Concentration Dependent Ion–Protein Interaction Patterns Underlying Protein Oligomerization Behaviours

Most proteins do not exist as monomers. Instead, proteins assemble into oligomeric structures, which range from small dimers to intermediately sized clusters to large polymers. Oligomerization is driven by protein–protein interactions between charged residues, (induced) dipoles, aromatic residues and hydrophobic patches. Ionic protein–protein interactions, and thus the oligomeric state of a protein, can be influenced by metal ions. There are several theories that strive to explain interactions between metal ions and charged proteins. Continuum electrostatic theories assume a decaying electrostatic potential from a charged protein surface which attracts oppositely charged ions to the point of charge neutralization, while the water solvent is treated as passive medium characterized only by its permittivity. More recent concepts, however, recognize the importance of water coordination. The hydration enthalpy of metal ions and ionic protein groups is envisaged as the driving force for ion pairing. Research and theory have so far focussed on single protein species in simple aqueous solutions. This work comparatively analyses Ca2+-induced oligomerization of the negatively charged SNAP25 protein in solution and in the crowded multi-component environment of the plasma membrane. It proves ion-induced protein oligomerization to be a fundamental chemico-physical principle that is conserved in both environments. The restricted protein movement and the manifold interactions with other proteins and lipids in the membrane appear to mainly influence the number of monomers comprised in an oligomer, but not the phenomenon of oligomerization itself. Comparison of Ca2+ to other positively charged metal ions indicates that ions need to convey a certain charge density and to possess a certain water affinity to induce membrane protein clustering. The results suggest a direct interaction between calcium ions and negatively charged protein residues. It appears that the stoichiometry of calcium–carboxylate group interactions determines the degree of oligomerization. At low calcium concentrations which induce protein clustering, the ions function as bridges between the carboxylate groups, and attenuate the negative protein charge and thus repulsive protein–protein interactions. At high calcium concentrations, binding of one or more calcium ions to a single negatively charged residue is frequently encountered. The calcium ions thus no longer function as bridges between several carboxylate groups. In addition, the local overcharging entails repulsive forces between proteins which again favour protein dispersion. The study provides a conceptual framework for the influence of ions on electrostatically driven protein–protein interactions and protein aggregation with implications for biological and industrial settings

Data perspective in process choreographies : modeling and execution

Process choreographies - communication between different organizations to exchange information - is part of daily business. While the correct ordering of exchanged messages can be modeled and enacted with current choreography techniques, no approach exists to describe the data perspective for a successful process choreography. In this paper, we describe an entirely model-driven approach for BPMN, the industry standard, to include the data perspective while maintaining control flow aspects by utilizing a recent concept to enact data dependencies in internal processes. This work provides a modeling guideline with the require artifacts and their operational semantics to allow automatic choreography enactment covering data retrieval, transformation, and correlation. We show applicability of our approach by an implementation for the Camunda BPM platform, a java-based process engine, and validate it with the service interaction patterns. Keywords: Process Modeling, Data Modeling, Process Choreographies, Process Enactment, BPMN, SQ

On the Relationships between Decision Management and Performance Measurement

Decision management is of utmost importance for the achievement of strategic and operational goals in any organisational context. Therefore, decisions should be considered as first-class citizens that need to be modelled, analysed, monitored to track their performance, and redesigned if necessary. Up to now, existing literature that studies decisions in the context of business processes has focused on the analysis of the definition of decisions themselves, in terms of accuracy, certainty, consistency, covering and correctness. However, to the best of our knowledge, no prior work exists that analyses the relationship between decisions and performance measurement. This paper identifies and analyses this relationship from three different perspectives, namely: the impact of decisions on process performance, the performance measurement of decisions, and the use of performance indicators in the definition of decisions. Furthermore, we also introduce solutions for the representation of these relationships based, amongst others, on the DMN standard.Ministerio de Economía y Competitividad BELI (TIN2015-70560-R)Junta de Andalucía P12-TIC-1867Junta de Andalucía P10-TIC-590

Phase Transitions of Single Semi-stiff Polymer Chains

We study numerically a lattice model of semiflexible homopolymers with nearest neighbor attraction and energetic preference for straight joints between bonded monomers. For this we use a new algorithm, the "Pruned-Enriched Rosenbluth Method" (PERM). It is very efficient both for relatively open configurations at high temperatures and for compact and frozen-in low-T states. This allows us to study in detail the phase diagram as a function of nn-attraction epsilon and stiffness x. It shows a theta-collapse line with a transition from open coils to molten compact globules (large epsilon) and a freezing transition toward a state with orientational global order (large stiffness x). Qualitatively this is similar to a recently studied mean field theory (Doniach et al. (1996), J. Chem. Phys. 105, 1601), but there are important differences. In contrast to the mean field theory, the theta-temperature increases with stiffness x. The freezing temperature increases even faster, and reaches the theta-line at a finite value of x. For even stiffer chains, the freezing transition takes place directly without the formation of an intermediate globule state. Although being in contrast with mean filed theory, the latter has been conjectured already by Doniach et al. on the basis of low statistics Monte Carlo simulations. Finally, we discuss the relevance of the present model as a very crude model for protein folding.Comment: 11 pages, Latex, 8 figure

A new bond fluctuation method for a polymer undergoing gel electrophoresis

We present a new computational methodology for the investigation of gel electrophoresis of polyelectrolytes. We have developed the method initially to incorporate sliding motion of tight parts of a polymer pulled by an electric field into the bond fluctuation method (BFM). Such motion due to tensile force over distances much larger than the persistent length is realized by non-local movement of a slack monomer at an either end of the tight part. The latter movement is introduced stochastically. This new BFM overcomes the well-known difficulty in the conventional BFM that polymers are trapped by gel fibers in relatively large fields. At the same time it also reproduces properly equilibrium properties of a polymer in a vanishing filed limit. The new BFM thus turns out an efficient computational method to study gel electrophoresis in a wide range of the electric field strength.Comment: 15 pages, 11 figure

Polydisperse star polymer solutions

We analyze the effect of polydispersity in the arm number on the effective interactions, structural correlations and the phase behavior of star polymers in a good solvent. The effective interaction potential between two star polymers with different arm numbers is derived using scaling theory. The resulting expression is tested against monomer-resolved molecular dynamics simulations. We find that the theoretical pair potential is in agreement with the simulation data in a much wider polydispersity range than other proposed potentials. We then use this pair potential as an input in a many-body theory to investigate polydispersity effects on the structural correlations and the phase diagram of dense star polymer solutions. In particular we find that a polydispersity of 10%, which is typical in experimental samples, does not significantly alter previous findings for the phase diagram of monodisperse solutions.Comment: 14 pages, 7 figure

A New Monte Carlo Algorithm for Protein Folding

We demonstrate that the recently proposed pruned-enriched Rosenbluth method (P. Grassberger, Phys. Rev. E 56 (1997) 3682) leads to extremely efficient algorithms for the folding of simple model proteins. We test them on several models for lattice heteropolymers, and compare to published Monte Carlo studies. In all cases our algorithms are faster than all previous ones, and in several cases we find new minimal energy states. In addition to ground states, our algorithms give estimates for the partition sum at finite temperatures.Comment: 4 pages, Latex incl. 3 eps-figs., submitted to Phys. Rev. Lett., revised version with changes in the tex

Scaling of Star Polymers with one to 80 Arms

We present large statistics simulations of 3-dimensional star polymers with up to $f=80$ arms, and with up to 4000 monomers per arm for small values of $f$. They were done for the Domb-Joyce model on the simple cubic lattice. This is a model with soft core exclusion which allows multiple occupancy of sites but punishes each same-site pair of monomers with a Boltzmann factor $v<1$. We use this to allow all arms to be attached at the central site, and we use the `magic' value $v=0.6$ to minimize corrections to scaling. The simulations are made with a very efficient chain growth algorithm with resampling, PERM, modified to allow simultaneous growth of all arms. This allows us to measure not only the swelling (as observed from the center-to-end distances), but also the partition sum. The latter gives very precise estimates of the critical exponents $\gamma_f$. For completeness we made also extensive simulations of linear (unbranched) polymers which give the best estimates for the exponent $\gamma$.Comment: 7 pages, 7 figure

A review of Monte Carlo simulations of polymers with PERM

In this review, we describe applications of the pruned-enriched Rosenbluth method (PERM), a sequential Monte Carlo algorithm with resampling, to various problems in polymer physics. PERM produces samples according to any given prescribed weight distribution, by growing configurations step by step with controlled bias, and correcting "bad" configurations by "population control". The latter is implemented, in contrast to other population based algorithms like e.g. genetic algorithms, by depth-first recursion which avoids storing all members of the population at the same time in computer memory. The problems we discuss all concern single polymers (with one exception), but under various conditions: Homopolymers in good solvents and at the $\Theta$ point, semi-stiff polymers, polymers in confining geometries, stretched polymers undergoing a forced globule-linear transition, star polymers, bottle brushes, lattice animals as a model for randomly branched polymers, DNA melting, and finally -- as the only system at low temperatures, lattice heteropolymers as simple models for protein folding. PERM is for some of these problems the method of choice, but it can also fail. We discuss how to recognize when a result is reliable, and we discuss also some types of bias that can be crucial in guiding the growth into the right directions.Comment: 29 pages, 26 figures, to be published in J. Stat. Phys. (2011