avoid the limitations associated with individual methods. Hierarchical combination of ligand and structure-based virtual screening approaches has received noteworthy success in numerous drug discovery campaigns. In hierarchical virtual screening, several filters using ligand and structure-based approaches are sequentially applied to reduce a large screening library to a number small enough for experimental testing. In this review, we focus on different hierarchical virtual screening strategies and their application in the discovery of small molecule modulators of important drug targets. Several virtual screening studies are discussed to demonstrate the successful application of hierarchical virtual screening in small molecule drug discovery. Copyright © 2014 Elsevier Inc. All rights reserved.

Early Probe and Drug Discovery in Academia: A Minireview.

PubMed

Roy, Anuradha

2018-02-09

Drug discovery encompasses processes ranging from target selection and validation to the selection of a development candidate. While comprehensive drug discovery work flows are implemented predominantly in the big pharma domain, early discovery focus in academia serves to identify probe molecules that can serve as tools to study targets or pathways. Despite differences in the ultimate goals of the private and academic sectors, the same basic principles define the best practices in early discovery research. A successful early discovery program is built on strong target definition and validation using a diverse set of biochemical and cell-based assays with functional relevance to the biological system being studied. The chemicals identified as hits undergo extensive scaffold optimization and are characterized for their target specificity and off-target effects in in vitro and in animal models. While the active compounds from screening campaigns pass through highly stringent chemical and Absorption, Distribution, Metabolism, and Excretion (ADME) filters for lead identification, the probe discovery involves limited medicinal chemistry optimization. The goal of probe discovery is identification of a compound with sub-µM activity and reasonable selectivity in the context of the target being studied. The compounds identified from probe discovery can also serve as starting scaffolds for lead optimization studies.

Alchemist multimodal workflows for diabetic retinopathy research, disease prevention and investigational drug discovery.

PubMed

Riposan, Adina; Taylor, Ian; Owens, David R; Rana, Omer; Conley, Edward C

2007-01-01

In this paper we present mechanisms for imaging and spectral data discovery, as applied to the early detection of pathologic mechanisms underlying diabetic retinopathy in research and clinical trial scenarios. We discuss the Alchemist framework, built using a generic peer-to-peer architecture, supporting distributed database queries and complex search algorithms based on workflow. The Alchemist is a domain-independent search mechanism that can be applied to search and data discovery scenarios in many areas. We illustrate Alchemist's ability to perform complex searches composed as a collection of peer-to-peer overlays, Grid-based services and workflows, e.g. applied to image and spectral data discovery, as applied to the early detection and prevention of retinal disease and investigational drug discovery. The Alchemist framework is built on top of decentralised technologies and uses industry standards such as Web services and SOAP for messaging.

Molecular basis of high viscosity in concentrated antibody solutions: Strategies for high concentration drug product development

PubMed Central

Tomar, Dheeraj S.; Kumar, Sandeep; Singh, Satish K.; Goswami, Sumit; Li, Li

2016-01-01

ABSTRACT Effective translation of breakthrough discoveries into innovative products in the clinic requires proactive mitigation or elimination of several drug development challenges. These challenges can vary depending upon the type of drug molecule. In the case of therapeutic antibody candidates, a commonly encountered challenge is high viscosity of the concentrated antibody solutions. Concentration-dependent viscosity behaviors of mAbs and other biologic entities may depend on pairwise and higher-order intermolecular interactions, non-native aggregation, and concentration-dependent fluctuations of various antibody regions. This article reviews our current understanding of molecular origins of viscosity behaviors of antibody solutions. We discuss general strategies and guidelines to select low viscosity candidates or optimize lead candidates for lower viscosity at early drug discovery stages. Moreover, strategies for formulation optimization and excipient design are also presented for candidates already in advanced product development stages. Potential future directions for research in this field are also explored. PMID:26736022

Switch in Site of Inhibition: A Strategy for Structure-Based Discovery of Human Topoisomerase IIα Catalytic Inhibitors

PubMed Central

2015-01-01

A study of structure-based modulation of known ligands of hTopoIIα, an important enzyme involved in DNA processes, coupled with synthesis and in vitro assays led to the establishment of a strategy of rational switch in mode of inhibition of the enzyme’s catalytic cycle. 6-Arylated derivatives of known imidazopyridine ligands were found to be selective inhibitors of hTopoIIα, while not showing TopoI inhibition and DNA binding. Interestingly, while the parent imidazopyridines acted as ATP-competitive inhibitors, arylated derivatives inhibited DNA cleavage similar to merbarone, indicating a switch in mode of inhibition from ATP-hydrolysis to the DNA-cleavage stage of catalytic cycle of the enzyme. The 6-aryl-imidazopyridines were relatively more cytotoxic than etoposide in cancer cells and less toxic to normal cells. Such unprecedented strategy will encourage research on “choice-based change” in target-specific mode of action for rapid drug discovery. PMID:25941559

Ligand Fishing: A Remarkable Strategy for Discovering Bioactive Compounds from Complex Mixture of Natural Products.

PubMed

Zhuo, Rongjie; Liu, Hao; Liu, Ningning; Wang, Yi

2016-11-11

Identification of active compounds from natural products is a critical and challenging task in drug discovery pipelines. Besides commonly used bio-guided screening approaches, affinity selection strategy coupled with liquid chromatography or mass spectrometry, known as ligand fishing, has been gaining increasing interest from researchers. In this review, we summarized this emerging strategy and categorized those methods as off-line or on-line mode according to their features. The separation principles of ligand fishing were introduced based on distinct analytical techniques, including biochromatography, capillary electrophoresis, ultrafiltration, equilibrium dialysis, microdialysis, and magnetic beads. The applications of ligand fishing approaches in the discovery of lead compounds were reviewed. Most of ligand fishing methods display specificity, high efficiency, and require less sample pretreatment, which makes them especially suitable for screening active compounds from complex mixtures of natural products. We also summarized the applications of ligand fishing in the modernization of Traditional Chinese Medicine (TCM), and propose some perspectives of this remarkable technique.

Targeting monoamine oxidases with multipotent ligands: an emerging strategy in the search of new drugs against neurodegenerative diseases.

PubMed

Pisani, L; Catto, M; Leonetti, F; Nicolotti, O; Stefanachi, A; Campagna, F; Carotti, A

2011-01-01

The socioeconomic burden of multi-factorial pathologies, such as neurodegenerative diseases (NDs), is enormous worldwide. Unfortunately, no proven disease-modifying therapy is available yet and in most cases (e.g., Alzheimer's and Parkinson's disease) the approved drugs exert only palliative and symptomatic effects. Nowadays, an emerging strategy for the discovery of disease-modifying drugs is based on the multi-target directed ligand (MTDL) design, an innovative shift from the traditional approach one-drug-one-target to the more ambitious one-drug-more-targets goal. Herein, we review the discovery strategy, the mechanism of action and the biopharmacological evaluation of multipotent ligands exhibiting monoamine oxidase (MAO) inhibition as the core activity with a potential for the treatment of NDs. In particular, MAO inhibitors exhibiting additional acetylcholinesterase (AChE) or nitric oxide synthase (NOS) inhibition, or ion chelation/antioxidant-radical scavenging/anti-inflammatory/A2A receptor antagonist/APP processing modulating activities have been thoroughly examined.

Implementing the Army NetCentric Data Strategy in a ServiceOriented Environment

DTIC Science & Technology

2009-04-23

D a t a D i s c o v e r y Data Retrieval Data Subscription Data Discovery D a t a A c c e s s Artifact Discovery Federated Search Data Search Data...define common interfaces to search and  retrieve data across the enterprise.  • Patterns • Search • Status • Receive – Services • Federated   Search • Artifact

The Impact of Highly and Minimally Guided Discovery Instruction on Promoting the Learning of Reasoning Strategies for Basic Add-1 and Doubles Combinations

ERIC Educational Resources Information Center

Baroody, Arthur J.; Purpura, David J.; Eiland, Michael D.; Reid, Erin E.

2015-01-01

A 9-month training experiment was conducted to evaluate the efficacy of highly and minimally guided discovery interventions targeting the add-1 rule (the sum of a number and one is the next number on the mental number list) and doubles relations (e.g., an everyday example of the double 5 + 5 is five fingers on the left hand and five fingers on the…

Opportunities for natural products in 21st century antibiotic discovery.

PubMed

Wright, Gerard D

2017-07-01

Natural products and their derivatives are mainstays of our antibiotic drugs, but they are increasingly in peril. The combination of widespread multidrug resistance in once susceptible bacterial pathogens, disenchantment with natural products as sources of new drugs, lack of success using synthetic compounds and target-based discovery methods, along with shifting economic and regulatory issues, conspire to move investment in research and development away from the antibiotics arena. The result is a growing crisis in antibiotic drug discovery that threatens modern medicine. 21 st century natural product research is perfectly positioned to fill the antibiotic discovery gap and bring new drug candidates to the clinic. Innovations in genomics and techniques to explore new sources of antimicrobial chemical matter are revealing new chemistry. Increasing appreciation of the value of narrow-spectrum drugs and re-examination of once discarded chemical scaffolds coupled with synthetic biology methods to generate new compounds and improve yields offer new strategies to revitalize once moribund natural product programs. The increasing awareness that the combination of antibiotics with adjuvants, non-antibiotic compounds that overcome resistance and enhance drug activity, can rescue older chemical scaffolds, and concepts such as blocking pathogen virulence present orthogonal strategies to traditional antibiotics. In all these areas, natural products offer chemical matter, shaped by natural selection, that is privileged in this therapeutic area. Natural product research is poised to regain prominence in delivering new drugs to solve the antibiotic crisis.

Learning in the context of distribution drift

DTIC Science & Technology

2017-05-09

published in the leading data mining journal, Data Mining and Knowledge Discovery (Webb et. al., 2016)1. We have shown that the previous qualitative...learner Low-bias learner Aggregated classifier Figure 7: Architecture for learning fr m streaming data in th co text of variable or unknown...Learning limited dependence Bayesian classifiers, in Proceedings of the Second International Conference on Knowledge Discovery and Data Mining (KDD

Drug Discovery Prospect from Untapped Species: Indications from Approved Natural Product Drugs

PubMed Central

Qin, Chu; Tao, Lin; Liu, Xin; Shi, Zhe; Zhang, Cun Long; Tan, Chun Yan; Chen, Yu Zong; Jiang, Yu Yang

2012-01-01

Due to extensive bioprospecting efforts of the past and technology factors, there have been questions about drug discovery prospect from untapped species. We analyzed recent trends of approved drugs derived from previously untapped species, which show no sign of untapped drug-productive species being near extinction and suggest high probability of deriving new drugs from new species in existing drug-productive species families and clusters. Case histories of recently approved drugs reveal useful strategies for deriving new drugs from the scaffolds and pharmacophores of the natural product leads of these untapped species. New technologies such as cryptic gene-cluster exploration may generate novel natural products with highly anticipated potential impact on drug discovery. PMID:22808057

Three-Component Reaction Discovery Enabled by Mass Spectrometry of Self-Assembled Monolayers

PubMed Central

Montavon, Timothy J.; Li, Jing; Cabrera-Pardo, Jaime R.; Mrksich, Milan; Kozmin, Sergey A.

2011-01-01

Multi-component reactions have been extensively employed in many areas of organic chemistry. Despite significant progress, the discovery of such enabling transformations remains challenging. Here, we present the development of a parallel, label-free reaction-discovery platform, which can be used for identification of new multi-component transformations. Our approach is based on the parallel mass spectrometric screening of interfacial chemical reactions on arrays of self-assembled monolayers. This strategy enabled the identification of a simple organic phosphine that can catalyze a previously unknown condensation of siloxy alkynes, aldehydes and amines to produce 3-hydroxy amides with high efficiency and diastereoselectivity. The reaction was further optimized using solution phase methods. PMID:22169871

Signals from the Fourth Dimension Regulate Drug Relapse.

PubMed

Mulholland, Patrick J; Chandler, L Judson; Kalivas, Peter W

2016-07-01

Despite the enormous societal burden of alcohol and drug addiction and abundant research describing drug-induced maladaptive synaptic plasticity, there are few effective strategies for treating substance use disorders. Recent awareness that synaptic plasticity involves astroglia and the extracellular matrix is revealing new possibilities for understanding and treating addiction. We first review constitutive corticostriatal adaptations that are elicited by and shared between all abused drugs from the perspective of tetrapartite synapses, and integrate recent discoveries regarding cell type-specificity in striatal neurons. Next, we describe recent discoveries that drug-seeking is associated with transient synaptic plasticity that requires all four synaptic elements and is shared across drug classes. Finally, we prognosticate how considering tetrapartite synapses can provide new treatment strategies for addiction. Copyright © 2016 Elsevier Ltd. All rights reserved.

Biosignature Discovery for Substance Use Disorders Using Statistical Learning.

PubMed

Baurley, James W; McMahan, Christopher S; Ervin, Carolyn M; Pardamean, Bens; Bergen, Andrew W

2018-02-01

There are limited biomarkers for substance use disorders (SUDs). Traditional statistical approaches are identifying simple biomarkers in large samples, but clinical use cases are still being established. High-throughput clinical, imaging, and 'omic' technologies are generating data from SUD studies and may lead to more sophisticated and clinically useful models. However, analytic strategies suited for high-dimensional data are not regularly used. We review strategies for identifying biomarkers and biosignatures from high-dimensional data types. Focusing on penalized regression and Bayesian approaches, we address how to leverage evidence from existing studies and knowledge bases, using nicotine metabolism as an example. We posit that big data and machine learning approaches will considerably advance SUD biomarker discovery. However, translation to clinical practice, will require integrated scientific efforts. Copyright © 2017 Elsevier Ltd. All rights reserved.

MALDI mass spectrometry imaging in rheumatic diseases.

PubMed

Rocha, Beatriz; Cillero-Pastor, Berta; Blanco, Francisco J; Ruiz-Romero, Cristina

2017-07-01

Mass spectrometry imaging (MSI) is a technique used to visualize the spatial distribution of biomolecules such as peptides, proteins, lipids or other organic compounds by their molecular masses. Among the different MSI strategies, MALDI-MSI provides a sensitive and label-free approach for imaging of a wide variety of protein or peptide biomarkers from the surface of tissue sections, being currently used in an increasing number of biomedical applications such as biomarker discovery and tissue classification. In the field of rheumatology, MALDI-MSI has been applied to date for the analysis of joint tissues such as synovial membrane or cartilage. This review summarizes the studies and key achievements obtained using MALDI-MSI to increase understanding on rheumatic pathologies and to describe potential diagnostic or prognostic biomarkers of these diseases. This article is part of a Special Issue entitled: MALDI Imaging, edited by Dr. Corinna Henkel and Prof. Peter Hoffmann. Copyright © 2016 Elsevier B.V. All rights reserved.

A bioinspired catalytic aerobic oxidative C-H functionalization of primary aliphatic amines: synthesis of 1,2-disubstituted benzimidazoles.

PubMed

Nguyen, Khac Minh Huy; Largeron, Martine

2015-09-01

Aerobic oxidative CH functionalization of primary aliphatic amines has been accomplished with a biomimetic cooperative catalytic system to furnish 1,2-disubstituted benzimidazoles that play an important role as drug discovery targets. This one-pot atom-economical multistep process, which proceeds under mild conditions, with ambient air and equimolar amounts of each coupling partner, constitutes a convenient environmentally friendly strategy to functionalize non-activated aliphatic amines that remain challenging substrates for non-enzymatic catalytic aerobic systems. © 2015 The Authors. Published by Wiley-VCH Verlag GmbH & Co. KGaA. This is an open access article under the terms of Creative Commons Attribution NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

The International Human Epigenome Consortium Data Portal.

PubMed

Bujold, David; Morais, David Anderson de Lima; Gauthier, Carol; Côté, Catherine; Caron, Maxime; Kwan, Tony; Chen, Kuang Chung; Laperle, Jonathan; Markovits, Alexei Nordell; Pastinen, Tomi; Caron, Bryan; Veilleux, Alain; Jacques, Pierre-Étienne; Bourque, Guillaume

2016-11-23

The International Human Epigenome Consortium (IHEC) coordinates the production of reference epigenome maps through the characterization of the regulome, methylome, and transcriptome from a wide range of tissues and cell types. To define conventions ensuring the compatibility of datasets and establish an infrastructure enabling data integration, analysis, and sharing, we developed the IHEC Data Portal (http://epigenomesportal.ca/ihec). The portal provides access to >7,000 reference epigenomic datasets, generated from >600 tissues, which have been contributed by seven international consortia: ENCODE, NIH Roadmap, CEEHRC, Blueprint, DEEP, AMED-CREST, and KNIH. The portal enhances the utility of these reference maps by facilitating the discovery, visualization, analysis, download, and sharing of epigenomics data. The IHEC Data Portal is the official source to navigate through IHEC datasets and represents a strategy for unifying the distributed data produced by international research consortia. Crown Copyright © 2016. Published by Elsevier Inc. All rights reserved.

Banking biological collections: data warehousing, data mining, and data dilemmas in genomics and global health policy.

PubMed

Blatt, R J R

2000-01-01

While DNA databases may offer the opportunity to (1) assess population-based prevalence of specific genes and variants, (2) simplify the search for molecular markers, (3) improve targeted drug discovery and development for disease management, (4) refine strategies for disease prevention, and (5) provide the data necessary for evidence-based decision-making, serious scientific and social questions remain. Whether samples are identified, coded, or anonymous, biological banking raises profound ethical and legal issues pertaining to access, informed consent, privacy and confidentiality of genomic information, civil liberties, patenting, and proprietary rights. This paper provides an overview of key policy issues and questions pertaining to biological banking, with a focus on developments in specimen collection, transnational distribution, and public health and academic-industry research alliances. It highlights the challenges posed by the commercialization of genomics, and proposes the need for harmonization of biological banking policies.

Algorithms for Discovery of Multiple Markov Boundaries

PubMed Central

Statnikov, Alexander; Lytkin, Nikita I.; Lemeire, Jan; Aliferis, Constantin F.

2013-01-01

Algorithms for Markov boundary discovery from data constitute an important recent development in machine learning, primarily because they offer a principled solution to the variable/feature selection problem and give insight on local causal structure. Over the last decade many sound algorithms have been proposed to identify a single Markov boundary of the response variable. Even though faithful distributions and, more broadly, distributions that satisfy the intersection property always have a single Markov boundary, other distributions/data sets may have multiple Markov boundaries of the response variable. The latter distributions/data sets are common in practical data-analytic applications, and there are several reasons why it is important to induce multiple Markov boundaries from such data. However, there are currently no sound and efficient algorithms that can accomplish this task. This paper describes a family of algorithms TIE* that can discover all Markov boundaries in a distribution. The broad applicability as well as efficiency of the new algorithmic family is demonstrated in an extensive benchmarking study that involved comparison with 26 state-of-the-art algorithms/variants in 15 data sets from a diversity of application domains. PMID:25285052

Bridging the gap to therapeutic strategies based on connexin/pannexin biology.

PubMed

Naus, Christian C; Giaume, Christian

2016-11-29

A unique workshop was recently held focusing on enhancing collaborations leading to identify and update the development of therapeutic strategies targeting connexin/pannexin large pore channels. Basic scientists exploring the functions of these channels in various pathologies gathered together with leading pharma companies which are targeting gap junction proteins for specific therapeutic applications. This highlights how paths of discovery research can converge with therapeutic strategies in innovative ways to enhance target identification and validation.

Single nucleotide polymorphism discovery in rainbow trout by deep sequencing of a reduced representation library.

PubMed

Sánchez, Cecilia Castaño; Smith, Timothy P L; Wiedmann, Ralph T; Vallejo, Roger L; Salem, Mohamed; Yao, Jianbo; Rexroad, Caird E

2009-11-25

To enhance capabilities for genomic analyses in rainbow trout, such as genomic selection, a large suite of polymorphic markers that are amenable to high-throughput genotyping protocols must be identified. Expressed Sequence Tags (ESTs) have been used for single nucleotide polymorphism (SNP) discovery in salmonids. In those strategies, the salmonid semi-tetraploid genomes often led to assemblies of paralogous sequences and therefore resulted in a high rate of false positive SNP identification. Sequencing genomic DNA using primers identified from ESTs proved to be an effective but time consuming methodology of SNP identification in rainbow trout, therefore not suitable for high throughput SNP discovery. In this study, we employed a high-throughput strategy that used pyrosequencing technology to generate data from a reduced representation library constructed with genomic DNA pooled from 96 unrelated rainbow trout that represent the National Center for Cool and Cold Water Aquaculture (NCCCWA) broodstock population. The reduced representation library consisted of 440 bp fragments resulting from complete digestion with the restriction enzyme HaeIII; sequencing produced 2,000,000 reads providing an average 6 fold coverage of the estimated 150,000 unique genomic restriction fragments (300,000 fragment ends). Three independent data analyses identified 22,022 to 47,128 putative SNPs on 13,140 to 24,627 independent contigs. A set of 384 putative SNPs, randomly selected from the sets produced by the three analyses were genotyped on individual fish to determine the validation rate of putative SNPs among analyses, distinguish apparent SNPs that actually represent paralogous loci in the tetraploid genome, examine Mendelian segregation, and place the validated SNPs on the rainbow trout linkage map. Approximately 48% (183) of the putative SNPs were validated; 167 markers were successfully incorporated into the rainbow trout linkage map. In addition, 2% of the sequences from the validated markers were associated with rainbow trout transcripts. The use of reduced representation libraries and pyrosequencing technology proved to be an effective strategy for the discovery of a high number of putative SNPs in rainbow trout; however, modifications to the technique to decrease the false discovery rate resulting from the evolutionary recent genome duplication would be desirable.

ADMET biosensors: up-to-date issues and strategies.

PubMed

Fang, Yan; Offenhaeusser, Andrease

2004-12-01

This insight review introduces the new concepts, theories, technology, instruments, frontier issues, and key strategies of ADMET (absorption, distribution, metabolism, elimination, and toxicity) biosensors, from the fermi to the quantum levels. Information about ADMET, originating from one author's invention, a patented pharmacotherapy for rescuing cardio-cerebral vascular stunning and regulating vascular endothelial growth-factor signaling at the post-genomic level, can be detected by a new generation of ADMET biosensor. This is a single-cell/single-molecule field-effect transistor (FET) hybrid system, where single molecules or single cells are assembled at the FET surface in a high density array manner via complementary metal-oxide-semiconductor (CMOS)-compatible technologies. Within a given nanometer distance, ADMET-mediated oxidation-reduction (redox) potentials, electrochemistry responses, and electron transfer processes can be simultaneously and directly probed by the gates of field-effect transistor arrays. The nanometer details of the functional coupling principles and characterization technologies of DNA single-molecule/single-cell FETs, as well as the design of lab-on-a-chip instruments, are indicated. Four frontier issues and key strategies are elucidated in detail. This can lead to innovative technology for high-throughout screening of labs-on-chips to resolve the pharmaceutical industry's current bottleneck via novel, FET-based drug discovery and single-molecule/single-cell screening methods, which can bring about a pharmaceutical industry revolution in the 21st century.

Computational Methods Used in Hit-to-Lead and Lead Optimization Stages of Structure-Based Drug Discovery.

PubMed

Heifetz, Alexander; Southey, Michelle; Morao, Inaki; Townsend-Nicholson, Andrea; Bodkin, Mike J

2018-01-01

GPCR modeling approaches are widely used in the hit-to-lead (H2L) and lead optimization (LO) stages of drug discovery. The aims of these modeling approaches are to predict the 3D structures of the receptor-ligand complexes, to explore the key interactions between the receptor and the ligand and to utilize these insights in the design of new molecules with improved binding, selectivity or other pharmacological properties. In this book chapter, we present a brief survey of key computational approaches integrated with hierarchical GPCR modeling protocol (HGMP) used in hit-to-lead (H2L) and in lead optimization (LO) stages of structure-based drug discovery (SBDD). We outline the differences in modeling strategies used in H2L and LO of SBDD and illustrate how these tools have been applied in three drug discovery projects.

High-throughput strategies for the discovery and engineering of enzymes for biocatalysis.

PubMed

Jacques, Philippe; Béchet, Max; Bigan, Muriel; Caly, Delphine; Chataigné, Gabrielle; Coutte, François; Flahaut, Christophe; Heuson, Egon; Leclère, Valérie; Lecouturier, Didier; Phalip, Vincent; Ravallec, Rozenn; Dhulster, Pascal; Froidevaux, Rénato

2017-02-01

Innovations in novel enzyme discoveries impact upon a wide range of industries for which biocatalysis and biotransformations represent a great challenge, i.e., food industry, polymers and chemical industry. Key tools and technologies, such as bioinformatics tools to guide mutant library design, molecular biology tools to create mutants library, microfluidics/microplates, parallel miniscale bioreactors and mass spectrometry technologies to create high-throughput screening methods and experimental design tools for screening and optimization, allow to evolve the discovery, development and implementation of enzymes and whole cells in (bio)processes. These technological innovations are also accompanied by the development and implementation of clean and sustainable integrated processes to meet the growing needs of chemical, pharmaceutical, environmental and biorefinery industries. This review gives an overview of the benefits of high-throughput screening approach from the discovery and engineering of biocatalysts to cell culture for optimizing their production in integrated processes and their extraction/purification.

Leveraging the contribution of thermodynamics in drug discovery with the help of fluorescence-based thermal shift assays.

PubMed

Hau, Jean Christophe; Fontana, Patrizia; Zimmermann, Catherine; De Pover, Alain; Erdmann, Dirk; Chène, Patrick

2011-06-01

The development of new drugs with better pharmacological and safety properties mandates the optimization of several parameters. Today, potency is often used as the sole biochemical parameter to identify and select new molecules. Surprisingly, thermodynamics, which is at the core of any interaction, is rarely used in drug discovery, even though it has been suggested that the selection of scaffolds according to thermodynamic criteria may be a valuable strategy. This poor integration of thermodynamics in drug discovery might be due to difficulties in implementing calorimetry experiments despite recent technological progress in this area. In this report, the authors show that fluorescence-based thermal shift assays could be used as prescreening methods to identify compounds with different thermodynamic profiles. This approach allows a reduction in the number of compounds to be tested in calorimetry experiments, thus favoring greater integration of thermodynamics in drug discovery.

Next-generation sequencing in clinical virology: Discovery of new viruses.

PubMed

Datta, Sibnarayan; Budhauliya, Raghvendra; Das, Bidisha; Chatterjee, Soumya; Vanlalhmuaka; Veer, Vijay

2015-08-12

Viruses are a cause of significant health problem worldwide, especially in the developing nations. Due to different anthropological activities, human populations are exposed to different viral pathogens, many of which emerge as outbreaks. In such situations, discovery of novel viruses is utmost important for deciding prevention and treatment strategies. Since last century, a number of different virus discovery methods, based on cell culture inoculation, sequence-independent PCR have been used for identification of a variety of viruses. However, the recent emergence and commercial availability of next-generation sequencers (NGS) has entirely changed the field of virus discovery. These massively parallel sequencing platforms can sequence a mixture of genetic materials from a very heterogeneous mix, with high sensitivity. Moreover, these platforms work in a sequence-independent manner, making them ideal tools for virus discovery. However, for their application in clinics, sample preparation or enrichment is necessary to detect low abundance virus populations. A number of techniques have also been developed for enrichment or viral nucleic acids. In this manuscript, we review the evolution of sequencing; NGS technologies available today as well as widely used virus enrichment technologies. We also discuss the challenges associated with their applications in the clinical virus discovery.

A Combinatorial Platform for the Optimization of Peptidomimetic Methyl-Lysine Reader Antagonists

NASA Astrophysics Data System (ADS)

Barnash, Kimberly D.

Post-translational modification of histone N-terminal tails mediates chromatin compaction and, consequently, DNA replication, transcription, and repair. While numerous post-translational modifications decorate histone tails, lysine methylation is an abundant mark important for both gene activation and repression. Methyl-lysine (Kme) readers function through binding mono-, di-, or trimethyl-lysine. Chemical intervention of Kme readers faces numerous challenges due to the broad surface-groove interactions between readers and their cognate histone peptides; yet, the increasing interest in understanding chromatin-modifying complexes suggests tractable lead compounds for Kme readers are critical for elucidating the mechanisms of chromatin dysregulation in disease states and validating the druggability of these domains and complexes. The successful discovery of a peptide-derived chemical probe, UNC3866, for the Polycomb repressive complex 1 (PRC1) chromodomain Kme readers has proven the potential for selective peptidomimetic inhibition of reader function. Unfortunately, the systematic modification of peptides-to-peptidomimetics is a costly and inefficient strategy for target-class hit discovery against Kme readers. Through the exploration of biased chemical space via combinatorial on-bead libraries, we have developed two concurrent methodologies for Kme reader chemical probe discovery. We employ biased peptide combinatorial libraries as a hit discovery strategy with subsequent optimization via iterative targeted libraries. Peptide-to-peptidomimetic optimization through targeted library design was applied based on structure-guided library design around the interaction of the endogenous peptide ligand with three target Kme readers. Efforts targeting the WD40 reader EED led to the discovery of the 3-mer peptidomimetic ligand UNC5115 while combinatorial repurposing of UNC3866 for off-target chromodomains resulted in the discovery of UNC4991, a CDYL/2-selective ligand, and UNC4848, a MPP8 and CDYL/2 ligand. Ultimately, our efforts demonstrate the generalizability of a peptidomimetic combinatorial platform for the optimization of Kme reader ligands in a target class manner.

A rational workflow for sequential virtual screening of chemical libraries on searching for new tyrosinase inhibitors.

PubMed

Le-Thi-Thu, Huong; Casanola-Martín, Gerardo M; Marrero-Ponce, Yovani; Rescigno, Antonio; Abad, Concepcion; Khan, Mahmud Tareq Hassan

2014-01-01

The tyrosinase is a bifunctional, copper-containing enzyme widely distributed in the phylogenetic tree. This enzyme is involved in the production of melanin and some other pigments in humans, animals and plants, including skin pigmentations in mammals, and browning process in plants and vegetables. Therefore, enzyme inhibitors has been under the attention of the scientist community, due to its broad applications in food, cosmetic, agricultural and medicinal fields, to avoid the undesirable effects of abnormal melanin overproduction. However, the research of novel chemical with antityrosinase activity demands the use of more efficient tools to speed up the tyrosinase inhibitors discovery process. This chapter is focused in the different components of a predictive modeling workflow for the identification and prioritization of potential new compounds with activity against the tyrosinase enzyme. In this case, two structure chemical libraries Spectrum Collection and Drugbank are used in this attempt to combine different virtual screening data mining techniques, in a sequential manner helping to avoid the usually expensive and time consuming traditional methods. Some of the sequential steps summarize here comprise the use of drug-likeness filters, similarity searching, classification and potency QSAR multiclassifier systems, modeling molecular interactions systems, and similarity/diversity analysis. Finally, the methodologies showed here provide a rational workflow for virtual screening hit analysis and selection as a promissory drug discovery strategy for use in target identification phase.

Building Cognition: The Construction of Computational Representations for Scientific Discovery.

PubMed

Chandrasekharan, Sanjay; Nersessian, Nancy J

2015-11-01

Novel computational representations, such as simulation models of complex systems and video games for scientific discovery (Foldit, EteRNA etc.), are dramatically changing the way discoveries emerge in science and engineering. The cognitive roles played by such computational representations in discovery are not well understood. We present a theoretical analysis of the cognitive roles such representations play, based on an ethnographic study of the building of computational models in a systems biology laboratory. Specifically, we focus on a case of model-building by an engineer that led to a remarkable discovery in basic bioscience. Accounting for such discoveries requires a distributed cognition (DC) analysis, as DC focuses on the roles played by external representations in cognitive processes. However, DC analyses by and large have not examined scientific discovery, and they mostly focus on memory offloading, particularly how the use of existing external representations changes the nature of cognitive tasks. In contrast, we study discovery processes and argue that discoveries emerge from the processes of building the computational representation. The building process integrates manipulations in imagination and in the representation, creating a coupled cognitive system of model and modeler, where the model is incorporated into the modeler's imagination. This account extends DC significantly, and we present some of the theoretical and application implications of this extended account. Copyright © 2014 Cognitive Science Society, Inc.

An endogenous foamy virus in the aye-aye (Daubentonia madagascariensis).

PubMed

Han, Guan-Zhu; Worobey, Michael

2012-07-01

We report the discovery and analysis of an endogenous foamy virus (PSFVaye) within the genome of the aye-aye (Daubentonia madagascariensis), a strepsirrhine primate from Madagascar. Phylogenetic analyses indicate that PSFVaye is divergent from all known simian foamy viruses, suggesting an association between foamy viruses and primates since the haplorrhine-strepsirrhine split. The discovery of PSFVaye indicates that primate foamy virus might be more broadly distributed than previously thought.

Use of eQTL Analysis for the Discovery of Target Genes Identified by GWAS

DTIC Science & Technology

2014-04-01

technology. Cases having a RIN number of 7.0 or greater were considered good quality. Once completed, the optimum set of 500 samples were then selected for...AD_________________ Award Number: W81XWH-11-1-0261 TITLE: Use of eQTL Analysis for the Discovery...Distribution Unlimited The views, opinions and/or findings contained in this report are those of the author(s) and

Session Initiation Protocol Network Encryption Device Plain Text Domain Discovery Service

DTIC Science & Technology

2007-12-07

MONITOR’S REPORT NUMBER(S) 12. DISTRIBUTION / AVAILABILITY STATEMENT 13. SUPPLEMENTARY NOTES 14. ABSTRACT 15. SUBJECT TERMS 16. SECURITY CLASSIFICATION OF: a...such as the TACLANE, have developed unique discovery methods to establish Plain Text Domain (PTD) Security Associations (SA). All of these techniques...can include network and host Internet Protocol (IP) addresses, Information System Security Office (ISSO) point of contact information and PTD status

Multi-Protein Dynamic Combinatorial Chemistry: A Novel Strategy that Leads to Simultaneous Discovery of Subfamily-Selective Inhibitors for Nucleic Acid Demethylases FTO and ALKBH3.

PubMed

Das, Mohua; Tianming, Yang; Jinghua, Dong; Prasetya, Fransisca; Yiming, Xie; Wong, Kendra; Cheong, Adeline; Woon, Esther C Y

2018-06-19

Dynamic combinatorial chemistry (DCC) is a powerful supramolecular approach for discovering ligands for biomolecules. To date, most, if not all, biologically-templated DCC employ only a single biomolecule in directing the self-assembly process. To expand the scope and potential of DCC, herein, we developed a novel multi-protein DCC strategy which combines the discriminatory power of zwitterionic 'thermal-tag' with the sensitivity of differential scanning fluorimetry. This strategy enables the discovery of ligands against several proteins of interest concurrently. It is remarkably sensitive and could differentiate the binding of ligands to structurally-similar subfamily members, which is extremely challenging to achieve. Through this approach, we were able to simultaneously identify subfamily-selective probes against two clinically important epigenetic enzymes, FTO (7; IC₅₀ = 2.6 µM) and ALKBH3 (8; IC₅₀ = 3.7 µM). To our knowledge, this is the first report of a subfamily-selective ALKBH3 inhibitor. The developed strategy could, in principle, be adapted to a broad range of proteins, thus it shall be of widespread scientific interest. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Use of mRNA expression signatures to discover small molecule inhibitors of skeletal muscle atrophy

PubMed Central

Adams, Christopher M.; Ebert, Scott M.; Dyle, Michael C.

2017-01-01

Purpose of review Here, we discuss a recently developed experimental strategy for discovering small molecules with potential to prevent and treat skeletal muscle atrophy. Recent findings Muscle atrophy involves and requires widespread changes in skeletal muscle gene expression, which generate complex but measurable patterns of positive and negative changes in skeletal muscle mRNA levels (a.k.a. mRNA expression signatures of muscle atrophy). Many bioactive small molecules generate their own characteristic mRNA expression signatures, and by identifying small molecules whose signatures approximate mirror images of muscle atrophy signatures, one may identify small molecules with potential to prevent and/or reverse muscle atrophy. Unlike a conventional drug discovery approach, this strategy does not rely on a predefined molecular target but rather exploits the complexity of muscle atrophy to identify small molecules that counter the entire spectrum of pathological changes in atrophic muscle. We discuss how this strategy has been used to identify two natural compounds, ursolic acid and tomatidine, that reduce muscle atrophy and improve skeletal muscle function. Summary Discovery strategies based on mRNA expression signatures can elucidate new approaches for preserving and restoring muscle mass and function. PMID:25807353

Use of mRNA expression signatures to discover small molecule inhibitors of skeletal muscle atrophy.

PubMed

Adams, Christopher M; Ebert, Scott M; Dyle, Michael C

2015-05-01

Here, we discuss a recently developed experimental strategy for discovering small molecules with potential to prevent and treat skeletal muscle atrophy. Muscle atrophy involves and requires widespread changes in skeletal muscle gene expression, which generate complex but measurable patterns of positive and negative changes in skeletal muscle mRNA levels (a.k.a. mRNA expression signatures of muscle atrophy). Many bioactive small molecules generate their own characteristic mRNA expression signatures, and by identifying small molecules whose signatures approximate mirror images of muscle atrophy signatures, one may identify small molecules with potential to prevent and/or reverse muscle atrophy. Unlike a conventional drug discovery approach, this strategy does not rely on a predefined molecular target but rather exploits the complexity of muscle atrophy to identify small molecules that counter the entire spectrum of pathological changes in atrophic muscle. We discuss how this strategy has been used to identify two natural compounds, ursolic acid and tomatidine, that reduce muscle atrophy and improve skeletal muscle function. Discovery strategies based on mRNA expression signatures can elucidate new approaches for preserving and restoring muscle mass and function.

Phenome-driven disease genetics prediction toward drug discovery.

PubMed

Chen, Yang; Li, Li; Zhang, Guo-Qiang; Xu, Rong

2015-06-15

Discerning genetic contributions to diseases not only enhances our understanding of disease mechanisms, but also leads to translational opportunities for drug discovery. Recent computational approaches incorporate disease phenotypic similarities to improve the prediction power of disease gene discovery. However, most current studies used only one data source of human disease phenotype. We present an innovative and generic strategy for combining multiple different data sources of human disease phenotype and predicting disease-associated genes from integrated phenotypic and genomic data. To demonstrate our approach, we explored a new phenotype database from biomedical ontologies and constructed Disease Manifestation Network (DMN). We combined DMN with mimMiner, which was a widely used phenotype database in disease gene prediction studies. Our approach achieved significantly improved performance over a baseline method, which used only one phenotype data source. In the leave-one-out cross-validation and de novo gene prediction analysis, our approach achieved the area under the curves of 90.7% and 90.3%, which are significantly higher than 84.2% (P < e(-4)) and 81.3% (P < e(-12)) for the baseline approach. We further demonstrated that our predicted genes have the translational potential in drug discovery. We used Crohn's disease as an example and ranked the candidate drugs based on the rank of drug targets. Our gene prediction approach prioritized druggable genes that are likely to be associated with Crohn's disease pathogenesis, and our rank of candidate drugs successfully prioritized the Food and Drug Administration-approved drugs for Crohn's disease. We also found literature evidence to support a number of drugs among the top 200 candidates. In summary, we demonstrated that a novel strategy combining unique disease phenotype data with system approaches can lead to rapid drug discovery. nlp. edu/public/data/DMN © The Author 2015. Published by Oxford University Press.

Mainstream Media and Social Media Reactions to the Discovery of Extraterrestrial Life

NASA Astrophysics Data System (ADS)

Jones, Morris

The rise of online social media (such as Facebook and Twitter) has overturned traditional top-down and stovepiped channels for mass communications. As social media have risen, traditional media sources have been steadily crippled by economic problems, resulting in a loss of capabilities and credibility. Information can propagate rapidly without the inclusion of traditional editorial checks and controls. Mass communications strategies for any type of major announcement must account for this new media landscape. Scientists announcing the discovery of extraterrestrial life will trigger a multifaceted and unpredictable percolation of the story through the public sphere. They will also potentially struggle with misinformation, rumours and hoaxes. The interplay of official announcements with the discussions of an extraterrestrial discovery on social media has parallels with traditional theories of mass communications. A wide spectrum of different messages is likely to be received by different segments of the community, based on their usage patterns of various media and online communications. The presentation and interpretation of a discovery will be hotly debated and contested within online media environments. In extreme cases, this could lead to "editorial wars" on collaborative media projects as well as cyber-attacks on certain online services and individuals. It is unlikely that a clear and coherent message can be propagated to a near-universal level. This has the potential to contribute to inappropriate reactions in some sectors of the community. Preventing unnecessary panic will be a priority. In turn, the monitoring of online and social media will provide a useful tool for assessing public reactions to a discovery of extraterrestrial life. This will help to calibrate public communications strategies following in the wake of an initial announcement.

Cracking the regulatory code of biosynthetic gene clusters as a strategy for natural product discovery.

PubMed

Rigali, Sébastien; Anderssen, Sinaeda; Naômé, Aymeric; van Wezel, Gilles P

2018-01-05

The World Health Organization (WHO) describes antibiotic resistance as "one of the biggest threats to global health, food security, and development today", as the number of multi- and pan-resistant bacteria is rising dangerously. Acquired resistance phenomena also impair antifungals, antivirals, anti-cancer drug therapy, while herbicide resistance in weeds threatens the crop industry. On the positive side, it is likely that the chemical space of natural products goes far beyond what has currently been discovered. This idea is fueled by genome sequencing of microorganisms which unveiled numerous so-called cryptic biosynthetic gene clusters (BGCs), many of which are transcriptionally silent under laboratory culture conditions, and by the fact that most bacteria cannot yet be cultivated in the laboratory. However, brute force antibiotic discovery does not yield the same results as it did in the past, and researchers have had to develop creative strategies in order to unravel the hidden potential of microorganisms such as Streptomyces and other antibiotic-producing microorganisms. Identifying the cis elements and their corresponding transcription factors(s) involved in the control of BGCs through bioinformatic approaches is a promising strategy. Theoretically, we are a few 'clicks' away from unveiling the culturing conditions or genetic changes needed to activate the production of cryptic metabolites or increase the production yield of known compounds to make them economically viable. In this opinion article, we describe and illustrate the idea beyond 'cracking' the regulatory code for natural product discovery, by presenting a series of proofs of concept, and discuss what still should be achieved to increase the rate of success of this strategy. Copyright © 2018 Elsevier Inc. All rights reserved.

New discoveries of sylvatic Triatoma infestans (Hemiptera: Reduviidae) throughout the Bolivian Chaco.

PubMed

Waleckx, Etienne; Depickère, Stéphanie; Salas, Renata; Aliaga, Claudia; Monje, Marcelo; Calle, Hiber; Buitrago, Rosio; Noireau, François; Brenière, Simone Frédérique

2012-03-01

Sylvatic populations of Triatoma infestans might be involved in the recolonization of human dwellings. We report here the discoveries of new T. infestans sylvatic foci in the Bolivian Chaco. Eighty-one triatomines were caught, 38 of which were identified as T. infestans. Triatoma sordida and Panstrongylus geniculatus were the other species collected. One T. infestans and one T. sordida were infected with Trypanosoma cruzi TcI; one T. infestans was infected with TcII. These discoveries add to the debate on the geographic distribution of sylvatic T. infestans populations, the geographic origin of the species, and the epidemiological role of these populations.

New Discoveries of Sylvatic Triatoma infestans (Hemiptera: Reduviidae) Throughout the Bolivian Chaco

PubMed Central

Waleckx, Etienne; Depickère, Stéphanie; Salas, Renata; Aliaga, Claudia; Monje, Marcelo; Calle, Hiber; Buitrago, Rosio; Noireau, François; Brenière, Simone Frédérique

2012-01-01

Sylvatic populations of Triatoma infestans might be involved in the recolonization of human dwellings. We report here the discoveries of new T. infestans sylvatic foci in the Bolivian Chaco. Eighty-one triatomines were caught, 38 of which were identified as T. infestans. Triatoma sordida and Panstrongylus geniculatus were the other species collected. One T. infestans and one T. sordida were infected with Trypanosoma cruzi TcI; one T. infestans was infected with TcII. These discoveries add to the debate on the geographic distribution of sylvatic T. infestans populations, the geographic origin of the species, and the epidemiological role of these populations. PMID:22403316

Privacy-Preserving Relationship Path Discovery in Social Networks

NASA Astrophysics Data System (ADS)

Mezzour, Ghita; Perrig, Adrian; Gligor, Virgil; Papadimitratos, Panos

As social networks sites continue to proliferate and are being used for an increasing variety of purposes, the privacy risks raised by the full access of social networking sites over user data become uncomfortable. A decentralized social network would help alleviate this problem, but offering the functionalities of social networking sites is a distributed manner is a challenging problem. In this paper, we provide techniques to instantiate one of the core functionalities of social networks: discovery of paths between individuals. Our algorithm preserves the privacy of relationship information, and can operate offline during the path discovery phase. We simulate our algorithm on real social network topologies.

An improved AVC strategy applied in distributed wind power system

NASA Astrophysics Data System (ADS)

Zhao, Y. N.; Liu, Q. H.; Song, S. Y.; Mao, W.

2016-08-01

Traditional AVC strategy is mainly used in wind farm and only concerns about grid connection point, which is not suitable for distributed wind power system. Therefore, this paper comes up with an improved AVC strategy applied in distributed wind power system. The strategy takes all nodes of distribution network into consideration and chooses the node having the most serious voltage deviation as control point to calculate the reactive power reference. In addition, distribution principles can be divided into two conditions: when wind generators access to network on single node, the reactive power reference is distributed according to reactive power capacity; when wind generators access to network on multi-node, the reference is distributed according to sensitivity. Simulation results show the correctness and reliability of the strategy. Compared with traditional control strategy, the strategy described in this paper can make full use of generators reactive power output ability according to the distribution network voltage condition and improve the distribution network voltage level effectively.

The future of discovery chemistry: quo vadis? Academic to industrial--the maturation of medicinal chemistry to chemical biology.

PubMed

Hoffmann, Torsten; Bishop, Cheryl

2010-04-01

At Roche, we set out to think about the future role of medicinal chemistry in drug discovery in a project involving both Roche internal stakeholders and external experts in drug discovery chemistry. To derive a coherent strategy, selected scientists were asked to take extreme positions and to derive two orthogonal strategic options: chemistry as the traditional mainstream science and chemistry as the central entrepreneurial science. We believe today's role of medicinal chemistry in industry has remained too narrow. To provide the innovation that industry requires, medicinal chemistry must play its part and diversify at pace with our increasing understanding of chemical biology and network pharmacology. 2010 Elsevier Ltd. All rights reserved.

NREL Explains the Higher Cellulolytic Activity of a Vital Microorganism

DOE Office of Scientific and Technical Information (OSTI.GOV)

The discovery of a new mode of action by C. thermocellum to convert biomass to biofuels is significant because the bacterium is already recognized as one of the most effective in the biosphere. Researchers found that, in addition to using common cellulase degradation mechanisms attached to cells, C. thermocellum also uses a new category of cell-free scaffolded enzymes. The new discovery will influence the strategies used to improve the cellulolytic activity of biomass degrading microbes going forward. Better understanding of this bacterium could lead to cheaper production of ethanol and drop-in fuels. Also, this discovery demonstrates that nature's biomass conversionmore » behaviors are not fully understood and remain as opportunities for future microbial/enzyme engineering efforts.« less

Discovery of a Chemical Probe Bisamide (CCT251236): An Orally Bioavailable Efficacious Pirin Ligand from a Heat Shock Transcription Factor 1 (HSF1) Phenotypic Screen

PubMed Central

2016-01-01

Phenotypic screens, which focus on measuring and quantifying discrete cellular changes rather than affinity for individual recombinant proteins, have recently attracted renewed interest as an efficient strategy for drug discovery. In this article, we describe the discovery of a new chemical probe, bisamide (CCT251236), identified using an unbiased phenotypic screen to detect inhibitors of the HSF1 stress pathway. The chemical probe is orally bioavailable and displays efficacy in a human ovarian carcinoma xenograft model. By developing cell-based SAR and using chemical proteomics, we identified pirin as a high affinity molecular target, which was confirmed by SPR and crystallography. PMID:28004573

Blueprint for antimicrobial hit discovery targeting metabolic networks.

PubMed

Shen, Y; Liu, J; Estiu, G; Isin, B; Ahn, Y-Y; Lee, D-S; Barabási, A-L; Kapatral, V; Wiest, O; Oltvai, Z N

2010-01-19

Advances in genome analysis, network biology, and computational chemistry have the potential to revolutionize drug discovery by combining system-level identification of drug targets with the atomistic modeling of small molecules capable of modulating their activity. To demonstrate the effectiveness of such a discovery pipeline, we deduced common antibiotic targets in Escherichia coli and Staphylococcus aureus by identifying shared tissue-specific or uniformly essential metabolic reactions in their metabolic networks. We then predicted through virtual screening dozens of potential inhibitors for several enzymes of these reactions and showed experimentally that a subset of these inhibited both enzyme activities in vitro and bacterial cell viability. This blueprint is applicable for any sequenced organism with high-quality metabolic reconstruction and suggests a general strategy for strain-specific antiinfective therapy.

Tiered analytics for purity assessment of macrocyclic peptides in drug discovery: Analytical consideration and method development.

PubMed

Qian Cutrone, Jingfang Jenny; Huang, Xiaohua Stella; Kozlowski, Edward S; Bao, Ye; Wang, Yingzi; Poronsky, Christopher S; Drexler, Dieter M; Tymiak, Adrienne A

2017-05-10

Synthetic macrocyclic peptides with natural and unnatural amino acids have gained considerable attention from a number of pharmaceutical/biopharmaceutical companies in recent years as a promising approach to drug discovery, particularly for targets involving protein-protein or protein-peptide interactions. Analytical scientists charged with characterizing these leads face multiple challenges including dealing with a class of complex molecules with the potential for multiple isomers and variable charge states and no established standards for acceptable analytical characterization of materials used in drug discovery. In addition, due to the lack of intermediate purification during solid phase peptide synthesis, the final products usually contain a complex profile of impurities. In this paper, practical analytical strategies and methodologies were developed to address these challenges, including a tiered approach to assessing the purity of macrocyclic peptides at different stages of drug discovery. Our results also showed that successful progression and characterization of a new drug discovery modality benefited from active analytical engagement, focusing on fit-for-purpose analyses and leveraging a broad palette of analytical technologies and resources. Copyright © 2017. Published by Elsevier B.V.

Past Strategies and Future Directions for Identifying AMP-Activated Protein Kinase (AMPK) Modulators

PubMed Central

Sinnett, Sarah E.; Brenman, Jay E.

2014-01-01

AMP-activated protein kinase (AMPK) is a promising therapeutic target for cancer, type II diabetes, and other illnesses characterized by abnormal energy utilization. During the last decade, numerous labs have published a range of methods for identifying novel AMPK modulators. The current understanding of AMPK structure and regulation, however, has propelled a paradigm shift in which many researchers now consider ADP to be an additional regulatory nucleotide of AMPK. How can the AMPK community apply this new understanding of AMPK signaling to translational research? Recent insights into AMPK structure, regulation, and holoenzyme-sensitive signaling may provide the hindsight needed to clearly evaluate the strengths and weaknesses of past AMPK drug discovery efforts. Improving future strategies for AMPK drug discovery will require pairing the current understanding of AMPK signaling with improved experimental designs. PMID:24583089

Therapeutic potentials of gene silencing by RNA interference: principles, challenges, and new strategies.

PubMed

Deng, Yan; Wang, Chi Chiu; Choy, Kwong Wai; Du, Quan; Chen, Jiao; Wang, Qin; Li, Lu; Chung, Tony Kwok Hung; Tang, Tao

2014-04-01

During recent decades there have been remarkable advances in biology, in which one of the most important discoveries is RNA interference (RNAi). RNAi is a specific post-transcriptional regulatory pathway that can result in silencing gene functions. Efforts have been done to translate this new discovery into clinical applications for disease treatment. However, technical difficulties restrict the development of RNAi, including stability, off-target effects, immunostimulation and delivery problems. Researchers have attempted to surmount these barriers and improve the bioavailability and safety of RNAi-based therapeutics by optimizing the chemistry and structure of these molecules. This paper aimed to describe the principles of RNA interference, review the therapeutic potential in various diseases and discuss the new strategies for in vivo delivery of RNAi to overcome the challenges. Copyright © 2013 Elsevier B.V. All rights reserved.

Malaria vaccines: high-throughput tools for antigens discovery with potential for their development

PubMed Central

Céspedes, Nora; Vallejo, Andrés; Arévalo-Herrera, Myriam

2013-01-01

Malaria is a disease induced by parasites of the Plasmodium genus, which are transmitted by Anopheles mosquitoes and represents a great socio-economic burden Worldwide. Plasmodium vivax is the second species of malaria Worldwide, but it is the most prevalent in Latin America and other regions of the planet. It is currently considered that vaccines represent a cost-effective strategy for controlling transmissible diseases and could complement other malaria control measures; however, the chemical and immunological complexity of the parasite has hindered development of effective vaccines. Recent availability of several genomes of Plasmodium species, as well as bioinformatic tools are allowing the selection of large numbers of proteins and analysis of their immune potential. Herein, we review recently developed strategies for discovery of novel antigens with potential for malaria vaccine development. PMID:24892459

Strategies for the follow-up of gravitational wave transients with the Cherenkov Telescope Array

NASA Astrophysics Data System (ADS)

Bartos, I.; Di Girolamo, T.; Gair, J. R.; Hendry, M.; Heng, I. S.; Humensky, T. B.; Márka, S.; Márka, Z.; Messenger, C.; Mukherjee, R.; Nieto, D.; O'Brien, P.; Santander, M.

2018-06-01

The observation of the electromagnetic counterpart of gravitational-wave (GW) transient GW170817 demonstrated the potential in extracting astrophysical information from multimessenger discoveries. The forthcoming deployment of the first telescopes of the Cherenkov Telescope Array (CTA) observatory will coincide with Advanced LIGO/Virgo's next observing run, O3, enabling the monitoring of gamma-ray emission at E > 20 GeV, and thus particle acceleration, from GW sources. CTA will not be greatly limited by the precision of GW localization as it will be capable of rapidly covering the GW error region with sufficient sensitivity. We examine the current status of GW searches and their follow-up effort, as well as the status of CTA, in order to identify some of the general strategies that will enhance CTA's contribution to multimessenger discoveries.

Five critical elements to ensure the precision medicine.

PubMed

Chen, Chengshui; He, Mingyan; Zhu, Yichun; Shi, Lin; Wang, Xiangdong

2015-06-01

The precision medicine as a new emerging area and therapeutic strategy has occurred and was practiced in the individual and brought unexpected successes, and gained high attentions from professional and social aspects as a new path to improve the treatment and prognosis of patients. There will be a number of new components to appear or be discovered, of which clinical bioinformatics integrates clinical phenotypes and informatics with bioinformatics, computational science, mathematics, and systems biology. In addition to those tools, precision medicine calls more accurate and repeatable methodologies for the identification and validation of gene discovery. Precision medicine will bring more new therapeutic strategies, drug discovery and development, and gene-oriented treatment. There is an urgent need to identify and validate disease-specific, mechanism-based, or epigenetics-dependent biomarkers to monitor precision medicine, and develop "precision" regulations to guard the application of precision medicine.

[Strategy and collaboration between medicinal chemists and pharmaceutical scientists for drug delivery systems].

PubMed

Mano, Takashi

2013-01-01

In order to successfully apply drug delivery systems (DDS) to new chemical entities (NCEs), collaboration between medicinal chemists and formulation scientists is critical for efficient drug discovery. Formulation scientists have to use 'language' that medicinal chemists understand to help promote mutual understanding, and medicinal chemists and formulation scientists have to set up strategies to use suitable DDS technologies at the discovery phase of the programmes to ensure successful transfer into the development phase. In this review, strategies of solubilisation formulation for oral delivery, inhalation delivery, nasal delivery and bioconjugation are all discussed. For example, for oral drug delivery, multiple initiatives can be proposed to improve the process to select an optimal delivery option for an NCE. From a technical perspective, formulation scientists have to explain the scope and limitations of formulations as some DDS technologies might be applicable only to limited chemical spaces. Other limitations could be the administered dose and, cost, time and resources for formulation development and manufacturing. Since DDS selection is best placed as part of lead-optimisation, formulation scientists need to be involved in discovery projects at lead selection and optimisation stages. The key to success in their collaboration is to facilitate communication between these two areas of expertise at both a strategic and scientific level. Also, it would be beneficial for medicinal chemists and formulation scientists to set common goals to improve the process of collaboration and build long term partnerships to improve DDS.

From genomics to metabolomics, moving toward an integrated strategy for the discovery of fungal secondary metabolites.

PubMed

Hautbergue, T; Jamin, E L; Debrauwer, L; Puel, O; Oswald, I P

2018-02-21

Fungal secondary metabolites are defined by bioactive properties that ensure adaptation of the fungus to its environment. Although some of these natural products are promising sources of new lead compounds especially for the pharmaceutical industry, others pose risks to human and animal health. The identification of secondary metabolites is critical to assessing both the utility and risks of these compounds. Since fungi present biological specificities different from other microorganisms, this review covers the different strategies specifically used in fungal studies to perform this critical identification. Strategies focused on the direct detection of the secondary metabolites are firstly reported. Particularly, advances in high-throughput untargeted metabolomics have led to the generation of large datasets whose exploitation and interpretation generally require bioinformatics tools. Then, the genome-based methods used to study the entire fungal metabolic potential are reported. Transcriptomic and proteomic tools used in the discovery of fungal secondary metabolites are presented as links between genomic methods and metabolomic experiments. Finally, the influence of the culture environment on the synthesis of secondary metabolites by fungi is highlighted as a major factor to consider in research on fungal secondary metabolites. Through this review, we seek to emphasize that the discovery of natural products should integrate all of these valuable tools. Attention is also drawn to emerging technologies that will certainly revolutionize fungal research and to the use of computational tools that are necessary but whose results should be interpreted carefully.

Drug discovery and development for rare genetic disorders.

PubMed

Sun, Wei; Zheng, Wei; Simeonov, Anton

2017-09-01

Approximately 7,000 rare diseases affect millions of individuals in the United States. Although rare diseases taken together have an enormous impact, there is a significant gap between basic research and clinical interventions. Opportunities now exist to accelerate drug development for the treatment of rare diseases. Disease foundations and research centers worldwide focus on better understanding rare disorders. Here, the state-of-the-art drug discovery strategies for small molecules and biological approaches for orphan diseases are reviewed. Rare diseases are usually genetic diseases; hence, employing pharmacogenetics to develop treatments and using whole genome sequencing to identify the etiologies for such diseases are appropriate strategies to exploit. Beginning with high throughput screening of small molecules, the benefits and challenges of target-based and phenotypic screens are discussed. Explanations and examples of drug repurposing are given; drug repurposing as an approach to quickly move programs to clinical trials is evaluated. Consideration is given to the category of biologics which include gene therapy, recombinant proteins, and autologous transplants. Disease models, including animal models and induced pluripotent stem cells (iPSCs) derived from patients, are surveyed. Finally, the role of biomarkers in drug discovery and development, as well as clinical trials, is elucidated. © 2017 Wiley Periodicals, Inc.

Draft Genome of Scalindua rubra, Obtained from the Interface Above the Discovery Deep Brine in the Red Sea, Sheds Light on Potential Salt Adaptation Strategies in Anammox Bacteria.

PubMed

Speth, Daan R; Lagkouvardos, Ilias; Wang, Yong; Qian, Pei-Yuan; Dutilh, Bas E; Jetten, Mike S M

2017-07-01

Several recent studies have indicated that members of the phylum Planctomycetes are abundantly present at the brine-seawater interface (BSI) above multiple brine pools in the Red Sea. Planctomycetes include bacteria capable of anaerobic ammonium oxidation (anammox). Here, we investigated the possibility of anammox at BSI sites using metagenomic shotgun sequencing of DNA obtained from the BSI above the Discovery Deep brine pool. Analysis of sequencing reads matching the 16S rRNA and hzsA genes confirmed presence of anammox bacteria of the genus Scalindua. Phylogenetic analysis of the 16S rRNA gene indicated that this Scalindua sp. belongs to a distinct group, separate from the anammox bacteria in the seawater column, that contains mostly sequences retrieved from high-salt environments. Using coverage- and composition-based binning, we extracted and assembled the draft genome of the dominant anammox bacterium. Comparative genomic analysis indicated that this Scalindua species uses compatible solutes for osmoadaptation, in contrast to other marine anammox bacteria that likely use a salt-in strategy. We propose the name Candidatus Scalindua rubra for this novel species, alluding to its discovery in the Red Sea.

Co-evolution of payoff strategy and interaction strategy in prisoner's dilemma game

NASA Astrophysics Data System (ADS)

Zhang, Kangjie; Cheng, Hongyan

2016-11-01

Co-evolutionary dynamical models, providing a realistic paradigm for investigating complex system, have been extensively studied. In this paper, the co-evolution of payoff strategy and interaction strategy is studied. Starting with an initial Gaussian distribution of payoff strategy r with the mean u and the variance q, we focus on the final distribution of the payoff strategy. We find that final distribution of the payoff strategy may display different structures depending on parameters. In the ranges u < - 1 and u > 3, the distribution displays a single-peak structure which is symmetric about r = u. The distribution manifests itself as a double-peak structure in the range - 1 < u < 3 although a fake three-peak structure shows up in range 1 < u < 2. The explanations on the formation of different types of payoff strategy distributions are presented.

QSAR studies in the discovery of novel type-II diabetic therapies.

PubMed

Abuhammad, Areej; Taha, Mutasem O

2016-01-01

Type-II diabetes mellitus (T2DM) is a complex chronic disease that represents a major therapeutic challenge. Despite extensive efforts in T2DM drug development, therapies remain unsatisfactory. Currently, there are many novel and important antidiabetic drug targets under investigation by many research groups worldwide. One of the main challenges to develop effective orally active hypoglycemic agents is off-target effects. Computational tools have impacted drug discovery at many levels. One of the earliest methods is quantitative structure-activity relationship (QSAR) studies. QSAR strategies help medicinal chemists understand the relationship between hypoglycemic activity and molecular properties. Hence, QSAR may hold promise in guiding the synthesis of specifically designed novel ligands that demonstrate high potency and target selectivity. This review aims to provide an overview of the QSAR strategies used to model antidiabetic agents. In particular, this review focuses on drug targets that raised recent scientific interest and/or led to successful antidiabetic agents in the market. Special emphasis has been made on studies that led to the identification of novel antidiabetic scaffolds. Computer-aided molecular design and discovery techniques like QSAR have a great potential in designing leads against complex diseases such as T2DM. Combined with other in silico techniques, QSAR can provide more useful and rational insights to facilitate the discovery of novel compounds. However, since T2DM is a complex disease that includes several faulty biological targets, multi-target QSAR studies are recommended in the future to achieve efficient antidiabetic therapies.

The Ocean 180 Video Challenge: An Innovative Broader Impacts Strategy for Helping Scientists Share Discoveries and Connect with Classrooms

NASA Astrophysics Data System (ADS)

Tankersley, R. A.; Watson, M.; Windsor, J. G.; Buckley, M.; Diederick, L.

2014-12-01

Scientists conduct exciting, ground-breaking research that addresses many of world's greatest challenges. Yet, far too often, the importance, meaning, and relevance of their discoveries are never shared with persons outside their discipline. Recognizing the need for scientists to communicate more effectively with the public, the Florida Center for Ocean Sciences Education Excellence (COSEE Florida) saw an opportunity to connect the two through film. In the fall 2013, COSEE Florida launched the Ocean 180 Video Challenge to tap into the competitive spirit of scientists and inspire them to share their latest discoveries with the public. The competition encouraged scientists to submit short, 3-minute video abstracts summarizing the important findings of recent peer-reviewed papers and highlighting the relevance, meaning, and implications of the research to persons outside their discipline. Videos were initially screened and evaluated by a team of science and communication experts and the winners (from a field of ten finalists) were selected by more than 30,000 middle school students from 285 schools in 13 countries. Our presentation will review the outcomes and lessons learned from the 2014 competition and describe how contest videos are being used for professional development/training and educational purposes. We will also describe how video competitions can benefit both scientists and the target audience and be effective outreach strategies for encouraging scientists to share new discoveries and their enthusiasm for science with K-12 students and the public.

Strategies for Utilizing Neuroimaging Biomarkers in CNS Drug Discovery and Development: CINP/JSNP Working Group Report.

PubMed

Suhara, Tetsuya; Chaki, Shigeyuki; Kimura, Haruhide; Furusawa, Makoto; Matsumoto, Mitsuyuki; Ogura, Hiroo; Negishi, Takaaki; Saijo, Takeaki; Higuchi, Makoto; Omura, Tomohiro; Watanabe, Rira; Miyoshi, Sosuke; Nakatani, Noriaki; Yamamoto, Noboru; Liou, Shyh-Yuh; Takado, Yuhei; Maeda, Jun; Okamoto, Yasumasa; Okubo, Yoshiaki; Yamada, Makiko; Ito, Hiroshi; Walton, Noah M; Yamawaki, Shigeto

2017-04-01

Despite large unmet medical needs in the field for several decades, CNS drug discovery and development has been largely unsuccessful. Biomarkers, particularly those utilizing neuroimaging, have played important roles in aiding CNS drug development, including dosing determination of investigational new drugs (INDs). A recent working group was organized jointly by CINP and Japanese Society of Neuropsychopharmacology (JSNP) to discuss the utility of biomarkers as tools to overcome issues of CNS drug development.The consensus statement from the working group aimed at creating more nuanced criteria for employing biomarkers as tools to overcome issues surrounding CNS drug development. To accomplish this, a reverse engineering approach was adopted, in which criteria for the utilization of biomarkers were created in response to current challenges in the processes of drug discovery and development for CNS disorders. Based on this analysis, we propose a new paradigm containing 5 distinct tiers to further clarify the use of biomarkers and establish new strategies for decision-making in the context of CNS drug development. Specifically, we discuss more rational ways to incorporate biomarker data to determine optimal dosing for INDs with novel mechanisms and targets, and propose additional categorization criteria to further the use of biomarkers in patient stratification and clinical efficacy prediction. Finally, we propose validation and development of new neuroimaging biomarkers through public-private partnerships to further facilitate drug discovery and development for CNS disorders. © The Author 2016. Published by Oxford University Press on behalf of CINP.

Open Access High Throughput Drug Discovery in the Public Domain: A Mount Everest in the Making

PubMed Central

Roy, Anuradha; McDonald, Peter R.; Sittampalam, Sitta; Chaguturu, Rathnam

2013-01-01

High throughput screening (HTS) facilitates screening large numbers of compounds against a biochemical target of interest using validated biological or biophysical assays. In recent years, a significant number of drugs in clinical trails originated from HTS campaigns, validating HTS as a bona fide mechanism for hit finding. In the current drug discovery landscape, the pharmaceutical industry is embracing open innovation strategies with academia to maximize their research capabilities and to feed their drug discovery pipeline. The goals of academic research have therefore expanded from target identification and validation to probe discovery, chemical genomics, and compound library screening. This trend is reflected in the emergence of HTS centers in the public domain over the past decade, ranging in size from modestly equipped academic screening centers to well endowed Molecular Libraries Probe Centers Network (MLPCN) centers funded by the NIH Roadmap initiative. These centers facilitate a comprehensive approach to probe discovery in academia and utilize both classical and cutting-edge assay technologies for executing primary and secondary screening campaigns. The various facets of academic HTS centers as well as their implications on technology transfer and drug discovery are discussed, and a roadmap for successful drug discovery in the public domain is presented. New lead discovery against therapeutic targets, especially those involving the rare and neglected diseases, is indeed a Mount Everestonian size task, and requires diligent implementation of pharmaceutical industry’s best practices for a successful outcome. PMID:20809896

A Comprehensive Tool and Analytical Pathway for Differential Molecular Profiling and Biomarker Discovery

DTIC Science & Technology

2014-10-20

three possiblities: AKR , B6, and BALB_B) and MUP Protein (containing two possibilities: Intact and Denatured), then you can view a plot of the Strain...the tags for the last two labels. Again, if the attribute Strain has three tags: AKR , B6, 74 Distribution A . Approved for public release...AFRL-RH-WP-TR-2014-0131 A COMPREHENSIVE TOOL AND ANALYTICAL PATHWAY FOR DIFFERENTIAL MOLECULAR PROFILING AND BIOMARKER DISCOVERY

Component architecture in drug discovery informatics.

PubMed

Smith, Peter M

2002-05-01

This paper reviews the characteristics of a new model of computing that has been spurred on by the Internet, known as Netcentric computing. Developments in this model led to distributed component architectures, which, although not new ideas, are now realizable with modern tools such as Enterprise Java. The application of this approach to scientific computing, particularly in pharmaceutical discovery research, is discussed and highlighted by a particular case involving the management of biological assay data.

Discovery of Sound in the Sea 2013 Annual Report

DTIC Science & Technology

2013-09-30

develop and maintain resources that address the long-term goal. The resources include a website (Figure 1), a tri-fold educational pamphlet (available in...on whale watches during the winter months. The DOSITS tri-fold brochure was translated to French for distribution at the 21st International...University of Rhode Island. (tri-fold pamphlet ) Vigness-Raposa, K.J., Scowcroft, G., Miller, J.H., and Ketten, D.R. 2012. Discovery of Sound in

Systematic and comprehensive strategy for metabolite profiling in bioanalysis using software-assisted HPLC-Q-TOF: magnoflorine as an example.

PubMed

Tian, Xiaoting; Zhang, Yucheng; Li, Zhixiong; Hu, Pei; Chen, Mingcang; Sun, Zhaolin; Lin, Yunfei; Pan, Guoyu; Huang, Chenggang

2016-03-01

Metabolite profiling plays a crucial role in drug discovery and development, and HPLC-Q-TOF has evolved into a powerful and effective high-resolution analytical tool for metabolite detection. However, traditional empirical identification is laborious and incomplete. This paper presents a systematic and comprehensive strategy for elucidating metabolite structures using software-assisted HPLC-Q-TOF that takes full advantage of data acquisition, data processing, and data mining technologies, especially for high-throughput metabolite screening. This strategy has been successfully applied in the study of magnoflorine metabolism based on our previous report of its poor bioavailability and drug-drug interactions. In this report, 23 metabolites of magnoflorine were tentatively identified with detailed fragmentation pathways in rat biological samples (urine, feces, plasma, and various organs) after i.p. or i.g. administration, and for most of these metabolites, the metabolic sites were determined. The phase I biotransformations of magnoflorine (M1-M7, M10-M14) consist of demethylation, dehydrogenation, hydroxylation, methylene to ketone transformation, N-ring opening, and dehydroxylation. The phase II biotransformations (M8, M9, and M15-M23) consist of methylation, acetylation, glucuronidation, and N-acetylcysteine conjugation. The results indicate that the extensive metabolism and wide tissue distribution of magnoflorine and its metabolites may partly contribute to its poor bioavailability and drug-drug interaction, and i.p. administration should thus be a suitable approach for isolating magnoflorine metabolites. In summary, this strategy could provide an efficient, rapid, and reliable method for the structural characterization of drug metabolites and may be applicable for general Q-TOF users.

Plant uncoupling mitochondrial proteins.

PubMed

Vercesi, Aníbal Eugênio; Borecký, Jiri; Maia, Ivan de Godoy; Arruda, Paulo; Cuccovia, Iolanda Midea; Chaimovich, Hernan

2006-01-01

Uncoupling proteins (UCPs) are membrane proteins that mediate purine nucleotide-sensitive free fatty acid-activated H(+) flux through the inner mitochondrial membrane. After the discovery of UCP in higher plants in 1995, it was acknowledged that these proteins are widely distributed in eukaryotic organisms. The widespread presence of UCPs in eukaryotes implies that these proteins may have functions other than thermogenesis. In this review, we describe the current knowledge of plant UCPs, including their discovery, biochemical properties, distribution, gene family, gene expression profiles, regulation of gene expression, and evolutionary aspects. Expression analyses and functional studies on the plant UCPs under normal and stressful conditions suggest that UCPs regulate energy metabolism in the cellular responses to stress through regulation of the electrochemical proton potential (Deltamu(H)+) and production of reactive oxygen species.

Strategies for the synthesis of supported gold palladium nanoparticles with controlled morphology and composition.

PubMed

Hutchings, Graham J; Kiely, Christopher J

2013-08-20

The discovery that supported gold nanoparticles are exceptionally effective catalysts for redox reactions has led to an explosion of interest in gold nanoparticles. In addition, incorporating a second metal as an alloy with gold can enhance the catalyst performance even more. The addition of small amounts of gold to palladium, in particular, and vice versa significantly enhances the activity of supported gold-palladium nanoparticles as redox catalysts through what researchers believe is an electronic effect. In this Account, we describe and discuss methodologies for the synthesis of supported gold-palladium nanoparticles and their use as heterogeneous catalysts. In general, three key challenges need to be addressed in the synthesis of bimetallic nanoparticles: (i) control of the particle morphology, (ii) control of the particle size distribution, and (iii) control of the nanoparticle composition. We describe three methodologies to address these challenges. First, we discuss the relatively simple method of coimpregnation. Impregnation allows control of particle morphology during alloy formation but does not control the particle compositions or the particle size distribution. Even so, we contend that this method is the best preparation method in the catalyst discovery phase of any project, since it permits the investigation of many different catalyst structures in one experiment, which may aid the identification of new catalysts. A second approach, sol-immobilization, allows enhanced control of the particle size distribution and the particle morphology, but control of the composition of individual nanoparticles is not possible. Finally, a modified impregnation method can allow the control of all three of these crucial parameters. We discuss the effect of the different methodologies on three redox reactions: benzyl alcohol oxidation, toluene oxidation, and the direct synthesis of hydrogen peroxide. We show that the coimpregnation method provides the best reaction selectivity for benzyl alcohol oxidation and the direct synthesis of hydrogen peroxide. However, because of the reaction mechanism, the sol-immobilzation method gives very active and selective catalysts for toluene oxidation. We discuss the possible nature of the preferred active structures of the supported nanoparticles for these reactions. This paper is based on the IACS Heinz Heinemann Award Lecture entitled "Catalysis using gold nanoparticles" which was given in Munich in July 2012.

Single nucleotide polymorphism (SNP) discovery in duplicated genomes: intron-primed exon-crossing (IPEC) as a strategy for avoiding amplification of duplicated loci in Atlantic salmon (Salmo salar) and other salmonid fishes

PubMed Central

Ryynänen, Heikki J; Primmer, Craig R

2006-01-01

Background Single nucleotide polymorphisms (SNPs) represent the most abundant type of DNA variation in the vertebrate genome, and their applications as genetic markers in numerous studies of molecular ecology and conservation of natural populations are emerging. Recent large-scale sequencing projects in several fish species have provided a vast amount of data in public databases, which can be utilized in novel SNP discovery in salmonids. However, the suggested duplicated nature of the salmonid genome may hamper SNP characterization if the primers designed in conserved gene regions amplify multiple loci. Results Here we introduce a new intron-primed exon-crossing (IPEC) method in an attempt to overcome this duplication problem, and also evaluate different priming methods for SNP discovery in Atlantic salmon (Salmo salar) and other salmonids. A total of 69 loci with differing priming strategies were screened in S. salar, and 27 of these produced ~13 kb of high-quality sequence data consisting of 19 SNPs or indels (one per 680 bp). The SNP frequency and the overall nucleotide diversity (3.99 × 10-4) in S. salar was lower than reported in a majority of other organisms, which may suggest a relative young population history for Atlantic salmon. A subset of primers used in cross-species analyses revealed considerable variation in the SNP frequencies and nucleotide diversities in other salmonids. Conclusion Sequencing success was significantly higher with the new IPEC primers; thus the total number of loci to screen in order to identify one potential polymorphic site was six times less with this new strategy. Given that duplication may hamper SNP discovery in some species, the IPEC method reported here is an alternative way of identifying novel polymorphisms in such cases. PMID:16872523

Drug discovery: Fighting evolution with chemical synthesis

NASA Astrophysics Data System (ADS)

Yan, Ming; Baran, Phil S.

2016-05-01

A synthetic strategy has been developed that provides easy access to structurally diverse analogues of naturally occurring antibiotics, providing a fresh means of attack in the war against drug-resistant bacteria. See Article p.338

Lead Discovery Strategies for Identification of Chlamydia pneumoniae Inhibitors.

PubMed

Hanski, Leena; Vuorela, Pia

2016-11-28

Throughout its known history, the gram-negative bacterium Chlamydia pneumoniae has remained a challenging target for antibacterial chemotherapy and drug discovery. Owing to its well-known propensity for persistence and recent reports on antimicrobial resistence within closely related species, new approaches for targeting this ubiquitous human pathogen are urgently needed. In this review, we describe the strategies that have been successfully applied for the identification of nonconventional antichlamydial agents, including target-based and ligand-based virtual screening, ethnopharmacological approach and pharmacophore-based design of antimicrobial peptide-mimicking compounds. Among the antichlamydial agents identified via these strategies, most translational work has been carried out with plant phenolics. Thus, currently available data on their properties as antichlamydial agents are described, highlighting their potential mechanisms of action. In this context, the role of mitogen-activated protein kinase activation in the intracellular growth and survival of C . pneumoniae is discussed. Owing to the complex and often complementary pathways applied by C. pneumoniae in the different stages of its life cycle, multitargeted therapy approaches are expected to provide better tools for antichlamydial therapy than agents with a single molecular target.

Lead Discovery Strategies for Identification of Chlamydia pneumoniae Inhibitors

PubMed Central

Hanski, Leena; Vuorela, Pia

2016-01-01

Throughout its known history, the gram-negative bacterium Chlamydia pneumoniae has remained a challenging target for antibacterial chemotherapy and drug discovery. Owing to its well-known propensity for persistence and recent reports on antimicrobial resistence within closely related species, new approaches for targeting this ubiquitous human pathogen are urgently needed. In this review, we describe the strategies that have been successfully applied for the identification of nonconventional antichlamydial agents, including target-based and ligand-based virtual screening, ethnopharmacological approach and pharmacophore-based design of antimicrobial peptide-mimicking compounds. Among the antichlamydial agents identified via these strategies, most translational work has been carried out with plant phenolics. Thus, currently available data on their properties as antichlamydial agents are described, highlighting their potential mechanisms of action. In this context, the role of mitogen-activated protein kinase activation in the intracellular growth and survival of C. pneumoniae is discussed. Owing to the complex and often complementary pathways applied by C. pneumoniae in the different stages of its life cycle, multitargeted therapy approaches are expected to provide better tools for antichlamydial therapy than agents with a single molecular target. PMID:27916800

Emerging Strategies and Integrated Systems Microbiology Technologies for Biodiscovery of Marine Bioactive Compounds

PubMed Central

Rocha-Martin, Javier; Harrington, Catriona; Dobson, Alan D.W.; O’Gara, Fergal

2014-01-01

Marine microorganisms continue to be a source of structurally and biologically novel compounds with potential use in the biotechnology industry. The unique physiochemical properties of the marine environment (such as pH, pressure, temperature, osmolarity) and uncommon functional groups (such as isonitrile, dichloroimine, isocyanate, and halogenated functional groups) are frequently found in marine metabolites. These facts have resulted in the production of bioactive substances with different properties than those found in terrestrial habitats. In fact, the marine environment contains a relatively untapped reservoir of bioactivity. Recent advances in genomics, metagenomics, proteomics, combinatorial biosynthesis, synthetic biology, screening methods, expression systems, bioinformatics, and the ever increasing availability of sequenced genomes provides us with more opportunities than ever in the discovery of novel bioactive compounds and biocatalysts. The combination of these advanced techniques with traditional techniques, together with the use of dereplication strategies to eliminate known compounds, provides a powerful tool in the discovery of novel marine bioactive compounds. This review outlines and discusses the emerging strategies for the biodiscovery of these bioactive compounds. PMID:24918453

Comparison of two probability distributions used to model sizes of undiscovered oil and gas accumulations: Does the tail wag the assessment?

USGS Publications Warehouse

Attanasi, E.D.; Charpentier, R.R.

2002-01-01

Undiscovered oil and gas assessments are commonly reported as aggregate estimates of hydrocarbon volumes. Potential commercial value and discovery costs are, however, determined by accumulation size, so engineers, economists, decision makers, and sometimes policy analysts are most interested in projected discovery sizes. The lognormal and Pareto distributions have been used to model exploration target sizes. This note contrasts the outcomes of applying these alternative distributions to the play level assessments of the U.S. Geological Survey's 1995 National Oil and Gas Assessment. Using the same numbers of undiscovered accumulations and the same minimum, medium, and maximum size estimates, substitution of the shifted truncated lognormal distribution for the shifted truncated Pareto distribution reduced assessed undiscovered oil by 16% and gas by 15%. Nearly all of the volume differences resulted because the lognormal had fewer larger fields relative to the Pareto. The lognormal also resulted in a smaller number of small fields relative to the Pareto. For the Permian Basin case study presented here, reserve addition costs were 20% higher with the lognormal size assumption. ?? 2002 International Association for Mathematical Geology.

Bringing your tools to CyVerse Discovery Environment using Docker

PubMed Central

Devisetty, Upendra Kumar; Kennedy, Kathleen; Sarando, Paul; Merchant, Nirav; Lyons, Eric

2016-01-01

Docker has become a very popular container-based virtualization platform for software distribution that has revolutionized the way in which scientific software and software dependencies (software stacks) can be packaged, distributed, and deployed. Docker makes the complex and time-consuming installation procedures needed for scientific software a one-time process. Because it enables platform-independent installation, versioning of software environments, and easy redeployment and reproducibility, Docker is an ideal candidate for the deployment of identical software stacks on different compute environments such as XSEDE and Amazon AWS. CyVerse’s Discovery Environment also uses Docker for integrating its powerful, community-recommended software tools into CyVerse’s production environment for public use. This paper will help users bring their tools into CyVerse Discovery Environment (DE) which will not only allows users to integrate their tools with relative ease compared to the earlier method of tool deployment in DE but will also help users to share their apps with collaborators and release them for public use. PMID:27803802

Bringing your tools to CyVerse Discovery Environment using Docker.

PubMed

Devisetty, Upendra Kumar; Kennedy, Kathleen; Sarando, Paul; Merchant, Nirav; Lyons, Eric

2016-01-01

Docker has become a very popular container-based virtualization platform for software distribution that has revolutionized the way in which scientific software and software dependencies (software stacks) can be packaged, distributed, and deployed. Docker makes the complex and time-consuming installation procedures needed for scientific software a one-time process. Because it enables platform-independent installation, versioning of software environments, and easy redeployment and reproducibility, Docker is an ideal candidate for the deployment of identical software stacks on different compute environments such as XSEDE and Amazon AWS. CyVerse's Discovery Environment also uses Docker for integrating its powerful, community-recommended software tools into CyVerse's production environment for public use. This paper will help users bring their tools into CyVerse Discovery Environment (DE) which will not only allows users to integrate their tools with relative ease compared to the earlier method of tool deployment in DE but will also help users to share their apps with collaborators and release them for public use.

Model of Distributed Learning Objects Repository for a Heterogenic Internet Environment

ERIC Educational Resources Information Center

Kaczmarek, Jerzy; Landowska, Agnieszka

2006-01-01

In this article, an extension of the existing structure of learning objects is described. The solution addresses the problem of the access and discovery of educational resources in the distributed Internet environment. An overview of e-learning standards, reference models, and problems with educational resources delivery is presented. The paper…

Common Ground: An Interactive Visual Exploration and Discovery for Complex Health Data

DTIC Science & Technology

2015-12-01

PREPARED FOR: U.S. Army Medical Research and Materiel Command Fort Detrick, Maryland 21702-5012 DISTRIBUTION STATEMENT: Approved for public ...Approved OMB No. 0704-0188 Public reporting burden for this collection of information is estimated to average 1 hour per response, including the time for...Maryland 21702-5012 11. SPONSOR/MONITOR’S REPORT NUMBER(S) 12. DISTRIBUTION / AVAILABILITY STATEMENT Approved for Public Release; Distribution

Discovery of specific ligands for oral squamous carcinoma to develop anti-cancer drug loaded precise targeting nanotherapeutics.

PubMed

Yang, Fan; Liu, Ruiwu; Kramer, Randall; Xiao, Wenwu; Jordan, Richard; Lam, Kit S

2012-12-01

Oral squamous cell carcinoma has a low five-year survival rate, which may be due to late detection and a lack of effective tumor-specific therapies. Using a high throughput drug discovery strategy termed one-bead one-compound combinatorial library, the authors identified six compounds with high binding affinity to different human oral squamous cell carcinoma cell lines but not to normal cells. Current work is under way to develop these ligands to oral squamous cell carcinoma specific imaging probes or therapeutic agents.

Recent advances on the encoding and selection methods of DNA-encoded chemical library.

PubMed

Shi, Bingbing; Zhou, Yu; Huang, Yiran; Zhang, Jianfu; Li, Xiaoyu

2017-02-01

DNA-encoded chemical library (DEL) has emerged as a powerful and versatile tool for ligand discovery in chemical biology research and in drug discovery. Encoding and selection methods are two of the most important technological aspects of DEL that can dictate the performance and utilities of DELs. In this digest, we have summarized recent advances on the encoding and selection strategies of DEL and also discussed the latest developments on DNA-encoded dynamic library, a new frontier in DEL research. Copyright © 2016 Elsevier Ltd. All rights reserved.

Chemical screening method for the rapid identification of microbial sources of marine invertebrate-associated metabolites.

PubMed

Berrue, Fabrice; Withers, Sydnor T; Haltli, Brad; Withers, Jo; Kerr, Russell G

2011-03-21

Marine invertebrates have proven to be a rich source of secondary metabolites. The growing recognition that marine microorganisms associated with invertebrate hosts are involved in the biosynthesis of secondary metabolites offers new alternatives for the discovery and development of marine natural products. However, the discovery of microorganisms producing secondary metabolites previously attributed to an invertebrate host poses a significant challenge. This study describes an efficient chemical screening method utilizing a 96-well plate-based bacterial cultivation strategy to identify and isolate microbial producers of marine invertebrate-associated metabolites.

Understanding the proton's spin structure

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fred Myhrer; Thomas, Anthony W.

2010-02-01

We discuss the tremendous progress that has been towards an understanding of how the spin of the proton is distributed on its quark and gluon constituents. This is a problem that began in earnest twenty years ago with the discovery of the proton "spin crisis" by the European Muon Collaboration. The discoveries prompted by that original work have given us unprecedented insight into the amount of spin carried by polarized gluons and the orbital angular momentum of the quarks.

Statistics of petroleum exploration in the Caribbean, Latin America, Western Europe, the Middle East, Africa, non-communist Asia, and the southwestern Pacific

USGS Publications Warehouse

Attanasi, E.D.; Root, David H.

1993-01-01

This circular presents a summary of the geographic location, amount, and results of petroleum exploration, including an atlas showing explored and delineated prospective areas through 1990. The data show that wildcat well drilling has continued through the last decade to expand the prospective area by about 40,000 to 50,000 square miles per year. However, the area delineated by 1970, which represents only about one-third of the prospective area delineated to date, contains about 80 percent of the oil discovered to date. This discovery distribution suggests that, from an overall prospective, the industry was successful in delineating the most productive areas early. The price increases of the 1970's and 1980's allowed the commercial exploration and development of fields in high-cost areas, such as the North Sea and Campos Basin, Brazil. Data on natural-gas discoveries also indicate that gas will be supplying an increasing share of the worldwide energy market. The size distribution of petroleum provinces is highly skewed. The skewed distribution and the stability in province size orderings suggest that intense exploration in identified provinces will not change the distribution of oil within the study area. Although evidence of the field-growth phenomenon outside the United States and Canada is presented, the data are not yet reliable enough for projecting future growth. The field-growth phenomenon implies not only that recent discoveries are substantially understated, but that field growth could become the dominant source of additions to proved reserves in the future.

Antitrypanosomatid drug discovery: an ongoing challenge and a continuing need

PubMed Central

Field, Mark C.; Horn, David; Fairlamb, Alan H.; Ferguson, Michael A. J.; Gray, David W.; Read, Kevin D.; De Rycker, Manu; Torrie, Leah S.; Wyatt, Paul G.; Wyllie, Susan; Gilbert, Ian H.

2017-01-01

The World Health Organization recognizes human African trypanosomiasis, Chagas’ disease and the leishmaniases as neglected tropical diseases. These diseases are caused by parasitic trypanosomatids and range in severity from mild and self-curing to near invariably fatal. Public health advances have substantially decreased the impact of these diseases in recent decades, but alone will not eliminate these diseases. Here we discuss why new drugs against trypanosomatids are needed, approaches that are under investigation to develop new drugs and why the drug discovery pipeline remains essentially unfilled. Additionally, we consider the important challenges to drug discovery strategies and the new technologies that can address them. The combination of new drugs, new technologies and public health initiatives are essential for the management and hopefully eventual elimination of trypanosomatid diseases from the human population. PMID:28239154

Label-assisted mass spectrometry for the acceleration of reaction discovery and optimization

NASA Astrophysics Data System (ADS)

Cabrera-Pardo, Jaime R.; Chai, David I.; Liu, Song; Mrksich, Milan; Kozmin, Sergey A.

2013-05-01

The identification of new reactions expands our knowledge of chemical reactivity and enables new synthetic applications. Accelerating the pace of this discovery process remains challenging. We describe a highly effective and simple platform for screening a large number of potential chemical reactions in order to discover and optimize previously unknown catalytic transformations, thereby revealing new chemical reactivity. Our strategy is based on labelling one of the reactants with a polyaromatic chemical tag, which selectively undergoes a photoionization/desorption process upon laser irradiation, without the assistance of an external matrix, and enables rapid mass spectrometric detection of any products originating from such labelled reactants in complex reaction mixtures without any chromatographic separation. This method was successfully used for high-throughput discovery and subsequent optimization of two previously unknown benzannulation reactions.

Molecular Networking As a Drug Discovery, Drug Metabolism, and Precision Medicine Strategy.

PubMed

Quinn, Robert A; Nothias, Louis-Felix; Vining, Oliver; Meehan, Michael; Esquenazi, Eduardo; Dorrestein, Pieter C

2017-02-01

Molecular networking is a tandem mass spectrometry (MS/MS) data organizational approach that has been recently introduced in the drug discovery, metabolomics, and medical fields. The chemistry of molecules dictates how they will be fragmented by MS/MS in the gas phase and, therefore, two related molecules are likely to display similar fragment ion spectra. Molecular networking organizes the MS/MS data as a relational spectral network thereby mapping the chemistry that was detected in an MS/MS-based metabolomics experiment. Although the wider utility of molecular networking is just beginning to be recognized, in this review we highlight the principles behind molecular networking and its use for the discovery of therapeutic leads, monitoring drug metabolism, clinical diagnostics, and emerging applications in precision medicine. Copyright © 2016. Published by Elsevier Ltd.

Blueprint for antimicrobial hit discovery targeting metabolic networks

PubMed Central

Shen, Y.; Liu, J.; Estiu, G.; Isin, B.; Ahn, Y-Y.; Lee, D-S.; Barabási, A-L.; Kapatral, V.; Wiest, O.; Oltvai, Z. N.

2010-01-01

Advances in genome analysis, network biology, and computational chemistry have the potential to revolutionize drug discovery by combining system-level identification of drug targets with the atomistic modeling of small molecules capable of modulating their activity. To demonstrate the effectiveness of such a discovery pipeline, we deduced common antibiotic targets in Escherichia coli and Staphylococcus aureus by identifying shared tissue-specific or uniformly essential metabolic reactions in their metabolic networks. We then predicted through virtual screening dozens of potential inhibitors for several enzymes of these reactions and showed experimentally that a subset of these inhibited both enzyme activities in vitro and bacterial cell viability. This blueprint is applicable for any sequenced organism with high-quality metabolic reconstruction and suggests a general strategy for strain-specific antiinfective therapy. PMID:20080587

[PCSK-9 inhibitors, effects on LDL-C and future implications: What you should know].

PubMed

Corral, P; Ruiz, A J

The discovery of proprotein convertase subtilisin/kexin type 9 (PCSK9) in 2003 in families with familial hypercholesterolemia (HF) later generated the development of pharmacological strategies in order to inhibit this protein. Twelve years after this discovery, the first two biological compounds (monoclonal antibodies) were approved, which have been shown to substantially decrease LDL-C and other lipid subfractions. The objective of the present article is to review the history of the discovery of PCSK9, its physiology and pathophysiology and subsequent pharmacological development. The objectives and goals reached to date and the pending questions regarding the efficacy and safety of its clinical use are presented. Copyright © 2017 SEH-LELHA. Publicado por Elsevier España, S.L.U. All rights reserved.

Recent Advances in the Discovery and Development of Marine Microbial Natural Products

PubMed Central

Xiong, Zhi-Qiang; Wang, Jian-Feng; Hao, Yu-You; Wang, Yong

2013-01-01

Marine microbial natural products (MMNPs) have attracted increasing attention from microbiologists, taxonomists, ecologists, agronomists, chemists and evolutionary biologists during the last few decades. Numerous studies have indicated that diverse marine microbes appear to have the capacity to produce an impressive array of MMNPs exhibiting a wide variety of biological activities such as antimicrobial, anti-tumor, anti-inflammatory and anti-cardiovascular agents. Marine microorganisms represent an underexplored reservoir for the discovery of MMNPs with unique scaffolds and for exploitation in the pharmaceutical and agricultural industries. This review focuses on MMNPs discovery and development over the past decades, including innovative isolation and culture methods, strategies for discovering novel MMNPs via routine screenings, metagenomics, genomics, combinatorial biosynthesis, and synthetic biology. The potential problems and future directions for exploring MMNPs are also discussed. PMID:23528949

Recent advances in the discovery and development of marine microbial natural products.

PubMed

Xiong, Zhi-Qiang; Wang, Jian-Feng; Hao, Yu-You; Wang, Yong

2013-03-08

Marine microbial natural products (MMNPs) have attracted increasing attention from microbiologists, taxonomists, ecologists, agronomists, chemists and evolutionary biologists during the last few decades. Numerous studies have indicated that diverse marine microbes appear to have the capacity to produce an impressive array of MMNPs exhibiting a wide variety of biological activities such as antimicrobial, anti-tumor, anti-inflammatory and anti-cardiovascular agents. Marine microorganisms represent an underexplored reservoir for the discovery of MMNPs with unique scaffolds and for exploitation in the pharmaceutical and agricultural industries. This review focuses on MMNPs discovery and development over the past decades, including innovative isolation and culture methods, strategies for discovering novel MMNPs via routine screenings, metagenomics, genomics, combinatorial biosynthesis, and synthetic biology. The potential problems and future directions for exploring MMNPs are also discussed.

NMR approaches in structure-based lead discovery: Recent developments and new frontiers for targeting multi-protein complexes

PubMed Central

Dias, David M.; Ciulli, Alessio

2014-01-01

Nuclear magnetic resonance (NMR) spectroscopy is a pivotal method for structure-based and fragment-based lead discovery because it is one of the most robust techniques to provide information on protein structure, dynamics and interaction at an atomic level in solution. Nowadays, in most ligand screening cascades, NMR-based methods are applied to identify and structurally validate small molecule binding. These can be high-throughput and are often used synergistically with other biophysical assays. Here, we describe current state-of-the-art in the portfolio of available NMR-based experiments that are used to aid early-stage lead discovery. We then focus on multi-protein complexes as targets and how NMR spectroscopy allows studying of interactions within the high molecular weight assemblies that make up a vast fraction of the yet untargeted proteome. Finally, we give our perspective on how currently available methods could build an improved strategy for drug discovery against such challenging targets. PMID:25175337

Overcoming hERG affinity in the discovery of maraviroc; a CCR5 antagonist for the treatment of HIV.

PubMed

Price, David A; Armour, Duncan; de Groot, Marcel; Leishman, Derek; Napier, Carolyn; Perros, Manos; Stammen, Blanda L; Wood, Anthony

2008-01-01

Avoiding cardiac liability associated with blockade of hERG (human ether a go-go) is key for successful drug discovery and development. This paper describes the work undertaken in the discovery of a potent CCR5 antagonist, maraviroc 34, for the treatment of HIV. In particular the use of a pharmacophore model of the hERG channel and a high throughput binding assay for the hERG channel are described that were critical to elucidate SAR to overcome hERG liabilities. The key SAR involves the introduction of polar substituents into regions of the molecule where it is postulated to undergo hydrophobic interactions with the ion channel. Within the CCR5 project there appeared to be no strong correlation between hERG affinity and physiochemical parameters such as pKa or lipophilicity. It is believed that chemists could apply these same strategies early in drug discovery to remove hERG interactions associated with lead compounds while retaining potency at the primary target.

High-throughput platform assay technology for the discovery of pre-microrna-selective small molecule probes.

PubMed

Lorenz, Daniel A; Song, James M; Garner, Amanda L

2015-01-21

MicroRNAs (miRNA) play critical roles in human development and disease. As such, the targeting of miRNAs is considered attractive as a novel therapeutic strategy. A major bottleneck toward this goal, however, has been the identification of small molecule probes that are specific for select RNAs and methods that will facilitate such discovery efforts. Using pre-microRNAs as proof-of-concept, herein we report a conceptually new and innovative approach for assaying RNA-small molecule interactions. Through this platform assay technology, which we term catalytic enzyme-linked click chemistry assay or cat-ELCCA, we have designed a method that can be implemented in high throughput, is virtually free of false readouts, and is general for all nucleic acids. Through cat-ELCCA, we envision the discovery of selective small molecule ligands for disease-relevant miRNAs to promote the field of RNA-targeted drug discovery and further our understanding of the role of miRNAs in cellular biology.

Speaking Up For Science

NASA Astrophysics Data System (ADS)

Spilhaus, Fred

2005-06-01

The Smithsonian Institution's National Museum of Natural History in Washington D.C. is planning to show a film, "A Privileged Planet" that promotes creationism in the form of "intelligent design." The film is based on the book by Guillermo Gonzalez and Jay Wesley Richards, both affiliated with the Discovery Institute, which advocates teaching "intelligent design" as science in U.S. public schools. By associating with the Discovery Institute, the Smithsonian Institution will associate science with creationism and damage their credibility. The film is slated for airing on 23 June, unless the Smithsonian comes to its senses.Why is this important? Because the film promotes a long term strategy of the Discovery Institute (//www.discovery.org/csc/) to replace "materialistic science" with "intelligent design." The film fosters the idea that science should include the supernatural. This is unacceptable. AGU's position is clear, creationism is not science and AGU opposes all efforts to promote creationism as science, (The full text of the AGU position statement can be found at: //www.agu.org/sci_soc/policy/positions/evolution.shtml).

17 CFR Appendix A to Part 36 - Guidance on Significant Price Discovery Contracts

Code of Federal Regulations, 2013 CFR

2013-04-01

... that can be combined with other contracts to exploit expected economic relationships in anticipation of...'s viability in an arbitrage strategy; and will rely on direct observation confirming the use of a...

17 CFR Appendix A to Part 36 - Guidance on Significant Price Discovery Contracts

Code of Federal Regulations, 2011 CFR

2011-04-01

... that can be combined with other contracts to exploit expected economic relationships in anticipation of...'s viability in an arbitrage strategy; and will rely on direct observation confirming the use of a...

17 CFR Appendix A to Part 36 - Guidance on Significant Price Discovery Contracts

Code of Federal Regulations, 2010 CFR

2010-04-01

... that can be combined with other contracts to exploit expected economic relationships in anticipation of...'s viability in an arbitrage strategy; and will rely on direct observation confirming the use of a...

17 CFR Appendix A to Part 36 - Guidance on Significant Price Discovery Contracts

Code of Federal Regulations, 2012 CFR

2012-04-01

... that can be combined with other contracts to exploit expected economic relationships in anticipation of...'s viability in an arbitrage strategy; and will rely on direct observation confirming the use of a...

17 CFR Appendix A to Part 36 - Guidance on Significant Price Discovery Contracts

Code of Federal Regulations, 2014 CFR

2014-04-01

... that can be combined with other contracts to exploit expected economic relationships in anticipation of...'s viability in an arbitrage strategy; and will rely on direct observation confirming the use of a...

Discovery sequence and the nature of low permeability gas accumulations

USGS Publications Warehouse

Attanasi, E.D.

2005-01-01

There is an ongoing discussion regarding the geologic nature of accumulations that host gas in low-permeability sandstone environments. This note examines the discovery sequence of the accumulations in low permeability sandstone plays that were classified as continuous-type by the U.S. Geological Survey for the 1995 National Oil and Gas Assessment. It compares the statistical character of historical discovery sequences of accumulations associated with continuous-type sandstone gas plays to those of conventional plays. The seven sandstone plays with sufficient data exhibit declining size with sequence order, on average, and in three of the seven the trend is statistically significant. Simulation experiments show that both a skewed endowment size distribution and a discovery process that mimics sampling proportional to size are necessary to generate a discovery sequence that consistently produces a statistically significant negative size order relationship. The empirical findings suggest that discovery sequence could be used to constrain assessed gas in untested areas. The plays examined represent 134 of the 265 trillion cubic feet of recoverable gas assessed in undeveloped areas of continuous-type gas plays in low permeability sandstone environments reported in the 1995 National Assessment. ?? 2005 International Association for Mathematical Geology.

Systematic development of small molecules to inhibit specific microscopic steps of Aβ42 aggregation in Alzheimer's disease.

PubMed

Habchi, Johnny; Chia, Sean; Limbocker, Ryan; Mannini, Benedetta; Ahn, Minkoo; Perni, Michele; Hansson, Oskar; Arosio, Paolo; Kumita, Janet R; Challa, Pavan Kumar; Cohen, Samuel I A; Linse, Sara; Dobson, Christopher M; Knowles, Tuomas P J; Vendruscolo, Michele

2017-01-10

The aggregation of the 42-residue form of the amyloid-β peptide (Aβ42) is a pivotal event in Alzheimer's disease (AD). The use of chemical kinetics has recently enabled highly accurate quantifications of the effects of small molecules on specific microscopic steps in Aβ42 aggregation. Here, we exploit this approach to develop a rational drug discovery strategy against Aβ42 aggregation that uses as a read-out the changes in the nucleation and elongation rate constants caused by candidate small molecules. We thus identify a pool of compounds that target specific microscopic steps in Aβ42 aggregation. We then test further these small molecules in human cerebrospinal fluid and in a Caenorhabditis elegans model of AD. Our results show that this strategy represents a powerful approach to identify systematically small molecule lead compounds, thus offering an appealing opportunity to reduce the attrition problem in drug discovery.

The enemy within: Targeting host–parasite interaction for antileishmanial drug discovery

PubMed Central

Späth, Gerald F.; Rachidi, Najma; Prina, Eric

2017-01-01

The state of antileishmanial chemotherapy is strongly compromised by the emergence of drug-resistant Leishmania. The evolution of drug-resistant phenotypes has been linked to the parasites’ intrinsic genome instability, with frequent gene and chromosome amplifications causing fitness gains that are directly selected by environmental factors, including the presence of antileishmanial drugs. Thus, even though the unique eukaryotic biology of Leishmania and its dependence on parasite-specific virulence factors provide valid opportunities for chemotherapeutical intervention, all strategies that target the parasite in a direct fashion are likely prone to select for resistance. Here, we review the current state of antileishmanial chemotherapy and discuss the limitations of ongoing drug discovery efforts. We finally propose new strategies that target Leishmania viability indirectly via mechanisms of host–parasite interaction, including parasite-released ectokinases and host epigenetic regulation, which modulate host cell signaling and transcriptional regulation, respectively, to establish permissive conditions for intracellular Leishmania survival. PMID:28594938

The enemy within: Targeting host-parasite interaction for antileishmanial drug discovery.

PubMed

Lamotte, Suzanne; Späth, Gerald F; Rachidi, Najma; Prina, Eric

2017-06-01

The state of antileishmanial chemotherapy is strongly compromised by the emergence of drug-resistant Leishmania. The evolution of drug-resistant phenotypes has been linked to the parasites' intrinsic genome instability, with frequent gene and chromosome amplifications causing fitness gains that are directly selected by environmental factors, including the presence of antileishmanial drugs. Thus, even though the unique eukaryotic biology of Leishmania and its dependence on parasite-specific virulence factors provide valid opportunities for chemotherapeutical intervention, all strategies that target the parasite in a direct fashion are likely prone to select for resistance. Here, we review the current state of antileishmanial chemotherapy and discuss the limitations of ongoing drug discovery efforts. We finally propose new strategies that target Leishmania viability indirectly via mechanisms of host-parasite interaction, including parasite-released ectokinases and host epigenetic regulation, which modulate host cell signaling and transcriptional regulation, respectively, to establish permissive conditions for intracellular Leishmania survival.

In-silico guided discovery of novel CCR9 antagonists

NASA Astrophysics Data System (ADS)

Zhang, Xin; Cross, Jason B.; Romero, Jan; Heifetz, Alexander; Humphries, Eric; Hall, Katie; Wu, Yuchuan; Stucka, Sabrina; Zhang, Jing; Chandonnet, Haoqun; Lippa, Blaise; Ryan, M. Dominic; Baber, J. Christian

2018-03-01

Antagonism of CCR9 is a promising mechanism for treatment of inflammatory bowel disease, including ulcerative colitis and Crohn's disease. There is limited experimental data on CCR9 and its ligands, complicating efforts to identify new small molecule antagonists. We present here results of a successful virtual screening and rational hit-to-lead campaign that led to the discovery and initial optimization of novel CCR9 antagonists. This work uses a novel data fusion strategy to integrate the output of multiple computational tools, such as 2D similarity search, shape similarity, pharmacophore searching, and molecular docking, as well as the identification and incorporation of privileged chemokine fragments. The application of various ranking strategies, which combined consensus and parallel selection methods to achieve a balance of enrichment and novelty, resulted in 198 virtual screening hits in total, with an overall hit rate of 18%. Several hits were developed into early leads through targeted synthesis and purchase of analogs.

From Discovery to Justification: Outline of an Ideal Research Program in Empirical Psychology

PubMed Central

Witte, Erich H.; Zenker, Frank

2017-01-01

The gold standard for an empirical science is the replicability of its research results. But the estimated average replicability rate of key-effects that top-tier psychology journals report falls between 36 and 39% (objective vs. subjective rate; Open Science Collaboration, 2015). So the standard mode of applying null-hypothesis significance testing (NHST) fails to adequately separate stable from random effects. Therefore, NHST does not fully convince as a statistical inference strategy. We argue that the replicability crisis is “home-made” because more sophisticated strategies can deliver results the successful replication of which is sufficiently probable. Thus, we can overcome the replicability crisis by integrating empirical results into genuine research programs. Instead of continuing to narrowly evaluate only the stability of data against random fluctuations (discovery context), such programs evaluate rival hypotheses against stable data (justification context). PMID:29163256

Collaboration versus outsourcing: the need to think outside the box.

PubMed

Robertson, Graeme M; Mayr, Lorenz M

2011-12-01

As has been widely reviewed elsewhere, the pharmaceutical industry is experiencing an 'innovation deficit' as evidenced by the decline in new chemical entity output. This decline, compounded by increased costs and regulatory requirements highlights the need to significantly revise strategic options across the drug-discovery spectrum. Within such revision(s), much of the focus has been on outsourcing to reduce, or at least contain, costs, but if the underlying predominance of 'closed collaborations' is not challenged to allow better use of combined knowledge and, thus, move towards a more genuine collaborative process then a 'numbers only' approach will not bring medium-to-long-term survival. There are many problems to confront in evolving new sustainable strategies, a real need to think differently exists and should to be cultivated. This article reviews current outsourcing and collaboration strategies to provide a perspective on how great knowledge sharing could help revise the drug-discovery process.

Symmetry as Bias: Rediscovering Special Relativity

NASA Technical Reports Server (NTRS)

Lowry, Michael R.

1992-01-01

This paper describes a rational reconstruction of Einstein's discovery of special relativity, validated through an implementation: the Erlanger program. Einstein's discovery of special relativity revolutionized both the content of physics and the research strategy used by theoretical physicists. This research strategy entails a mutual bootstrapping process between a hypothesis space for biases, defined through different postulated symmetries of the universe, and a hypothesis space for physical theories. The invariance principle mutually constrains these two spaces. The invariance principle enables detecting when an evolving physical theory becomes inconsistent with its bias, and also when the biases for theories describing different phenomena are inconsistent. Structural properties of the invariance principle facilitate generating a new bias when an inconsistency is detected. After a new bias is generated. this principle facilitates reformulating the old, inconsistent theory by treating the latter as a limiting approximation. The structural properties of the invariance principle can be suitably generalized to other types of biases to enable primal-dual learning.

The EuroGEOSS Advanced Operating Capacity

NASA Astrophysics Data System (ADS)

Nativi, S.; Vaccari, L.; Stock, K.; Diaz, L.; Santoro, M.

2012-04-01

The concept of multidisciplinary interoperability for managing societal issues is a major challenge presently faced by the Earth and Space Science Informatics community. With this in mind, EuroGEOSS project was launched on May 1st 2009 for a three year period aiming to demonstrate the added value to the scientific community and society of providing existing earth observing systems and applications in an interoperable manner and used within the GEOSS and INSPIRE frameworks. In the first period, the project built an Initial Operating Capability (IOC) in the three strategic areas of Drought, Forestry and Biodiversity; this was then enhanced into an Advanced Operating Capacity (AOC) for multidisciplinary interoperability. Finally, the project extended the infrastructure to other scientific domains (geology, hydrology, etc.). The EuroGEOSS multidisciplinary AOC is based on the Brokering Approach. This approach aims to achieve multidisciplinary interoperability by developing an extended SOA (Service Oriented Architecture) where a new type of "expert" components is introduced: the Broker. These implement all mediation and distribution functionalities needed to interconnect the distributed and heterogeneous resources characterizing a System of Systems (SoS) environment. The EuroGEOSS AOC is comprised of the following components: • EuroGEOSS Discovery Broker: providing harmonized discovery functionalities by mediating and distributing user queries against tens of heterogeneous services; • EuroGEOSS Access Broker: enabling users to seamlessly access and use heterogeneous remote resources via a unique and standard service; • EuroGEOSS Web 2.0 Broker: enhancing the capabilities of the Discovery Broker with queries towards the new Web 2.0 services; • EuroGEOSS Semantic Discovery Broker: enhancing the capabilities of the Discovery Broker with semantic query-expansion; • EuroGEOSS Natural Language Search Component: providing users with the possibilities to search for resources using natural language queries; • Service Composition Broker: allowing users to compose and execute complex Business Processes, based on the technology developed by the FP7 UncertWeb project. Recently, the EuroGEOSS Brokering framework was presented at the GEO-VIII Plenary and Exhibition in Istanbul and introduced into the GEOSS Common Infrastructure.

A Kernel Embedding-Based Approach for Nonstationary Causal Model Inference.

PubMed

Hu, Shoubo; Chen, Zhitang; Chan, Laiwan

2018-05-01

Although nonstationary data are more common in the real world, most existing causal discovery methods do not take nonstationarity into consideration. In this letter, we propose a kernel embedding-based approach, ENCI, for nonstationary causal model inference where data are collected from multiple domains with varying distributions. In ENCI, we transform the complicated relation of a cause-effect pair into a linear model of variables of which observations correspond to the kernel embeddings of the cause-and-effect distributions in different domains. In this way, we are able to estimate the causal direction by exploiting the causal asymmetry of the transformed linear model. Furthermore, we extend ENCI to causal graph discovery for multiple variables by transforming the relations among them into a linear nongaussian acyclic model. We show that by exploiting the nonstationarity of distributions, both cause-effect pairs and two kinds of causal graphs are identifiable under mild conditions. Experiments on synthetic and real-world data are conducted to justify the efficacy of ENCI over major existing methods.

High-throughput discovery of rare human nucleotide polymorphisms by Ecotilling

PubMed Central

Till, Bradley J.; Zerr, Troy; Bowers, Elisabeth; Greene, Elizabeth A.; Comai, Luca; Henikoff, Steven

2006-01-01

Human individuals differ from one another at only ∼0.1% of nucleotide positions, but these single nucleotide differences account for most heritable phenotypic variation. Large-scale efforts to discover and genotype human variation have been limited to common polymorphisms. However, these efforts overlook rare nucleotide changes that may contribute to phenotypic diversity and genetic disorders, including cancer. Thus, there is an increasing need for high-throughput methods to robustly detect rare nucleotide differences. Toward this end, we have adapted the mismatch discovery method known as Ecotilling for the discovery of human single nucleotide polymorphisms. To increase throughput and reduce costs, we developed a universal primer strategy and implemented algorithms for automated band detection. Ecotilling was validated by screening 90 human DNA samples for nucleotide changes in 5 gene targets and by comparing results to public resequencing data. To increase throughput for discovery of rare alleles, we pooled samples 8-fold and found Ecotilling to be efficient relative to resequencing, with a false negative rate of 5% and a false discovery rate of 4%. We identified 28 new rare alleles, including some that are predicted to damage protein function. The detection of rare damaging mutations has implications for models of human disease. PMID:16893952

"Discoveries in Planetary Sciences": Slide Sets Highlighting New Advances for Astronomy Educators

NASA Astrophysics Data System (ADS)

Brain, David; Schneider, N.; Molaverdikhani, K.; Afsharahmadi, F.

2012-10-01

We present two new features of an ongoing effort to bring recent newsworthy advances in planetary science to undergraduate lecture halls. The effort, called 'Discoveries in Planetary Sciences', summarizes selected recently announced discoveries that are 'too new for textbooks' in the form of 3-slide PowerPoint presentations. The first slide describes the discovery, the second slide discusses the underlying planetary science concepts at a level appropriate for students of 'Astronomy 101', and the third presents the big picture implications of the discovery. A fourth slide includes links to associated press releases, images, and primary sources. This effort is generously sponsored by the Division for Planetary Sciences of the American Astronomical Society, and the slide sets are available at http://dps.aas.org/education/dpsdisc/ for download by undergraduate instructors or any interested party. Several new slide sets have just been released, and we summarize the topics covered. The slide sets are also being translated into languages other than English (including Spanish and Farsi), and we will provide an overview of the translation strategy and process. Finally, we will present web statistics on how many people are using the slide sets, as well as individual feedback from educators.

An overview of aldehyde oxidase: an enzyme of emerging importance in novel drug discovery.

PubMed

Rashidi, Mohammad-Reza; Soltani, Somaieh

2017-03-01

Given the rising trend in medicinal chemistry strategy to reduce cytochrome P450-dependent metabolism, aldehyde oxidase (AOX) has recently gained increased attention in drug discovery programs and the number of drug candidates that are metabolized by AOX is steadily growing. Areas covered: Despite the emerging importance of AOX in drug discovery, there are certain major recognized problems associated with AOX-mediated metabolism of drugs. Intra- and inter-species variations in AOX activity, the lack of reliable and predictive animal models using the common experimental animals, and failure in the predictions of in vivo metabolic activity of AOX using traditional in vitro methods are among these issues that are covered in this article. A comprehensive review of computational human AOX (hAOX) related studies are also provided. Expert opinion: Following the recent progress in the stem cell field, the authors recommend the application of organoids technology as an effective tool to solve the fundamental problems associated with the evaluation of AOX in drug discovery. The recent success in resolving the hAOX crystal structure can too be another valuable data source for the study of AOX-catalyzed metabolism of new drug candidates, using computer-aided drug discovery methods.

Discovery – The Link to H.Pylori Bacteria

Cancer.gov

NCI supported research to solidify the link between H. pylori infections and stomach cancer. As a result, new cancer treatment and prevention strategies are being developed, encouraging scientists to carefully examine other cancers for viral and bacterial connections.

Ensuring Strategic Stability In The Second Nuclear Age

DTIC Science & Technology

2016-02-16

War College Carlisle Barracks, PA: Strategic Studies Institute, 2013), 5. 7. John C. Wohlstetter, Sleepwalking with the Bomb, (Seattle, WA...2015_national_security_strategy.pdf. Wohlstetter, John C. Sleepwalking with the Bomb. Seattle, WA: Discovery Institute Press, 2012.

TREND 2000

NASA Technical Reports Server (NTRS)

1996-01-01

The Educator Resource Center has created the Technology, Research, Education and Discovery (TREND) 2000 computer lab at NASA's John C. Stennis Space Center to facilitate the integration of technology into schools' curriculums by providing innovative and creative classroom strategies using state-of-the-art technology.

Distribution of Bemisia tabaci (Hemiptera: Aleyrodidae) biotypes in Florida - Investigating the "Q" invasion

USDA-ARS?s Scientific Manuscript database

After the 2004 discovery of the Bemisia tabaci Q biotype in the U.S., there was an urgent need to determine its distribution. As part of a coordinated country-wide effort, an extensive survey of B. tabaci biotypes was conducted in Florida, with the cooperation of growers and state agencies, to moni...

Patterns of Creation and Discovery: An Analysis of Defense Laboratory Patenting and Innovation

DTIC Science & Technology

2013-01-01

Manufacturing Material science, manufacturing processes AFRL RY Sensors Radio frequency and electro-optic sensing, sensor fusion, network-enabled...MONITOR’S ACRONYM(S) 11 . SPONSOR/MONITOR’S REPORT NUMBER(S) 12. DISTRIBUTION/AVAILABILITY STATEMENT Approved for public release; distribution unlimited...2.2 A DOD-relevant definition of innovation as use .............................................................................. 11 2.3 Patent trends

Strategy to Identify and Test Putative Light-Sensitive Non-Opsin G-Protein-Coupled Receptors: A Case Study.

PubMed

Faggionato, Davide; Serb, Jeanne M

2017-08-01

The rise of high-throughput RNA sequencing (RNA-seq) and de novo transcriptome assembly has had a transformative impact on how we identify and study genes in the phototransduction cascade of non-model organisms. But the advantage provided by the nearly automated annotation of RNA-seq transcriptomes may at the same time hinder the possibility for gene discovery and the discovery of new gene functions. For example, standard functional annotation based on domain homology to known protein families can only confirm group membership, not identify the emergence of new biochemical function. In this study, we show the importance of developing a strategy that circumvents the limitations of semiautomated annotation and apply this workflow to photosensitivity as a means to discover non-opsin photoreceptors. We hypothesize that non-opsin G-protein-coupled receptor (GPCR) proteins may have chromophore-binding lysines in locations that differ from opsin. Here, we provide the first case study describing non-opsin light-sensitive GPCRs based on tissue-specific RNA-seq data of the common bay scallop Argopecten irradians (Lamarck, 1819). Using a combination of sequence analysis and three-dimensional protein modeling, we identified two candidate proteins. We tested their photochemical properties and provide evidence showing that these two proteins incorporate 11-cis and/or all-trans retinal and react to light photochemically. Based on this case study, we demonstrate that there is potential for the discovery of new light-sensitive GPCRs, and we have developed a workflow that starts from RNA-seq assemblies to the discovery of new non-opsin, GPCR-based photopigments.

Controlling the Rate of GWAS False Discoveries

PubMed Central

Brzyski, Damian; Peterson, Christine B.; Sobczyk, Piotr; Candès, Emmanuel J.; Bogdan, Malgorzata; Sabatti, Chiara

2017-01-01

With the rise of both the number and the complexity of traits of interest, control of the false discovery rate (FDR) in genetic association studies has become an increasingly appealing and accepted target for multiple comparison adjustment. While a number of robust FDR-controlling strategies exist, the nature of this error rate is intimately tied to the precise way in which discoveries are counted, and the performance of FDR-controlling procedures is satisfactory only if there is a one-to-one correspondence between what scientists describe as unique discoveries and the number of rejected hypotheses. The presence of linkage disequilibrium between markers in genome-wide association studies (GWAS) often leads researchers to consider the signal associated to multiple neighboring SNPs as indicating the existence of a single genomic locus with possible influence on the phenotype. This a posteriori aggregation of rejected hypotheses results in inflation of the relevant FDR. We propose a novel approach to FDR control that is based on prescreening to identify the level of resolution of distinct hypotheses. We show how FDR-controlling strategies can be adapted to account for this initial selection both with theoretical results and simulations that mimic the dependence structure to be expected in GWAS. We demonstrate that our approach is versatile and useful when the data are analyzed using both tests based on single markers and multiple regression. We provide an R package that allows practitioners to apply our procedure on standard GWAS format data, and illustrate its performance on lipid traits in the North Finland Birth Cohort 66 cohort study. PMID:27784720

Controlling the Rate of GWAS False Discoveries.

PubMed

Brzyski, Damian; Peterson, Christine B; Sobczyk, Piotr; Candès, Emmanuel J; Bogdan, Malgorzata; Sabatti, Chiara

2017-01-01

With the rise of both the number and the complexity of traits of interest, control of the false discovery rate (FDR) in genetic association studies has become an increasingly appealing and accepted target for multiple comparison adjustment. While a number of robust FDR-controlling strategies exist, the nature of this error rate is intimately tied to the precise way in which discoveries are counted, and the performance of FDR-controlling procedures is satisfactory only if there is a one-to-one correspondence between what scientists describe as unique discoveries and the number of rejected hypotheses. The presence of linkage disequilibrium between markers in genome-wide association studies (GWAS) often leads researchers to consider the signal associated to multiple neighboring SNPs as indicating the existence of a single genomic locus with possible influence on the phenotype. This a posteriori aggregation of rejected hypotheses results in inflation of the relevant FDR. We propose a novel approach to FDR control that is based on prescreening to identify the level of resolution of distinct hypotheses. We show how FDR-controlling strategies can be adapted to account for this initial selection both with theoretical results and simulations that mimic the dependence structure to be expected in GWAS. We demonstrate that our approach is versatile and useful when the data are analyzed using both tests based on single markers and multiple regression. We provide an R package that allows practitioners to apply our procedure on standard GWAS format data, and illustrate its performance on lipid traits in the North Finland Birth Cohort 66 cohort study. Copyright © 2017 by the Genetics Society of America.

Leveraging existing data for prioritization of the ecological risks of human and veterinary pharmaceuticals to aquatic organisms

PubMed Central

LaLone, Carlie A.; Berninger, Jason P.; Villeneuve, Daniel L.; Ankley, Gerald T.

2014-01-01

Medicinal innovation has led to the discovery and use of thousands of human and veterinary drugs. With this comes the potential for unintended effects on non-target organisms exposed to pharmaceuticals inevitably entering the environment. The impracticality of generating whole-organism chronic toxicity data representative of all species in the environment has necessitated prioritization of drugs for focused empirical testing as well as field monitoring. Current prioritization strategies typically emphasize likelihood for exposure (i.e. predicted/measured environmental concentrations), while incorporating only rather limited consideration of potential effects of the drug to non-target organisms. However, substantial mammalian pharmacokinetic and mechanism/mode of action (MOA) data are produced during drug development to understand drug target specificity and efficacy for intended consumers. An integrated prioritization strategy for assessing risks of human and veterinary drugs would leverage available pharmacokinetic and toxicokinetic data for evaluation of the potential for adverse effects to non-target organisms. In this reiview, we demonstrate the utility of read-across approaches to leverage mammalian absorption, distribution, metabolism and elimination data; analyse cross-species molecular target conservation and translate therapeutic MOA to an adverse outcome pathway(s) relevant to aquatic organisms as a means to inform prioritization of drugs for focused toxicity testing and environmental monitoring. PMID:25405975

Exobiological exploration of Mars.

PubMed

Klein, H P; DeVincenzi, D L

1995-03-01

Of all the other planets in the solar system, Mars remains the most promising for further elucidating concepts about chemical evolution and the origin of life. Strategies were developed to pursue three exobiological objectives for Mars exploration: determining the abundance and distribution of the biogenic elements and organic compounds, detecting evidence of an ancient biota on Mars, and determining whether indigenous organisms exist anywhere on the planet. The three strategies are quite similar and, in fact, share the same sequence of phases. In the first phase, each requires global reconnaissance and remote sensing by orbiters to select sites of interest for detailed in situ analyses. In the second phase, lander missions are conducted to characterize the chemical and physical properties of the selected sites. The third phase involves conducting "critical" experiments at sites whose properties make them particularly attractive for exobiology. These critical experiments would include, for example, identification of organics, detection of fossils, and detection of extant life. The fourth phase is the detailed analysis of samples returned from these sites in Earth-based laboratories to confirm and extend previous discoveries. Finally, in the fifth phase, human exploration is needed to establish the geological settings for the earlier findings or to discover and explore sites that are not accessible to robotic spacecraft.

Integration of Lead Discovery Tactics and the Evolution of the Lead Discovery Toolbox.

PubMed

Leveridge, Melanie; Chung, Chun-Wa; Gross, Jeffrey W; Phelps, Christopher B; Green, Darren

2018-06-01

There has been much debate around the success rates of various screening strategies to identify starting points for drug discovery. Although high-throughput target-based and phenotypic screening has been the focus of this debate, techniques such as fragment screening, virtual screening, and DNA-encoded library screening are also increasingly reported as a source of new chemical equity. Here, we provide examples in which integration of more than one screening approach has improved the campaign outcome and discuss how strengths and weaknesses of various methods can be used to build a complementary toolbox of approaches, giving researchers the greatest probability of successfully identifying leads. Among others, we highlight case studies for receptor-interacting serine/threonine-protein kinase 1 and the bromo- and extra-terminal domain family of bromodomains. In each example, the unique insight or chemistries individual approaches provided are described, emphasizing the synergy of information obtained from the various tactics employed and the particular question each tactic was employed to answer. We conclude with a short prospective discussing how screening strategies are evolving, what this screening toolbox might look like in the future, how to maximize success through integration of multiple tactics, and scenarios that drive selection of one combination of tactics over another.

On Detecting Repetition from Fast Radio Bursts

NASA Astrophysics Data System (ADS)

Connor, Liam; Petroff, Emily

2018-07-01

Fast radio bursts (FRBs) are bright, millisecond-duration radio pulses of unknown origin. To date, only one (FRB 121102) out of several dozen has been seen to repeat, though the extent to which it is exceptional remains unclear. We discuss detecting repetition from FRBs, which will be very important for understanding their physical origin, and which also allows for host galaxy localization. We show how the combination of instrument sensitivity, beam shapes, and individual FRB luminosity functions affect the detection of sources with repetition that is not necessarily described by a homogeneous Poisson process. We demonstrate that the Canadian Hydrogen Intensity Mapping Experiment (CHIME) could detect many new repeating FRBs for which host galaxies could be subsequently localized using other interferometers, but it will not be an ideal instrument for monitoring FRB 121102. If the luminosity distributions of repeating FRBs are given by power laws with significantly more dim than bright bursts, CHIME’s repetition discoveries could preferentially come not from its own discoveries, but from sources first detected with lower-sensitivity instruments like the Australian Square Kilometer Array Pathfinder in fly’s eye mode. We then discuss observing strategies for upcoming surveys, and advocate following up sources at approximately regular intervals and with telescopes of higher sensitivity when possible. Finally, we discuss doing pulsar-like periodicity searching on FRB follow-up data, based on the idea that while most pulses are undetectable, folding on an underlying rotation period could reveal the hidden signal.

Tile-Based Fisher Ratio Analysis of Comprehensive Two-Dimensional Gas Chromatography Time-of-Flight Mass Spectrometry (GC × GC – TOFMS) Data using a Null Distribution Approach

DOE Office of Scientific and Technical Information (OSTI.GOV)

Parsons, Brendon A.; Marney, Luke C.; Siegler, William C.

Multi-dimensional chromatographic instrumentation produces information-rich, and chemically complex data containing meaningful chemical signals and/or chemical patterns. Two-dimensional gas chromatography coupled with time-of-flight mass spectrometry (GC × GC – TOFMS) is a prominent instrumental platform that has been applied extensively for discovery-based experimentation, where samples are sufficiently volatile or amenable to derivatization. Use of GC × GC – TOFMS and associated data analysis strategies aim to uncover meaningful chemical signals or chemical patterns. However, for complex samples, meaningful chemical information is often buried in a background of less meaningful chemical signal and noise. In this report, we utilize the tile-based F-ratiomore » software in concert with the standard addition method by spiking non-native chemicals into a diesel fuel matrix at low concentrations. While the previous work studied the concentration range of 100-1000 ppm, the current study focuses on the 0 ppm to 100 ppm analyte spike range. This study demonstrates the sensitivity and selectivity of the tile-based F-ratio software for discovery of true positives in the non-targeted analysis of a chemically complex and analytically challenging sample matrix. By exploring the low concentration spike levels, we gain a better understanding of the limit of detection (LOD) of the tile-based F-ratio software with GC × GC – TOFMS data.« less

ADDME – Avoiding Drug Development Mistakes Early: central nervous system drug discovery perspective

PubMed Central

Tsaioun, Katya; Bottlaender, Michel; Mabondzo, Aloise

2009-01-01

The advent of early absorption, distribution, metabolism, excretion, and toxicity (ADMET) screening has increased the attrition rate of weak drug candidates early in the drug-discovery process, and decreased the proportion of compounds failing in clinical trials for ADMET reasons. This paper reviews the history of ADMET screening and its place in pharmaceutical development, and central nervous system drug discovery in particular. Assays that have been developed in response to specific needs and improvements in technology that result in higher throughput and greater accuracy of prediction of human mechanisms of absorption and toxicity are discussed. The paper concludes with the authors' forecast of new models that will better predict human efficacy and toxicity. PMID:19534730

Enhanced Detection of Low-Abundance Human Plasma Proteins by Integrating Polyethylene Glycol Fractionation and Immunoaffinity Depletion

PubMed Central

Liu, Haipeng; Yu, Jia; Qiao, Rui; Zhou, Mi; Yang, Yongtao; Zhou, Jian; Xie, Peng

2016-01-01

The enormous depth complexity of the human plasma proteome poses a significant challenge for current mass spectrometry-based proteomic technologies in terms of detecting low-level proteins in plasma, which is essential for successful biomarker discovery efforts. Typically, a single-step analytical approach cannot reduce this intrinsic complexity. Current simplex immunodepletion techniques offer limited capacity for detecting low-abundance proteins, and integrated strategies are thus desirable. In this respect, we developed an improved strategy for analyzing the human plasma proteome by integrating polyethylene glycol (PEG) fractionation with immunoaffinity depletion. PEG fractionation of plasma proteins is simple, rapid, efficient, and compatible with a downstream immunodepletion step. Compared with immunodepletion alone, our integrated strategy substantially improved the proteome coverage afforded by PEG fractionation. Coupling this new protocol with liquid chromatography-tandem mass spectrometry, 135 proteins with reported normal concentrations below 100 ng/mL were confidently identified as common low-abundance proteins. A side-by-side comparison indicated that our integrated strategy was increased by average 43.0% in the identification rate of low-abundance proteins, relying on an average 65.8% increase of the corresponding unique peptides. Further investigation demonstrated that this combined strategy could effectively alleviate the signal-suppressive effects of the major high-abundance proteins by affinity depletion, especially with moderate-abundance proteins after incorporating PEG fractionation, thereby greatly enhancing the detection of low-abundance proteins. In sum, the newly developed strategy of incorporating PEG fractionation to immunodepletion methods can potentially aid in the discovery of plasma biomarkers of therapeutic and clinical interest. PMID:27832179

Phenome-driven disease genetics prediction toward drug discovery

PubMed Central

Chen, Yang; Li, Li; Zhang, Guo-Qiang; Xu, Rong

2015-01-01

Motivation: Discerning genetic contributions to diseases not only enhances our understanding of disease mechanisms, but also leads to translational opportunities for drug discovery. Recent computational approaches incorporate disease phenotypic similarities to improve the prediction power of disease gene discovery. However, most current studies used only one data source of human disease phenotype. We present an innovative and generic strategy for combining multiple different data sources of human disease phenotype and predicting disease-associated genes from integrated phenotypic and genomic data. Results: To demonstrate our approach, we explored a new phenotype database from biomedical ontologies and constructed Disease Manifestation Network (DMN). We combined DMN with mimMiner, which was a widely used phenotype database in disease gene prediction studies. Our approach achieved significantly improved performance over a baseline method, which used only one phenotype data source. In the leave-one-out cross-validation and de novo gene prediction analysis, our approach achieved the area under the curves of 90.7% and 90.3%, which are significantly higher than 84.2% (P < e−4) and 81.3% (P < e−12) for the baseline approach. We further demonstrated that our predicted genes have the translational potential in drug discovery. We used Crohn’s disease as an example and ranked the candidate drugs based on the rank of drug targets. Our gene prediction approach prioritized druggable genes that are likely to be associated with Crohn’s disease pathogenesis, and our rank of candidate drugs successfully prioritized the Food and Drug Administration-approved drugs for Crohn’s disease. We also found literature evidence to support a number of drugs among the top 200 candidates. In summary, we demonstrated that a novel strategy combining unique disease phenotype data with system approaches can lead to rapid drug discovery. Availability and implementation: nlp.case.edu/public/data/DMN Contact: rxx@case.edu PMID:26072493

A fragment-based approach leading to the discovery of a novel binding site and the selective CK2 inhibitor CAM4066.

PubMed

De Fusco, Claudia; Brear, Paul; Iegre, Jessica; Georgiou, Kathy Hadje; Sore, Hannah F; Hyvönen, Marko; Spring, David R

2017-07-01

Recently we reported the discovery of a potent and selective CK2α inhibitor CAM4066. This compound inhibits CK2 activity by exploiting a pocket located outside the ATP binding site (αD pocket). Here we describe in detail the journey that led to the discovery of CAM4066 using the challenging fragment linking strategy. Specifically, we aimed to develop inhibitors by linking a high-affinity fragment anchored in the αD site to a weakly binding warhead fragment occupying the ATP site. Moreover, we describe the remarkable impact that molecular modelling had on the development of this novel chemical tool. The work described herein shows potential for the development of a novel class of CK2 inhibitors. Copyright © 2017. Published by Elsevier Ltd.

Discovery of potent HIV-1 non-nucleoside reverse transcriptase inhibitors from arylthioacetanilide structural motif.

PubMed

Li, Wenxin; Li, Xiao; De Clercq, Erik; Zhan, Peng; Liu, Xinyong

2015-09-18

The poor pharmacokinetics, side effects and particularly the rapid emergence of drug resistance compromise the efficiency of the clinically used anti-HIV drugs. Therefore, the discovery of novel and effective NNRTIs is still an extremely primary mission. Arylthioacetanilide family is one of the highly active HIV-1 NNRTIs against wide-type (WT) HIV-1 and a wide range of drug-resistant mutant strains. Especially, VRX-480773 and RDEA806 have been chosen as candidates for further clinical studies. In this article, we review the discovery and development of the arylthioacetanilides, and, especially, pay much attention to the structural modifications, SARs conclusions and molecular modeling. Moreover, several medicinal chemistry strategies to overcome drug resistance involved in the optimization process of arylthioacetanilides are highlighted, providing valuable clues for further investigations. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

4-Hydroxyphenylpyruvate Dioxygenase Inhibitors: From Chemical Biology to Agrochemicals.

PubMed

Ndikuryayo, Ferdinand; Moosavi, Behrooz; Yang, Wen-Chao; Yang, Guang-Fu

2017-10-04

The development of new herbicides is receiving considerable attention to control weed biotypes resistant to current herbicides. Consequently, new enzymes are always desired as targets for herbicide discovery. 4-Hydroxyphenylpyruvate dioxygenase (HPPD, EC 1.13.11.27) is an enzyme engaged in photosynthetic activity and catalyzes the transformation of 4-hydroxyphenylpyruvic acid (HPPA) into homogentisic acid (HGA). HPPD inhibitors constitute a promising area of discovery and development of innovative herbicides with some advantages, including excellent crop selectivity, low application rates, and broad-spectrum weed control. HPPD inhibitors have been investigated for agrochemical interests, and some of them have already been commercialized as herbicides. In this review, we mainly focus on the chemical biology of HPPD, discovery of new potential inhibitors, and strategies for engineering transgenic crops resistant to current HPPD-inhibiting herbicides. The conclusion raises some relevant gaps for future research directions.

Translational biomarkers: from discovery and development to clinical practice.

PubMed

Subramanyam, Meena; Goyal, Jaya

The refinement of disease taxonomy utilizing molecular phenotypes has led to significant improvements in the precision of disease diagnosis and customization of treatment options. This has also spurred efforts to identify novel biomarkers to understand the impact of therapeutically altering the underlying molecular network on disease course, and to support decision-making in drug discovery and development. However, gaps in knowledge regarding disease heterogeneity, combined with the inadequacies of surrogate disease model systems, make it challenging to demonstrate the unequivocal association of molecular and physiological biomarkers to disease pathology. This article will discuss the current landscape in biomarker research and highlight strategies being adopted to increase the likelihood of transitioning biomarkers from discovery to medical practice to enable more objective decision making, and to improve health outcome. Copyright © 2016 Elsevier Ltd. All rights reserved.

Developing Investigation Skills in an Introductory Multistep Synthesis Using Fluorene Oxidation and Reduction

ERIC Educational Resources Information Center

Stocksdale, Mark G; Pointer, Roy D; Benson, Barret W.; Fletcher, Steven E. S.; Henry, Ian; Ogren, Paul J.; Berg, Michael A. G.

2004-01-01

A two-step oxidation-reduction sequence that incorporates several important aspects of synthesis into introductory organic chemistry laboratories is described. This experiment is an excellent vehicle for introducing elements of discovery and intermediate yield improvement strategies.

Towards a privacy preserving cohort discovery framework for clinical research networks.

PubMed

Yuan, Jiawei; Malin, Bradley; Modave, François; Guo, Yi; Hogan, William R; Shenkman, Elizabeth; Bian, Jiang

2017-02-01

The last few years have witnessed an increasing number of clinical research networks (CRNs) focused on building large collections of data from electronic health records (EHRs), claims, and patient-reported outcomes (PROs). Many of these CRNs provide a service for the discovery of research cohorts with various health conditions, which is especially useful for rare diseases. Supporting patient privacy can enhance the scalability and efficiency of such processes; however, current practice mainly relies on policy, such as guidelines defined in the Health Insurance Portability and Accountability Act (HIPAA), which are insufficient for CRNs (e.g., HIPAA does not require encryption of data - which can mitigate insider threats). By combining policy with privacy enhancing technologies we can enhance the trustworthiness of CRNs. The goal of this research is to determine if searchable encryption can instill privacy in CRNs without sacrificing their usability. We developed a technique, implemented in working software to enable privacy-preserving cohort discovery (PPCD) services in large distributed CRNs based on elliptic curve cryptography (ECC). This technique also incorporates a block indexing strategy to improve the performance (in terms of computational running time) of PPCD. We evaluated the PPCD service with three real cohort definitions: (1) elderly cervical cancer patients who underwent radical hysterectomy, (2) oropharyngeal and tongue cancer patients who underwent robotic transoral surgery, and (3) female breast cancer patients who underwent mastectomy) with varied query complexity. These definitions were tested in an encrypted database of 7.1 million records derived from the publically available Healthcare Cost and Utilization Project (HCUP) Nationwide Inpatient Sample (NIS). We assessed the performance of the PPCD service in terms of (1) accuracy in cohort discovery, (2) computational running time, and (3) privacy afforded to the underlying records during PPCD. The empirical results indicate that the proposed PPCD can execute cohort discovery queries in a reasonable amount of time, with query runtime in the range of 165-262s for the 3 use cases, with zero compromise in accuracy. We further show that the search performance is practical because it supports a highly parallelized design for secure evaluation over encrypted records. Additionally, our security analysis shows that the proposed construction is resilient to standard adversaries. PPCD services can be designed for clinical research networks. The security construction presented in this work specifically achieves high privacy guarantees by preventing both threats originating from within and beyond the network. Copyright © 2016 Elsevier Inc. All rights reserved.

The changing landscape of gene editing in hematopoietic stem cells: a step towards Cas9 clinical translation.

PubMed

Dever, Daniel P; Porteus, Matthew H

2017-11-01

Since the discovery two decades ago that programmable endonucleases can be engineered to modify human cells at single nucleotide resolution, the concept of genome editing was born. Now these technologies are being applied to therapeutically relevant cell types, including hematopoietic stem cells (HSC), which possess the power to repopulate an entire blood and immune system. The purpose of this review is to discuss the changing landscape of genome editing in hematopoietic stem cells (GE-HSC) from the discovery stage to the preclinical stage, with the imminent goal of clinical translation for the treatment of serious genetic diseases of the blood and immune system. With the discovery that the RNA-programmable (sgRNA) clustered regularly interspace short palindromic repeats (CRISPR)-Cas9 nuclease (Cas9/sgRNA) systems can be easily used to precisely modify the human genome in 2012, a genome-editing revolution of hematopoietic stem cells (HSC) has bloomed. We have observed that over the last 2 years, academic institutions and small biotech companies are developing HSC-based Cas9/sgRNA genome-editing curative strategies to treat monogenic disorders, including β-hemoglobinopathies and primary immunodeficiencies. We will focus on recent publications (within the past 2 years) that employ different genome-editing strategies to 'hijack' the cell's endogenous double-strand repair pathways to confer a disease-specific therapeutic advantage. The number of genome-editing strategies in HSCs that could offer therapeutic potential for diseases of the blood and immune system have dramatically risen over the past 2 years. The HSC-based genome-editing field is primed to enter clinical trials in the subsequent years. We will summarize the major advancements for the development of novel autologous GE-HSC cell and gene therapy strategies for hematopoietic diseases that are candidates for curative allogeneic bone marrow transplantation.

The Modeling and Simulation Catalog for Discovery, Knowledge and Reuse

NASA Technical Reports Server (NTRS)

Stone, George F. III; Greenberg, Brandi; Daehler-Wilking, Richard; Hunt, Steven

2011-01-01

The DoD M&S Steering Committee has noted that the current DoD and Service's modeling and simulation resource repository (MSRR) services are not up-to-date limiting their value to the using communities. However, M&S leaders and managers also determined that the Department needs a functional M&S registry card catalog to facilitate M&S tool and data visibility to support M&S activities across the DoD. The M&S Catalog will discover and access M&S metadata maintained at nodes distributed across DoD networks in a centrally managed, decentralized process that employs metadata collection and management. The intent is to link information stores, precluding redundant location updating. The M&S Catalog uses a standard metadata schemas based on the DoD's Net-Centric Data Strategy Community of Interest metadata specification. The Air Force, Navy and OSD (CAPE) have provided initial information to participating DoD nodes, but plans on the horizon are being made to bring in hundreds of source providers.

Beyond regulation: A social compact' for gas and electricity

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stram, B.; Thorn, T.

The public utility covenant, granting franchise protection to firms in return for just and reasonable rate regulation, has come under increasing scrutiny as socially inefficient for several reasons. First, cost-based regulation fails to adequately incite cost-minimization and new product development. Second, public utility regulation has turned into a micro-management exercise where prospective strategies are laboriously scrutinized and past performance is penalized from 20-20 hind-sight. Third, traditional regulation has provided a forum for nontraditional special interest regulation that may not be in the ratepayer's interest. An alternative to the regulatory covenant is the social compact where long-term contracts among the affectedmore » parties set price and service terms. The advantages of such contracting would be to reduce the administrative costs of regulation, better incite the market's entrepreneurial discovery process, deregulate upstream production and transportation, and eliminate extraneous regulation of electric and gas distribution. The winners would be gas consumers and the most efficient industry suppliers.« less

Supramolecular core-shell nanoparticles for photoconductive device applications

NASA Astrophysics Data System (ADS)

Cheng, Chih-Chia; Chen, Jem-Kun; Shieh, Yeong-Tarng; Lee, Duu-Jong

2016-08-01

We report a breakthrough discovery involving supramolecular-based strategies to construct novel core-shell heterojunction nanoparticles with hydrophilic adenine-functionalized polythiophene (PAT) as the core and hydrophobic phenyl-C61-butyric acid methyl ester (PCBM) as the shell, which enables the conception of new functional supramolecular assemblies for constructing functional nanomaterials for applications in optoelectronic devices. The generated nanoparticles exhibit uniform spherical shape, well-controlled tuning of particle size with narrow size distributions, and excellent electrochemical stability in solution and the solid state owing to highly efficient energy transfer from PAT to PCBM. When the PAT/PCBM nanoparticles were fabricated into a photoconducting layer in an electronic device, the resulting device showed excellent electric conduction characteristics, including an electrically-tunable voltage-controlled switch, and high short-circuit current and open-circuit voltage. These observations demonstrate how the self-assembly of PAT/PCBM into specific nanostructures may help to promote efficient charge generation and transport processes, suggesting potential for a wide variety of applications as a promising candidate material for bulk heterojunction polymer devices.

Detectability of Chelyabinsk-like impactors with Pan-STARRS

NASA Astrophysics Data System (ADS)

Micheli, Marco; Wainscoat, Richard J.; Denneau, Larry

2018-03-01

In this work we present the results of our analysis of the detectability of an object in the size range of the recent Chelyabinsk impactor under the current discovery and follow-up capabilities, using the specific observational strategy of the Pan-STARRS survey as a reference point. We first discuss the observability of real-life cases inspired by the impact trajectories of 2008 TC3, 2014 AA, the past Earth encounters with 2014 RC and 2015 TB145, the upcoming fly-by of 2012 TC4 and the Chelyabinsk event. We then expand our analysis with the investigation of synthetic impactors with realistic orbital distributions. Among the various conclusions of our analysis, we discuss how the time of first detectability of an object does not necessarily correspond to the moment when that same object can be recognized as an impactor. We also point out how objects discovered only a few days before impact can be immediately identified as impactors, partly thanks to the good astrometric quality that telescopes like Pan-STARRS currently achieve.

A distributed computational search strategy for the identification of diagnostics targets: application to finding aptamer targets for methicillin-resistant staphylococci.

PubMed

Flanagan, Keith; Cockell, Simon; Harwood, Colin; Hallinan, Jennifer; Nakjang, Sirintra; Lawry, Beth; Wipat, Anil

2014-06-30

The rapid and cost-effective identification of bacterial species is crucial, especially for clinical diagnosis and treatment. Peptide aptamers have been shown to be valuable for use as a component of novel, direct detection methods. These small peptides have a number of advantages over antibodies, including greater specificity and longer shelf life. These properties facilitate their use as the detector components of biosensor devices. However, the identification of suitable aptamer targets for particular groups of organisms is challenging. We present a semi-automated processing pipeline for the identification of candidate aptamer targets from whole bacterial genome sequences. The pipeline can be configured to search for protein sequence fragments that uniquely identify a set of strains of interest. The system is also capable of identifying additional organisms that may be of interest due to their possession of protein fragments in common with the initial set. Through the use of Cloud computing technology and distributed databases, our system is capable of scaling with the rapidly growing genome repositories, and consequently of keeping the resulting data sets up-to-date. The system described is also more generically applicable to the discovery of specific targets for other diagnostic approaches such as DNA probes, PCR primers and antibodies.

Protein Structure Initiative Material Repository: an open shared public resource of structural genomics plasmids for the biological community

PubMed Central

Cormier, Catherine Y.; Mohr, Stephanie E.; Zuo, Dongmei; Hu, Yanhui; Rolfs, Andreas; Kramer, Jason; Taycher, Elena; Kelley, Fontina; Fiacco, Michael; Turnbull, Greggory; LaBaer, Joshua

2010-01-01

The Protein Structure Initiative Material Repository (PSI-MR; http://psimr.asu.edu) provides centralized storage and distribution for the protein expression plasmids created by PSI researchers. These plasmids are a resource that allows the research community to dissect the biological function of proteins whose structures have been identified by the PSI. The plasmid annotation, which includes the full length sequence, vector information and associated publications, is stored in a freely available, searchable database called DNASU (http://dnasu.asu.edu). Each PSI plasmid is also linked to a variety of additional resources, which facilitates cross-referencing of a particular plasmid to protein annotations and experimental data. Plasmid samples can be requested directly through the website. We have also developed a novel strategy to avoid the most common concern encountered when distributing plasmids namely, the complexity of material transfer agreement (MTA) processing and the resulting delays this causes. The Expedited Process MTA, in which we created a network of institutions that agree to the terms of transfer in advance of a material request, eliminates these delays. Our hope is that by creating a repository of expression-ready plasmids and expediting the process for receiving these plasmids, we will help accelerate the accessibility and pace of scientific discovery. PMID:19906724

A new mechanism for aging: chemical "age spots" in immortal DNA strands in distributed stem cells.

PubMed

Sherley, James L

2008-01-01

The existence of immortal DNA strands (IDSs) in distributed stem cells (DSCs) of adult human tissues was first inferred by Cairns. Cairns deduced the existence of IDSs by connecting two seemingly disparate observations - one his own and the other belonging to Lark. Cairns noted a mathematical discrepancy between predicted human tissue cell mutation rates and human cancer incidence. He integrated this insight with Lark's earlier discovery of non-random mitotic chromosome segregation in both plant root tip cells and mouse fetal fibroblast cultures to predict the existence of IDSs as the essential elements of a mutation-defense mechanism in DSCs. Since Cairns' seminal prediction, several laboratories have identified IDSs in diverse mammalian cells with DSC properties. Past studies focused on the potential roles of IDSs as originally envisioned in DSC genetic fidelity or in the maintenance of the DSC phenotype. Another possible consequence of IDSs, aging, has received little attention. Herein, the potential for cumulative chemical modifications and decompositions (i.e., "age spots") of IDSs in DSCs to act as a major determinant of human aging is considered. If accrued chemical alterations of IDSs prove to be essential determinants of aging, then a means to restore IDSs may yield new strategies for tissue rejuvenation.

A distributed computational search strategy for the identification of diagnostics targets: Application to finding aptamer targets for methicillin-resistant staphylococci.

PubMed

Flanagan, Keith; Cockell, Simon; Harwood, Colin; Hallinan, Jennifer; Nakjang, Sirintra; Lawry, Beth; Wipat, Anil

2014-06-01

The rapid and cost-effective identification of bacterial species is crucial, especially for clinical diagnosis and treatment. Peptide aptamers have been shown to be valuable for use as a component of novel, direct detection methods. These small peptides have a number of advantages over antibodies, including greater specificity and longer shelf life. These properties facilitate their use as the detector components of biosensor devices. However, the identification of suitable aptamer targets for particular groups of organisms is challenging. We present a semi-automated processing pipeline for the identification of candidate aptamer targets from whole bacterial genome sequences. The pipeline can be configured to search for protein sequence fragments that uniquely identify a set of strains of interest. The system is also capable of identifying additional organisms that may be of interest due to their possession of protein fragments in common with the initial set. Through the use of Cloud computing technology and distributed databases, our system is capable of scaling with the rapidly growing genome repositories, and consequently of keeping the resulting data sets up-to-date. The system described is also more generically applicable to the discovery of specific targets for other diagnostic approaches such as DNA probes, PCR primers and antibodies.

The pivotal role of multimodality reporter sensors in drug discovery: from cell based assays to real time molecular imaging.

PubMed

Ray, Pritha

2011-04-01

Development and marketing of new drugs require stringent validation that are expensive and time consuming. Non-invasive multimodality molecular imaging using reporter genes holds great potential to expedite these processes at reduced cost. New generations of smarter molecular imaging strategies such as Split reporter, Bioluminescence resonance energy transfer, Multimodality fusion reporter technologies will further assist to streamline and shorten the drug discovery and developmental process. This review illustrates the importance and potential of molecular imaging using multimodality reporter genes in drug development at preclinical phases.

Natural Products as a Foundation for Drug Discovery

PubMed Central

Beutler, John A.

2009-01-01

Natural products have contributed to the development of many drugs for diverse indications. While most U.S. pharmaceutical companies have reduced or eliminated their in-house natural product groups, new paradigms and new enterprises have evolved to carry on a role for natural products in the pharmaceutical industry. Many of the reasons for the decline in popularity of natural products are being addressed by the development of new techniques for screening and production. This overview aims to inform pharmacologists of current strategies and techniques that make natural products a viable strategic choice for inclusion in drug discovery programs. PMID:20161632

The Study of “big data” to support internal business strategists

NASA Astrophysics Data System (ADS)

Ge, Mei

2018-01-01

How is big data different from previous data analysis systems? The primary purpose behind traditional small data analytics that all managers are more or less familiar with is to support internal business strategies. But big data also offers a promising new dimension: to discover new opportunities to offer customers high-value products and services. The study focus to introduce some strategists which big data support to. Business decisions using big data can also involve some areas for analytics. They include customer satisfaction, customer journeys, supply chains, risk management, competitive intelligence, pricing, discovery and experimentation or facilitating big data discovery.

Schistosoma comparative genomics: integrating genome structure, parasite biology and anthelmintic discovery

PubMed Central

Swain, Martin T.; Larkin, Denis M.; Caffrey, Conor R.; Davies, Stephen J.; Loukas, Alex; Skelly, Patrick J.; Hoffmann, Karl F.

2011-01-01

Schistosoma genomes provide a comprehensive resource for identifying the molecular processes that shape parasite evolution and for discovering novel chemotherapeutic or immunoprophylactic targets. Here, we demonstrate how intra- and intergenus comparative genomics can be used to drive these investigations forward, illustrate the advantages and limitations of these approaches and review how post genomic technologies offer complementary strategies for genome characterisation. While sequencing and functional characterisation of other schistosome/platyhelminth genomes continues to expedite anthelmintic discovery, we contend that future priorities should equally focus on improving assembly quality, and chromosomal assignment, of existing schistosome/platyhelminth genomes. PMID:22024648

Transmission of chronic wasting disease in Wisconsin white-tailed deer: Implications for disease spread and management

USGS Publications Warehouse

Jennelle, Christopher S.; Henaux, Viviane; Wasserberg, Gideon; Thiagarajan, Bala; Rolley, Robert E.; Samuel, Michael D.

2014-01-01

Few studies have evaluated the rate of infection or mode of transmission for wildlife diseases, and the implications of alternative management strategies. We used hunter harvest data from 2002 to 2013 to investigate chronic wasting disease (CWD) infection rate and transmission modes, and address how alternative management approaches affect disease dynamics in a Wisconsin white-tailed deer population. Uncertainty regarding demographic impacts of CWD on cervid populations, human and domestic animal health concerns, and potential economic consequences underscore the need for strategies to control CWD distribution and prevalence. Using maximum-likelihood methods to evaluate alternative multi-state deterministic models of CWD transmission, harvest data strongly supports a frequency-dependent transmission structure with sex-specific infection rates that are two times higher in males than females. As transmissible spongiform encephalopathies are an important and difficult-to-study class of diseases with major economic and ecological implications, our work supports the hypothesis of frequency-dependent transmission in wild deer at a broad spatial scale and indicates that effective harvest management can be implemented to control CWD prevalence. Specifically, we show that harvest focused on the greater-affected sex (males) can result in stable population dynamics and control of CWD within the next 50 years, given the constraints of the model. We also provide a quantitative estimate of geographic disease spread in southern Wisconsin, validating qualitative assessments that CWD spreads relatively slowly. Given increased discovery and distribution of CWD throughout North America, insights from our study are valuable to management agencies and to the general public concerned about the impacts of CWD on white-tailed deer populations.

Transmission of Chronic Wasting Disease in Wisconsin White-Tailed Deer: Implications for Disease Spread and Management

PubMed Central

Jennelle, Christopher S.; Henaux, Viviane; Wasserberg, Gideon; Thiagarajan, Bala; Rolley, Robert E.; Samuel, Michael D.

2014-01-01

Few studies have evaluated the rate of infection or mode of transmission for wildlife diseases, and the implications of alternative management strategies. We used hunter harvest data from 2002 to 2013 to investigate chronic wasting disease (CWD) infection rate and transmission modes, and address how alternative management approaches affect disease dynamics in a Wisconsin white-tailed deer population. Uncertainty regarding demographic impacts of CWD on cervid populations, human and domestic animal health concerns, and potential economic consequences underscore the need for strategies to control CWD distribution and prevalence. Using maximum-likelihood methods to evaluate alternative multi-state deterministic models of CWD transmission, harvest data strongly supports a frequency-dependent transmission structure with sex-specific infection rates that are two times higher in males than females. As transmissible spongiform encephalopathies are an important and difficult-to-study class of diseases with major economic and ecological implications, our work supports the hypothesis of frequency-dependent transmission in wild deer at a broad spatial scale and indicates that effective harvest management can be implemented to control CWD prevalence. Specifically, we show that harvest focused on the greater-affected sex (males) can result in stable population dynamics and control of CWD within the next 50 years, given the constraints of the model. We also provide a quantitative estimate of geographic disease spread in southern Wisconsin, validating qualitative assessments that CWD spreads relatively slowly. Given increased discovery and distribution of CWD throughout North America, insights from our study are valuable to management agencies and to the general public concerned about the impacts of CWD on white-tailed deer populations. PMID:24658535

A General-purpose Framework for Parallel Processing of Large-scale LiDAR Data

NASA Astrophysics Data System (ADS)

Li, Z.; Hodgson, M.; Li, W.

2016-12-01

Light detection and ranging (LiDAR) technologies have proven efficiency to quickly obtain very detailed Earth surface data for a large spatial extent. Such data is important for scientific discoveries such as Earth and ecological sciences and natural disasters and environmental applications. However, handling LiDAR data poses grand geoprocessing challenges due to data intensity and computational intensity. Previous studies received notable success on parallel processing of LiDAR data to these challenges. However, these studies either relied on high performance computers and specialized hardware (GPUs) or focused mostly on finding customized solutions for some specific algorithms. We developed a general-purpose scalable framework coupled with sophisticated data decomposition and parallelization strategy to efficiently handle big LiDAR data. Specifically, 1) a tile-based spatial index is proposed to manage big LiDAR data in the scalable and fault-tolerable Hadoop distributed file system, 2) two spatial decomposition techniques are developed to enable efficient parallelization of different types of LiDAR processing tasks, and 3) by coupling existing LiDAR processing tools with Hadoop, this framework is able to conduct a variety of LiDAR data processing tasks in parallel in a highly scalable distributed computing environment. The performance and scalability of the framework is evaluated with a series of experiments conducted on a real LiDAR dataset using a proof-of-concept prototype system. The results show that the proposed framework 1) is able to handle massive LiDAR data more efficiently than standalone tools; and 2) provides almost linear scalability in terms of either increased workload (data volume) or increased computing nodes with both spatial decomposition strategies. We believe that the proposed framework provides valuable references on developing a collaborative cyberinfrastructure for processing big earth science data in a highly scalable environment.

NATpipe: an integrative pipeline for systematical discovery of natural antisense transcripts (NATs) and phase-distributed nat-siRNAs from de novo assembled transcriptomes

PubMed Central

Yu, Dongliang; Meng, Yijun; Zuo, Ziwei; Xue, Jie; Wang, Huizhong

2016-01-01

Nat-siRNAs (small interfering RNAs originated from natural antisense transcripts) are a class of functional small RNA (sRNA) species discovered in both plants and animals. These siRNAs are highly enriched within the annealed regions of the NAT (natural antisense transcript) pairs. To date, great research efforts have been taken for systematical identification of the NATs in various organisms. However, developing a freely available and easy-to-use program for NAT prediction is strongly demanded by researchers. Here, we proposed an integrative pipeline named NATpipe for systematical discovery of NATs from de novo assembled transcriptomes. By utilizing sRNA sequencing data, the pipeline also allowed users to search for phase-distributed nat-siRNAs within the perfectly annealed regions of the NAT pairs. Additionally, more reliable nat-siRNA loci could be identified based on degradome sequencing data. A case study on the non-model plant Dendrobium officinale was performed to illustrate the utility of NATpipe. Finally, we hope that NATpipe would be a useful tool for NAT prediction, nat-siRNA discovery, and related functional studies. NATpipe is available at www.bioinfolab.cn/NATpipe/NATpipe.zip. PMID:26858106

Optimization of the genotyping-by-sequencing strategy for population genomic analysis in conifers.

PubMed

Pan, Jin; Wang, Baosheng; Pei, Zhi-Yong; Zhao, Wei; Gao, Jie; Mao, Jian-Feng; Wang, Xiao-Ru

2015-07-01

Flexibility and low cost make genotyping-by-sequencing (GBS) an ideal tool for population genomic studies of nonmodel species. However, to utilize the potential of the method fully, many parameters affecting library quality and single nucleotide polymorphism (SNP) discovery require optimization, especially for conifer genomes with a high repetitive DNA content. In this study, we explored strategies for effective GBS analysis in pine species. We constructed GBS libraries using HpaII, PstI and EcoRI-MseI digestions with different multiplexing levels and examined the effect of restriction enzymes on library complexity and the impact of sequencing depth and size selection of restriction fragments on sequence coverage bias. We tested and compared UNEAK, Stacks and GATK pipelines for the GBS data, and then developed a reference-free SNP calling strategy for haploid pine genomes. Our GBS procedure proved to be effective in SNP discovery, producing 7000-11 000 and 14 751 SNPs within and among three pine species, respectively, from a PstI library. This investigation provides guidance for the design and analysis of GBS experiments, particularly for organisms for which genomic information is lacking. © 2014 John Wiley & Sons Ltd.

Distribution and abundance of Anoplophora glabripennis in stands of its native host in South Korea and China

Treesearch

David W. Williams; Hai-Poong Lee

2003-01-01

Following up on our discovery in 2000 that Acer mono is a native host of Anoplophora glabripennis, we spent eight weeks searching for the beetle in natural forest stands in South Korea and China. We wanted to assess the distribution and abundance of beetles in closed forest stands of native hosts.

Radiochemistry and the Study of Fission

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rundberg, Robert S.

These are slides from a lecture given at UC Berkeley. Radiochemistry has been used to study fission since its discovery. Radiochemical methods are used to determine cumulative mass yields. These measurements have led to the two-mode fission hypothesis to model the neutron energy dependence of fission product yields. Fission product yields can be used for the nuclear forensics of nuclear explosions. The mass yield curve depends on both the fuel and the neutron spectrum of a device. Recent studies have shown that the nuclear structure of the compound nucleus can affect the mass yield distribution. The following topics are covered:more » In the beginning: the discovery of fission; forensics using fission products: what can be learned from fission products, definitions of R-values and Q-values, fission bases, K-factors and fission chambers, limitations; the neutron energy dependence of the mass yield distribution (the two mode fission hypothesis); the influence of nuclear structure on the mass yield distribution. In summary: Radiochemistry has been used to study fission since its discovery. Radiochemical measurement of fission product yields have provided the highest precision data for developing fission models and for nuclear forensics. The two-mode fission hypothesis provides a description of the neutron energy dependence of the mass yield curve. However, data is still rather sparse and more work is needed near second and third chance fission. Radiochemical measurements have provided evidence for the importance of nuclear states in the compound nucleus in predicting the mass yield curve in the resonance region.« less

Genomics for the identification of novel antimicrobials

USDA-ARS?s Scientific Manuscript database

There is a critical need in animal agriculture for developing novel antimicrobials and alternative strategies to reduce the use of antibiotics and address the challenges of antimicrobial resistance. High-throughput gene expression analysis is providing new tools that are enabling the discovery of h...

Analysis of Product Distribution Strategy in Digital Publishing Industry Based on Game-Theory

NASA Astrophysics Data System (ADS)

Xu, Li-ping; Chen, Haiyan

2017-04-01

The digital publishing output increased significantly year by year. It has been the most vigorous point of economic growth and has been more important to press and publication industry. Its distribution channel has been diversified, which is different from the traditional industry. A deep research has been done in digital publishing industry, for making clear of the constitution of the industry chain and establishing the model of industry chain. The cooperative and competitive relationship between different distribution channels have been analyzed basing on a game-theory. By comparing the distribution quantity and the market size between the static distribution strategy and dynamic distribution strategy, we get the theory evidence about how to choose the distribution strategy to get the optimal benefit.

The Effect of Various Strategies on the Acquisition, Retention, and Transfer of a Serial Positioning Task

DTIC Science & Technology

1979-07-01

child development and behavior. N. Y.: Academic Press, 1974. Craik , F. I.M., & Lockhart , R. S. Levels of processing : A framework for memory research...F. I. M. Craik & L. S. Cermak (Eds.), Levels of processing and theories of memory. Hillsdale, N. J.: Erlbaum, 1978. Bruner, J. S. The act of discovery... Lockhart , 1972; Craik & Tulving, 1975). Although the dependent measures differ, the conclusions drawn remain similar. Strategy usage has a facilitatory

A New Strategy for Analyzing Time-Series Data Using Dynamic Networks: Identifying Prospective Biomarkers of Hepatocellular Carcinoma.

PubMed

Huang, Xin; Zeng, Jun; Zhou, Lina; Hu, Chunxiu; Yin, Peiyuan; Lin, Xiaohui

2016-08-31

Time-series metabolomics studies can provide insight into the dynamics of disease development and facilitate the discovery of prospective biomarkers. To improve the performance of early risk identification, a new strategy for analyzing time-series data based on dynamic networks (ATSD-DN) in a systematic time dimension is proposed. In ATSD-DN, the non-overlapping ratio was applied to measure the changes in feature ratios during the process of disease development and to construct dynamic networks. Dynamic concentration analysis and network topological structure analysis were performed to extract early warning information. This strategy was applied to the study of time-series lipidomics data from a stepwise hepatocarcinogenesis rat model. A ratio of lyso-phosphatidylcholine (LPC) 18:1/free fatty acid (FFA) 20:5 was identified as the potential biomarker for hepatocellular carcinoma (HCC). It can be used to classify HCC and non-HCC rats, and the area under the curve values in the discovery and external validation sets were 0.980 and 0.972, respectively. This strategy was also compared with a weighted relative difference accumulation algorithm (wRDA), multivariate empirical Bayes statistics (MEBA) and support vector machine-recursive feature elimination (SVM-RFE). The better performance of ATSD-DN suggests its potential for a more complete presentation of time-series changes and effective extraction of early warning information.

A New Strategy for Analyzing Time-Series Data Using Dynamic Networks: Identifying Prospective Biomarkers of Hepatocellular Carcinoma

NASA Astrophysics Data System (ADS)

Huang, Xin; Zeng, Jun; Zhou, Lina; Hu, Chunxiu; Yin, Peiyuan; Lin, Xiaohui

2016-08-01

Time-series metabolomics studies can provide insight into the dynamics of disease development and facilitate the discovery of prospective biomarkers. To improve the performance of early risk identification, a new strategy for analyzing time-series data based on dynamic networks (ATSD-DN) in a systematic time dimension is proposed. In ATSD-DN, the non-overlapping ratio was applied to measure the changes in feature ratios during the process of disease development and to construct dynamic networks. Dynamic concentration analysis and network topological structure analysis were performed to extract early warning information. This strategy was applied to the study of time-series lipidomics data from a stepwise hepatocarcinogenesis rat model. A ratio of lyso-phosphatidylcholine (LPC) 18:1/free fatty acid (FFA) 20:5 was identified as the potential biomarker for hepatocellular carcinoma (HCC). It can be used to classify HCC and non-HCC rats, and the area under the curve values in the discovery and external validation sets were 0.980 and 0.972, respectively. This strategy was also compared with a weighted relative difference accumulation algorithm (wRDA), multivariate empirical Bayes statistics (MEBA) and support vector machine-recursive feature elimination (SVM-RFE). The better performance of ATSD-DN suggests its potential for a more complete presentation of time-series changes and effective extraction of early warning information.

New strategies in drug discovery.

PubMed

Ohlstein, Eliot H; Johnson, Anthony G; Elliott, John D; Romanic, Anne M

2006-01-01

Gene identification followed by determination of the expression of genes in a given disease and understanding of the function of the gene products is central to the drug discovery process. The ability to associate a specific gene with a disease can be attributed primarily to the extraordinary progress that has been made in the areas of gene sequencing and information technologies. Selection and validation of novel molecular targets have become of great importance in light of the abundance of new potential therapeutic drug targets that have emerged from human gene sequencing. In response to this revolution within the pharmaceutical industry, the development of high-throughput methods in both biology and chemistry has been necessitated. Further, the successful translation of basic scientific discoveries into clinical experimental medicine and novel therapeutics is an increasing challenge. As such, a new paradigm for drug discovery has emerged. This process involves the integration of clinical, genetic, genomic, and molecular phenotype data partnered with cheminformatics. Central to this process, the data generated are managed, collated, and interpreted with the use of informatics. This review addresses the use of new technologies that have arisen to deal with this new paradigm.

"Drug" Discovery with the Help of Organic Chemistry.

PubMed

Itoh, Yukihiro; Suzuki, Takayoshi

2017-01-01

The first step in "drug" discovery is to find compounds binding to a potential drug target. In modern medicinal chemistry, the screening of a chemical library, structure-based drug design, and ligand-based drug design, or a combination of these methods, are generally used for identifying the desired compounds. However, they do not necessarily lead to success and there is no infallible method for drug discovery. Therefore, it is important to explore medicinal chemistry based on not only the conventional methods but also new ideas. So far, we have found various compounds as drug candidates. In these studies, some strategies based on organic chemistry have allowed us to find drug candidates, through 1) construction of a focused library using organic reactions and 2) rational design of enzyme inhibitors based on chemical reactions catalyzed by the target enzyme. Medicinal chemistry based on organic chemical reactions could be expected to supplement the conventional methods. In this review, we present drug discovery with the help of organic chemistry showing examples of our explorative studies on histone deacetylase inhibitors and lysine-specific demethylase 1 inhibitors.

Novel Directions for Diabetes Mellitus Drug Discovery

PubMed Central

Maiese, Kenneth; Chong, Zhao Zhong; Shang, Yan Chen; Wang, Shaohui

2012-01-01

Introduction Diabetes mellitus impacts almost 200 million individuals worldwide and leads to debilitating complications. New avenues of drug discovery must target the underlying cellular processes of oxidative stress, apoptosis, autophagy, and inflammation that can mediate multi-system pathology during diabetes mellitus. Areas Covered We examine novel directions for drug discovery that involve the β-nicotinamide adenine dinucleotide (NAD+) precursor nicotinamide, the cytokine erythropoietin, the NAD+-dependent protein histone deacetylase SIRT1, the serine/threonine-protein kinase mammalian target of rapamycin (mTOR), and the wingless pathway. Implications for the targeting of these pathways that oversee gluconeogenic genes, insulin signaling and resistance, fatty acid beta-oxidation, inflammation, and cellular survival are presented. Expert Opinion Nicotinamide, erythropoietin, and the downstram pathways of SIRT1, mTOR, forkhead transcription factors, and wingless signaling offer exciting prospects for novel directions of drug discovery for the treatment of metabolic disorders. Future investigations must dissect the complex relationship and fine modulation of these pathways for the successful translation of robust reparative and regenerative strategies against diabetes mellitus and the complications of this disorder. PMID:23092114

Targeting cysteine proteases in trypanosomatid disease drug discovery.

PubMed

Ferreira, Leonardo G; Andricopulo, Adriano D

2017-12-01

Chagas disease and human African trypanosomiasis are endemic conditions in Latin America and Africa, respectively, for which no effective and safe therapy is available. Efforts in drug discovery have focused on several enzymes from these protozoans, among which cysteine proteases have been validated as molecular targets for pharmacological intervention. These enzymes are expressed during the entire life cycle of trypanosomatid parasites and are essential to many biological processes, including infectivity to the human host. As a result of advances in the knowledge of the structural aspects of cysteine proteases and their role in disease physiopathology, inhibition of these enzymes by small molecules has been demonstrated to be a worthwhile approach to trypanosomatid drug research. This review provides an update on drug discovery strategies targeting the cysteine peptidases cruzain from Trypanosoma cruzi and rhodesain and cathepsin B from Trypanosoma brucei. Given that current chemotherapy for Chagas disease and human African trypanosomiasis has several drawbacks, cysteine proteases will continue to be actively pursued as valuable molecular targets in trypanosomatid disease drug discovery efforts. Copyright © 2017. Published by Elsevier Inc.

NMR approaches in structure-based lead discovery: recent developments and new frontiers for targeting multi-protein complexes.

PubMed

Dias, David M; Ciulli, Alessio

2014-01-01

Nuclear magnetic resonance (NMR) spectroscopy is a pivotal method for structure-based and fragment-based lead discovery because it is one of the most robust techniques to provide information on protein structure, dynamics and interaction at an atomic level in solution. Nowadays, in most ligand screening cascades, NMR-based methods are applied to identify and structurally validate small molecule binding. These can be high-throughput and are often used synergistically with other biophysical assays. Here, we describe current state-of-the-art in the portfolio of available NMR-based experiments that are used to aid early-stage lead discovery. We then focus on multi-protein complexes as targets and how NMR spectroscopy allows studying of interactions within the high molecular weight assemblies that make up a vast fraction of the yet untargeted proteome. Finally, we give our perspective on how currently available methods could build an improved strategy for drug discovery against such challenging targets. Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.

Predictors of timing of pregnancy discovery.

PubMed

McCarthy, Molly; Upadhyay, Ushma; Biggs, M Antonia; Anthony, Renaisa; Holl, Jennifer; Roberts, Sarah Cm

2018-04-01

Earlier pregnancy discovery is important in the context of prenatal and abortion care. We evaluated characteristics associated with later pregnancy discovery among women seeking abortion care. Data come from a survey of women seeking abortion care at four family planning facilities in Utah. The participants completed a survey during the state-mandated abortion information visit they are required to complete prior to having an abortion. The outcome in this study was pregnancy discovery before versus after 6 weeks since respondents' last menstrual period (LMP). We used logistic regression to estimate the relationship between sociodemographic and health-related independent variables of interest and pregnancy discovery before versus after 6 weeks. Among the 458 women in the sample, 28% discovered their pregnancy later than 6 weeks since LMP. Most (n=366, 80%) knew the exact date of their LMP and a significant minority estimated it (n=92, 20%). Those who estimated the date of their LMP had higher odds of later pregnancy discovery than those who knew the exact date (adjusted odds ratio (aOR)=1.81[1.07-3.07]). Those who used illicit drugs weekly, daily, or almost daily had higher odds of later pregnancy discovery (aOR=6.33[2.44, 16.40]). Women who did not track their menstrual periods and those who frequently used drugs had higher odds of discovering their pregnancies later. Women who estimated the date of their LMP and who frequently used drugs may benefit from strategies to help them recognize their pregnancies earlier and link them to care when they discover their pregnancies later. Copyright © 2017 Elsevier Inc. All rights reserved.

Machine Learning Based Classifier for Falsehood Detection

NASA Astrophysics Data System (ADS)

Mallikarjun, H. M.; Manimegalai, P., Dr.; Suresh, H. N., Dr.

2017-08-01

The investigation of physiological techniques for Falsehood identification tests utilizing the enthusiastic aggravations started as a part of mid 1900s. The need of Falsehood recognition has been a piece of our general public from hundreds of years back. Different requirements drifted over the general public raising the need to create trick evidence philosophies for Falsehood identification. The established similar addressing tests have been having a tendency to gather uncertain results against which new hearty strategies are being explored upon for acquiring more productive Falsehood discovery set up. Electroencephalography (EEG) is a non-obtrusive strategy to quantify the action of mind through the anodes appended to the scalp of a subject. Electroencephalogram is a record of the electric signs produced by the synchronous activity of mind cells over a timeframe. The fundamental goal is to accumulate and distinguish the important information through this action which can be acclimatized for giving surmising to Falsehood discovery in future analysis. This work proposes a strategy for Falsehood discovery utilizing EEG database recorded on irregular people of various age gatherings and social organizations. The factual investigation is directed utilizing MATLAB v-14. It is a superior dialect for specialized registering which spares a considerable measure of time with streamlined investigation systems. In this work center is made on Falsehood Classification by Support Vector Machine (SVM). 72 Samples are set up by making inquiries from standard poll with a Wright and wrong replies in a diverse era from the individual in wearable head unit. 52 samples are trained and 20 are tested. By utilizing Bluetooth based Neurosky’s Mindwave kit, brain waves are recorded and qualities are arranged appropriately. In this work confusion matrix is derived by matlab programs and accuracy of 56.25 % is achieved.

Discovery Strategies of Bioactive Compounds Synthesized by Nonribosomal Peptide Synthetases and Type-I Polyketide Synthases Derived from Marine Microbiomes

PubMed Central

Amoutzias, Grigoris D.; Chaliotis, Anargyros; Mossialos, Dimitris

2016-01-01

Considering that 70% of our planet’s surface is covered by oceans, it is likely that undiscovered biodiversity is still enormous. A large portion of marine biodiversity consists of microbiomes. They are very attractive targets of bioprospecting because they are able to produce a vast repertoire of secondary metabolites in order to adapt in diverse environments. In many cases secondary metabolites of pharmaceutical and biotechnological interest such as nonribosomal peptides (NRPs) and polyketides (PKs) are synthesized by multimodular enzymes named nonribosomal peptide synthetases (NRPSes) and type-I polyketide synthases (PKSes-I), respectively. Novel findings regarding the mechanisms underlying NRPS and PKS evolution demonstrate how microorganisms could leverage their metabolic potential. Moreover, these findings could facilitate synthetic biology approaches leading to novel bioactive compounds. Ongoing advances in bioinformatics and next-generation sequencing (NGS) technologies are driving the discovery of NRPs and PKs derived from marine microbiomes mainly through two strategies: genome-mining and metagenomics. Microbial genomes are now sequenced at an unprecedented rate and this vast quantity of biological information can be analyzed through genome mining in order to identify gene clusters encoding NRPSes and PKSes of interest. On the other hand, metagenomics is a fast-growing research field which directly studies microbial genomes and their products present in marine environments using culture-independent approaches. The aim of this review is to examine recent developments regarding discovery strategies of bioactive compounds synthesized by NRPS and type-I PKS derived from marine microbiomes and to highlight the vast diversity of NRPSes and PKSes present in marine environments by giving examples of recently discovered bioactive compounds. PMID:27092515

An integrated strategy for the systematic characterization and discovery of new indole alkaloids from Uncaria rhynchophylla by UHPLC/DAD/LTQ-Orbitrap-MS.

PubMed

Pan, Huiqin; Yang, Wenzhi; Zhang, Yibei; Yang, Min; Feng, Ruihong; Wu, Wanying; Guo, Dean

2015-08-01

The exploration of new chemical entities from herbal medicines may provide candidates for the in silico screening of drug leads. However, this significant work is hindered by the presence of multiple classes of plant metabolites and many re-discovered structures. This study presents an integrated strategy that uses ultrahigh-performance liquid chromatography/linear ion-trap quadrupole/Orbitrap mass spectrometry (UHPLC/LTQ-Orbitrap-MS) coupled with in-house library data for the systematic characterization and discovery of new potentially bioactive molecules. Exploration of the indole alkaloids from Uncaria rhynchophylla (UR) is presented as a model study. Initially, the primary characterization of alkaloids was achieved using mass defect filtering and neutral loss filtering. Subsequently, phytochemical isolation obtained 14 alkaloid compounds as reference standards, including a new one identified as 16,17-dihydro-O-demethylhirsuteine by NMR analyses. The direct-infusion fragmentation behaviors of these isolated alkaloids were studied to provide diagnostic structural information facilitating the rapid differentiation and characterization of four different alkaloid subtypes. Ultimately, after combining the experimental results with a survey of an in-house library containing 129 alkaloids isolated from the Uncaria genus, a total of 92 alkaloids (60 free alkaloids and 32 alkaloid O-glycosides) were identified or tentatively characterized, 56 of which are potential new alkaloids for the Uncaria genus. Hydroxylation on ring A, broad variations in the C-15 side chain, new N-oxides, and numerous O-glycosides, represent the novel features of the newly discovered indole alkaloid structures. These results greatly expand our knowledge of UR chemistry and are useful for the computational screening of potentially bioactive molecules from indole alkaloids. Graphical Abstract A four-step integrated strategy for the systematic characterization and efficient discovery of new indole alkaloids from Uncaria rhynchophylla.

The discovery and geophysical response of the Atlántida Cu-Au porphyry deposit, Chile

NASA Astrophysics Data System (ADS)

Hope, Matthew; Andersson, Steve

2016-03-01

The discovery of the Atlántida Cu-Au-Mo porphyry deposit, which is unconformably overlain by 25-80 m of gravels, is a recent example of exploration success under cover in a traditional mining jurisdiction. Early acquisition of geophysics was a key tool in the discovery, and in later guiding further exploration drilling throughout the life of the project. Detailed review of the geophysical response of the deposit, with respect to the distribution of lithologies and alteration, coupled with their petrophysical properties has allowed full characterisation, despite no exposure at the surface of host rock nor porphyry-style mineralisation. Data acquired over the project include induced polarisation, magnetotellurics, ground and airborne magnetics, ground-based gravimetry, and petrophysical sampling. The distribution of the key geological features of the deposit has been inferred via acquisition of petrophysical properties and interpretation of surface geophysical datasets. Magnetic susceptibility is influenced strongly by both alteration and primary lithology, whilst density variations are dominated by primary lithological control. Several studies have shown that electrical properties may map the footprint of the hydrothermal system and associated mineralisation, via a combination of chargeability and resistivity. These properties are observed in geophysical datasets acquired at surface and allow further targeting and sterilisation at the deposit and project scale. By understanding these geophysical characteristics in a geological context, these data can be used to infer distribution of lithological units, depth to exploration targets and the potential for high grade mineralisation. Future exploration will likely be increasingly reliant on the understanding of the surface manifestations of buried deposits in remotely acquired data. This review summarises the application and results of these principles at the Atlántida project of northern Chile. Geophysical data can be used to improve the chances of discovery beneath post-mineral cover, and also improve drilling results throughout the advanced exploration of the program. The process of data review against geological control information is essential.

The Climate-G testbed: towards a large scale data sharing environment for climate change

NASA Astrophysics Data System (ADS)

Aloisio, G.; Fiore, S.; Denvil, S.; Petitdidier, M.; Fox, P.; Schwichtenberg, H.; Blower, J.; Barbera, R.

2009-04-01

The Climate-G testbed provides an experimental large scale data environment for climate change addressing challenging data and metadata management issues. The main scope of Climate-G is to allow scientists to carry out geographical and cross-institutional climate data discovery, access, visualization and sharing. Climate-G is a multidisciplinary collaboration involving both climate and computer scientists and it currently involves several partners such as: Centro Euro-Mediterraneo per i Cambiamenti Climatici (CMCC), Institut Pierre-Simon Laplace (IPSL), Fraunhofer Institut für Algorithmen und Wissenschaftliches Rechnen (SCAI), National Center for Atmospheric Research (NCAR), University of Reading, University of Catania and University of Salento. To perform distributed metadata search and discovery, we adopted a CMCC metadata solution (which provides a high level of scalability, transparency, fault tolerance and autonomy) leveraging both on P2P and grid technologies (GRelC Data Access and Integration Service). Moreover, data are available through OPeNDAP/THREDDS services, Live Access Server as well as the OGC compliant Web Map Service and they can be downloaded, visualized, accessed into the proposed environment through the Climate-G Data Distribution Centre (DDC), the web gateway to the Climate-G digital library. The DDC is a data-grid portal allowing users to easily, securely and transparently perform search/discovery, metadata management, data access, data visualization, etc. Godiva2 (integrated into the DDC) displays 2D maps (and animations) and also exports maps for display on the Google Earth virtual globe. Presently, Climate-G publishes (through the DDC) about 2TB of data related to the ENSEMBLES project (also including distributed replicas of data) as well as to the IPCC AR4. The main results of the proposed work are: wide data access/sharing environment for climate change; P2P/grid metadata approach; production-level Climate-G DDC; high quality tools for data visualization; metadata search/discovery across several countries/institutions; open environment for climate change data sharing.

It takes a team: reflections on insecticide discoveries, toxicological problems and enjoying the unexpected.

PubMed

Wing, Keith D

2017-04-01

Absorption/distribution/metabolism/excretion (ADME)-related studies are mandatory in agrochemical development/registration, but can also play a valuable role in the discovery process. In combination with target-site potency, bioavailability/ADME characteristics determine agrochemical bioactivity and selectivity, and these concerns can dictate the fate of a discovery lead area. Bioavailability/ADME research was critical to the eventual commercialization of three different insecticide chemistries examined in this paper. In one situation, improved systemicity in anthranilic diamides was required to expand pest spectrum. In another, ADME tools were needed to improve the selective toxicity and non-target safety of sodium channel blocker insecticides. Finally, differential ADME characteristics of two classes of hormone agonists dictated differential insecticidal activity, and were useful in optimizing the dibenzoylhydrazine ecdysone agonists. ADME discovery research will help companies to advance novel, efficacious and selective agrochemicals, but organizational patience and a desire to understand lead areas in depth are required. © 2016 Society of Chemical Industry. © 2016 Society of Chemical Industry.

COMPUTER-AIDED DRUG DISCOVERY AND DEVELOPMENT (CADDD): in silico-chemico-biological approach

PubMed Central

Kapetanovic, I.M.

2008-01-01

It is generally recognized that drug discovery and development are very time and resources consuming processes. There is an ever growing effort to apply computational power to the combined chemical and biological space in order to streamline drug discovery, design, development and optimization. In biomedical arena, computer-aided or in silico design is being utilized to expedite and facilitate hit identification, hit-to-lead selection, optimize the absorption, distribution, metabolism, excretion and toxicity profile and avoid safety issues. Commonly used computational approaches include ligand-based drug design (pharmacophore, a 3-D spatial arrangement of chemical features essential for biological activity), structure-based drug design (drug-target docking), and quantitative structure-activity and quantitative structure-property relationships. Regulatory agencies as well as pharmaceutical industry are actively involved in development of computational tools that will improve effectiveness and efficiency of drug discovery and development process, decrease use of animals, and increase predictability. It is expected that the power of CADDD will grow as the technology continues to evolve. PMID:17229415

Sequence-Based Genotyping for Marker Discovery and Co-Dominant Scoring in Germplasm and Populations

PubMed Central

Truong, Hoa T.; Ramos, A. Marcos; Yalcin, Feyruz; de Ruiter, Marjo; van der Poel, Hein J. A.; Huvenaars, Koen H. J.; Hogers, René C. J.; van Enckevort, Leonora. J. G.; Janssen, Antoine; van Orsouw, Nathalie J.; van Eijk, Michiel J. T.

2012-01-01

Conventional marker-based genotyping platforms are widely available, but not without their limitations. In this context, we developed Sequence-Based Genotyping (SBG), a technology for simultaneous marker discovery and co-dominant scoring, using next-generation sequencing. SBG offers users several advantages including a generic sample preparation method, a highly robust genome complexity reduction strategy to facilitate de novo marker discovery across entire genomes, and a uniform bioinformatics workflow strategy to achieve genotyping goals tailored to individual species, regardless of the availability of a reference sequence. The most distinguishing features of this technology are the ability to genotype any population structure, regardless whether parental data is included, and the ability to co-dominantly score SNP markers segregating in populations. To demonstrate the capabilities of SBG, we performed marker discovery and genotyping in Arabidopsis thaliana and lettuce, two plant species of diverse genetic complexity and backgrounds. Initially we obtained 1,409 SNPs for arabidopsis, and 5,583 SNPs for lettuce. Further filtering of the SNP dataset produced over 1,000 high quality SNP markers for each species. We obtained a genotyping rate of 201.2 genotypes/SNP and 58.3 genotypes/SNP for arabidopsis (n = 222 samples) and lettuce (n = 87 samples), respectively. Linkage mapping using these SNPs resulted in stable map configurations. We have therefore shown that the SBG approach presented provides users with the utmost flexibility in garnering high quality markers that can be directly used for genotyping and downstream applications. Until advances and costs will allow for routine whole-genome sequencing of populations, we expect that sequence-based genotyping technologies such as SBG will be essential for genotyping of model and non-model genomes alike. PMID:22662172

Privileged structures: efficient chemical "navigators" toward unexplored biologically relevant chemical spaces.

PubMed

Kim, Jonghoon; Kim, Heejun; Park, Seung Bum

2014-10-22

In the search for new therapeutic agents for currently incurable diseases, attention has turned to traditionally "undruggable" targets, and collections of drug-like small molecules with high diversity and quality have become a prerequisite for new breakthroughs. To generate such collections, the diversity-oriented synthesis (DOS) strategy was developed, which aims to populate new chemical space with drug-like compounds containing a high degree of molecular diversity. The resulting DOS-derived libraries have been of great value for the discovery of various bioactive small molecules and therapeutic agents, and thus DOS has emerged as an essential tool in chemical biology and drug discovery. However, the key challenge has become how to design and synthesize drug-like small-molecule libraries with improved biological relevancy as well as maximum molecular diversity. This Perspective presents the development of privileged substructure-based DOS (pDOS), an efficient strategy for the construction of polyheterocyclic compound libraries with high biological relevancy. We envisioned the specific interaction of drug-like small molecules with certain biopolymers via the incorporation of privileged substructures into polyheterocyclic core skeletons. The importance of privileged substructures such as benzopyran, pyrimidine, and oxopiperazine in rigid skeletons was clearly demonstrated through the discovery of bioactive small molecules and the subsequent identification of appropriate target biomolecule using a method called "fluorescence difference in two-dimensional gel electrophoresis". Focusing on examples of pDOS-derived bioactive compounds with exceptional specificity, we discuss the capability of privileged structures to serve as chemical "navigators" toward biologically relevant chemical spaces. We also provide an outlook on chemical biology research and drug discovery using biologically relevant compound libraries constructed by pDOS, biology-oriented synthesis, or natural product-inspired DOS.

First centenary of Röntgen's discovery of X-rays

NASA Astrophysics Data System (ADS)

Valkovic, V.

1996-04-01

Usually it takes a decade or even several decades, from a discovery to its practical applications. This was not the case with X-rays; they were widely applied in medical and industrial radiography within a year of their discovery in 1895 by W.C. Röntgen. Today, X-ray analysis covers a wide range of techniques and fields of applications: from deduction of atomic arrangements by observation of diffraction phenomena to measurements of trace element concentration levels, distributions and maps by measuring fluorescence, X-ray attenuation or scattering. Although the contribution of analytical applications of X-rays to the present knowledge is difficult to surpass, modern application cover a wide range of activities from three-dimensional microfabrication using synchroton radiation to collecting information from the deep space by X-ray astronomy.

Recent Advances and Perspectives in Cancer Drug Design.

PubMed

Magalhaes, Luma G; Ferreira, Leonardo L G; Andricopulo, Adriano D

2018-01-01

Cancer is one of the leading causes of death worldwide. With the increase in life expectancy, the number of cancer cases has reached unprecedented levels. In this scenario, the pharmaceutical industry has made significant investments in this therapeutic area. Despite these efforts, cancer drug research remains a remarkably challenging field, and therapeutic innovations have not yet achieved expected clinical results. However, the physiopathology of the disease is now better understood, and the discovery of novel molecular targets has refreshed the expectations of developing improved treatments. Several noteworthy advances have been made, among which the development of targeted therapies is the most significant. Monoclonal antibodies and antibody-small molecule conjugates have emerged as a worthwhile approach to improve drug selectivity and reduce adverse effects, which are the main challenges in cancer drug discovery. This review will examine the current panorama of drug research and development (R&D) with emphasis on some of the major advances brought to clinical trials and to the market in the past five years. Breakthrough discoveries will be highlighted along with the medicinal chemistry strategies used throughout the discovery process. In addition, this review will provide perspectives and updates on the discovery of novel molecular targets as well as drugs with innovative mechanisms of action.

Twenty years on: the impact of fragments on drug discovery.

PubMed

Erlanson, Daniel A; Fesik, Stephen W; Hubbard, Roderick E; Jahnke, Wolfgang; Jhoti, Harren

2016-09-01

After 20 years of sometimes quiet growth, fragment-based drug discovery (FBDD) has become mainstream. More than 30 drug candidates derived from fragments have entered the clinic, with two approved and several more in advanced trials. FBDD has been widely applied in both academia and industry, as evidenced by the large number of papers from universities, non-profit research institutions, biotechnology companies and pharmaceutical companies. Moreover, FBDD draws on a diverse range of disciplines, from biochemistry and biophysics to computational and medicinal chemistry. As the promise of FBDD strategies becomes increasingly realized, now is an opportune time to draw lessons and point the way to the future. This Review briefly discusses how to design fragment libraries, how to select screening techniques and how to make the most of information gleaned from them. It also shows how concepts from FBDD have permeated and enhanced drug discovery efforts.

Pharmacokinetic/Pharmacodynamic-Driven Drug Development

PubMed Central

Gallo, James M.

2010-01-01

The drug discovery and development enterprise, traditionally an industrial juggernaut, has spanned into the academic arena that is partially motivated by the National Institutes of Health Roadmap highlighting translational science and medicine. Since drug discovery and development represents a pipeline of basic to clinical investigations it meshes well with the prime “bench to the bedside” directive of translational medicine. The renewed interest in drug discovery and develpoment in academia provides an opportunity to rethink the hiearchary of studies with the hope to improve the staid approaches that have been critizied for lacking innovation. One area that has received limited attention concerns the use of pharmacokinetic [PK] and pharmacodynamic [PD] studies in the drug development process. Using anticancer drug development as a focus, this review will address past and current deficencies in how PK/PD studies are conducted and offer new strategies that might bridge the gap between preclinical and clinical trials. PMID:20687184

Response-Guided Community Detection: Application to Climate Index Discovery

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bello, Gonzalo; Angus, Michael; Pedemane, Navya

Discovering climate indices-time series that summarize spatiotemporal climate patterns-is a key task in the climate science domain. In this work, we approach this task as a problem of response-guided community detection; that is, identifying communities in a graph associated with a response variable of interest. To this end, we propose a general strategy for response-guided community detection that explicitly incorporates information of the response variable during the community detection process, and introduce a graph representation of spatiotemporal data that leverages information from multiple variables. We apply our proposed methodology to the discovery of climate indices associated with seasonal rainfall variability.more » Our results suggest that our methodology is able to capture the underlying patterns known to be associated with the response variable of interest and to improve its predictability compared to existing methodologies for data-driven climate index discovery and official forecasts.« less

The current state of GPCR-based drug discovery to treat metabolic disease.

PubMed

Sloop, Kyle W; Emmerson, Paul J; Statnick, Michael A; Willard, Francis S

2018-02-02

One approach of modern drug discovery is to identify agents that enhance or diminish signal transduction cascades in various cell types and tissues by modulating the activity of GPCRs. This strategy has resulted in the development of new medicines to treat many conditions, including cardiovascular disease, psychiatric disorders, HIV/AIDS, certain forms of cancer and Type 2 diabetes mellitus (T2DM). These successes justify further pursuit of GPCRs as disease targets and provide key learning that should help guide identifying future therapeutic agents. This report reviews the current landscape of GPCR drug discovery with emphasis on efforts aimed at developing new molecules for treating T2DM and obesity. We analyse historical efforts to generate GPCR-based drugs to treat metabolic disease in terms of causal factors leading to success and failure in this endeavour. © 2018 The British Pharmacological Society.

Dereplication of peptidic natural products through database search of mass spectra

PubMed Central

Mohimani, Hosein; Gurevich, Alexey; Mikheenko, Alla; Garg, Neha; Nothias, Louis-Felix; Ninomiya, Akihiro; Takada, Kentaro; Dorrestein, Pieter C.; Pevzner, Pavel A.

2016-01-01

Peptidic Natural Products (PNPs) are widely used compounds that include many antibiotics and a variety of other bioactive peptides. While recent breakthroughs in PNP discovery raised the challenge of developing new algorithms for their analysis, identification of PNPs via database search of tandem mass spectra remains an open problem. To address this problem, natural product researchers utilize dereplication strategies that identify known PNPs and lead to the discovery of new ones even in cases when the reference spectra are not present in existing spectral libraries. DEREPLICATOR is a new dereplication algorithm that enabled high-throughput PNP identification and that is compatible with large-scale mass spectrometry-based screening platforms for natural product discovery. After searching nearly one hundred million tandem mass spectra in the Global Natural Products Social (GNPS) molecular networking infrastructure, DEREPLICATOR identified an order of magnitude more PNPs (and their new variants) than any previous dereplication efforts. PMID:27820803

Bioinformatics and peptidomics approaches to the discovery and analysis of food-derived bioactive peptides.

PubMed

Agyei, Dominic; Tsopmo, Apollinaire; Udenigwe, Chibuike C

2018-06-01

There are emerging advancements in the strategies used for the discovery and development of food-derived bioactive peptides because of their multiple food and health applications. Bioinformatics and peptidomics are two computational and analytical techniques that have the potential to speed up the development of bioactive peptides from bench to market. Structure-activity relationships observed in peptides form the basis for bioinformatics and in silico prediction of bioactive sequences encrypted in food proteins. Peptidomics, on the other hand, relies on "hyphenated" (liquid chromatography-mass spectrometry-based) techniques for the detection, profiling, and quantitation of peptides. Together, bioinformatics and peptidomics approaches provide a low-cost and effective means of predicting, profiling, and screening bioactive protein hydrolysates and peptides from food. This article discuses the basis, strengths, and limitations of bioinformatics and peptidomics approaches currently used for the discovery and analysis of food-derived bioactive peptides.

The 2015 Nobel Prize in Chemistry The Discovery of Essential Mechanisms that Repair DNA Damage.

PubMed

Lindahl, Tomas; Modrich, Paul; Sancar, Aziz

2016-01-01

The Royal Swedish Academy awarded the Nobel Prize in Chemistry for 2015 to Tomas Lindahl, Paul Modrich and Aziz Sancar for their discoveries in fundamental mechanisms of DNA repair. This pioneering research described three different essential pathways that correct DNA damage, safeguard the integrity of the genetic code to ensure its accurate replication through generations, and allow proper cell division. Working independently of each other, Tomas Lindahl, Paul Modrich and Aziz Sancar delineated the mechanisms of base excision repair, mismatch repair and nucleotide excision repair, respectively. These breakthroughs challenged and dismissed the early view that the DNA molecule was very stable, paving the way for the discovery of human hereditary diseases associated with distinct DNA repair deficiencies and a susceptibility to cancer. It also brought a deeper understanding of cancer as well as neurodegenerative or neurological diseases, and let to novel strategies to treat cancer.

Synthesis-Spectroscopy Roadmap Problems: Discovering Organic Chemistry

ERIC Educational Resources Information Center

Kurth, Laurie L.; Kurth, Mark J.

2014-01-01

Organic chemistry problems that interrelate and integrate synthesis with spectroscopy are presented. These synthesis-spectroscopy roadmap (SSR) problems uniquely engage second-year undergraduate organic chemistry students in the personal discovery of organic chemistry. SSR problems counter the memorize-or-bust strategy that many students tend to…

Constructivism in Reading Education.

ERIC Educational Resources Information Center

Stanovich, Keith

1994-01-01

In the development of word recognition skills, self-discovery may not be the most efficacious mode of learning, and it may be useful to isolate or fractionate cognitive components. Successful intervention directed at word recognition involves exogenous constructivism, in which explicit instruction and teacher-directed strategy teaching are not…

Virtual Cities--A Regional Discovery Project.

ERIC Educational Resources Information Center

Stanfel, Julie

1993-01-01

Describes the "Virtual Cities" project, a virtual reality satellite teleconference with students age 12 to 17 from Canada, Italy, and the United States held during the International Council for Educational Media 1992 conference. A visual database overlaid with instructional gaming strategies provided students with the opportunity to…

Information Science Research: The Search for the Nature of Information.

ERIC Educational Resources Information Center

Kochen, Manfred

1984-01-01

High-level scientific research in the information sciences is illustrated by sampling of recent discoveries involving adaptive information processing strategies, computer and information systems, centroid scaling, economic growth of computer and communication industries, and information flow in biological systems. Relationship of information…

Remarks to Eighth Annual State of Modeling and Simulation

DTIC Science & Technology

1999-06-04

organization, training as well as materiel Discovery vice Verification Tolerance for Surprise Free play Red Team Iterative Process Push to failure...Account for responsive & innovative future adversaries – free play , adaptive strategies and tactics by professional red teams • Address C2 issues & human

Systematic development of small molecules to inhibit specific microscopic steps of Aβ42 aggregation in Alzheimer’s disease

PubMed Central

Habchi, Johnny; Chia, Sean; Limbocker, Ryan; Mannini, Benedetta; Ahn, Minkoo; Perni, Michele; Hansson, Oskar; Arosio, Paolo; Kumita, Janet R.; Challa, Pavan Kumar; Cohen, Samuel I. A.; Dobson, Christopher M.; Knowles, Tuomas P. J.; Vendruscolo, Michele

2017-01-01

The aggregation of the 42-residue form of the amyloid-β peptide (Aβ42) is a pivotal event in Alzheimer’s disease (AD). The use of chemical kinetics has recently enabled highly accurate quantifications of the effects of small molecules on specific microscopic steps in Aβ42 aggregation. Here, we exploit this approach to develop a rational drug discovery strategy against Aβ42 aggregation that uses as a read-out the changes in the nucleation and elongation rate constants caused by candidate small molecules. We thus identify a pool of compounds that target specific microscopic steps in Aβ42 aggregation. We then test further these small molecules in human cerebrospinal fluid and in a Caenorhabditis elegans model of AD. Our results show that this strategy represents a powerful approach to identify systematically small molecule lead compounds, thus offering an appealing opportunity to reduce the attrition problem in drug discovery. PMID:28011763

A review of the ligands and related targeting strategies for active targeting of paclitaxel to tumours.

PubMed

Li, Juan; Wang, Fengshan; Sun, Deqing; Wang, Rongmei

2016-08-01

It has been 30 years since the discovery of the anti-tumour property of paclitaxel (PTX), which has been successfully applied in clinic for the treatment of carcinomas of the lungs, breast and ovarian. However, PTX is poorly soluble in water and has no targeting and selectivity to tumour tissue. Recent advances in active tumour targeting of PTX delivery vehicles have addressed some of the issues related to lack of solubility in water and non-specific toxicities associated with PTX. These PTX delivery vehicles are designed for active targeting to specific cancer cells by the addition of ligands for recognition by specific receptors/antigens on cancer cells. This article will focus on various ligands and related targeting strategies serving as potential tools for active targeting of PTX to tumour tissues, illustrating their use in different tumour models. This review also highlights the need of further studies on the discovery of receptors in different cells of specific organ and ligands with binding efficiency to these specific receptors.

A Network-Biology Informed Computational Drug Repositioning Strategy to Target Disease Risk Trajectories and Comorbidities of Peripheral Artery Disease.

PubMed

Shameer, Khader; Dow, Garrett; Glicksberg, Benjamin S; Johnson, Kipp W; Ze, Yi; Tomlinson, Max S; Readhead, Ben; Dudley, Joel T; Kullo, Iftikhar J

2018-01-01

Currently, drug discovery approaches focus on the design of therapies that alleviate an index symptom by reengineering the underlying biological mechanism in agonistic or antagonistic fashion. For example, medicines are routinely developed to target an essential gene that drives the disease mechanism. Therapeutic overloading where patients get multiple medications to reduce the primary and secondary side effect burden is standard practice. This single-symptom based approach may not be scalable, as we understand that diseases are more connected than random and molecular interactions drive disease comorbidities. In this work, we present a proof-of-concept drug discovery strategy by combining network biology, disease comorbidity estimates, and computational drug repositioning, by targeting the risk factors and comorbidities of peripheral artery disease, a vascular disease associated with high morbidity and mortality. Individualized risk estimation and recommending disease sequelae based therapies may help to lower the mortality and morbidity of peripheral artery disease.

Comprehensive analysis of T cell epitope discovery strategies using 17DD yellow fever virus structural proteins and BALB/c (H2d) mice model.

PubMed

Maciel, Milton; Kellathur, Srinivasan N; Chikhlikar, Pryia; Dhalia, Rafael; Sidney, John; Sette, Alessandro; August, Thomas J; Marques, Ernesto T A

2008-08-15

Immunomics research uses in silico epitope prediction, as well as in vivo and in vitro approaches. We inoculated BALB/c (H2d) mice with 17DD yellow fever vaccine to investigate the correlations between approaches used for epitope discovery: ELISPOT assays, binding assays, and prediction software. Our results showed a good agreement between ELISPOT and binding assays, which seemed to correlate with the protein immunogenicity. PREDBALB/c prediction software partially agreed with the ELISPOT and binding assay results, but presented low specificity. The use of prediction software to exclude peptides containing no epitopes, followed by high throughput screening of the remaining peptides by ELISPOT, and the use of MHC-biding assays to characterize the MHC restrictions demonstrated to be an efficient strategy. The results allowed the characterization of 2 MHC class I and 17 class II epitopes in the envelope protein of the YF virus in BALB/c (H2d) mice.

Integrating functional genomics to accelerate mechanistic personalized medicine.

PubMed

Tyner, Jeffrey W

2017-03-01

The advent of deep sequencing technologies has resulted in the deciphering of tremendous amounts of genetic information. These data have led to major discoveries, and many anecdotes now exist of individual patients whose clinical outcomes have benefited from novel, genetically guided therapeutic strategies. However, the majority of genetic events in cancer are currently undrugged, leading to a biological gap between understanding of tumor genetic etiology and translation to improved clinical approaches. Functional screening has made tremendous strides in recent years with the development of new experimental approaches to studying ex vivo and in vivo drug sensitivity. Numerous discoveries and anecdotes also exist for translation of functional screening into novel clinical strategies; however, the current clinical application of functional screening remains largely confined to small clinical trials at specific academic centers. The intersection between genomic and functional approaches represents an ideal modality to accelerate our understanding of drug sensitivities as they relate to specific genetic events and further understand the full mechanisms underlying drug sensitivity patterns.

Avoiding reification. Heuristic effectiveness of mathematics and the prediction of the Ω- particle

NASA Astrophysics Data System (ADS)

Ginammi, Michele

2016-02-01

According to Steiner (1998), in contemporary physics new important discoveries are often obtained by means of strategies which rely on purely formal mathematical considerations. In such discoveries, mathematics seems to have a peculiar and controversial role, which apparently cannot be accounted for by means of standard methodological criteria. M. Gell-Mann and Y. Ne'eman's prediction of the Ω- particle is usually considered a typical example of application of this kind of strategy. According to Bangu (2008), this prediction is apparently based on the employment of a highly controversial principle-what he calls the "reification principle". Bangu himself takes this principle to be methodologically unjustifiable, but still indispensable to make the prediction logically sound. In the present paper I will offer a new reconstruction of the reasoning that led to this prediction. By means of this reconstruction, I will show that we do not need to postulate any "reificatory" role of mathematics in contemporary physics and I will contextually clarify the representative and heuristic role of mathematics in science.

A Network-Biology Informed Computational Drug Repositioning Strategy to Target Disease Risk Trajectories and Comorbidities of Peripheral Artery Disease

PubMed Central

Shameer, Khader; Dow, Garrett; Glicksberg, Benjamin S.; Johnson, Kipp W.; Ze, Yi; Tomlinson, Max S.; Readhead, Ben; Dudley, Joel T.; Kullo, Iftikhar J.

2018-01-01

Currently, drug discovery approaches focus on the design of therapies that alleviate an index symptom by reengineering the underlying biological mechanism in agonistic or antagonistic fashion. For example, medicines are routinely developed to target an essential gene that drives the disease mechanism. Therapeutic overloading where patients get multiple medications to reduce the primary and secondary side effect burden is standard practice. This single-symptom based approach may not be scalable, as we understand that diseases are more connected than random and molecular interactions drive disease comorbidities. In this work, we present a proof-of-concept drug discovery strategy by combining network biology, disease comorbidity estimates, and computational drug repositioning, by targeting the risk factors and comorbidities of peripheral artery disease, a vascular disease associated with high morbidity and mortality. Individualized risk estimation and recommending disease sequelae based therapies may help to lower the mortality and morbidity of peripheral artery disease. PMID:29888052

Citation Discovery Tools for Conducting Adaptive Meta-analyses to Update Systematic Reviews.

PubMed

Bae, Jong-Myon; Kim, Eun Hee

2016-03-01

The systematic review (SR) is a research methodology that aims to synthesize related evidence. Updating previously conducted SRs is necessary when new evidence has been produced, but no consensus has yet emerged on the appropriate update methodology. The authors have developed a new SR update method called 'adaptive meta-analysis' (AMA) using the 'cited by', 'similar articles', and 'related articles' citation discovery tools in the PubMed and Scopus databases. This study evaluates the usefulness of these citation discovery tools for updating SRs. Lists were constructed by applying the citation discovery tools in the two databases to the articles analyzed by a published SR. The degree of overlap between the lists and distribution of excluded results were evaluated. The articles ultimately selected for the SR update meta-analysis were found in the lists obtained from the 'cited by' and 'similar' tools in PubMed. Most of the selected articles appeared in both the 'cited by' lists in Scopus and PubMed. The Scopus 'related' tool did not identify the appropriate articles. The AMA, which involves using both citation discovery tools in PubMed, and optionally, the 'related' tool in Scopus, was found to be useful for updating an SR.

Asteroid Detection Results Using the Space Surveillance Telescope

DTIC Science & Technology

2015-10-18

Distribution Statement A: Approved for public release, distribution unlimited. Asteroid Detection Results Using the Space Surveillance Telescope...issued a series of directives to the National Air and Space Administration (NASA), setting Near-Earth Asteroid (NEA) search and discovery targets in...order to protect the Earth and its inhabitants from the threat of asteroid impact. The focus of the original 1998 Congressional mandate was to catalog

Hybrid data acquisition and processing strategies with increased throughput and selectivity: pSMART analysis for global qualitative and quantitative analysis.

PubMed

Prakash, Amol; Peterman, Scott; Ahmad, Shadab; Sarracino, David; Frewen, Barbara; Vogelsang, Maryann; Byram, Gregory; Krastins, Bryan; Vadali, Gouri; Lopez, Mary

2014-12-05

Data-dependent acquisition (DDA) and data-independent acquisition strategies (DIA) have both resulted in improved understanding of proteomics samples. Both strategies have advantages and disadvantages that are well-published, where DDA is typically applied for deep discovery and DIA may be used to create sample records. In this paper, we present a hybrid data acquisition and processing strategy (pSMART) that combines the strengths of both techniques and provides significant benefits for qualitative and quantitative peptide analysis. The performance of pSMART is compared to published DIA strategies in an experiment that allows the objective assessment of DIA performance with respect to interrogation of previously acquired MS data. The results of this experiment demonstrate that pSMART creates fewer decoy hits than a standard DIA strategy. Moreover, we show that pSMART is more selective, sensitive, and reproducible than either standard DIA or DDA strategies alone.

Local Sparse Bump Hunting

PubMed Central

Dazard, Jean-Eudes; Rao, J. Sunil

2010-01-01

The search for structures in real datasets e.g. in the form of bumps, components, classes or clusters is important as these often reveal underlying phenomena leading to scientific discoveries. One of these tasks, known as bump hunting, is to locate domains of a multidimensional input space where the target function assumes local maxima without pre-specifying their total number. A number of related methods already exist, yet are challenged in the context of high dimensional data. We introduce a novel supervised and multivariate bump hunting strategy for exploring modes or classes of a target function of many continuous variables. This addresses the issues of correlation, interpretability, and high-dimensionality (p ≫ n case), while making minimal assumptions. The method is based upon a divide and conquer strategy, combining a tree-based method, a dimension reduction technique, and the Patient Rule Induction Method (PRIM). Important to this task, we show how to estimate the PRIM meta-parameters. Using accuracy evaluation procedures such as cross-validation and ROC analysis, we show empirically how the method outperforms a naive PRIM as well as competitive non-parametric supervised and unsupervised methods in the problem of class discovery. The method has practical application especially in the case of noisy high-throughput data. It is applied to a class discovery problem in a colon cancer micro-array dataset aimed at identifying tumor subtypes in the metastatic stage. Supplemental Materials are available online. PMID:22399839

Discovery of cryptophycin-1 and BCN-183577: examples of strategies and problems in the detection of antitumor activity in mice.

PubMed

Corbett, T H; Valeriote, F A; Demchik, L; Lowichik, N; Polin, L; Panchapor, C; Pugh, S; White, K; Kushner, J; Rake, J; Wentland, M; Golakoti, T; Hetzel, C; Ogino, J; Patterson, G; Moore, R

1997-01-01

Historically, many new anticancer agents were first detected in a prescreen; usually consisting of a molecular/biochemical target or a cellular cytotoxicity assay. The agent then progressed to in vivo evaluation against transplanted human or mouse tumors. If the investigator had a large drug supply and ample resources, multiple tests were possible, with variations in tumor models, tumor and drug routes, dose-decrements, dose-schedules, number of groups, etc. However, in most large programs involving several hundred in vivo tests yearly, resource limitations and drug supply limitations have usually dictated a single trial. Under such restrictive conditions, we have implemented a flexible in vivo testing protocol. With this strategy, the tumor model is dictated by in vitro cellular sensitivity; drug route by water solubility (with water soluble agents injected intravenously); dosage decrement by drug supply, dose-schedule by toxicities encountered, etc. In this flexible design, many treatment parameters can be changed during the course of treatment (e.g., dose and schedule). The discovery of two active agents are presented (Cryptophycin-1, and Thioxanthone BCN 183577). Both were discovered by the intravenous route of administration. Both would have been missed if they were tested intraperitoneally, the usual drug route used in discovery protocols. It is also likely that they would have been missed with an easy to execute fixed protocol design, even if injected i.v.

Optimal route discovery for soft QOS provisioning in mobile ad hoc multimedia networks

NASA Astrophysics Data System (ADS)

Huang, Lei; Pan, Feng

2007-09-01

In this paper, we propose an optimal routing discovery algorithm for ad hoc multimedia networks whose resource keeps changing, First, we use stochastic models to measure the network resource availability, based on the information about the location and moving pattern of the nodes, as well as the link conditions between neighboring nodes. Then, for a certain multimedia packet flow to be transmitted from a source to a destination, we formulate the optimal soft-QoS provisioning problem as to find the best route that maximize the probability of satisfying its desired QoS requirements in terms of the maximum delay constraints. Based on the stochastic network resource model, we developed three approaches to solve the formulated problem: A centralized approach serving as the theoretical reference, a distributed approach that is more suitable to practical real-time deployment, and a distributed dynamic approach that utilizes the updated time information to optimize the routing for each individual packet. Examples of numerical results demonstrated that using the route discovered by our distributed algorithm in a changing network environment, multimedia applications could achieve better QoS statistically.

Discovery of Paragonimus westermani in Vietnam and its molecular phylogenetic status in P. westermani complex.

PubMed

Doanh, Pham Ngoc; Shinohara, Akio; Horii, Yoichiro; Habe, Shigehisa; Nawa, Yukifumi

2009-04-01

Paragonimus westermani is the most well-known species among the genus Paragonimus. It is widely distributed in Asia with considerable genetic diversity to form P. westermani species complex. While P. westermani distributed in Japan, Korea, China, and Taiwan are genetically homogeneous to form the East Asia group, those found in other geographic areas are heterogeneous and would be divided into several groups. Recent discoveries of P. westermani in India and Sri Lanka highlighted new insights on molecular phylogenetic relationship of geographic isolates of this species complex. Since Vietnam is located at the east end of Southeast Asia, the intermediate position between South and East Asia, it is of interest to see whether P. westermani is distributed in this country. Here, we report that P. westermani metacercariae were found in mountainous crabs, Potamiscus sp., collected in Quangtri province in the central Vietnam. Adult worms were successfully obtained by experimental infection in cats. Molecular phylogenetic analyses revealed that P. westermani of Vietnamese isolates have high similarities with those of East Asia group.

Managing motherhood: strategies used by new mothers to maintain perceptions of wellness.

PubMed

Currie, Janet

2009-07-01

The first year or so of motherhood can represent a transitional lifestyle change; however, experiences are not well understood from the mother's own perspective. In a series of interviews, nine mothers related their beliefs and ideas about strategies utilized to maintain a perceived sense of wellness. The mothers used three main strategies: (a) obtaining help, (b) having a plan, and (c) taking time-out. Discovery of a successful strategy lead to a mother feeling greater confidence in the efficacy of her selected method, calmer, and in greater control. In order to achieve a true sense of increasing control over her own health, however, it is recommended a mother prioritize strategies to meet her own personal needs in addition to meeting the needs of others.

Conceptual biology, hypothesis discovery, and text mining: Swanson's legacy.

PubMed

Bekhuis, Tanja

2006-04-03

Innovative biomedical librarians and information specialists who want to expand their roles as expert searchers need to know about profound changes in biology and parallel trends in text mining. In recent years, conceptual biology has emerged as a complement to empirical biology. This is partly in response to the availability of massive digital resources such as the network of databases for molecular biologists at the National Center for Biotechnology Information. Developments in text mining and hypothesis discovery systems based on the early work of Swanson, a mathematician and information scientist, are coincident with the emergence of conceptual biology. Very little has been written to introduce biomedical digital librarians to these new trends. In this paper, background for data and text mining, as well as for knowledge discovery in databases (KDD) and in text (KDT) is presented, then a brief review of Swanson's ideas, followed by a discussion of recent approaches to hypothesis discovery and testing. 'Testing' in the context of text mining involves partially automated methods for finding evidence in the literature to support hypothetical relationships. Concluding remarks follow regarding (a) the limits of current strategies for evaluation of hypothesis discovery systems and (b) the role of literature-based discovery in concert with empirical research. Report of an informatics-driven literature review for biomarkers of systemic lupus erythematosus is mentioned. Swanson's vision of the hidden value in the literature of science and, by extension, in biomedical digital databases, is still remarkably generative for information scientists, biologists, and physicians.

Encoded Library Synthesis Using Chemical Ligation and the Discovery of sEH Inhibitors from a 334-Million Member Library

NASA Astrophysics Data System (ADS)

Litovchick, Alexander; Dumelin, Christoph E.; Habeshian, Sevan; Gikunju, Diana; Guié, Marie-Aude; Centrella, Paolo; Zhang, Ying; Sigel, Eric A.; Cuozzo, John W.; Keefe, Anthony D.; Clark, Matthew A.

2015-06-01

A chemical ligation method for construction of DNA-encoded small-molecule libraries has been developed. Taking advantage of the ability of the Klenow fragment of DNA polymerase to accept templates with triazole linkages in place of phosphodiesters, we have designed a strategy for chemically ligating oligonucleotide tags using cycloaddition chemistry. We have utilized this strategy in the construction and selection of a small molecule library, and successfully identified inhibitors of the enzyme soluble epoxide hydrolase.

A bioinformatics knowledge discovery in text application for grid computing

PubMed Central

Castellano, Marcello; Mastronardi, Giuseppe; Bellotti, Roberto; Tarricone, Gianfranco

2009-01-01

Background A fundamental activity in biomedical research is Knowledge Discovery which has the ability to search through large amounts of biomedical information such as documents and data. High performance computational infrastructures, such as Grid technologies, are emerging as a possible infrastructure to tackle the intensive use of Information and Communication resources in life science. The goal of this work was to develop a software middleware solution in order to exploit the many knowledge discovery applications on scalable and distributed computing systems to achieve intensive use of ICT resources. Methods The development of a grid application for Knowledge Discovery in Text using a middleware solution based methodology is presented. The system must be able to: perform a user application model, process the jobs with the aim of creating many parallel jobs to distribute on the computational nodes. Finally, the system must be aware of the computational resources available, their status and must be able to monitor the execution of parallel jobs. These operative requirements lead to design a middleware to be specialized using user application modules. It included a graphical user interface in order to access to a node search system, a load balancing system and a transfer optimizer to reduce communication costs. Results A middleware solution prototype and the performance evaluation of it in terms of the speed-up factor is shown. It was written in JAVA on Globus Toolkit 4 to build the grid infrastructure based on GNU/Linux computer grid nodes. A test was carried out and the results are shown for the named entity recognition search of symptoms and pathologies. The search was applied to a collection of 5,000 scientific documents taken from PubMed. Conclusion In this paper we discuss the development of a grid application based on a middleware solution. It has been tested on a knowledge discovery in text process to extract new and useful information about symptoms and pathologies from a large collection of unstructured scientific documents. As an example a computation of Knowledge Discovery in Database was applied on the output produced by the KDT user module to extract new knowledge about symptom and pathology bio-entities. PMID:19534749

A bioinformatics knowledge discovery in text application for grid computing.

PubMed

Castellano, Marcello; Mastronardi, Giuseppe; Bellotti, Roberto; Tarricone, Gianfranco

2009-06-16

A fundamental activity in biomedical research is Knowledge Discovery which has the ability to search through large amounts of biomedical information such as documents and data. High performance computational infrastructures, such as Grid technologies, are emerging as a possible infrastructure to tackle the intensive use of Information and Communication resources in life science. The goal of this work was to develop a software middleware solution in order to exploit the many knowledge discovery applications on scalable and distributed computing systems to achieve intensive use of ICT resources. The development of a grid application for Knowledge Discovery in Text using a middleware solution based methodology is presented. The system must be able to: perform a user application model, process the jobs with the aim of creating many parallel jobs to distribute on the computational nodes. Finally, the system must be aware of the computational resources available, their status and must be able to monitor the execution of parallel jobs. These operative requirements lead to design a middleware to be specialized using user application modules. It included a graphical user interface in order to access to a node search system, a load balancing system and a transfer optimizer to reduce communication costs. A middleware solution prototype and the performance evaluation of it in terms of the speed-up factor is shown. It was written in JAVA on Globus Toolkit 4 to build the grid infrastructure based on GNU/Linux computer grid nodes. A test was carried out and the results are shown for the named entity recognition search of symptoms and pathologies. The search was applied to a collection of 5,000 scientific documents taken from PubMed. In this paper we discuss the development of a grid application based on a middleware solution. It has been tested on a knowledge discovery in text process to extract new and useful information about symptoms and pathologies from a large collection of unstructured scientific documents. As an example a computation of Knowledge Discovery in Database was applied on the output produced by the KDT user module to extract new knowledge about symptom and pathology bio-entities.

Activity-based protein profiling for biochemical pathway discovery in cancer

PubMed Central

Nomura, Daniel K.; Dix, Melissa M.; Cravatt, Benjamin F.

2011-01-01

Large-scale profiling methods have uncovered numerous gene and protein expression changes that correlate with tumorigenesis. However, determining the relevance of these expression changes and which biochemical pathways they affect has been hindered by our incomplete understanding of the proteome and its myriad functions and modes of regulation. Activity-based profiling platforms enable both the discovery of cancer-relevant enzymes and selective pharmacological probes to perturb and characterize these proteins in tumour cells. When integrated with other large-scale profiling methods, activity-based proteomics can provide insight into the metabolic and signalling pathways that support cancer pathogenesis and illuminate new strategies for disease diagnosis and treatment. PMID:20703252

Oncology drug discovery: planning a turnaround.

PubMed

Toniatti, Carlo; Jones, Philip; Graham, Hilary; Pagliara, Bruno; Draetta, Giulio

2014-04-01

We have made remarkable progress in our understanding of the pathophysiology of cancer. This improved understanding has resulted in increasingly effective targeted therapies that are better tolerated than conventional cytotoxic agents and even curative in some patients. Unfortunately, the success rate of drug approval has been limited, and therapeutic improvements have been marginal, with too few exceptions. In this article, we review the current approach to oncology drug discovery and development, identify areas in need of improvement, and propose strategies to improve patient outcomes. We also suggest future directions that may improve the quality of preclinical and early clinical drug evaluation, which could lead to higher approval rates of anticancer drugs.

Bacteriophage-based synthetic biology for the study of infectious diseases

PubMed Central

Lu, Timothy K.

2014-01-01

Since their discovery, bacteriophages have contributed enormously to our understanding of molecular biology as model systems. Furthermore, bacteriophages have provided many tools that have advanced the fields of genetic engineering and synthetic biology. Here, we discuss bacteriophage-based technologies and their application to the study of infectious diseases. New strategies for engineering genomes have the potential to accelerate the design of novel phages as therapies, diagnostics, and tools. Though almost a century has elapsed since their discovery, bacteriophages continue to have a major impact on modern biological sciences, especially with the growth of multidrug-resistant bacteria and interest in the microbiome. PMID:24997401

Report from solar physics

NASA Technical Reports Server (NTRS)

Walker, A. B. C.; Acton, L.; Brueckner, G.; Chupp, E. L.; Hudson, H. S.; Roberts, W.

1989-01-01

A discussion of the nature of solar physics is followed by a brief review of recent advances in the field. These advances include: the first direct experimental confirmation of the central role played by thermonuclear processes in stars; the discovery that the 5-minute oscillations of the Sun are a global seismic phenomenon that can be used as a probe of the structure and dynamical behavior of the solar interior; the discovery that the solar magnetic field is subdivided into individual flux tubes with field strength exceeding 1000 gauss. Also covered was a science strategy for pure solar physics. Brief discussions are given of solar-terrestrial physics, solar/stellar relationships, and suggested space missions.

Translational bioinformatics: linking the molecular world to the clinical world.

PubMed

Altman, R B

2012-06-01

Translational bioinformatics represents the union of translational medicine and bioinformatics. Translational medicine moves basic biological discoveries from the research bench into the patient-care setting and uses clinical observations to inform basic biology. It focuses on patient care, including the creation of new diagnostics, prognostics, prevention strategies, and therapies based on biological discoveries. Bioinformatics involves algorithms to represent, store, and analyze basic biological data, including DNA sequence, RNA expression, and protein and small-molecule abundance within cells. Translational bioinformatics spans these two fields; it involves the development of algorithms to analyze basic molecular and cellular data with an explicit goal of affecting clinical care.

Testing models of parental investment strategy and offspring size in ants.

PubMed

Gilboa, Smadar; Nonacs, Peter

2006-01-01

Parental investment strategies can be fixed or flexible. A fixed strategy predicts making all offspring a single 'optimal' size. Dynamic models predict flexible strategies with more than one optimal size of offspring. Patterns in the distribution of offspring sizes may thus reveal the investment strategy. Static strategies should produce normal distributions. Dynamic strategies should often result in non-normal distributions. Furthermore, variance in morphological traits should be positively correlated with the length of developmental time the traits are exposed to environmental influences. Finally, the type of deviation from normality (i.e., skewed left or right, or platykurtic) should be correlated with the average offspring size. To test the latter prediction, we used simulations to detect significant departures from normality and categorize distribution types. Data from three species of ants strongly support the predicted patterns for dynamic parental investment. Offspring size distributions are often significantly non-normal. Traits fixed earlier in development, such as head width, are less variable than final body weight. The type of distribution observed correlates with mean female dry weight. The overall support for a dynamic parental investment model has implications for life history theory. Predicted conflicts over parental effort, sex investment ratios, and reproductive skew in cooperative breeders follow from assumptions of static parental investment strategies and omnipresent resource limitations. By contrast, with flexible investment strategies such conflicts can be either absent or maladaptive.

Advocating for Student Health through Grassroots Curricular Development

ERIC Educational Resources Information Center

Barcelona, Jeanne M.; Goetten, Julia

2018-01-01

One strategy for creating a healthy school culture is to integrate health concepts into core subject areas. In this article, a health and wellness coordinator and a curriculum specialist explain the meticulous process and discoveries that led to the development of a district-specific health curriculum.

Insights about Psychotherapy Training and Curricular Sequencing: Portal of Discovery

ERIC Educational Resources Information Center

McGowen, K. Ramsey; Miller, Merry Noel; Floyd, Michael; Miller, Barney; Coyle, Brent

2009-01-01

Objective: The authors discuss the curricular implications of a research project originally designed to evaluate the instructional strategy of using standardized patients in a psychotherapy training seminar. Methods: The original project included second-year residents enrolled in an introductory psychotherapy seminar that employed sequential…

Advances in the discovery of novel repellents and application strategies

USDA-ARS?s Scientific Manuscript database

The United States Department of Agriculture’s (USDA) Insects Affecting Man and Animals Research Laboratory in Orlando, Florida received its first sample insecticide, a natural pyrethrin mixture, in 1942. In 1963, this laboratory moved to Gainesville, Florida, where it now resides at the Center for ...

High-Throughput Screening of Ototoxic and Otoprotective Pharmacological Drugs

ERIC Educational Resources Information Center

Kalinec, Federico

2005-01-01

Drug ototoxicity research has relied traditionally on animal models for the discovery and development of therapeutic interventions. More than 50 years of research, however, has delivered few--if any--successful clinical strategies for preventing or ameliorating the ototoxic effects of common pharmacological drugs such as aminoglycoside…

A Reference Implementation of the OGC CSW EO Standard for the ESA HMA-T project

NASA Astrophysics Data System (ADS)

Bigagli, Lorenzo; Boldrini, Enrico; Papeschi, Fabrizio; Vitale, Fabrizio

2010-05-01

This work was developed in the context of the ESA Heterogeneous Missions Accessibility (HMA) project, whose main objective is to involve the stakeholders, namely National space agencies, satellite or mission owners and operators, in an harmonization and standardization process of their ground segment services and related interfaces. Among HMA objectives was the specification, conformance testing, and experimentation of two Extension Packages (EPs) of the ebRIM Application Profile (AP) of the OGC Catalog Service for the Web (CSW) specification: the Earth Observation Products (EO) EP (OGC 06-131) and the Cataloguing of ISO Metadata (CIM) EP (OGC 07-038). Our contributions have included the development and deployment of Reference Implementations (RIs) for both the above specifications, and their integration with the ESA Service Support Environment (SSE). The RIs are based on the GI-cat framework, an implementation of a distributed catalog service, able to query disparate Earth and Space Science data sources (e.g. OGC Web Services, Unidata THREDDS) and to expose several standard interfaces for data discovery (e.g. OGC CSW ISO AP). Following our initial planning, the GI-cat framework has been extended in order to expose the CSW.ebRIM-CIM and CSW.ebRIM-EO interfaces, and to distribute queries to CSW.ebRIM-CIM and CSW.ebRIM-EO data sources. We expected that a mapping strategy would suffice for accommodating CIM, but this proved to be unpractical during implementation. Hence, a model extension strategy was eventually implemented for both the CIM and EO EPs, and the GI-cat federal model was enhanced in order to support the underlying ebRIM AP. This work has provided us with new insights into the different data models for geospatial data, and the technologies for their implementation. The extension is used by suitable CIM and EO profilers (front-end mediator components) and accessors (back-end mediator components), that relate ISO 19115 concepts to EO and CIM ones. Moreover, a mapping to GI-cat federal model was developed for each EP (quite limited for EO; complete for CIM), in order to enable the discovery of resources through any of GI-cat profilers. The query manager was also improved. GI-cat-EO and -CIM installation packages were made available for distribution, and two RI instances were deployed on the Amazon EC2 facility (plus an ad-hoc instance returning incorrect control data). Integration activities of the EO RI with the ESA SSE Portal for Earth Observation Products were also successfully carried on. During our work, we have contributed feedback and comments to the CIM and EO EP specification working groups. Our contributions resulted in version 0.2.5 of the EO EP, recently approved as an OGC standard, and were useful to consolidate version 0.1.11 of the CIM EP (still being developed).

New marine natural products from sponges (Porifera) of the order Dictyoceratida (2001 to 2012); a promising source for drug discovery, exploration and future prospects.

PubMed

Mehbub, Mohammad F; Perkins, Michael V; Zhang, Wei; Franco, Christopher M M

2016-01-01

The discovery of new drugs can no longer rely primarily on terrestrial resources, as they have been heavily exploited for over a century. During the last few decades marine sources, particularly sponges, have proven to be a most promising source of new natural products for drug discovery. This review considers the order Dictyoceratida in the Phylum Porifera from which the largest number of new marine natural products have been reported over the period 2001-2012. This paper examines all the sponges from the order Dictyoceratida that were reported as new compounds during the time period in a comprehensive manner. The distinctive physical characteristics and the geographical distribution of the different families are presented. The wide structural diversity of the compounds produced and the variety of biological activities they exhibited is highlighted. As a representative of sponges, insights into this order and avenues for future effective natural product discovery are presented. The research institutions associated with the various studies are also highlighted with the aim of facilitating collaborative relationships, as well as to acknowledge the major international contributors to the discovery of novel sponge metabolites. The order Dictyoceratida is a valuable source of novel chemical structures which will continue to contribute to a new era of drug discovery. Copyright © 2015 Elsevier Inc. All rights reserved.

Exploration and exploitation of Victorian science in Darwin's reading notebooks.

PubMed

Murdock, Jaimie; Allen, Colin; DeDeo, Simon

2017-02-01

Search in an environment with an uncertain distribution of resources involves a trade-off between exploitation of past discoveries and further exploration. This extends to information foraging, where a knowledge-seeker shifts between reading in depth and studying new domains. To study this decision-making process, we examine the reading choices made by one of the most celebrated scientists of the modern era: Charles Darwin. From the full-text of books listed in his chronologically-organized reading journals, we generate topic models to quantify his local (text-to-text) and global (text-to-past) reading decisions using Kullback-Liebler Divergence, a cognitively-validated, information-theoretic measure of relative surprise. Rather than a pattern of surprise-minimization, corresponding to a pure exploitation strategy, Darwin's behavior shifts from early exploitation to later exploration, seeking unusually high levels of cognitive surprise relative to previous eras. These shifts, detected by an unsupervised Bayesian model, correlate with major intellectual epochs of his career as identified both by qualitative scholarship and Darwin's own self-commentary. Our methods allow us to compare his consumption of texts with their publication order. We find Darwin's consumption more exploratory than the culture's production, suggesting that underneath gradual societal changes are the explorations of individual synthesis and discovery. Our quantitative methods advance the study of cognitive search through a framework for testing interactions between individual and collective behavior and between short- and long-term consumption choices. This novel application of topic modeling to characterize individual reading complements widespread studies of collective scientific behavior. Copyright © 2016 Elsevier B.V. All rights reserved.

Exploring the unknown: assumptions about allelic architecture and strategies for susceptibility variant discovery.

PubMed

McCarthy, Mark I

2009-07-03

Identification of common-variant associations for many common disorders has been highly effective, but the loci detected so far typically explain only a small proportion of the genetic predisposition to disease. Extending explained genetic variance is one of the major near-term goals of human genetic research. Next-generation sequencing technologies offer great promise, but optimal strategies for their deployment remain uncertain, not least because we lack a clear view of the characteristics of the variants being sought. Here, I discuss what can and cannot be inferred about complex trait disease architecture from the information currently available and review the implications for future research strategies.

Screening strategies to identify new chemical diversity for drug development to treat kinetoplastid infections.

PubMed

Don, Rob; Ioset, Jean-Robert

2014-01-01

The Drugs for Neglected Diseases initiative (DNDi) has defined and implemented an early discovery strategy over the last few years, in fitting with its virtual R&D business model. This strategy relies on a medium- to high-throughput phenotypic assay platform to expedite the screening of compound libraries accessed through its collaborations with partners from the pharmaceutical industry. We review the pragmatic approaches used to select compound libraries for screening against kinetoplastids, taking into account screening capacity. The advantages, limitations and current achievements in identifying new quality series for further development into preclinical candidates are critically discussed, together with attractive new approaches currently under investigation.

Mining the human plasma proteome with three-dimensional strategies by high-resolution Quadrupole Orbitrap Mass Spectrometry.

PubMed

Zhao, Yan; Chang, Cheng; Qin, Peibin; Cao, Qichen; Tian, Fang; Jiang, Jing; Li, Xianyu; Yu, Wenfeng; Zhu, Yunping; He, Fuchu; Ying, Wantao; Qian, Xiaohong

2016-01-21

Human plasma is a readily available clinical sample that reflects the status of the body in normal physiological and disease states. Although the wide dynamic range and immense complexity of plasma proteins are obstacles, comprehensive proteomic analysis of human plasma is necessary for biomarker discovery and further verification. Various methods such as immunodepletion, protein equalization and hyper fractionation have been applied to reduce the influence of high-abundance proteins (HAPs) and to reduce the high level of complexity. However, the depth at which the human plasma proteome has been explored in a relatively short time frame has been limited, which impedes the transfer of proteomic techniques to clinical research. Development of an optimal strategy is expected to improve the efficiency of human plasma proteome profiling. Here, five three-dimensional strategies combining HAP depletion (the 1st dimension) and protein fractionation (the 2nd dimension), followed by LC-MS/MS analysis (the 3rd dimension) were developed and compared for human plasma proteome profiling. Pros and cons of the five strategies are discussed for two issues: HAP depletion and complexity reduction. Strategies A and B used proteome equalization and tandem Seppro IgY14 immunodepletion, respectively, as the first dimension. Proteome equalization (strategy A) was biased toward the enrichment of basic and low-molecular weight proteins and had limited ability to enrich low-abundance proteins. By tandem removal of HAPs (strategy B), the efficiency of HAP depletion was significantly increased, whereas more off-target proteins were subtracted simultaneously. In the comparison of complexity reduction, strategy D involved a deglycosylation step before high-pH RPLC separation. However, the increase in sequence coverage did not increase the protein number as expected. Strategy E introduced SDS-PAGE separation of proteins, and the results showed oversampling of HAPs and identification of fewer proteins. Strategy C combined single Seppro IgY14 immunodepletion, high-pH RPLC fractionation and LC-MS/MS analysis. It generated the largest dataset, containing 1544 plasma protein groups and 258 newly identified proteins in a 30-h-machine-time analysis, making it the optimum three-dimensional strategy in our study. Further analysis of the integrated data from the five strategies showed identical distribution patterns in terms of sequence features and GO functional analysis with the 1929-plasma-protein dataset, further supporting the reliability of our plasma protein identifications. The characterization of 20 cytokines in the concentration range from sub-nanograms/milliliter to micrograms/milliliter demonstrated the sensitivity of the current strategies. Copyright © 2015 Elsevier B.V. All rights reserved.

Future technology insight: mass spectrometry imaging as a tool in drug research and development

PubMed Central

Cobice, D F; Goodwin, R J A; Andren, P E; Nilsson, A; Mackay, C L; Andrew, R

2015-01-01

In pharmaceutical research, understanding the biodistribution, accumulation and metabolism of drugs in tissue plays a key role during drug discovery and development. In particular, information regarding pharmacokinetics, pharmacodynamics and transport properties of compounds in tissues is crucial during early screening. Historically, the abundance and distribution of drugs have been assessed by well-established techniques such as quantitative whole-body autoradiography (WBA) or tissue homogenization with LC/MS analysis. However, WBA does not distinguish active drug from its metabolites and LC/MS, while highly sensitive, does not report spatial distribution. Mass spectrometry imaging (MSI) can discriminate drug and its metabolites and endogenous compounds, while simultaneously reporting their distribution. MSI data are influencing drug development and currently used in investigational studies in areas such as compound toxicity. In in vivo studies MSI results may soon be used to support new drug regulatory applications, although clinical trial MSI data will take longer to be validated for incorporation into submissions. We review the current and future applications of MSI, focussing on applications for drug discovery and development, with examples to highlight the impact of this promising technique in early drug screening. Recent sample preparation and analysis methods that enable effective MSI, including quantitative analysis of drugs from tissue sections will be summarized and key aspects of methodological protocols to increase the effectiveness of MSI analysis for previously undetectable targets addressed. These examples highlight how MSI has become a powerful tool in drug research and development and offers great potential in streamlining the drug discovery process. PMID:25766375

Strategic Roadmap for the U.S. Geoscience Information Network

NASA Astrophysics Data System (ADS)

Allison, M. L.; Gallagher, K. T.; Richard, S. M.; Hutchison, V. B.

2012-04-01

An external advisory working group has prepared a 5-year strategic roadmap for the U.S. Geoscience Information Network (USGIN). USGIN is a partnership of the Association of American State Geologists (AASG) and the U.S. Geological Survey (USGS), who formally agreed in 2007 to develop a national geoscience information framework that is distributed, interoperable, uses open source standards and common protocols, respects and acknowledges data ownership, fosters communities of practice to grow, and develops new Web services and clients. The intention of the USGIN is to benefit the geological surveys by reducing the cost of online data publication and access provision, and to benefit society through easier (lower cost) access to public domain geoscience data. This information supports environmental planning, resource-development, hazard mitigation design, and decision-making. USGIN supposes that sharing resources for system development and maintenance, standardizing data discovery and creating better access mechanisms, causes cost of data access and maintenance to be reduced. Standardization in a wide variety of business domains provides economic benefits that range between 0.2 and 0.9% of the gross national product. We suggest that the economic benefits of standardization also apply in the informatics domain. Standardized access to rich data resources will create collaborative opportunities in science and business. Development and use of shared protocols and interchange formats for data publication will create a market for user applications, facilitating geoscience data discovery and utility for the benefit of society. The USGIN Working Group envisions further development of tools and capabilities, in addition to extending the community of practice that currently involves geoinformatics practitioners from the USGS and AASG. Promoting engagement and participation of the state geological surveys, and increasing communication between the states, USGS, and other stakeholders are prerequisites for community development. A key element of community building is personal interaction. The USGIN community can establish an identity for geological survey informatics practitioners, can assist in prioritizing technical development that is specific to the geological survey community, and can leverage development taking place in the larger community. Policies, protocols, and procedures for developing, reviewing, and distributing specifications can be adopted from established practices developed by existing organizations, such as the OGC. Documenting and promoting best practices through demonstrations, education, and outreach within the geological survey community is paramount for fostering deployment of interoperable services for data discovery and distribution. Evolution of the current Balkanized geoinformatics practice into a more cohesive and effective community has been and will continue to be an incremental process. The role of USGIN as an entity in this larger community requires organization, planning, promotion, and funding. As a member of a community activity, the role of USGIN as a leader in the community must be organic and emergent. Essential implementation activities include: • Establish a long-term governance model • Develop a business model • Explore testbed opportunities • Develop marketing strategy

An Efficient Approach to Evaluate Reporter Ion Behavior from MALDI-MS/MS Data for Quantification Studies using Isobaric Tags

PubMed Central

Cologna, Stephanie M.; Crutchfield, Christopher A.; Searle, Brian C.; Blank, Paul S.; Toth, Cynthia L.; Ely, Alexa M.; Picache, Jaqueline A.; Backlund, Peter S.; Wassif, Christopher A.; Porter, Forbes D.; Yergey, Alfred L.

2017-01-01

Protein quantification, identification and abundance determination are important aspects of proteome characterization and are crucial in understanding biological mechanisms and human diseases. Different strategies are available to quantify proteins using mass spectrometric detection, and most are performed at the peptide level and include both targeted and un-targeted methodologies. Discovery-based or un-targeted approaches oftentimes use covalent tagging strategies (i.e., iTRAQ®, TMT™) where reporter ion signals collected in the tandem MS experiment are used for quantification. Herein we investigate the behavior of the iTRAQ 8-plex chemistry using MALDI-TOF/TOF instrumentation. The experimental design and data analysis approach described is simple and straightforward, which allows researchers to optimize data collection and proper analysis within a laboratory. iTRAQ reporter ion signals were normalized within each spectrum to remove peptide biases. An advantage of this approach is that missing reporter ion values can be accepted for purposes of protein identification and quantification with the need for ANOVA analysis. We investigate the distribution of reporter ion peak areas in an equimolar system and a mock biological system and provide recommendations for establishing fold-change cutoff values at the peptide level for iTRAQ datasets. These data provide a unique dataset available to the community for informatics training and analysis. PMID:26288259

MAP: an iterative experimental design methodology for the optimization of catalytic search space structure modeling.

PubMed

Baumes, Laurent A

2006-01-01

One of the main problems in high-throughput research for materials is still the design of experiments. At early stages of discovery programs, purely exploratory methodologies coupled with fast screening tools should be employed. This should lead to opportunities to find unexpected catalytic results and identify the "groups" of catalyst outputs, providing well-defined boundaries for future optimizations. However, very few new papers deal with strategies that guide exploratory studies. Mostly, traditional designs, homogeneous covering, or simple random samplings are exploited. Typical catalytic output distributions exhibit unbalanced datasets for which an efficient learning is hardly carried out, and interesting but rare classes are usually unrecognized. Here is suggested a new iterative algorithm for the characterization of the search space structure, working independently of learning processes. It enhances recognition rates by transferring catalysts to be screened from "performance-stable" space zones to "unsteady" ones which necessitate more experiments to be well-modeled. The evaluation of new algorithm attempts through benchmarks is compulsory due to the lack of past proofs about their efficiency. The method is detailed and thoroughly tested with mathematical functions exhibiting different levels of complexity. The strategy is not only empirically evaluated, the effect or efficiency of sampling on future Machine Learning performances is also quantified. The minimum sample size required by the algorithm for being statistically discriminated from simple random sampling is investigated.

OpenZika: An IBM World Community Grid Project to Accelerate Zika Virus Drug Discovery

PubMed Central

Perryman, Alexander L.; Horta Andrade, Carolina

2016-01-01

The Zika virus outbreak in the Americas has caused global concern. To help accelerate this fight against Zika, we launched the OpenZika project. OpenZika is an IBM World Community Grid Project that uses distributed computing on millions of computers and Android devices to run docking experiments, in order to dock tens of millions of drug-like compounds against crystal structures and homology models of Zika proteins (and other related flavivirus targets). This will enable the identification of new candidates that can then be tested in vitro, to advance the discovery and development of new antiviral drugs against the Zika virus. The docking data is being made openly accessible so that all members of the global research community can use it to further advance drug discovery studies against Zika and other related flaviviruses. PMID:27764115

OpenZika: An IBM World Community Grid Project to Accelerate Zika Virus Drug Discovery.

PubMed

Ekins, Sean; Perryman, Alexander L; Horta Andrade, Carolina

2016-10-01

The Zika virus outbreak in the Americas has caused global concern. To help accelerate this fight against Zika, we launched the OpenZika project. OpenZika is an IBM World Community Grid Project that uses distributed computing on millions of computers and Android devices to run docking experiments, in order to dock tens of millions of drug-like compounds against crystal structures and homology models of Zika proteins (and other related flavivirus targets). This will enable the identification of new candidates that can then be tested in vitro, to advance the discovery and development of new antiviral drugs against the Zika virus. The docking data is being made openly accessible so that all members of the global research community can use it to further advance drug discovery studies against Zika and other related flaviviruses.

Efficient exact motif discovery.

PubMed

Marschall, Tobias; Rahmann, Sven

2009-06-15

The motif discovery problem consists of finding over-represented patterns in a collection of biosequences. It is one of the classical sequence analysis problems, but still has not been satisfactorily solved in an exact and efficient manner. This is partly due to the large number of possibilities of defining the motif search space and the notion of over-representation. Even for well-defined formalizations, the problem is frequently solved in an ad hoc manner with heuristics that do not guarantee to find the best motif. We show how to solve the motif discovery problem (almost) exactly on a practically relevant space of IUPAC generalized string patterns, using the p-value with respect to an i.i.d. model or a Markov model as the measure of over-representation. In particular, (i) we use a highly accurate compound Poisson approximation for the null distribution of the number of motif occurrences. We show how to compute the exact clump size distribution using a recently introduced device called probabilistic arithmetic automaton (PAA). (ii) We define two p-value scores for over-representation, the first one based on the total number of motif occurrences, the second one based on the number of sequences in a collection with at least one occurrence. (iii) We describe an algorithm to discover the optimal pattern with respect to either of the scores. The method exploits monotonicity properties of the compound Poisson approximation and is by orders of magnitude faster than exhaustive enumeration of IUPAC strings (11.8 h compared with an extrapolated runtime of 4.8 years). (iv) We justify the use of the proposed scores for motif discovery by showing our method to outperform other motif discovery algorithms (e.g. MEME, Weeder) on benchmark datasets. We also propose new motifs on Mycobacterium tuberculosis. The method has been implemented in Java. It can be obtained from http://ls11-www.cs.tu-dortmund.de/people/marschal/paa_md/.

Perfluoroalkyl acids and related chemistries Toxicokinetics and modes of action

EPA Science Inventory

The perfluoroalkyl acid salts (both carboxylates and sulfonates, hereafter designated as PFAAs) and their derivatives are important chemicals that have numerous consumer and industrial applications. However, recent discoveries that some of these compounds have global distribution...

A Role for Fragment-Based Drug Design in Developing Novel Lead Compounds for Central Nervous System Targets.

PubMed

Wasko, Michael J; Pellegrene, Kendy A; Madura, Jeffry D; Surratt, Christopher K

2015-01-01

Hundreds of millions of U.S. dollars are invested in the research and development of a single drug. Lead compound development is an area ripe for new design strategies. Therapeutic lead candidates have been traditionally found using high-throughput in vitro pharmacological screening, a costly method for assaying thousands of compounds. This approach has recently been augmented by virtual screening (VS), which employs computer models of the target protein to narrow the search for possible leads. A variant of VS is fragment-based drug design (FBDD), an emerging in silico lead discovery method that introduces low-molecular weight fragments, rather than intact compounds, into the binding pocket of the receptor model. These fragments serve as starting points for "growing" the lead candidate. Current efforts in virtual FBDD within central nervous system (CNS) targets are reviewed, as is a recent rule-based optimization strategy in which new molecules are generated within a 3D receptor-binding pocket using the fragment as a scaffold. This process not only places special emphasis on creating synthesizable molecules but also exposes computational questions worth addressing. Fragment-based methods provide a viable, relatively low-cost alternative for therapeutic lead discovery and optimization that can be applied to CNS targets to augment current design strategies.

A Role for Fragment-Based Drug Design in Developing Novel Lead Compounds for Central Nervous System Targets

PubMed Central

Wasko, Michael J.; Pellegrene, Kendy A.; Madura, Jeffry D.; Surratt, Christopher K.

2015-01-01

Hundreds of millions of U.S. dollars are invested in the research and development of a single drug. Lead compound development is an area ripe for new design strategies. Therapeutic lead candidates have been traditionally found using high-throughput in vitro pharmacological screening, a costly method for assaying thousands of compounds. This approach has recently been augmented by virtual screening (VS), which employs computer models of the target protein to narrow the search for possible leads. A variant of VS is fragment-based drug design (FBDD), an emerging in silico lead discovery method that introduces low-molecular weight fragments, rather than intact compounds, into the binding pocket of the receptor model. These fragments serve as starting points for “growing” the lead candidate. Current efforts in virtual FBDD within central nervous system (CNS) targets are reviewed, as is a recent rule-based optimization strategy in which new molecules are generated within a 3D receptor-binding pocket using the fragment as a scaffold. This process not only places special emphasis on creating synthesizable molecules but also exposes computational questions worth addressing. Fragment-based methods provide a viable, relatively low-cost alternative for therapeutic lead discovery and optimization that can be applied to CNS targets to augment current design strategies. PMID:26441817

Novel strategies for anti-aging drug discovery.

PubMed

Saraswat, Komal; Rizvi, Syed Ibrahim

2017-09-01

Scientific achievements in the last few decades, leading to effective therapeutic interventions, have dramatically improved human life expectancy. Consequently, aging has become a significant problem and represents the major risk factor for most human pathologies including diabetes, cardiovascular diseases, neurological disorders, and cancer. Scientific discoveries over the past two decades have been instrumental in dissecting molecular mechanism(s) which play important roles in determining longevity. The same understanding has also led to the acknowledgement of the plurality of 'causes' which act either alone or in combination to create the condition which can be defined as 'aging'. Areas covered: Over the years, several concepts have been put forward for the development of a viable anti-aging regimen. In this review, the authors extensively review anti aging interventions based on caloric restriction, activation of telomerase, autophagy inducers, senolytic therapeutics, plasma membrane redox system (PMRS) activators, epigenetic modulators, and stem cell therapies. Expert opinion: Based upon our current understanding, one of the most promising approaches for a successful anti-aging strategy includes the activation of adenosine monophosphate dependent protein kinase (AMPK). Another strategy may involve activation of PMRS. Future research efforts are likely to focus on nutrient and energy sensing molecular pathways which include mTOR, IGF-1, AMPK and the sirtuins.

Building Community-Engaged Health Research and Discovery Infrastructure on the South Side of Chicago: Science in Service to Community Priorities

PubMed Central

Lindau, Stacy Tessler; Makelarski, Jennifer A.; Chin, Marshall H.; Desautels, Shane; Johnson, Daniel; Johnson, Waldo E.; Miller, Doriane; Peters, Susan; Robinson, Connie; Schneider, John; Thicklin, Florence; Watson, Natalie P.; Wolfe, Marcus; Whitaker, Eric

2011-01-01

Objective To describe the roles community members can and should play in, and an asset-based strategy used by Chicago’s South Side Health and Vitality Studies for, building sustainable, large-scale community health research infrastructure. The Studies are a family of research efforts aiming to produce actionable knowledge to inform health policy, programming, and investments for the region. Methods Community and university collaborators, using a consensus-based approach, developed shared theoretical perspectives, guiding principles, and a model for collaboration in 2008, which were used to inform an asset-based operational strategy. Ongoing community engagement and relationship-building support the infrastructure and research activities of the Studies. Results Key steps in the asset-based strategy include: 1) continuous community engagement and relationship building, 2) identifying community priorities, 3) identifying community assets, 4) leveraging assets, 5) conducting research, 6) sharing knowledge and 7) informing action. Examples of community member roles, and how these are informed by the Studies’ guiding principles, are provided. Conclusions Community and university collaborators, with shared vision and principles, can effectively work together to plan innovative, large-scale community-based research that serves community needs and priorities. Sustainable, effective models are needed to realize NIH’s mandate for meaningful translation of biomedical discovery into improved population health. PMID:21236295

A Thoroughly Validated Virtual Screening Strategy for Discovery of Novel HDAC3 Inhibitors.

PubMed

Hu, Huabin; Xia, Jie; Wang, Dongmei; Wang, Xiang Simon; Wu, Song

2017-01-18

Histone deacetylase 3 (HDAC3) has been recently identified as a potential target for the treatment of cancer and other diseases, such as chronic inflammation, neurodegenerative diseases, and diabetes. Virtual screening (VS) is currently a routine technique for hit identification, but its success depends on rational development of VS strategies. To facilitate this process, we applied our previously released benchmarking dataset, i.e., MUBD-HDAC3 to the evaluation of structure-based VS (SBVS) and ligand-based VS (LBVS) combinatorial approaches. We have identified FRED (Chemgauss4) docking against a structural model of HDAC3, i.e., SAHA-3 generated by a computationally inexpensive "flexible docking", as the best SBVS approach and a common feature pharmacophore model, i.e., Hypo1 generated by Catalyst/HipHop as the optimal model for LBVS. We then developed a pipeline that was composed of Hypo1, FRED (Chemgauss4), and SAHA-3 sequentially, and demonstrated that it was superior to other combinations in terms of ligand enrichment. In summary, we present the first highly-validated, rationally-designed VS strategy specific to HDAC3 inhibitor discovery. The constructed pipeline is publicly accessible for the scientific community to identify novel HDAC3 inhibitors in a time-efficient and cost-effective way.

Connecting Neuronal Cell Protective Pathways and Drug Combinations in a Huntington's Disease Model through the Application of Quantitative Systems Pharmacology.

PubMed

Pei, Fen; Li, Hongchun; Henderson, Mark J; Titus, Steven A; Jadhav, Ajit; Simeonov, Anton; Cobanoglu, Murat Can; Mousavi, Seyed H; Shun, Tongying; McDermott, Lee; Iyer, Prema; Fioravanti, Michael; Carlisle, Diane; Friedlander, Robert M; Bahar, Ivet; Taylor, D Lansing; Lezon, Timothy R; Stern, Andrew M; Schurdak, Mark E

2017-12-19

Quantitative Systems Pharmacology (QSP) is a drug discovery approach that integrates computational and experimental methods in an iterative way to gain a comprehensive, unbiased understanding of disease processes to inform effective therapeutic strategies. We report the implementation of QSP to Huntington's Disease, with the application of a chemogenomics platform to identify strategies to protect neuronal cells from mutant huntingtin induced death. Using the STHdh Q111 cell model, we investigated the protective effects of small molecule probes having diverse canonical modes-of-action to infer pathways of neuronal cell protection connected to drug mechanism. Several mechanistically diverse protective probes were identified, most of which showed less than 50% efficacy. Specific combinations of these probes were synergistic in enhancing efficacy. Computational analysis of these probes revealed a convergence of pathways indicating activation of PKA. Analysis of phospho-PKA levels showed lower cytoplasmic levels in STHdh Q111 cells compared to wild type STHdh Q7 cells, and these levels were increased by several of the protective compounds. Pharmacological inhibition of PKA activity reduced protection supporting the hypothesis that protection may be working, in part, through activation of the PKA network. The systems-level studies described here can be broadly applied to any discovery strategy involving small molecule modulation of disease phenotype.

A Thoroughly Validated Virtual Screening Strategy for Discovery of Novel HDAC3 Inhibitors

PubMed Central

Hu, Huabin; Xia, Jie; Wang, Dongmei; Wang, Xiang Simon; Wu, Song

2017-01-01

Histone deacetylase 3 (HDAC3) has been recently identified as a potential target for the treatment of cancer and other diseases, such as chronic inflammation, neurodegenerative diseases, and diabetes. Virtual screening (VS) is currently a routine technique for hit identification, but its success depends on rational development of VS strategies. To facilitate this process, we applied our previously released benchmarking dataset, i.e., MUBD-HDAC3 to the evaluation of structure-based VS (SBVS) and ligand-based VS (LBVS) combinatorial approaches. We have identified FRED (Chemgauss4) docking against a structural model of HDAC3, i.e., SAHA-3 generated by a computationally inexpensive “flexible docking”, as the best SBVS approach and a common feature pharmacophore model, i.e., Hypo1 generated by Catalyst/HipHop as the optimal model for LBVS. We then developed a pipeline that was composed of Hypo1, FRED (Chemgauss4), and SAHA-3 sequentially, and demonstrated that it was superior to other combinations in terms of ligand enrichment. In summary, we present the first highly-validated, rationally-designed VS strategy specific to HDAC3 inhibitor discovery. The constructed pipeline is publicly accessible for the scientific community to identify novel HDAC3 inhibitors in a time-efficient and cost-effective way. PMID:28106794

Novel drug discovery strategies for atherosclerosis that target necrosis and necroptosis.

PubMed

Coornaert, Isabelle; Hofmans, Sam; Devisscher, Lars; Augustyns, Koen; Van Der Veken, Pieter; De Meyer, Guido R Y; Martinet, Wim

2018-06-01

Formation and enlargement of a necrotic core play a pivotal role in atherogenesis. Since the discovery of necroptosis, which is a regulated form of necrosis, prevention of necrotic cell death has become an attractive therapeutic goal to reduce plaque formation. Areas covered: This review highlights the triggers and consequences of (unregulated) necrosis and necroptosis in atherosclerosis. The authors discuss different pharmacological strategies to inhibit necrotic cell death in advanced atherosclerotic plaques. Expert opinion: Addition of a necrosis or necroptosis inhibitor to standard statin therapy could be a promising strategy for primary prevention of cardiovascular disease. However, a necrosis inhibitor cannot block all necrosis stimuli in atherosclerotic plaques. A necroptosis inhibitor could be more effective, because necroptosis is mediated by specific proteins, termed receptor-interacting serine/threonine-protein kinases (RIPK) and mixed lineage kinase domain-like pseudokinase (MLKL). Currently, only RIPK1 inhibitors have been successfully used in atherosclerotic mouse models to inhibit necroptosis. However, because RIPK1 is involved in both necroptosis and apoptosis, and also RIPK1-independent necroptosis can occur, we feel that targeting RIPK3 and MLKL could be a more attractive therapeutic approach to inhibit necroptosis. Therefore, future challenges will consist of developing RIPK3 and MLKL inhibitors applicable in both preclinical and clinical settings.

Teaching the Silk Road: A Journey of Pedagogical Discovery.

ERIC Educational Resources Information Center

Andrea, A. J.; Mierse, William

2002-01-01

Describes a course for first-year college students that focuses on the Silk Road. Discusses the problems that occurs in such a course, types of resources used, basic strategies and tactics taken, and the focus on mapmaking in the beginning of the course. Includes an annotated bibliography. (CMK)

LC-MS and 1H NMR as an improved dereplication tool to identify antifungal diterpenoids from Sagittaria latifolia

USDA-ARS?s Scientific Manuscript database

A dereplication strategy using a combination of liquid chromatography-mass spectrometry (LC-MS) and proton nuclear magnetic resonance spectroscopy (1H NMR) to facilitate compound identification towards antifungal natural product discovery is presented. This analytical approach takes advantage of th...

Whole Language Discovery Activities for the Primary Grades.

ERIC Educational Resources Information Center

Riley, Margaret C.; Coe, Donna L.

For the K-3 teacher, this book presents hundreds of ready-to-use individual and group activities for developing reading, writing, listening, and speaking skills, all correlated with other curriculum areas and organized into nine monthly sections. The book includes teaching strategies, individual and group games, activity sheets, quizzes, writing…

Designing and Using Software Tools for Educational Purposes: FLAT, a Case Study

ERIC Educational Resources Information Center

Castro-Schez, J. J.; del Castillo, E.; Hortolano, J.; Rodriguez, A.

2009-01-01

Educational software tools are considered to enrich teaching strategies, providing a more compelling means of exploration and feedback than traditional blackboard methods. Moreover, software simulators provide a more motivating link between theory and practice than pencil-paper methods, encouraging active and discovery learning in the students.…

Sequencing the Cacao Genome: Overall Strategy and SNP Discovery for Cacao Improvement.

USDA-ARS?s Scientific Manuscript database

On June 26, 2008, the United States Department of Agriculture-Agricultural Research Service (USDA-ARS), Mars, Incorporated, and IBM announced that they are combining their scientific resources to sequence and analyze the entire genome of Theobroma cacao L., an understory tree from the Amazon basin w...

Advising Community College Students: Exploring Traditional and Emerging Theory. In Brief

ERIC Educational Resources Information Center

Makela, Julia Panke

2006-01-01

Community college advising and counseling practitioners provide a productive setting for establishing a positive tone for self and academic discovery, while assisting students in finding their place within higher education. This brief compares current advising strategies for under-prepared students or students with low college readiness. One of…

Blueprint for Student Success: A Guide to Research-Based Teaching Practices K-12.

ERIC Educational Resources Information Center

Jones, Susan J.

This book presents a reality-based approach to classroom instruction designed to help learners at all levels achieve lifelong success. It offers teaching strategies, activities, and applications to enhance student achievement, stressing the importance of learning through discovery, creativity, application, adaptation, and high level thinking. It…

Welcome the Child: A Child Advocacy Guide for Churches. Revised and Expanded Edition.

ERIC Educational Resources Information Center

Daley, Shannon P.; Guy, Kathleen A.

This guide is intended to help church congregations develop and/or strengthen plans for children's ministries and child advocacy. Specifically the work aims to affirm children's growth, discoveries, and experiences and to provide strategies to congregations for helping children whose physical, emotional, social, economic, and educational…

Omics methods for probing the mode of action of natural phytotoxins

USDA-ARS?s Scientific Manuscript database

For a little over a decade, omics methods (transcriptomics, proteomics, metabolomics, and physionomics) have been used to discover and probe the mode of action of both synthetic and natural phytotoxins. For mode of action discovery, the strategy for each of these approaches is to generate an omics...

Building Connections: Strategies to Address Rurality and Accessibility Challenges

ERIC Educational Resources Information Center

Hartman, Sara; Hines-Bergmeier, Jennifer

2015-01-01

Operating a museum in a high poverty, underserved area creates many challenges related to accessibility, programming, and funding. Over the course of nearly a decade, the Ohio Valley Museum of Discovery (OVMoD) has identified several organizational practices that help mitigate these challenges. Located in the southeastern corner of Appalachian…

Science Lab: A Peer Approach.

ERIC Educational Resources Information Center

Ronca, Courtney C.

The two goals of this program were to increase the number of classroom teachers using the lab and to increase the amount of time that the science lab was used. The solution strategy chosen was a combination of peer tutoring, orientation presentations, small group discovery experiments and activities, and individual science experiment stations. The…

On Prolonging Network Lifetime through Load-Similar Node Deployment in Wireless Sensor Networks

PubMed Central

Li, Qiao-Qin; Gong, Haigang; Liu, Ming; Yang, Mei; Zheng, Jun

2011-01-01

This paper is focused on the study of the energy hole problem in the Progressive Multi-hop Rotational Clustered (PMRC)-structure, a highly scalable wireless sensor network (WSN) architecture. Based on an analysis on the traffic load distribution in PMRC-based WSNs, we propose a novel load-similar node distribution strategy combined with the Minimum Overlapping Layers (MOL) scheme to address the energy hole problem in PMRC-based WSNs. In this strategy, sensor nodes are deployed in the network area according to the load distribution. That is, more nodes shall be deployed in the range where the average load is higher, and then the loads among different areas in the sensor network tend to be balanced. Simulation results demonstrate that the load-similar node distribution strategy prolongs network lifetime and reduces the average packet latency in comparison with existing nonuniform node distribution and uniform node distribution strategies. Note that, besides the PMRC structure, the analysis model and the proposed load-similar node distribution strategy are also applicable to other multi-hop WSN structures. PMID:22163809

Discovering discovery patterns with Predication-based Semantic Indexing.

PubMed

Cohen, Trevor; Widdows, Dominic; Schvaneveldt, Roger W; Davies, Peter; Rindflesch, Thomas C

2012-12-01

In this paper we utilize methods of hyperdimensional computing to mediate the identification of therapeutically useful connections for the purpose of literature-based discovery. Our approach, named Predication-based Semantic Indexing, is utilized to identify empirically sequences of relationships known as "discovery patterns", such as "drug x INHIBITS substance y, substance y CAUSES disease z" that link pharmaceutical substances to diseases they are known to treat. These sequences are derived from semantic predications extracted from the biomedical literature by the SemRep system, and subsequently utilized to direct the search for known treatments for a held out set of diseases. Rapid and efficient inference is accomplished through the application of geometric operators in PSI space, allowing for both the derivation of discovery patterns from a large set of known TREATS relationships, and the application of these discovered patterns to constrain search for therapeutic relationships at scale. Our results include the rediscovery of discovery patterns that have been constructed manually by other authors in previous research, as well as the discovery of a set of previously unrecognized patterns. The application of these patterns to direct search through PSI space results in better recovery of therapeutic relationships than is accomplished with models based on distributional statistics alone. These results demonstrate the utility of efficient approximate inference in geometric space as a means to identify therapeutic relationships, suggesting a role of these methods in drug repurposing efforts. In addition, the results provide strong support for the utility of the discovery pattern approach pioneered by Hristovski and his colleagues. Copyright © 2012 Elsevier Inc. All rights reserved.

Discovering discovery patterns with predication-based Semantic Indexing

PubMed Central

Cohen, Trevor; Widdows, Dominic; Schvaneveldt, Roger W.; Davies, Peter; Rindflesch, Thomas C.

2012-01-01

In this paper we utilize methods of hyperdimensional computing to mediate the identification of therapeutically useful connections for the purpose of literature-based discovery. Our approach, named Predication-based Semantic Indexing, is utilized to identify empirically sequences of relationships known as “discovery patterns”, such as “drug x INHIBITS substance y, substance y CAUSES disease z” that link pharmaceutical substances to diseases they are known to treat. These sequences are derived from semantic predications extracted from the biomedical literature by the SemRep system, and subsequently utilized to direct the search for known treatments for a held out set of diseases. Rapid and efficient inference is accomplished through the application of geometric operators in PSI space, allowing for both the derivation of discovery patterns from a large set of known TREATS relationships, and the application of these discovered patterns to constrain search for therapeutic relationships at scale. Our results include the rediscovery of discovery patterns that have been constructed manually by other authors in previous research, as well as the discovery of a set of previously unrecognized patterns. The application of these patterns to direct search through PSI space results in better recovery of therapeutic relationships than is accomplished with models based on distributional statistics alone. These results demonstrate the utility of efficient approximate inference in geometric space as a means to identify therapeutic relationships, suggesting a role of these methods in drug repurposing efforts. In addition, the results provide strong support for the utility of the discovery pattern approach pioneered by Hristovski and his colleagues. PMID:22841748

A Distributed Cache Update Deployment Strategy in CDN

NASA Astrophysics Data System (ADS)

E, Xinhua; Zhu, Binjie

2018-04-01

The CDN management system distributes content objects to the edge of the internet to achieve the user's near access. Cache strategy is an important problem in network content distribution. A cache strategy was designed in which the content effective diffusion in the cache group, so more content was storage in the cache, and it improved the group hit rate.

Detection of extended galactic sources with an underwater neutrino telescope

DOE Office of Scientific and Technical Information (OSTI.GOV)

Leisos, A.; Tsirigotis, A. G.; Tzamarias, S. E.

2014-11-18

In this study we investigate the discovery capability of a Very Large Volume Neutrino Telescope to Galactic extended sources. We focus on the brightest HESS gamma rays sources which are considered also as very high energy neutrino emitters. We use the unbinned method taking into account both the spatial and the energy distribution of high energy neutrinos and we investigate parts of the Galactic plane where nearby potential neutrino emitters form neutrino source clusters. Neutrino source clusters as well as isolated neutrino sources are combined to estimate the observation period for 5 sigma discovery of neutrino signals from these objects.

KSC-07pd2026

NASA Image and Video Library

2007-07-19

KENNEDY SPACE CENTER, Fla. -- In the Orbiter Processing Facility bay 3, workers are ready to move a main bus switching unit into Discovery's payload bay. A main bus switching unit is used for power distribution, circuit protection and fault isolation on the space station's power system. The units route power to proper locations in the space station, such as from solar arrays through umbilicals into the U.S. Lab. The unit will be installed on the external stowage platform 2 attached to the Quest airlock for temporary storage. Discovery is targeted to launch mission STS-120 no earlier than Oct. 20. Photo credit: NASA/Jim Grossmann