Crystal Structure of Two Anti-Porphyrin Antibodies with Peroxidase Activity

We report the crystal structures at 2.05 and 2.45 Å resolution of two antibodies, 13G10 and 14H7, directed against an iron(III)-αααβ-carboxyphenylporphyrin, which display some peroxidase activity. Although these two antibodies differ by only one amino acid in their variable λ-light chain and display 86% sequence identity in their variable heavy chain, their complementary determining regions (CDR) CDRH1 and CDRH3 adopt very different conformations. The presence of Met or Leu residues at positions preceding residue H101 in CDRH3 in 13G10 and 14H7, respectively, yields to shallow combining sites pockets with different shapes that are mainly hydrophobic. The hapten and other carboxyphenyl-derivatized iron(III)-porphyrins have been modeled in the active sites of both antibodies using protein ligand docking with the program GOLD. The hapten is maintained in the antibody pockets of 13G10 and 14H7 by a strong network of hydrogen bonds with two or three carboxylates of the carboxyphenyl substituents of the porphyrin, respectively, as well as numerous stacking and van der Waals interactions with the very hydrophobic CDRH3. However, no amino acid residue was found to chelate the iron. Modeling also allows us to rationalize the recognition of alternative porphyrinic cofactors by the 13G10 and 14H7 antibodies and the effect of imidazole binding on the peroxidase activity of the 13G10/porphyrin complexes

Clonal chromosomal mosaicism and loss of chromosome Y in elderly men increase vulnerability for SARS-CoV-2

The pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2, COVID-19) had an estimated overall case fatality ratio of 1.38% (pre-vaccination), being 53% higher in males and increasing exponentially with age. Among 9578 individuals diagnosed with COVID-19 in the SCOURGE study, we found 133 cases (1.42%) with detectable clonal mosaicism for chromosome alterations (mCA) and 226 males (5.08%) with acquired loss of chromosome Y (LOY). Individuals with clonal mosaic events (mCA and/or LOY) showed a 54% increase in the risk of COVID-19 lethality. LOY is associated with transcriptomic biomarkers of immune dysfunction, pro-coagulation activity and cardiovascular risk. Interferon-induced genes involved in the initial immune response to SARS-CoV-2 are also down-regulated in LOY. Thus, mCA and LOY underlie at least part of the sex-biased severity and mortality of COVID-19 in aging patients. Given its potential therapeutic and prognostic relevance, evaluation of clonal mosaicism should be implemented as biomarker of COVID-19 severity in elderly people. Among 9578 individuals diagnosed with COVID-19 in the SCOURGE study, individuals with clonal mosaic events (clonal mosaicism for chromosome alterations and/or loss of chromosome Y) showed an increased risk of COVID-19 lethality

Impact of COVID-19 on cardiovascular testing in the United States versus the rest of the world

Objectives: This study sought to quantify and compare the decline in volumes of cardiovascular procedures between the United States and non-US institutions during the early phase of the coronavirus disease-2019 (COVID-19) pandemic. Background: The COVID-19 pandemic has disrupted the care of many non-COVID-19 illnesses. Reductions in diagnostic cardiovascular testing around the world have led to concerns over the implications of reduced testing for cardiovascular disease (CVD) morbidity and mortality. Methods: Data were submitted to the INCAPS-COVID (International Atomic Energy Agency Non-Invasive Cardiology Protocols Study of COVID-19), a multinational registry comprising 909 institutions in 108 countries (including 155 facilities in 40 U.S. states), assessing the impact of the COVID-19 pandemic on volumes of diagnostic cardiovascular procedures. Data were obtained for April 2020 and compared with volumes of baseline procedures from March 2019. We compared laboratory characteristics, practices, and procedure volumes between U.S. and non-U.S. facilities and between U.S. geographic regions and identified factors associated with volume reduction in the United States. Results: Reductions in the volumes of procedures in the United States were similar to those in non-U.S. facilities (68% vs. 63%, respectively; p = 0.237), although U.S. facilities reported greater reductions in invasive coronary angiography (69% vs. 53%, respectively; p < 0.001). Significantly more U.S. facilities reported increased use of telehealth and patient screening measures than non-U.S. facilities, such as temperature checks, symptom screenings, and COVID-19 testing. Reductions in volumes of procedures differed between U.S. regions, with larger declines observed in the Northeast (76%) and Midwest (74%) than in the South (62%) and West (44%). Prevalence of COVID-19, staff redeployments, outpatient centers, and urban centers were associated with greater reductions in volume in U.S. facilities in a multivariable analysis. Conclusions: We observed marked reductions in U.S. cardiovascular testing in the early phase of the pandemic and significant variability between U.S. regions. The association between reductions of volumes and COVID-19 prevalence in the United States highlighted the need for proactive efforts to maintain access to cardiovascular testing in areas most affected by outbreaks of COVID-19 infection

Development and applications of molecular modelling techniques for the design and optimization of artificial metalloenzymes

La búsqueda de procesos de síntesis de moléculas orgánicas altamente eficientes y selectivos es uno de los retos de la química. En los últimos años, las enzimas se han presentado como una seria alternativa a los catalizadores homogéneos tradicionales debido a su alta eficiencia y selectividad natural. Desafortunadamente, las reacciones que pueden catalizar estas especies se suelen restringir a aquellas que tienen importancia para el huésped que las alberga, limitando su aplicación en el ámbito químico/industrial. Para poder solventar estas limitaciones se han desarrollado las llamadas metaloenzimas artificiales. Estos híbridos se obtienen a partir de la inserción de un catalizador homogéneo en una proteína. De este modo el receptor protege el cofactor inorgánico y aporta un entorno quiral (enantioselectivo) mientras que el metal es responsable de la reactividad del sistema. Pero el diseño de estos híbridos representa todo un reto: la proteína no ha sido diseñada evolutivamente para reconocer el fragmento inorgánico y el complejo resultante puede no reconocer de forma eficiente el sustrato. Todo esto provoca que la enzima diseñada presente deficiencias en cuanto a la eficiencia catalítica y/o selectividad. Las técnicas de modelización molecular pueden resultar de gran ayuda en el proceso de diseño y de optimización de las metaloenzimas artificiales. Sin embargo, su aplicación en este tipo de sistemas no es trivial. Necesitamos técnicas que permiten una amplia y rápida búsqueda tanto del espacio conformacional como del químico (mecánica molecular) así cómo técnicas que permitan una descripción precisa del metal y sus propiedad electrónicas (mecánica cuántica). Lamentablemente, estas últimas son demasiado costosas a nivel computacional cómo para poder tratar sistemas de estas dimensiones. En esta tesis nos hemos basado en la combinación de diferentes técnicas de modelización molecular, basadas tanto en aproximaciones mecanoclásicas como mecanocuánticas, para poder solventar estas limitaciones. Este enfoque ha sido aplicado al diseño y optimización de metaloenzimas artificiales. En primer lugar hemos estudiado la unión entre el cofactor inorgánico y la proteína, obteniendo una gran correlación entre los modelos teóricos y los resultados experimentales. A continuación las hemos aplicado al estudio de la reactividad del sistema, tanto a la unión del sustrato al complejo proteína-cofactor como a la caracterización de los estados de transición más probables. En este último caso hemos podido comprobar que estos protocolos integrativos son capaces de ofrecer un nivel muy aceptable de predictibilidad de la enantioselectividad del sistema. Aunque en esta tesis hemos demostrado la gran utilidad que pueden tener los protocolos que integran diversas técnicas de modelización molecular en el estudio de complejos biometálicos, su desarrollo no es trivial. La mayoría de programas de modelización molecular no han sido diseñados para ser utilizados en tándem y todos ellos tienen su propia forma de tratar la información molecular. Para solventar estas incompatibilidades se necesitaría una plataforma integrativa que englobara todas estas técnicas y regulara el flujo de información entre ellas. A nivel comercial estas plataformas ya existen, pero su uso es altamente restrictivo ya que son muy caras y son de código cerrado, dejando muy poco margen para su adaptabilidad a cada problema molecular. Por este motivo en esta tesis nos hemos centrado en el desarrollo de una plataforma integrativa de código abierto accesible a toda la comunidad de modelizadores. Hasta el momento, esta plataforma incluye interfaces para realizar cálculos de modos normales y dinámicas moleculares, así como permitir el análisis de cálculos cuánticos con Gaussian y cálculos de docking proteína-ligando con GOLD. Se espera incorporar muchas mas técnicas en un futuro próximo.The search of highly efficient and selective processes for the synthesis of organic molecules is one of the challenges of chemistry. In the last years, enzymes have positioned as a clear alternative to traditional homogeneous catalysts due to their high natural efficiency and selectivity. Unfortunately, their range of different reactions is restricted to those that are useful for their host. To solve this limitation the so-called artificial metalloenzymes have been developed. These hybrids are based on the insertion of an homogeneous catalyst into a protein scaffold. This way, the receptor protects the inorganic cofactor and provides with a chiral (enantioselective) environment while the metal is responsible for the reactivity of the system. However, their design is highly challenging: the protein has not been optimized to bind such inorganic compounds and the resulting complex may not efficiently recognize the substrate. Altogether, these could mean that the artificial enzyme has several deficiencies in terms of catalytic efficiency and/or enantioselectivity. Molecular modelling techniques could aid in the design and optimization of artificial metalloenzymes. However, their application is not straightforward due to the complexity of these hybrids. We need both techniques allowing wide and fast conformational and chemical space searches (molecular mechanics) and techniques offering an accurate description of the metal and its electronic states (quantum mechanics). Unfortunately, the later ones are too computational intensive to treat systems of a huge size such as enzymes. In this Ph. D. thesis we combined several molecular modeling techniques, based either in classical or quantum mechanics approximations, to solve those limitations. This approach has been applied on the design and optimization of artificial metalloenzymes. First, we have studied the binding of the inorfanic cofactor in the protein scaffold, obtaining very good agreement between the theoretical models and the experimental results. Afterwards, we applied them to the study of the reactivity of the system, including the binding of the substrate to the cofactor-protein complex and the characterization of the most-likely transition states. In this last case we demonstrated that these kind of integrative protocols are able to offer high predictive profiles of the enantioselectivity of the system. Even though in Ph. D. thesis we have demonstrated the great utility that integrative approaches encompassing several different molecular modeling tehcniques could have in the study of biometallic complexes, their development is far from easy. The major part of modeling softwares have not been designed to be part of this kind of integrative protocols and each one of them has their own way to treat the molecular data. To solve those incompatibilities, it is necessary an integrative platform encompassing all those techniques that regulates the flux of information between them. This kind of platforms are already available at a commercial level, but they are rather expensive and are based on a black-box approach, thus the user cannot adapt them to its own molecular problem. For this reason, in this thesis we have developed an integrative platform, which is open-code and freely-available to all the members of the modeling community. At the moment, it includes interfaces to perform Normal Modes Analysis and Molecular Dynamics simulations. Additionally, it is also able to analyze the results of quantum calculations performed with Gaussian and protein-ligand dockings performed with GOLD. More implementations are still under development

Development and applications of molecular modelling techniques for the design and optimization of artificial metalloenzymes

La búsqueda de procesos de síntesis de moléculas orgánicas altamente eficientes y selectivos es uno de los retos de la química. En los últimos años, las enzimas se han presentado como una seria alternativa a los catalizadores homogéneos tradicionales debido a su alta eficiencia y selectividad natural. Desafortunadamente, las reacciones que pueden catalizar estas especies se suelen restringir a aquellas que tienen importancia para el huésped que las alberga, limitando su aplicación en el ámbito químico/industrial. Para poder solventar estas limitaciones se han desarrollado las llamadas metaloenzimas artificiales. Estos híbridos se obtienen a partir de la inserción de un catalizador homogéneo en una proteína. De este modo el receptor protege el cofactor inorgánico y aporta un entorno quiral (enantioselectivo) mientras que el metal es responsable de la reactividad del sistema. Pero el diseño de estos híbridos representa todo un reto: la proteína no ha sido diseñada evolutivamente para reconocer el fragmento inorgánico y el complejo resultante puede no reconocer de forma eficiente el sustrato. Todo esto provoca que la enzima diseñada presente deficiencias en cuanto a la eficiencia catalítica y/o selectividad. Las técnicas de modelización molecular pueden resultar de gran ayuda en el proceso de diseño y de optimización de las metaloenzimas artificiales. Sin embargo, su aplicación en este tipo de sistemas no es trivial. Necesitamos técnicas que permiten una amplia y rápida búsqueda tanto del espacio conformacional como del químico (mecánica molecular) así cómo técnicas que permitan una descripción precisa del metal y sus propiedad electrónicas (mecánica cuántica). Lamentablemente, estas últimas son demasiado costosas a nivel computacional cómo para poder tratar sistemas de estas dimensiones. En esta tesis nos hemos basado en la combinación de diferentes técnicas de modelización molecular, basadas tanto en aproximaciones mecanoclásicas como mecanocuánticas, para poder solventar estas limitaciones. Este enfoque ha sido aplicado al diseño y optimización de metaloenzimas artificiales. En primer lugar hemos estudiado la unión entre el cofactor inorgánico y la proteína, obteniendo una gran correlación entre los modelos teóricos y los resultados experimentales. A continuación las hemos aplicado al estudio de la reactividad del sistema, tanto a la unión del sustrato al complejo proteína-cofactor como a la caracterización de los estados de transición más probables. En este último caso hemos podido comprobar que estos protocolos integrativos son capaces de ofrecer un nivel muy aceptable de predictibilidad de la enantioselectividad del sistema. Aunque en esta tesis hemos demostrado la gran utilidad que pueden tener los protocolos que integran diversas técnicas de modelización molecular en el estudio de complejos biometálicos, su desarrollo no es trivial. La mayoría de programas de modelización molecular no han sido diseñados para ser utilizados en tándem y todos ellos tienen su propia forma de tratar la información molecular. Para solventar estas incompatibilidades se necesitaría una plataforma integrativa que englobara todas estas técnicas y regulara el flujo de información entre ellas. A nivel comercial estas plataformas ya existen, pero su uso es altamente restrictivo ya que son muy caras y son de código cerrado, dejando muy poco margen para su adaptabilidad a cada problema molecular. Por este motivo en esta tesis nos hemos centrado en el desarrollo de una plataforma integrativa de código abierto accesible a toda la comunidad de modelizadores. Hasta el momento, esta plataforma incluye interfaces para realizar cálculos de modos normales y dinámicas moleculares, así como permitir el análisis de cálculos cuánticos con Gaussian y cálculos de docking proteína-ligando con GOLD. Se espera incorporar muchas mas técnicas en un futuro próximo.The search of highly efficient and selective processes for the synthesis of organic molecules is one of the challenges of chemistry. In the last years, enzymes have positioned as a clear alternative to traditional homogeneous catalysts due to their high natural efficiency and selectivity. Unfortunately, their range of different reactions is restricted to those that are useful for their host. To solve this limitation the so-called artificial metalloenzymes have been developed. These hybrids are based on the insertion of an homogeneous catalyst into a protein scaffold. This way, the receptor protects the inorganic cofactor and provides with a chiral (enantioselective) environment while the metal is responsible for the reactivity of the system. However, their design is highly challenging: the protein has not been optimized to bind such inorganic compounds and the resulting complex may not efficiently recognize the substrate. Altogether, these could mean that the artificial enzyme has several deficiencies in terms of catalytic efficiency and/or enantioselectivity. Molecular modelling techniques could aid in the design and optimization of artificial metalloenzymes. However, their application is not straightforward due to the complexity of these hybrids. We need both techniques allowing wide and fast conformational and chemical space searches (molecular mechanics) and techniques offering an accurate description of the metal and its electronic states (quantum mechanics). Unfortunately, the later ones are too computational intensive to treat systems of a huge size such as enzymes. In this Ph. D. thesis we combined several molecular modeling techniques, based either in classical or quantum mechanics approximations, to solve those limitations. This approach has been applied on the design and optimization of artificial metalloenzymes. First, we have studied the binding of the inorfanic cofactor in the protein scaffold, obtaining very good agreement between the theoretical models and the experimental results. Afterwards, we applied them to the study of the reactivity of the system, including the binding of the substrate to the cofactor-protein complex and the characterization of the most-likely transition states. In this last case we demonstrated that these kind of integrative protocols are able to offer high predictive profiles of the enantioselectivity of the system. Even though in Ph. D. thesis we have demonstrated the great utility that integrative approaches encompassing several different molecular modeling tehcniques could have in the study of biometallic complexes, their development is far from easy. The major part of modeling softwares have not been designed to be part of this kind of integrative protocols and each one of them has their own way to treat the molecular data. To solve those incompatibilities, it is necessary an integrative platform encompassing all those techniques that regulates the flux of information between them. This kind of platforms are already available at a commercial level, but they are rather expensive and are based on a black-box approach, thus the user cannot adapt them to its own molecular problem. For this reason, in this thesis we have developed an integrative platform, which is open-code and freely-available to all the members of the modeling community. At the moment, it includes interfaces to perform Normal Modes Analysis and Molecular Dynamics simulations. Additionally, it is also able to analyze the results of quantum calculations performed with Gaussian and protein-ligand dockings performed with GOLD. More implementations are still under development

Crystal Structure of Two Anti-Porphyrin Antibodies with Peroxidase Activity

We report the crystal structures at 2.05 and 2.45 Å resolution of two antibodies, 13G10 and 14H7, directed against an iron(III)-αααβ-carboxyphenylporphyrin, which display some peroxidase activity. Although these two antibodies differ by only one amino acid in their variable λ-light chain and display 86% sequence identity in their variable heavy chain, their complementary determining regions (CDR) CDRH1 and CDRH3 adopt very different conformations. The presence of Met or Leu residues at positions preceding residue H101 in CDRH3 in 13G10 and 14H7, respectively, yields to shallow combining sites pockets with different shapes that are mainly hydrophobic. The hapten and other carboxyphenyl-derivatized iron(III)-porphyrins have been modeled in the active sites of both antibodies using protein ligand docking with the program GOLD. The hapten is maintained in the antibody pockets of 13G10 and 14H7 by a strong network of hydrogen bonds with two or three carboxylates of the carboxyphenyl substituents of the porphyrin, respectively, as well as numerous stacking and van der Waals interactions with the very hydrophobic CDRH3. However, no amino acid residue was found to chelate the iron. Modeling also allows us to rationalize the recognition of alternative porphyrinic cofactors by the 13G10 and 14H7 antibodies and the effect of imidazole binding on the peroxidase activity of the 13G10/porphyrin complexes

Influence of a Maximal Incremental Test Until Exhaustion on the Urinary Excretion of Steroid Hormones in Trained Cyclists

This study aimed to assess the effect of a maximum incremental stress test through urinary concentrations of steroid hormones in trained cyclists. Twenty male cyclists participated in the study (23.83 ± 2.3 years; 1.76 ± 0.03 m; 66.94 ± 3.59 kg; training volume: 20.50 ± 2.35 h/week). Athletes performed a maximum incremental test until exhaustion on a cycle ergometer and urine samples were collected at three different time points: before, immediately after, and 48 h after the test. Lactate, creatinine and urinary concentrations of testicular and adrenal androgens were obtained as well as urinary concentrations of glucocorticoid hormones. An increase in lactate was observed after the test (p < 0.01). There were decreases in the urinary excretion of androgenic hormones after the test, which were significant in testosterone, androsterone, androstenedione, total adrenal androgen and total testicular androgen (p < 0.05). The values were restored after 48 h (p < 0.05). Urinary cortisol concentrations decreased after the test (p < 0.05). A decrease was also observed in the ratio of anabolic/catabolic hormones (p < 0.05) increasing 48 h after the test (p < 0.05). Increased acute physical exercise until exhaustion causes variations in the urinary excretions of steroid hormones which were restored 48 h after exercise. Urinary excretion of steroid hormones could be a valid method of monitoring training loads

Association of Nutritional Risk at Admission with the Development of Sarcopenia in Adult Intensive Care Unit Patients at Nuevo Hospital Civil de Guadalajara "Dr. Juan I. Menchaca"

The risk of malnutrition and sarcopenia in the intensive care unit is a common problem among hospitalized patients. There are multiple factors that indirectly influence the development of these conditions, both related to the disease for which the patient is admitted to the unit (abdominal surgeries with intestinal dysfunction, pancreatitis), the complications inherent to a patient in the intensive care unit resulting from standard management (sedation, analgesia, immobility, muscle paralysis), as well as the nutritional management, which often tends to be inadequate (lack of enteral feeding tube placement, inadequate calculation of caloric requirements, omission of diet by the nursing department). Both a high risk of malnutrition (or malnutrition itself) and sarcopenia have a negative impact on the patients' progress, leading to prolonged hospital stay, longer recovery time, and increased mortality. Therefore, it is important to understand the nutritional risk of the patient and its relationship with sarcopenia in our setting

Incorporation of manganese complexes into xylanase: new artificial metalloenzymes for enantioselective epoxidation.

International audienceHere we report the best artificial metalloenzyme to date for the selective oxidation of aromatic alkenes; it was obtained by noncovalent insertion of Mn(III)-meso-tetrakis(p-carboxyphenyl)porphyrin [Mn(TpCPP), 1-Mn] into a host protein, xylanase 10A from Streptomyces lividans (Xln10A). Two metallic complexes-N,N'-ethylene bis(2-hydroxybenzylimine)-5,5'-dicarboxylic acid Mn(III) [(Mn-salen), 2-Mn] and 1-Mn-were associated with Xln10A, and the two hybrid biocatalysts were characterised by UV-visible spectroscopy, circular dichroism and molecular modelling. Only the artificial metalloenzyme based on 1-Mn and Xln10A was studied for its catalytic properties in the oxidation of various substituted styrene derivatives by KHSO(5): after optimisation, the 1-Mn-Xln10A artificial metalloenzyme was able to catalyse the oxidation of para-methoxystyrene by KHSO(5) with a 16 % yield and the best enantioselectivity (80 % in favour of the R isomer) ever reported for an artificial metalloenzyme