Rui D. M. Travasso

The folding of knotted proteins: insights from lattice simulations.

We carry out systematic Monte Carlo simulations of Gō lattice proteins to investigate and compare the folding processes of two model proteins whose native structures differ from each other due to the presence of a trefoil knot located near the terminus of one of the protein chains. We show that the folding time of the knotted fold is larger than that of the unknotted protein and that this difference in folding time is particularly striking in the temperature region below the optimal folding temperature. Both proteins display similar folding transition temperatures, which is indicative of similar thermal stabilities. By using the folding probability reaction coordinate as an estimator of folding progression we have found out that the formation of the knot is mainly a late folding event in our shallow knot system.

Non-native interactions play an effective role in protein folding dynamics

Systematic Monte Carlo simulations of simple lattice models show that the final stage of protein folding is an ordered process where native contacts get locked (i.e., the residues come into contact and remain in contact for the duration of the folding process) in a well‐defined order. The detailed study of the folding dynamics of protein‐like sequences designed as to exhibit different contact energy distributions, as well as different degrees of sequence optimization (i.e., participation of non‐native interactions in the folding process), reveals significant differences in the corresponding locking scenarios—the collection of native contacts and their average locking times, which are largely ascribable to the dynamics of non‐native contacts. Furthermore, strong evidence for a positive role played by non‐native contacts at an early folding stage was also found. Interestingly, for topologically simple target structures, a positive interplay between native and non‐native contacts is observed also toward the end of the folding process, suggesting that non‐native contacts may indeed affect the overall folding process. For target models exhibiting clear two‐state kinetics, the relation between the nucleation mechanism of folding and the locking scenario is investigated. Our results suggest that the stabilization of the folding transition state can be achieved through the establishment of a very small network of native contacts that are the first to lock during the folding process.

Glassy behavior in a ferromagnetic p -spin model

Recent work has suggested the existence of glassy behavior in a ferromagnetic model with a four-spin interaction. Motivated by these findings, we have studied the dynamics of this model using Monte Carlo simulations with particular attention being paid to two-time quantities. We find that the system shares many features in common with glass forming liquids. In particular, the model exhibits: (i) a very long-lived metastable state, (ii) autocorrelation functions that show stretched exponential relaxation, (iii) a non-equilibrium timescale that appears to diverge at a well defined temperature, and (iv) low temperature aging behaviour characteristic of glasses.

Localized redox relays as a privileged mode of cytoplasmic hydrogen peroxide signaling

Hydrogen peroxide (H2O2) is a key signaling agent. Its best characterized signaling actions in mammalian cells involve the early oxidation of thiols in cytoplasmic phosphatases, kinases and transcription factors. However, these redox targets are orders of magnitude less H2O2-reactive and abundant than cytoplasmic peroxiredoxins. How can they be oxidized in a signaling time frame? Here we investigate this question using computational reaction-diffusion models of H2O2 signaling. The results show that at H2O2 supply rates commensurate with mitogenic signaling a H2O2 concentration gradient with a length scale of a few tenths of μm is established. Even near the supply sites H2O2 concentrations are far too low to oxidize typical targets in an early mitogenic signaling time frame. Furthermore, any inhibition of the peroxiredoxin or increase in H2O2 supply able to drastically increase the local H2O2 concentration would collapse the concentration gradient and/or cause an extensive oxidation of the peroxiredoxins I and II, inconsistent with experimental observations. In turn, the local concentrations of peroxiredoxin sulfenate and disulfide forms exceed those of H2O2 by several orders of magnitude. Redox targets reacting with these forms at rate constants much lower than that for, say, thioredoxin could be oxidized within seconds. Moreover, the spatial distribution of the concentrations of these peroxiredoxin forms allows them to reach targets within 1 μm from the H2O2 sites while maintaining signaling localized. The recruitment of peroxiredoxins to specific sites such as caveolae can dramatically increase the local concentrations of the sulfenic and disulfide forms, thus further helping these species to outcompete H2O2 for the oxidation of redox targets. Altogether, these results suggest that H2O2 signaling is mediated by localized redox relays whereby peroxiredoxins are oxidized to sulfenate and disulfide forms at H2O2 supply sites and these forms in turn oxidize the redox targets near these sites.

The phase-field model in tumor growth

Tumor growth is becoming a central problem in biophysics both from its social and medical interest and, more fundamentally, because it is a remarkable example of an emergent complex system. Focusing on the description of the spatial and dynamical features of tumor growth, in this paper we review recent tumor modeling approaches using a technique borrowed from materials science: the phase-field models. These models allow us, with a large degree of generality, to identify the paramount mechanisms causing the uncontrolled growth of tumor cells as well as to propose new guidelines for experimentation both in simulation and in the laboratory. We finish by discussing open directions of research in phase-field modeling of tumor growth to catalyze the interest of physicists and mathematicians in this emergent field.

Why Do Protein Folding Rates Correlate with Metrics of Native Topology

For almost 15 years, the experimental correlation between protein folding rates and the contact order parameter has been under scrutiny. Here, we use a simple simulation model combined with a native-centric interaction potential to investigate the physical roots of this empirical observation. We simulate a large set of circular permutants, thus eliminating dependencies of the folding rate on other protein properties (e.g. stability). We show that the rate-contact order correlation is a consequence of the fact that, in high contact order structures, the contact order of the transition state ensemble closely mirrors the contact order of the native state. This happens because, in these structures, the native topology is represented in the transition state through the formation of a network of tertiary interactions that are distinctively long-ranged.

Modeling the morphology and mechanical properties of sheared ternary mixtures.

Through a combination of simulation techniques, we determine both the structural evolution and mechanical properties of blends formed from immiscible ternary mixtures. In this approach, we first use the lattice Boltzmann method to simulate the phase separation dynamics of A/B/C fluid mixtures for varying compositions within the spinodal region. We also investigate the effect of an imposed shear on the phase ordering of the mixture. We assume that the fluid is quenched sufficiently rapidly that the phase-separated structure is preserved in the resultant solid. Then, the output from our morphological studies serves as the input to the lattice spring model, which is used to simulate the elastic response of solids to an applied deformation. These simulations reveal how the local stress and strain fields and the global Youngs modulus depend on the composition of the blend and the stiffness of the components. By comparing the results for the sheared and unsheared cases, we can isolate optimal processing conditions for enhancing the mechanical performance of the blends. Overall, the findings provide fundamental insight into the relationship between structure, processing, and properties for heterogeneous materials and can yield guidelines for formulating blends with the desired macroscopic mechanical behavior.

Phase-field simulations: Materials Science meets Biology and Medicine

The phase-field has become established as one of the most important methods for examining the development of non-equilibrium microstructures. It permits an elegant and multifaceted description of complex nonlinear problems with moving boundaries, which are otherwise hard to model. It is particularly well suited to model systems where different phases coexist, being able to describe quantitatively the dynamics as a function of the mechanical properties of each phase. Originally developed to examine the dynamics of various phase transition processes such as spinodal decomposition, order-disorder transitions, as well as melting and solidification processes, the phase-field method has now become capable of contributing to entirely new fields such as fracture dynamics, directed solidification or microfluidics, as well as being able to describe and predict different properties in composite materials, shapes and dynamics of vesicles or ordered nanoscopic patterning. It has become in the last years an important bridge between different fields, bringing people together, leading to a new way of approaching problems and prompting a rapid development of many aspects in Materials Science. The various phase-field models developed so far have matured sufficiently to allow their use in realistic applications with a high degree of success. The advances in programming in the last few years have been so rapid that there are now commercial packages available on the market for industrial applications using phase-field. The phase-field and other such techniques devised in the context of Materials Science, are now ripe to be used in different and maybe more complex systems. There is currently an increasing interest in biologically related problems, proven by the high amount of works devoted to these issues in the recent literature. Clearly, the analysis of many Biological problems should be tightly coupled with the development of new applications of Materials Science methods. This is particularly striking in problems of growth (e.g. cancer, embryogenesis) where the evolution of tensions between different tissues relates to cell differentiation, thus influencing the mechanical properties and growth of a particular tissue. It is then required to transfer Materials Science methods to address Biological and Medical problems. In this new interdisciplinary framework, techniques such as phase-field modelling can have important contributions in the field of Biological modelling. This transfer process is already starting, and in particular phase-field methods are currently becoming highly successful in describing the equilibrium and dynamics of biological materials. A current example is the dynamics of biological vesicles, in aqueous solutions. Phase-field methods were used in the modelling of such structures in shear flows as a function of the hematocrit value, which is connected with a

The protein folding transition state: Insights from kinetics and thermodynamics

We perform extensive lattice Monte Carlo simulations of protein folding to construct and compare the equilibrium and the kinetic transition state ensembles of a model protein that folds to the native state with two-state kinetics. The kinetic definition of the transition state is based on the folding probability analysis method, and therefore on the selection of conformations with 0.4<P(fold)<0.6, while for the equilibrium characterization we consider conformations for which the evaluated values of several reaction coordinates correspond to the maximum of the free energy measured as a function of those reaction coordinates. Our results reveal a high degree of structural similarity between the ensembles determined by the two methods. However, the folding probability distribution of the conformations belonging to our definition of the equilibrium transition state (0.2<P(fold)<0.8) is broader than that displayed by the kinetic transition state.

Pathways to folding, nucleation events, and native geometry

We perform extensive Monte Carlo simulations of a lattice model and the Gō potential [N. Gō and H. Taketomi, Proc. Natl. Acad. Sci. U.S.A. 75, 559563 (1978)] to investigate the existence of folding pathways at the level of contact cluster formation for two native structures with markedly different geometries. Our analysis of folding pathways revealed a common underlying folding mechanism, based on nucleation phenomena, for both protein models. However, folding to the more complex geometry (i.e., that with more nonlocal contacts) is driven by a folding nucleus whose geometric traits more closely resemble those of the native fold. For this geometry folding is clearly a more cooperative process.