Charged dendrimers revisited: Effective charge and surface potential of dendritic polyglycerol sulfate

We investigate key electrostatic features of charged dendrimers at hand of the biomedically important dendritic polyglycerol sulfate (dPGS) macromolecule using multi-scale computer simulations and Zetasizer experiments. In our simulation study, we first develop an effective mesoscale Hamiltonian specific to dPGS based on input from all-atom, explicit-water simulations of dPGS of low generation. Employing this in coarse-grained, implicit-solvent/explicit-salt Langevin dynamics simulations, we then study dPGS structural and electrostatic properties up to the sixth generation. By systematically mapping then the calculated electrostatic potential onto the Debye-H\"uckel form -- that serves as a basic defining equation for the effective charge -- we determine well-defined effective net charges and corresponding radii, surface charge densities, and surface potentials of dPGS. The latter are found to be up to one order of magnitude smaller than the bare values and consistent with previously derived theories on charge renormalization and weak saturation for high dendrimer generations (charges). Finally, we find that the surface potential of the dendrimers estimated from the simulations compare very well with our new electrophoretic experiments

Electrostatics Versus Hydration

The interaction between dendritic polyglycerol sulfate (dPGS) of the second generation and lysozyme was studied by isothermal titration calorimetry (ITC) at different temperatures and salt concentrations. Analysis by ITC showed that 2–3 lysozyme molecules were bound to each dPGS. The resulting binding constant Kb and the Gibbs free energy ΔGo decreased markedly with increasing salt concentration but were nearly independent of temperature. The salt dependence of Kb led to the conclusion that ca. 3 counterions bound to dPGS were released upon complex formation. The gain in entropy ΔGci by this counterion-release scales logarithmically with salt concentration and is the main driving force for binding. The temperature dependence of ΔGo was analyzed by the nonlinear van’t Hoff plot, taking into account a finite heat capacity change ΔCp,vH. This evaluation led to the binding enthalpy ΔHvH and the binding entropy ΔSvH. Both quantities varied strongly with temperature and even changed sign, but they compensated each other throughout the entire range of temperature. Coarse-grained computer simulations with explicit salt and implicit water were used to obtain the binding free energies that agreed with ITC results. Thus, electrostatic factors were the driving forces for binding whereas all hydration contributions leading to the strongly varying ΔHvH and ΔSvH canceled out. The calorimetric enthalpy ΔHITC measured directly by ITC differed largely from ΔHvH. ITC measurements done in two buffer systems with different ionization enthalpies revealed that binding was linked to buffer ionization and a partial protonation of the protein

Cu2O@PNIPAM core–shell microgels as novel inkjet materials for the preparation of CuO hollow porous nanocubes gas sensing layers

There has been long-standing interest in developing metal oxide-based sensors with high sensitivity, selectivity, fast response and low material consumption. Here we report for the first time the utilization of Cu2O@PNIPAM core–shell microgels with a nanocube-shaped core structure for construction of novel CuO gas sensing layers. The hybrid microgels show significant improvement in colloidal stability as compared to native Cu2O nanocubes. Consequently, a homogeneous thin film of Cu2O@PNIPAM nanoparticles can be engineered in a quite low solid content (1.5 wt%) by inkjet printing of the dispersion at an optimized viscosity and surface tension. Most importantly, thermal treatment of the Cu2O@PNIPAM microgels forms porous CuO nanocubes, which show much faster response to relevant trace NO2 gases than sensors produced from bare Cu2O nanocubes. This outcome is due to the fact that the PNIPAM shell can successfully hinder the aggregation of CuO nanoparticles during pyrolysis, which enables full utilization of the sensor layers and better access of the gas to active sites. These results point out great potential of such an innovative system as gas sensors with low cost, fast response and high sensitivitH. J. gratefully acknowledges financial support of the CSC scholarship. S. P. acknowledges funding from the Community of Madrid under grant number 2016-T1/AMB-1695

Thermodynamische Untersuchung von dendritischem Polyglycerolsulfat in Interaktion mit Proteinen

Here we investigate the interaction between proteins and dendritic polyglycerol sulfate by calorimetry. The thermodynamic parameters of the complexation were measured to reveal the driving forces by varying temperature, ionic strength, and polymer size. Firstly, the binding enthalpy and entropy between human serum albumin and dPGS changed drastically with temperature without evident disturbance of the secondary structure. ITC experiments and MD simulations with implicit water agreed on the binding affinity, which demonstrated that the binding was totally governed by electrostatics, mainly, counterion-release. Thus the binding affinity was stable with temperature accompanied by strong enthalpy-entropy compensation. Secondly, lysozyme with positive net charge showed high binding affinity to dPGS at low salt concentration. The binding number increased with the polymer size, whereas the binding affinity showed only a weak dependence due to similar effective charge densities of different dPGS renormalized by counterion condensation. Here again the binding was driven by electrostatics, mainly by counterion-release and the number of released ions determined by the interface at the protein binding site increased very slightly with the polymer size. The number of released counterions was temperature-independent, thus the corresponding entropy gain increased slightly with temperature. The binding enthalpy was found largely different from the calorimetric enthalpy due to linked equilibria, i.e. buffer ionization and protein protonation, which contributed to the observed overall enthalpy and heat capacity change.In dieser Arbeit wurde die Interaktion zwischen Proteinen und dendritischem poly glycerinsulfat mittels Kalorimetrie untersucht. Die thermodynamischen Eigenschaften der Bindungskomplexe wurden durch Variation der Temperatur, Ionenstärke und Polymergröße bestimmt, um die Triebkräfte zu identifizieren. Dabei ändern sich zunächst Bindungsenthalpie und -entropie von dPGS zu Humanalbumin sehr stark mit der Temperatur ohne sichtbare Störung der Sekundärstruktur. Die mittels ITC bestimmte freie Bindungsenergie stimmt hierbei mit der durch MD Simulation unter Einbezug von Wasser ermittelten öberein. Dies zeigt, dass die Bindung von elektrostatischen Effekten, hauptsächlich von der Freisetzung von Gegenionen, bestimmt wird. Folglich ist die freie Bindungsenergie gegen die Temperatur konstant, begleitet von starken Enthalpie-Entropie Kompensation. Des Weiteren zeigt Lysozym mit positiver Nettoladung eine hohe Bindungsaffinität zu dPGS bei niedrigen Salzkonzentrationen. Die Koordinationszahl steigt mit der Polymergröße, während die freie Bindungsenergie nur eine schwache Abhängigkeit zeigt. Grund hierfür ist die Kondensation der Gegenionen auf den dPGS-Molekülen, die zu eine vergleichbaren Oberflächenladungsdichte bei allen Generationen führt. Auch hier wurde die Bindung durch Elektrostatik dominiert, hauptsächlich durch Freisetzung von Gegenionen und weil die Anzahl freigesetzter Ionen, die durch die Grenzfläche an der Bindungsstelle des Proteins bestimmt wird, sich mit der Polymergröße leicht erhöht. Die Anzahl freigesetzter Gegenionen ist nicht temperaturabhängig, wodurch sich der zugehörige Entropiegewinn mit der Temperatur leicht erhöht. Wegen der gekoppelten Gleichgewichte, d.h. wegen der Ionisierung des Puffers und der Protonierung des Proteins, welche zur beobachteten Gesamtenthalpie und zur Änderung der Wärmekapazität beitragen, weicht die Bindungsenthalpie stark von der kalorimetrischen Enthalpie ab

Cluster Analysis on Locally Asymptotically Self-Similar Processes with Known Number of Clusters

We conduct cluster analysis of a class of locally asymptotically self-similar stochastic processes with finite covariance structures, which includes Brownian motion, fractional Brownian motion, and multifractional Brownian motion as paradigmatic examples. Given the true number of clusters, a new covariance-based dissimilarity measure is introduced, based on which we obtain approximately asymptotically consistent algorithms for clustering locally asymptotically self-similar stochastic processes. In the simulation study, clustering data sampled from fractional and multifractional Brownian motions with distinct Hurst parameters illustrates the approximated asymptotic consistency of the proposed algorithms. Clustering global financial markets’ equity indexes returns and sovereign CDS spreads provides a successful real world application. Implementations in MATLAB of the proposed algorithms and the simulation study are publicly shared in GitHub