71 research outputs found

    Protein Design Using Continuous Rotamers

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    Optimizing amino acid conformation and identity is a central problem in computational protein design. Protein design algorithms must allow realistic protein flexibility to occur during this optimization, or they may fail to find the best sequence with the lowest energy. Most design algorithms implement side-chain flexibility by allowing the side chains to move between a small set of discrete, low-energy states, which we call rigid rotamers. In this work we show that allowing continuous side-chain flexibility (which we call continuous rotamers) greatly improves protein flexibility modeling. We present a large-scale study that compares the sequences and best energy conformations in 69 protein-core redesigns using a rigid-rotamer model versus a continuous-rotamer model. We show that in nearly all of our redesigns the sequence found by the continuous-rotamer model is different and has a lower energy than the one found by the rigid-rotamer model. Moreover, the sequences found by the continuous-rotamer model are more similar to the native sequences. We then show that the seemingly easy solution of sampling more rigid rotamers within the continuous region is not a practical alternative to a continuous-rotamer model: at computationally feasible resolutions, using more rigid rotamers was never better than a continuous-rotamer model and almost always resulted in higher energies. Finally, we present a new protein design algorithm based on the dead-end elimination (DEE) algorithm, which we call iMinDEE, that makes the use of continuous rotamers feasible in larger systems. iMinDEE guarantees finding the optimal answer while pruning the search space with close to the same efficiency of DEE. Availability: Software is available under the Lesser GNU Public License v3. Contact the authors for source code

    The medicalization of current educational research and its effects on education policy and school reforms

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    Este artículo parte del supuesto de la aparición de una cultura pedagogizada durante los últimos 200 años, según la cual los problemas sociales percibidos se traducen en desafíos educativos. En consecuencia, tanto la investigación como las instituciones educativas crecieron, y una política educativa surgió como resultado de las negociaciones entre los profesionales, los investigadores y los responsables políticos. El documento mantiene que algunas experiencias específicas ocurridas durante la Segunda Guerra Mundial, provocaron un cambio fundamental en el papel social y cultural de los círculos académicos, que condujo a una cultura tecnocrática caracterizada por una mayor confianza mostrada hacia los expertos en lugar de a la práctica profesional (es decir, los maestros y administradores). Bajo este cambio tecnocrático, en primer lugar surgió un sistema tecnológico de razonamiento, que luego fue sustituido por un “paradigma” médico. El nuevo paradigma condujo a una medicalización de la investigación social, en el cual se da por sentado un particular entendimiento organicista de la realidad social, y su investigación se realiza bajo las más discutibles premisas. El resultado es que pese a la creciente importancia de la investigación en general, este cambio expertocrático y médico de la investigación social dio lugar a una reducción drástica de las oportunidades reformistas al privar a las partes interesadas de una amplia gama de investigación educativa, experiencia profesional, sentido común, y debate político.This paper starts from the assumption of the emergence of an educationalized culture over the last 200 years according to which perceived social problems are translated into educational challenges. As a result, both educational institutions and educational research grew, and educational policy resulted from negotiations between professionals, researchers, and policy makers. The paper argues that specific experiences in the Second World War triggered a fundamental shift in the social and cultural role of academia, leading up to a technocratic culture characterized by confidence in experts rather than in practicing professionals (i.e., teachers and administrators). In this technocratic shift, first a technological system of reasoning emerged, and it was then replaced by a medical “paradigm.” The new paradigm led to a medicalization of social research, in which a particular organistic understanding of the social reality is taken for granted and research is conducted under the mostly undiscussed premises of this particular understanding. The result is that despite the increased importance of research in general, this expertocratic and medical shift of social research led to a massive reduction in reform opportunities by depriving the reform stakeholders of abroad range of education research, professional experience, common sense, and political deliberation.Grupo FORCE (HUM-386). Departamento de Didáctica y Organización Escolar de la Universidad de Granad

    Extracellular phosphorylation of a receptor tyrosine kinase controls synaptic localization of NMDA receptors and regulates pathological pain

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    <div><p>Extracellular phosphorylation of proteins was suggested in the late 1800s when it was demonstrated that casein contains phosphate. More recently, extracellular kinases that phosphorylate extracellular serine, threonine, and tyrosine residues of numerous proteins have been identified. However, the functional significance of extracellular phosphorylation of specific residues in the nervous system is poorly understood. Here we show that synaptic accumulation of GluN2B-containing N-methyl-D-aspartate receptors (NMDARs) and pathological pain are controlled by ephrin-B-induced extracellular phosphorylation of a single tyrosine (p*Y504) in a highly conserved region of the fibronectin type III (FN3) domain of the receptor tyrosine kinase EphB2. Ligand-dependent Y504 phosphorylation modulates the EphB-NMDAR interaction in cortical and spinal cord neurons. Furthermore, Y504 phosphorylation enhances NMDAR localization and injury-induced pain behavior. By mediating inducible extracellular interactions that are capable of modulating animal behavior, extracellular tyrosine phosphorylation of EphBs may represent a previously unknown class of mechanism mediating protein interaction and function.</p></div

    Synaptic currents and accumulation of N-methyl-D-aspartate receptors (NMDARs) at synaptic sites are controlled by phosphorylation of EphB2 Y504.

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    <p>(A) Experimental approach for the figure is illustrated. (B) Mean traces of whole-cell patch-clamp recording at 50 mV show the evoked and miniature excitatory postsynaptic currents (EPSCs) of primary rat cortical day in vitro (DIV) 21–23 neurons expressing enhanced green fluorescent protein (EGFP) without or with EphB2 wild type (WT) and Y504 mutants induced by light stimulation of neurons that express optogenetic light-sensitive channels (channelrhodopsin-2). (C) Effects of overexpression of EphB2 WT and Y504 mutants on the mean amplitude of evoked, spontaneous, and miniature EPSCs (30 milliseconds after the evoked EPSC peak) in mature cultured neurons. Overexpression of EphB2 WT or Y504E significantly increased amplitude of the NMDAR-dependent component of evoked EPSCs compared to the control or the Y504F mutant (****<i>p <</i> 0001, ANOVA followed by Fisher’s exact test, <i>n</i> = 375, 332, 581, and 200 events for control, EphB2 WT, Y504E, and Y504F, respectively). In addition, the amplitude of Y504E-overexpressing neurons was significantly higher than that of WT-overexpressing neurons (**<i>p <</i> 0.02, ANOVA followed by Fisher’s exact test). (D) Representative sample traces of whole-cell patch-clamp recording at 50 mV show that NMDAR-dependent currents in control neurons and neurons expressing EphB2 WT and Y504E, but not Y504F, are greatly reduced by GluN2B-specific antagonist Ro 25–6981 (Ro25). (E) Cumulative probability histogram of miniature EPSC (mESPC) amplitude for Y504E before and after application of Ro25 (2.5 μM). Inset: mean traces of mEPSCs after treatment with Ro25 (<i>p <</i> 0.001, Kolmogorov—Smirnov [K–S] test, <i>n</i> = 720 for Y504E and <i>n</i> = 427 for Y504E + Ro25). Vertical scale bar = 20 picoamperes (pA); horizontal scale bar = 10 milliseconds. (F) Cumulative probability histogram of mEPSC amplitude Y504F as in (E) (<i>p</i> = 0.0775, K–S test, <i>n</i> = 414 for Y504F and <i>n</i> = 404 for Y504F + Ro25). Vertical scale bar = 10 pA; horizontal scale bar = 10 milliseconds. (G) Model depicting 2 scenarios of VGLUT1 (blue), EphB2 (red), and GluN1 (green) localization at dendritic spines. (H) High-contrast images of dendrites of DIV 21 cortical neurons expressing EGFP, EphB2 short hairpin RNA (shRNA), and RNA interference (RNAi)-insensitive FLAG-tagged EphB2 WT, EphB2-Y504E, or EphB2-Y504F. Top panels show confocal EGFP staining (white), second panels show stimulated emission depletion (STED) EphB2 staining (red), third panels show STED GluN1 staining (green), fourth panels show confocal VGLUT1 (presynaptic marker) staining (blue), and bottom panels show merged images. White arrows indicate examples of triple colocalization of EphB2, GluN1, and VGLUT1. Scale bar = 1 μm, 0.5 μm inset. (I) Quantification of the effects of expression of EphB2 Y504 mutants on localization of VGLUT1 to dendritic spines in DIV 21 rat cortical neurons transfected at DIV 14. Graph shows fraction of spines containing VGLUT1 (not significant, ANOVA followed by Fisher’s exact test). (J) Quantification of the effects of expression of EphB2 Y504 mutants on colocalization with GluN1 in dendritic spines in DIV 21 rat cortical neurons transfected at DIV 14. Graph shows percentage of spines containing colocalized EphB2 and GluN1 puncta as defined by Fig 5G (*<i>p <</i> 0.05, ***<i>p <</i> 0.005, ANOVA followed by Fisher’s exact test). (K) Quantification of the effects of expression of EphB2 Y504 mutants on colocalization with GluN1 at synaptic sites in DIV 21 rat cortical neurons transfected at DIV 14. Graph shows percentage of spines containing triple colocalized puncta as defined by Fig 5G (***<i>p <</i> 0.005, ****<i>p <</i> 0.0005, ANOVA followed by Fisher’s exact test).</p
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