1,721,890 research outputs found
LEAN construcción en el diseño y ejecución de obras civiles
No full textNogueira Serrano, Luis; director de proyecto: Soto Pérez, Anselmo César2023-2024Máster Universitario en Ingeniería de Caminos, Canales y PuertosEscuela Politécnica Superio
Affinity Can have Many Faces: Thermodynamic and Kinetic Properties of Ras-Effector Complex Formation
No full textThe ubiquitin domain superfold: structure-based sequence alignments and characterization of binding epitopes
No full textUbiquitin-like domains are present, apart from ubiquitin-like proteins themselves, in many multidomain proteins involved in different signal transduction processes. The sequence conservation for all ubiquitin superfold family members is rather poor, even between subfamily members, leading to mistakes in sequence alignments using conventional sequence alignment methods. However, a correct alignment is essential, especially for in silico methods that predict binding partners on the basis of sequence and structure. In this study, using 3D-structural information we have generated and manually corrected sequence alignments for proteins of the five ubiquitin superfold subfamilies. On the basis of this alignment, we suggest domains for which structural information will be useful to allow homology modelling. In addition, we have analysed the energetic and electrostatic properties of ubiquitin-like domains in complex with various functional binding proteins using the protein design algorithm FoldX. On the basis of an in silico alanine-scanning mutagenesis, we provide a detailed binding epitope mapping of the hotspots of the ubiquitin domain fold, involved in the interaction with different domains and proteins. Finally, we provide a consensus fingerprint sequence that identifies all sequences described to belong to the ubiquitin superfold family. It is possible that the method that we describe may be applied to other domain families sharing a similar fold but having low levels of sequence homology. (c) 2005 Elsevier Ltd. All rights reserved
Cell type-specific importance of ras-c-raf complex association rate constants for MAPK signaling
No full textWe generated 17 c-Raf (RAF proto-oncogene serine-threonine protein kinase) mutants with altered Ras-Raf association and dissociation rates to investigate the role of electrostatically driven Ras-Raf association rates on epidermal growth factor (EGF)-activated mitogen-activated protein kinase (MAPK) signal transduction. Some of these mutants had compensating changes in association and dissociation rates, enabling the effects of changes in association rate to be distinguished from those of changes in affinity. In rabbit kidney (RK13) cells, these mutants affected downstream signaling, with changes in Ras-c-Raf association rates having a greater effect on MAPK signaling than did similar changes in dissociation rates. Mutants with compensating decreases in both association and dissociation rates stimulated less extracellular signal regulated kinase (ERK)-dependent reporter activity than did wild-type c-Raf, whereas the converse was true for mutants with increased association and dissociation rates. In marked contrast, the mutants had little or no effect on signaling in human embryonic kidney (HEK) 293 cells. These two cell lines also showed distinct patterns of EGF-dependent ERKphosphorylation and signaling: ERK activation and signaling were transient in HEK293 cells and sustained in RK13 cells, with the difference resulting from the lack of negative feedback from ERK to Sos (Son of Sevenless) in the latter. Computer simulation revealed that, in the presence of negative feedback, changes in the rate of Ras-c-Raf binding have little effect on ERK activation. Thus, EGF-MAPK activation kinetics and feedback regulation is cell type specific and depends on the network topology
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Analyzing protein interaction networks using structural information
No full textDetermining protein interaction networks and predicting network changes in time and space are crucial to understanding and modeling a biological system. In the past few years, the combination of experimental and computational tools has allowed great progress toward reaching this goal. Experimental methods include the large-scale determination of protein interactions using two-hybrid or pull-down analysis as well as proteomics. The latter one is especially valuable when changes in protein concentrations over time are recorded. Computational tools include methods to predict and validate protein interactions on the basis of structural information and bioinformatics tools that analyze and integrate data for the same purpose. In this review, we focus on the use of structural information in combination with computational tools to predict new protein interactions, to determine which interactions are compatible with each other, to obtain some functional insight into single and multiple mutations, and to estimate equilibrium and kinetic parameters. Finally, we discuss the importance of establishing criteria to biologically validate protein interactions
Engineering Signal Transduction Pathways
No full textCells respond to their environment by sensing signals and translating them into changes in gene expression. In recent years, synthetic networks have been designed in both prokaryotic and eukaryotic systems to create new functionalities and for specific applications. In this review, we discuss the challenges associated with engineering signal transduction pathways. Furthermore, we address advantages and disadvantages of engineering signaling pathways in prokaryotic and eukaryotic cells, highlighting recent examples, and discuss how progress in synthetic biology might impact biotechnology and biomedicine
opathy and cancer missense mutations
No full textThe Ras/MAPK syndromes ('RASopathies') are a class of developmental disorders caused by germline mutations in 15 genes encoding proteins of the Ras/mitogen-activated protein kinase (MAPK) pathway frequently involved in cancer. Little is known about the molecular mechanisms underlying the differences in mutations of the same protein causing either cancer or RASopathies. Here, we shed light on 956 RASopathy and cancer missense mutations by combining protein network data with mutational analyses based on 3D structures. Using the protein design algorithm FoldX, we predict that most of the missense mutations with destabilising energies are in structural regions that control the activation of proteins, and only a few are predicted to compromise protein folding. We find a trend that energy changes are higher for cancer compared to RASopathy mutations. Through network modelling, we show that partly compensatory mutations in RASopathies result in only minor downstream pathway deregulation. In summary, we suggest that quantitative rather than qualitative network differences determine the phenotypic outcome of RASopathy compared to cancer mutations
Structures in systems biology
No full textOil and water do not normally mix, and apparently structural biology and systems biology look like two different universes. It can be argued that structural biology could play a very important role in systems biology. Although at the final stage of understanding a signal transduction pathway, a cell, an organ or a living system, structures could be obviated, we need them to be able to reach that stage. Structures of macromolecules, especially molecular machines, could provide quantitative parameters, help to elucidate functional networks or enable rational designed perturbation experiments for reverse engineering. The role of structural biology in systems biology should be to provide enough understanding so that macromolecules can be translated into dots or even into equations devoid of atoms
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