736 research outputs found
Students And Eli Weisel at the 1993 Commencement Ceremony
No full textNobel-prize winning author, Eli Weisel, at the 1993 Commencement Ceremony, with students
Eli Weisel and University President Francis J. Mertz at 1993 Commencement
No full textNobel-prize winning author, Eli Weisel, at the 1993 Commencement Ceremony, shaking hands with University President Francis J. Mertz
PocketGraph : graph representation of binding site volumes
No full textThe representation of small molecules as molecular graphs is a common technique in various fields of cheminformatics. This approach employs abstract descriptions of topology and properties for rapid analyses and comparison. Receptor-based methods in contrast mostly depend on more complex representations impeding simplified analysis and limiting the possibilities of property assignment. In this study we demonstrate that ligand-based methods can be applied to receptor-derived binding site analysis. We introduce the new method PocketGraph that translates representations of binding site volumes into linear graphs and enables the application of graph-based methods to the world of protein pockets. The method uses the PocketPicker algorithm for characterization of binding site volumes and employs a Growing Neural Gas procedure to derive graph representations of pocket topologies. Self-organizing map (SOM) projections revealed a limited number of pocket topologies. We argue that there is only a small set of pocket shapes realized in the known ligand-receptor complexes
Satellite-based delivery of educational content to geographically isolated communities: A service based approach
No full textEnabling learning for members of geographically
isolated communities presents benefits in terms of
promoting regional development and cost savings for governments and companies. However, notwithstanding recent advances in e-Learning, from both technological and pedagogical perspectives, there are very few, if any,
recognised methodologies for user-led design of satellite-based e-learning infrastructures. In this paper, we present a methodology for designing a satellite and wireless based network infrastructure and learning services to support distance learning for such isolated communities. This methodology entails (a) the involvement of community members in the development of targeted learning services from an early stage, and (b) a service-oriented approach to learning solution deployment. Results show, that, while the technological premises of distance learning can be
accommodated by hybrid satellite/wireless infrastructures,this has to be complemented with (a) high-quality audio–visual educational material, and (b) the opportunity for community members to interact with other community
members either as groups (common-room oriented scenarios) or individuals (home-based scenarios), thus providing an impetus for learner engagement in both formal and informal activities
Elevated telomerase activity, minimal telomere loss in cord blood long-term cultures with extensive stem cell replication
No full textFuzzy virtual ligands for virtual screening
No full textA new method to bridge the gap between ligand and receptor-based methods in virtual screening (VS) is presented. We introduce a structure-derived virtual ligand (VL) model as an extension to a previously published pseudo-ligand technique [1]: LIQUID [2] fuzzy pharmacophore virtual screening is combined with grid-based protein binding site predictions of PocketPicker [3]. This approach might help reduce bias introduced by manual selection of binding site residues and introduces pocket shape information to the VL. It allows for a combination of several protein structure models into a single "fuzzy" VL representation, which can be used to scan screening compound collections for ligand structures with a similar potential pharmacophore. PocketPicker employs an elaborate grid-based scanning procedure to determine buried cavities and depressions on the protein's surface. Potential binding sites are represented by clusters of grid probes characterizing the shape and accessibility of a cavity. A rule-based system is then applied to project reverse pharmacophore types onto the grid probes of a selected pocket. The pocket pharmacophore types are assigned depending on the properties and geometry of the protein residues surrounding the pocket with regard to their relative position towards the grid probes. LIQUID is used to cluster representative pocket probes by their pharmacophore types describing a fuzzy VL model. The VL is encoded in a correlation vector, which can then be compared to a database of pre-calculated ligand models. A retrospective screening using the fuzzy VL and several protein structures was evaluated by ten fold cross-validation with ROC-AUC and BEDROC metrics, obtaining a significant enrichment of actives. Future work will be devoted to prospective screening using a novel protein target of Helicobacter pylori and compounds from commercial providers
Analysis of shape, properties and "druggability" of protein binding pockets
No full textKenntnisse über die dreidimensionale Struktur therapeutisch relevanter Zielproteine bieten wertvolle Informationen für den rationalen Wirkstoffentwurf. Die stetig wachsende Zahl aufgeklärter Kristallstrukturen von Proteinen ermöglicht eine qualitative und quantitative rechnergestützte Untersuchung von spezifischen Protein-Liganden Wechselwirkungen. Im Rahmen dieser Arbeit wurden neue Algorithmen für die Identifikation und den Ähnlichkeitsvergleich von Proteinbindetaschen und ihren Eigenschaften entwickelt und in dem Programm PocketomePicker zusammengefasst. Die Software gliedert sich in die Routinen PocketPicker, PocketShapelets und PocketGraph. Ferner wurde in dieser Arbeit die Methode ReverseLIQUID reimplementiert und im Rahmen einer Kooperation für das strukturbasierte Virtuelle Screening angewendet. Die genannten Methoden und ihre wissenschaftliche Anwendungen sollte hier zusammengefasst werden: Die Methode PocketPicker ermöglicht die Vorhersage potentieller Bindetaschen auf Proteinoberflächen. Diese Technik implementiert einen geometrischen Ansatz auf Basis „künstlicher Gitter“ zur Identifikation zusammenhängender vergrabener Bereiche der Proteinoberfläche als Orte möglicher Ligandenbindestellen. Die Methode erreicht eine korrekte Vorhersage der tatsächlichen Bindetasche für 73 % der Einträge eines repräsentativen Datensatzes von Proteinstrukturen. Für 90 % der Proteinstrukturen wird die tatsächlich Ligandenbindestelle unter den drei wahrscheinlichsten vorhergesagten Taschen gefunden. PocketPicker übertrifft die Vorhersagequalität anderer etablierter Algorithmen und ermöglicht Taschenidentifikationen auf apo-Strukturen ohne signifikante Einbußen des Vorhersageerfolges. Andere Verfahren weisen deutlich eingeschränkte Ergebnisse bei der Anwendung auf apo-Strukturen auf. PocketPicker erlaubt den alignmentfreien Ähnlichkeitsvergleich von Bindetaschenfor-men durch die Kodierung berechneter Bindevolumen als Korrelationsdeskriptoren. Dieser Ansatz wurde erfolgreich für Funktionsvorhersage von Bindetaschen aus Homologiemodellen von APOBEC3C und Glutamat Dehydrogenase des Malariaerregers Plasmodium falciparum angewendet. Diese beiden Projekte wurden in Zusammenarbeit mit Kollaborationspartnern durchgeführt. Zudem wurden PocketPicker Korrelationsdeskriptoren erfolgreich für die automatisierte Konformationsanalyse der enzymatischen Tasche von Aldose Reduktase angewendet. Für detaillierte Analysen der Form und der physikochemischen Eigenschaften von Proteinbindetaschen wurde in dieser Arbeit die Methode PocketShapelets entwickelt. Diese Technik ermöglicht strukturelle Alignments von extrahierten Bindevolumen durch Zerlegungen der Oberfläche von Proteinbindetaschen. Die Überlagerung gelingt durch die Identifikation strukturell ähnlicher Oberflächenkurvaturen zweier Taschen. PocketShapelets wurde erfolgreich zur Analyse funktioneller Ähnlichkeit von Bindetaschen verwendet, die auf Betrachtungen physikochemischer Eigenschaften basiert. Zur Analyse der topologischen Vielfalt von Bindetaschengeometrien wurde in dieser Arbeit die Methode PocketGraph entwickelt. Dieser Ansatz nutzt das Konzept des sog. „Wachsenden Neuronalen Gases“ aus dem Bereich des maschinellen Lernens für eine automatische Extraktion des strukturellen Aufbaus von Bindetaschen. Ferner ermöglicht diese Methode die Zerlegung einer Bindestelle in ihre Subtaschen. Die von PocketPicker charakterisierten Taschenvolumen bilden die Grundlage für die Methode ReverseLIQUID. Dieses Programm wurde in dieser Arbeit weiterentwickelt und im Rahmen einer Kooperation zur Identifikation eines Inhibitors der Serinprotease HtrA des Erregers Helicobacter pylori verwendet. Mit ReverseLIQUID konnte ein strukturbasiertes Pharmakophormodell für das Virtuelle Screening erstellt werden. Dieser Ansatz ermöglichte die Identifikation einer Substanz mit niedrig mikromolarer Affinität gegenüber der Zielstruktur.Knowledge of the three-dimensional structure therapeutically relevant target proteins provides valuable information for rational drug design. The constantly increasing numbers of available crystal structures enable qualitative and quantitative analysis of specific protein-ligand interactions in silico. In this work novel algorithms for the identification and the comparison of protein binding sites and their properties were developed and combined in the program PocketomePicker. The software combines the routines PocketPicker, PocketShapelets and PocketGraph. Furthermore, the method ReverseLIQUID was re-implemented in this work and used for the structure-based virtual screening with a cooperation partner. The programs and their scientific applications are summarized here: The method PocketPicker is designed for the prediction of potential binding sites on protein surfaces. The technique implements a geometric approach based on the concept of “artificial grids” for the identification of continuous buried regions of the protein surface that might act as potential ligand binding sites. The method yields correct predications of the actual binding site for 73 % of the entries in a representative data set of protein structures. For 90 % of the proteins the actual binding site is found among the top three predicted binding pockets. PocketPicker exceeds the predictive quality of other established algorithms and enables correct binding site identifications on apo structures without significant drops of the prediction success. This is not achieved by other programs. PocketPicker enables alignment-free comparisons of binding site shapes by encoding extracted binding volumes as correlation vectors. This approach was used for successful predictions of binding site functionality for homology models of APOBEC3C and glutamate dehydrogenase of the malaria pathogen Plasmodium falciparum. These projects were carried out with collaboration partners. Furthermore, PocketPicker correlation descriptors were used for automated analysis of binding site conformations of aldose reductase active sites. The method PocketShapelets was implemented in this work for detailed analysis of shapes and physicochemical properties of protein binding sites. This approach enables structural alignments of extracted binding volumes by surface decomposition of protein binding sites. The structural superposition is achieved by identification of structurally similar surface curvatures of different binding pockets. PocketShapelets was successfully used for the analysis of functional similarity of binding sites based on observations of physicochemical properties. PocketGraph was developed for the analysis of the structural diversity of binding site geometries. This approach uses the “Growing Neural Gas” concept used in machine learning for an automated extraction of the structural organization of binding sites. Furthermore, the method enables the decomposition of binding sites into subpockets. The pocket volumes characterized by PocketPicker are the foundation of another program called ReverseLIQUID. This method was refined in this work and used for the identification of a Helicobacter pylori serine protease HtrA inhibitor. This project was performed with a collaboration partner. A receptor-based pharmacophore model was derived using ReverseLIQUID and used for virtual screening. This approach led to the identification of a substance with low micromolar affinity towards the target protein
Impact of Elotuzumab Plus Pomalidomide/Dexamethasone on Health-related Quality of Life for Patients with Relapsed/Refractory Multiple Myeloma: Final Data from the Phase 2 ELOQUENT-3 Trial
No full textTriplet regimens containing immunomodulatory drugs and proteasome inhibitors (PIs) have improved outcomes and extended survival for patients with relapsed/refractory multiple myeloma (RRMM). We evaluated updated health-related quality of life (HRQoL) findings from the phase 2 ELOQUENT-3 clinical trial (NCT02654132) after 4 years of treatment with elotuzumab plus pomalidomide and dexamethasone (EPd) and assessed the impact of the addition of elotuzumab on patients' HRQoL. HRQoL was assessed as an exploratory endpoint using the MD Anderson Symptom Inventory for Multiple Myeloma (MDASI-MM), which evaluates symptom severity, symptom interference, and HRQoL, and the 3-level EQ-5D, a patient-reported measure of health utility and general health. Statistical analyses included descriptive responder, longitudinal mixed-model, and time-to-first-deterioration (TTD) analyses using prespecified minimally important differences and responder definitions. Of 117 randomized patients, 106 (EPd, n = 55; pomalidomide and dexamethasone [Pd], n = 51) were eligible for inclusion in HRQoL analyses. Completion rates at almost all on-treatment visits were ≥80%. The proportion of patients treated with EPd who improved or maintained stable HRQoL until cycle 13 ranged from 82% to 96% for MDASI-MM total symptom score and 64% to 85% for MDASI-MM symptom interference. Across measurements, there were no clinically meaningful differences in changes from baseline between treatment arms, and TTD was not significantly different for EPd versus Pd. In conclusion, HRQoL was not impacted by the addition of elotuzumab to Pd and did not significantly deteriorate in patients with RRMM previously treated with lenalidomide and a PI in ELOQUENT-3
Once- versus twice-weekly carfilzomib in relapsed and refractory multiple myeloma by select patient characteristics: phase 3 A.R.R.O.W. study subgroup analysis
No full textThe phase 3 A.R.R.O.W. study demonstrated that treatment with once-weekly carfilzomib (70 mg/m2) and dexamethasone (once-weekly Kd70 mg/m2) improved progression-free survival compared with twice-weekly carfilzomib (27 mg/m2) and dexamethasone (twice-weekly Kd27 mg/m2) in patients with relapsed and refractory multiple myeloma (RRMM; median, 11.2 versus 7.6 months; hazard ratio [HR] = 0.69; 95% confidence interval, 0.54–0.88; P = 0.0029). Once-weekly dosing also improved response rates and depth of response. We performed a subgroup analysis from A.R.R.O.W. according to age (<65, 65–74, or ≥75 years), renal function (creatinine clearance <50, ≥50–<80, or ≥80 mL/min), number of prior therapies (2 or 3), and bortezomib-refractory status (yes or no). Compared with twice-weekly Kd27 mg/m2, once-weekly Kd70 mg/m2 reduced the risk of progression or death (HR = 0.60–0.85) and increased overall response rates in nearly all the examined subgroups, consistent with reports in the overall A.R.R.O.W. population. The safety profiles of once-weekly Kd70 mg/m2 across subgroups were also generally consistent with those in the overall population. Findings from this subgroup analysis generally demonstrate a favorable benefit–risk profile of once-weekly Kd70 mg/m2, further supporting once-weekly carfilzomib dosing as an appropriate treatment option for patients with RRMM, regardless of baseline patient and disease characteristics
Childhood asthma and environmental exposures at swimming pools: state of the science and research recommendations.
No full textOBJECTIVES: Recent studies have explored the potential for swimming pool disinfection by-products (DBPs), which are respiratory irritants, to cause asthma in young children. Here we describe the state of the science on methods for understanding children's exposure to DBPs and biologics at swimming pools and associations with new-onset childhood asthma and recommend a research agenda to improve our understanding of this issue. DATA SOURCES: A workshop was held in Leuven, Belgium, 21-23 August 2007, to evaluate the literature and to develop a research agenda to better understand children's exposures in the swimming pool environment and their potential associations with new-onset asthma. Participants, including clinicians, epidemiologists, exposure scientists, pool operations experts, and chemists, reviewed the literature, prepared background summaries, and held extensive discussions on the relevant published studies, knowledge of asthma characterization and exposures at swimming pools, and epidemiologic study designs. SYNTHESIS: Childhood swimming and new-onset childhood asthma have clear implications for public health. If attendance at indoor pools increases risk of childhood asthma, then concerns are warranted and action is necessary. If there is no such relationship, these concerns could unnecessarily deter children from indoor swimming and/or compromise water disinfection. CONCLUSIONS: Current evidence of an association between childhood swimming and new-onset asthma is suggestive but not conclusive. Important data gaps need to be filled, particularly in exposure assessment and characterization of asthma in the very young. Participants recommended that additional evaluations using a multidisciplinary approach are needed to determine whether a clear association exists
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