721 research outputs found

    Structure and function of the metagenomic plastic-degrading polyester hydrolase PHL7 bound to its product

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    The recently discovered metagenomic-derived polyester hydrolase PHL7 is able to efficiently degrade amorphous polyethylene terephthalate (PET) in post-consumer plastic waste. We present the cocrystal structure of this hydrolase with its hydrolysis product terephthalic acid and elucidate the influence of 17 single mutations on the PET-hydrolytic activity and thermal stability of PHL7. The substrate-binding mode of terephthalic acid is similar to that of the thermophilic polyester hydrolase LCC and deviates from the mesophilic IsPETase. The subsite I modifications L93F and Q95Y, derived from LCC, increased the thermal stability, while exchange of H185S, derived from IsPETase, reduced the stability of PHL7. The subsite II residue H130 is suggested to represent an adaptation for high thermal stability, whereas L210 emerged as the main contributor to the observed high PET-hydrolytic activity. Variant L210T showed significantly higher activity, achieving a degradation rate of 20 µm h−1 with amorphous PET films

    Química dinámica combinatoria : optimización de la química reversible y aplicación en el descubrimiento de fármacos

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    Tesis inédita de la Universidad Complutense de Madrid, Facultad de Ciencias Químicas, leída el 26-01-2023Dynamic combinatorial chemistry is defined as “the chemistry under thermodynamic control”. It is based on the combination of building blocks that react with each other through reversible chemical bonds to form the final products, reaching the thermodynamic equilibrium (dynamic combinatorial library, DCL). This chemistry is able to respond to external stimuli such as pH, temperature, or the addition of a biomolecule acting as a template. For instance, adding a template will shift the equilibrium towards the formation of the compounds with higher affinity to the template.Templated-DCLs developed under physiological conditions require an effective design of the dynamic chemical system composed of a biomolecule as a template, reversible chemistry that works effectively under physiological conditions, structurally diverse building blocks compatible with the target, and an analysis method. Protein-directed dynamic combinatorial chemistry (P-D DCC) is currently a powerful and efficient tool for discovering ligands with high affinity to a protein target. In this thesis, adding two different protein targets, NCS1 and glucose oxidase, shifted the DCL equilibrium to forming the best ligands in a pool of compounds...La química dinámica combinatoria se define como la química bajo control termodinámico. Se basa en la combinación de monómeros (en inglés, building blocks), que reaccionan entre sí a través de enlaces químicos reversibles formando compuestos, hasta alcanzar el equilibrio termodinámico (librería dinámica combinatoria, DCL, del inglés dynamic combinatorial library). Esta química reversible, en unas condiciones concretas, tiene la capacidad de responder a estímulos externos como el pH, la temperatura o la adición de una biomolécula que actúe como plantilla. En este último caso, el equilibrio se desplazará hacia la formación de complejos más estables y afines por la plantilla. En condiciones fisiológicas y en presencia de una plantilla, las DCLs requieren de un sistema químico-dinámico eficiente compuesto, además de la biomolécula que actúa como plantilla, de una química reversible adecuada y de unos monómeros estructuralmente distintos compatibles con la biomolécula y del método de análisis. La química dinámica combinatoria dirigida por proteínas (en inglés, protein-directed DCC, P-D DCC) se considera actualmente una herramienta eficaz y potente para encontrar ligandos que poseen una afinidad alta por la proteína que actúa como plantilla. En esta tesis, la adición de dos proteínas diferentes como dianas, NCS1 y glucosa oxidasa, desplaza el equilibrio de la dcl hacia la formación de los ligandos más prometedores del conjunto de compuestos formados en el equilibrio..Fac. de Ciencias QuímicasTRUEunpu

    Metal Cations in Protein Force Fields: From Data Set Creation and Benchmarks to Polarizable Force Field Implementation and Adjustment

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    Metal cations are essential to life. About one-third of all proteins require metal cofactors to accurately fold or to function. Computer simulations using empirical parameters and classical molecular mechanics models (force fields) are the standard tool to investigate proteins’ structural dynamics and functions in silico. Despite many successes, the accuracy of force fields is limited when cations are involved. The focus of this thesis is the development of tools and strategies to create system-specific force field parameters to accurately describe cation-protein interactions. The accuracy of a force field mainly relies on (i) the parameters derived from increasingly large quantum chemistry or experimental data and (ii) the physics behind the energy formula. The first part of this thesis presents a large and comprehensive quantum chemistry data set on a consistent computational footing that can be used for force field parameterization and benchmarking. The data set covers dipeptides of the 20 proteinogenic amino acids with different possible side chain protonation states, 3 divalent cations (Ca2+, Mg2+, and Ba2+), and a wide relative energy range. Crucial properties related to force field development, such as partial charges, interaction energies, etc., are also provided. To make the data available, the data set was uploaded to the NOMAD repository and its data structure was formalized in an ontology. Besides a proper data basis for parameterization, the physics covered by the terms of the additive force field formulation model impacts its applicability. The second part of this thesis benchmarks three popular non-polarizable force fields and the polarizable Drude model against a quantum chemistry data set. After some adjustments, the Drude model was found to reproduce the reference interaction energy substantially better than the non-polarizable force fields, which showed the importance of explicitly addressing polarization effects. Tweaking of the Drude model involved Boltzmann-weighted fitting to optimize Thole factors and Lennard-Jones parameters. The obtained parameters were validated by (i) their ability to reproduce reference interaction energies and (ii) molecular dynamics simulations of the N-lobe of calmodulin. This work facilitates the improvement of polarizable force fields for cation-protein interactions by quantum chemistry-driven parameterization combined with molecular dynamics simulations in the condensed phase. While the Drude model exhibits its potential simulating cation-protein interactions, it lacks description of charge transfer effects, which are significant between cation and protein. The CTPOL model extends the classical force field formulation by charge transfer (CT) and polarization (POL). Since the CTPOL model is not readily available in any of the popular molecular-dynamics packages, it was implemented in OpenMM. Furthermore, an open-source parameterization tool, called FFAFFURR, was implemented that enables the (system specific) parameterization of OPLS-AA and CTPOL models. Following the method established in the previous part, the performance of FFAFFURR was evaluated by its ability to reproduce quantum chemistry energies and molecular dynamics simulations of the zinc finger protein. In conclusion, this thesis steps towards the development of next-generation force fields to accurately describe cation-protein interactions by providing (i) reference data, (ii) a force field model that includes charge transfer and polarization, and (iii) a freely-available parameterization tool.Metallkationen sind für das Leben unerlässlich. Etwa ein Drittel aller Proteine benötigen Metall-Cofaktoren, um sich korrekt zu falten oder zu funktionieren. Computersimulationen unter Verwendung empirischer Parameter und klassischer Molekülmechanik-Modelle (Kraftfelder) sind ein Standardwerkzeug zur Untersuchung der strukturellen Dynamik und Funktionen von Proteinen in silico. Trotz vieler Erfolge ist die Genauigkeit der Kraftfelder begrenzt, wenn Kationen beteiligt sind. Der Schwerpunkt dieser Arbeit liegt auf der Entwicklung von Werkzeugen und Strategien zur Erstellung systemspezifischer Kraftfeldparameter zur genaueren Beschreibung von Kationen-Protein-Wechselwirkungen. Die Genauigkeit eines Kraftfelds hängt hauptsächlich von (i) den Parametern ab, die aus immer größeren quantenchemischen oder experimentellen Daten abgeleitet werden, und (ii) der Physik hinter der Kraftfeld-Formel. Im ersten Teil dieser Arbeit wird ein großer und umfassender quantenchemischer Datensatz auf einer konsistenten rechnerischen Grundlage vorgestellt, der für die Parametrisierung und das Benchmarking von Kraftfeldern verwendet werden kann. Der Datensatz umfasst Dipeptide der 20 proteinogenen Aminosäuren mit verschiedenen möglichen Seitenketten-Protonierungszuständen, 3 zweiwertige Kationen (Ca2+, Mg2+ und Ba2+) und einen breiten relativen Energiebereich. Wichtige Eigenschaften für die Entwicklung von Kraftfeldern, wie Wechselwirkungsenergien, Partialladungen usw., werden ebenfalls bereitgestellt. Um die Daten verfügbar zu machen, wurde der Datensatz in das NOMAD-Repository hochgeladen und seine Datenstruktur wurde in einer Ontologie formalisiert. Neben einer geeigneten Datenbasis für die Parametrisierung beeinflusst die Physik, die von den Termen des additiven Kraftfeld-Modells abgedeckt wird, dessen Anwendbarkeit. Der zweite Teil dieser Arbeit vergleicht drei populäre nichtpolarisierbare Kraftfelder und das polarisierbare Drude-Modell mit einem Datensatz aus der Quantenchemie. Nach einigen Anpassungen stellte sich heraus, dass das Drude-Modell die Referenzwechselwirkungsenergie wesentlich besser reproduziert als die nichtpolarisierbaren Kraftfelder, was zeigt, wie wichtig es ist, Polarisationseffekte explizit zu berücksichtigen. Die Anpassung des Drude-Modells umfasste eine Boltzmann-gewichtete Optimierung der Thole-Faktoren und Lennard-Jones-Parameter. Die erhaltenen Parameter wurden validiert durch (i) ihre Fähigkeit, Referenzwechselwirkungsenergien zu reproduzieren und (ii) Molekulardynamik-Simulationen des Calmodulin-N-Lobe. Diese Arbeit demonstriert die Verbesserung polarisierbarer Kraftfelder für Kationen-Protein-Wechselwirkungen durch quantenchemisch gesteuerte Parametrisierung in Kombination mit Molekulardynamiksimulationen in der kondensierten Phase. Während das Drude-Modell sein Potenzial bei der Simulation von Kation - Protein - Wechselwirkungen zeigt, fehlt ihm die Beschreibung von Ladungstransfereffekten, die zwischen Kation und Protein von Bedeutung sind. Das CTPOL-Modell erweitert die klassische Kraftfeldformulierung um den Ladungstransfer (CT) und die Polarisation (POL). Da das CTPOL-Modell in keinem der gängigen Molekulardynamik-Pakete verfügbar ist, wurde es in OpenMM implementiert. Außerdem wurde ein Open-Source-Parametrisierungswerkzeug namens FFAFFURR implementiert, welches die (systemspezifische) Parametrisierung von OPLS-AA und CTPOL-Modellen ermöglicht. In Anlehnung an die im vorangegangenen Teil etablierte Methode wurde die Leistung von FFAFFURR anhand seiner Fähigkeit, quantenchemische Energien und Molekulardynamiksimulationen des Zinkfingerproteins zu reproduzieren, bewertet. Zusammenfassend lässt sich sagen, dass diese Arbeit einen Schritt in Richtung der Entwicklung von Kraftfeldern der nächsten Generation zur genauen Beschreibung von Kationen-Protein-Wechselwirkungen darstellt, indem sie (i) Referenzdaten, (ii) ein Kraftfeldmodell, das Ladungstransfer und Polarisation einschließt, und (iii) ein frei verfügbares Parametrisierungswerkzeug bereitstellt

    New computational methods for structural modeling protein-protein and protein-nucleic acid interactions

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    Programa de Doctorat en Biomedicina[eng] The study of the 3D structural details of protein-protein and protein-DNA interactions is essential to understand biomolecular functions at the molecular level. Given the difficulty of the structural determination of these complexes by experimental techniques, computational tools are becoming a powerful to increase the actual structural coverage of protein-protein and protein-DNA interactions. pyDock is one of these tools, which uses its scoring function to determine the quality of models generated by other tools. pyDock is usually combined with the model sampling methods FTDOCK or ZDOCK. This combination has shown a consistently good prediction performance in community-wide assessment experiments like CAPRI or CASP and has provided biological insights and insightful interpretation of experiments by modeling many biomolecular interactions of biomedical and biotechnological interest. This software combination has demonstrated good predictive performance in the blinded evaluation experiments CAPRI and CASP. It has provided biological insights by modeling many biomolecular interactions of biomedical and biotechnological interest. Here, we describe a pyDock software update, which includes its adaptation to the newest python code, the capability of including cofactor and other small molecules, and an internal parallelization to use the computational resources more efficiently. A strategy was designed to integrate the template-based docking and ab initio docking approaches by creating a new scoring function based on the pyDock scoring energy basis function and the TM-score measure of structural similarity of protein structures. This strategy was partially used for our participation in the 7th CAPRI, the 3rd CASP-CAPRI and the 4th CASP-CAPRI joint experiments. These experiments were challenging, as we needed to model protein-protein complexes, multimeric oligomerization proteins, protein-peptide, and protein-oligosaccharide interactions. Many proposed targets required the efficient integration of rigid-body docking, template-based modeling, flexible optimization, multi- parametric scoring, and experimental restraints. This was especially relevant for the multi- molecular assemblies proposed in the 3er and 4th CASP-CAPRI joint experiments. In addition, a case study, in which electron transfer protein complexes were modelled to test the software new capabilities. Good results were achieved as the structural models obtained help explaining the differences in photosynthetic efficiency between red and green algae

    Development and application of NMR methods to study biomolecular dynamics

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    Structural biology has generated profound insights into biomolecular machines. The molecular basis of processes like binding, folding, catalysis and regulation, which underlie the inner working of living organisms would have largely remained unexplored without the thousands of structures that have been solved over the years. But these machines, formed by proteins and nucleic acids, are inherently dynamic, and information about this fourth dimension, the modulation of their structure with time, is often lacking. Nuclear magnetic resonance (NMR) is exquisitely suited to characterize dynamics over a wide timescale, from picoseconds, where amplitudes and correlation times can be extracted, to microsecond, milliseconds and seconds, where in favourable cases information about the kinetics, the thermodynamics and the structure of an excited state can be retrieved. With increasing size of the molecular system under consideration, however, this characterization is progressively challenging for NMR, and the analysis often focuses on 13CH3 spin systems in a perdeuterated background. As an alternative approach, fluorine NMR has grown in popularity. The 19F isotope can be introduced site-specifically, it gives rise to background-free one-dimensional spectra and the technique bypasses the need for perdeuteration. In my disseration, I expanded the existing toolkit of 19F NMR, applied 19F experiments that report on dynamics to high-molecular weight systems and combined their advantages with established methyl group NMR techniques. Development of 19F relaxation dispersion experiments To develop 19F relaxation dispersion (RD) experiments, I used a 7.5 kDa cold shock protein from the thermophilic organism Thermotoga maritima as a protein folding/unfolding model system. The global analysis of three RD experiments showed consistent results for the two-state exchange process. Our new rotating frame relaxation pulse sequences allowed to extract the absolute chemical shift of the unfolded state and significantly extended the range of timescales that can be assessed experimentally. Employing a 360 kDa double heptameric complex, I validated the applicability of the experiments on a highly challenging assembly. Conformational changes in the exoribonuclease Xrn2 The 5'-3' exoribonuclease Xrn2 operates in the nucleus in RNA processing and RNA turn-over pathways. Static structures of its cytoplasmic homologue Xrn1 in the presence of substrates implicate that the enzymes undergo conformational changes to progress through the catalytic cycle. Here, I solved the X-ray structure of Xrn2 from the thermophilic organism Chaetomium thermophilum to 3 Å resolution and combined methyl group and fluorine relaxation dispersion to characterize the exchange in a 100 kDa apo protein core construct in solution. Upon binding of a substrate, the conformational equilibrium is substantially shifted towards the active state. Importantly, the 19F experiments allowed to characterize dynamics in these unstable samples and I could show that the exchange of the enzyme:substrate complex are largely suppressed. Multi-site exchange in a neomycin-sensing riboswitch The existence of multiple sparsely populated states complicates the characterization of an exchanging system. Using a synthetic neomycin-binding riboswitch bound to different aminoglycoside ligands, I demonstrated that fluorine NMR can be employed to study exchange topologies with up to four states. To this end, I take advantage of an additional off-resonance technique, 19F chemical exchange saturation transfer. Combined with 19F RD and longitudinal exchange experiments, the results support the notion of a modular impact of aminoglycoside functional groups on the riboswitch dynamics. Taken together, these results expand and complement the NMR toolbox to study exchanging systems, with an emphasis on high-molecular weight systems and intricate exchange topologies involving more than two states. Furthermore, they elucidate the molecular dynamics in the 5'-3' exoribonuclease Xrn2 and provide a conceptional framework to study dynamics in related systems such as Xrn1

    Molecular modeling of drug delivery systems based on carbon nanostructures: structure, function, and potential applications for anticancer complexes of Pt(II)

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    The medication with Pt(II) drugs (cisplatin, carboplatin, and oxaliplatin) has been an effective alternative for treating cancers due to their notable inhibition of cancer cells growth and the prevention of metastasis. Nevertheless, the low selectivity of these metallodrugs for malignant cells produces severe side effects, which limit this chemotherapy. In this context, carbon nanohorns (CNHs) have been considered potential nanovectors for drugs, since they present low toxicity, drug-loading capacity, biodegradation routes, and biocompatibility when oxidized. However, there is still a lack of studies regarding the molecular behavior of these nanocarriers on cell membranes. The present work aims to characterize the interactions between inclusion complexes drug@CNH, which are formed by platinum drugs encapsulated in CNHs, and plasma membranes by using molecular dynamics simulations. The results demonstrated that the van der Waals contribution played a primary role (∼74%) for the complex stability, which explain the confined dynamics of drugs inside the CNHs. The free energy profiles revealed an endergonic character of the drug release processes from CNHs, in which the energy barrier for oxaliplatin release (~24 kcal mol–1 ) was ~30% larger than those for carboplatin and cisplatin (~18 kcal mol-1 ). The simulations also showed four stages of the interaction mechanism CNH--membrane: approach, insertion, permeation, and internalization. Despite the low structural disturbance of the membranes, the free energy barrier of ∼55 kcal mol-1 for the CNHs translocation indicated that this transport is kinetically unfavorable by passive process. The in silico experiments evidenced that the most likely mechanism of cisplatin delivery from CNHs involve the approach and insertion stages, where the nanovector adheres on the surface of cancer cells, as reported in in vitro studies. After this retention, the drug load may be slowly released in the tumor site. Finally, simulations of the cellular uptake of Pt(II) drugs also pointed out significant energy barriers (~30 kcal mol-1 ) for this process, which reflects their low permeability in membranes as discussed in experimental studies. In addition to reinforcing the potential of CNH as nanovector of Pt(II) drugs, the results presented in this thesis may assist and drive new experimental studies with CNHs, focusing on the development of less aggressive formulations for cancer treatments.A medicação com fármacos a base de Pt(II) (cisplatina, carboplatina e oxaliplatina) tem sido uma alternativa efetiva para tratar cânceres devido à sua notável inibição do crescimento de células cancerosas e a prevenção de metástases. No entanto, a baixa seletividade dessas metalodrogas por células cancerosas gera severos efeitos colaterais. Nesse contexto, nanohorns de carbono (CNHs) têm sido considerados potenciais nanovetores de fármacos, devido a baixa toxicidade, capacidade de carreamento de fármacos, rotas de biodegradação, e biocompatibilidade quando oxidados. Porém, existe uma carência de estudos tratando o comportamento desses nanocarreadores em biomembranas. Esse trabalho tem como objetivo caracterizar as interações entre complexos de inclusão fármaco@CNH, formados por fármacos de Pt(II) encapsulados em CNHs, e membranas usando simulações por dinâmica molecular. Os resultados demonstraram que a contribuição de van der Waals teve um papel primário (∼74%) na estabilidade dos complexos, o que explica a dinâmica confinada dos fármacos dentro dos CNHs. Os perfis de energia livre revelaram o caráter endergônico da liberação dos fármacos a partir de CNHs, nos quais a barreira de energia para a liberação da oxaliplatina (~24 kcal mol– 1 ) é ~30% maior do que aquelas para carboplatina e cisplatina. As simulações mostraram quatro estágios do mecanismo de interação CNH-membrana: aproximação, inserção, permeação e internalização. Apesar do baixo distúrbio estrutural das membranas, a barreira de energia livre de ∼55 kcal mol-1 para a translocação de CNHs indicou que esse transporte é desfavorável cineticamente via o processo passivo. Os experimentos in silico evidenciam que o mecanismo mais provável de entrega de cisplatina a partir de CNHs envolve a aproximação e inserção, onde o nanovetor adere na superfície de células cancerosas, como reportado em estudos in vitro. Após essa retenção, a carga de fármaco deve ser ligeiramente liberada no tumor. As simulações de captação celular de fármacos de Pt(II) também apontaram barreiras de energia significativas (∼30 kcal mol-1 ) para esse processo, o que reflete a baixa permeabilidade deles em membranas como discutido em estudos experimentais. Além de reforçar o potencial de CNHs como nanovetores de fármacos de Pt(II), os resultados apresentados nessa tese podem auxiliar e impulsionar novos estudos com CNHs, focando no desenvolvimento de formulações menos agressivas para tratamentos de câncer.FAPEMIG - Fundação de Amparo à Pesquisa do Estado de Minas Gerai

    Studying DNA opening during transcription by the RNA polymerase II with molecular dynamics simulations, a sampling challenge

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    Die RNA-Polymerase II (RNAP II) ist ein makromolekularer Komplex, der die RNA aus einer DNA-Matrize synthetisiert. Während des Initiationsschritts der Transkription, öffnet RNAP II die doppelsträngige DNA, um den DNA-Code freizulegen. Da die Bildung der DNA-Transkriptionsblase nur unzureichend verstanden ist, nutzten wir Molekulardynamik-Simulationen (MD), um Erkenntnisse über diesen Prozess zu erlangen. Da die DNA-Öffnung auf Zeitskalen erfolgt, die für einfache MD Simulationen nicht zugänglich sind, prüften wir verschiedene Enhanced Sampling Methoden, um die MD Simulationen zu beschleunigen und den DNA-Öffnungsprozess zu untersuchen. Wir fanden heraus, dass die vielversprechendste Methode zur Untersuchung der DNA-Öffnung die Steuerung von Simulationen mit einer Kombination aus (i) geführter DNA-Rotation und (ii) Path Collective Variables war. Auf diese Weise erhielten wir kontinuierliche atomare Trajektorien des gesamten DNA-Öffnungsprozesses, welche qualitative Einblicke in die Rolle der Protein–DNA Wechselwirkungen im Allgemeinen ermöglichten. Mit dem Ziel die DNA-Öffnung quantitativer zu beschreiben, möchten wir weitere Enhanced Sampling Techniken untersuchen, welche wir auf einen einfachen Prozess anwenden: die Permeation von Fosmidomycin durch das OprO Porin. Es zeigte sich, dass das Replica-Exchange Umbrella Sampling in der Lage ist, die Genauigkeit des Profils der freien Energie drastisch zu erhöhen, im Vergleich zu gewöhnlichem Umbrella Sampling.RNA polymerase II (RNAP II) is a macro-molecular complex that synthesizes RNA by reading the DNA code, a process called transcription. During the initiation step of transcription, RNAP II opens double-stranded DNA in order to read the DNA code. Since formation of the DNA transcription bubble remains poorly understood, we used molecular dynamics simulations (MD) to provide atomic-level insights into this process. Because DNA opening occurs at time-scales that are not accessible to plain MD simulations, we have explored different enhanced sampling methods to accelerate MD simulations enabling to study the DNA opening process. Ultimately, by steering simulations with a combination of (i) guided DNA rotation and (ii) path collective variables, we obtained a continuous atomic trajectories of the complete DNA opening process. The simulations provided qualitative insights into the role of loop dynamics and protein-DNA interactions during DNA opening. With the aim of obtaining a more quantitative description of DNA opening, we decided to further explore alternative enhanced sampling techniques applied on a simpler process, yet still challenging from a sampling perspective, that is drug permeation through the OprO porin. This study showed that replica-exchange umbrella sampling (REUS) is able to drastically increase precision of free energy profiles compared to standard umbrella sampling

    The adaptability of the ion binding site by the Ag(I)/Cu(I) periplasmic chaperone SilF

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    The periplasmic chaperone SilF has been identified as part of an Ag(I) detoxification system in Gram negative bacteria. Sil proteins also bind Cu(I), but with reported weaker affinity, therefore leading to the designation of a specific detoxification system for Ag(I). Using isothermal titration calorimetry we show that binding of both ions is not only tighter than previously thought, but of very similar affinities. We investigated the structural origins of ion binding using molecular dynamics and QM/MM simulations underpinned by structural and biophysical experiments. The results of this analysis showed that the binding site adapts to accommodate either ion, with key interactions with the solvent in the case of Cu(I). The implications of this are that Gram negative bacteria do not appear to have evolved a specific Ag(I) efflux system but take advantage of the existing Cu(I) detoxification system. Therefore, there are consequences for how we define a particular metal resistance mechanism and understand its evolution in the environment

    Applications and Properties of Magnetic Nanoparticles

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    This Special Issue aimed to cover the new developments in the synthesis and characterization of magnetic nanoconstructs ranging from conventional metal oxide nanoparticles to novel molecule-based or hybrid multifunctional nano-objects. At the same time, the focus was on the potential of these novel magnetic nanoconstructs in several possible applications, e.g. sensing, energy storage, and nanomedicine

    Crystallographic Studies of Enzymes (Volume II)

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    In this Special Issue of Crystals, entitled "Crystallographic Studies of Enzymes (Volume II)", eleven research papers on key findings and methodologies of structure, function, and reaction mechanisms of enzymes are presented
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