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We develop a multi-scale approach to simulate hydrated nanobio systems under realistic condi- tions (e.g., nanoparticles and protein solutions at physiological conditions over time-scales up to hours). We combine atomistic simulations of water at bio-interfaces (e.g., proteins or membranes) and nano-interfaces (e.g., nanoparticles or graphene sheets) and coarse-grain models of hydration water for protein folding and protein design. We study protein self-assembly and crystallization, in bulk or under confinement, and the kinetics of protein adsorption onto nanoparticles, verify- ing our predictions in collaboration with several experimental groups. We try to find answers for fundamental questions (Why water is so important for life? Which properties make water unique for biological processes?) and applications (Can we design better drugs? Can we limit protein- aggregations causing Alzheimer? How to implement nanotheranostic?). Here we focus only on the two larger scales of our approach: (i) The coarse-grain description of hydrated proteins and protein folding at sub-nanometric length-scale and milliseconds-to-seconds time-scales, and (ii) the coarse-grain modeling of protein self-assembly on nanoparticles at 10-to-100 nm length-scale and seconds-to-hours time-scales.
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Water plays a fundamental role in protein stability. However, the effect of the properties of water on the behaviour of proteins is only partially understood. Several theories have been proposed to give insight into the mechanisms of cold and pressure denaturation, or the limits of temperature and pressure above which no protein has a stable, functional state, or how unfolding and aggregation are related. Here we review our results based on a theoretical approach that can rationalise the water contribution to protein solutions free energy. We show, using Monte Carlo simulations, how we can rationalise experimental data with our recent results. We discuss how our findings can help develop new strategies for the design of novel synthetic biopolymers or possible approaches for mitigating neurodegenerative pathologies.
Protein aggregation in the form of amyloid fibrils has important biological and technological implications. Although the self-assembly process is highly efficient, aggregates not in the fibrillar form would also occur and it is important to include these disordered species when discussing the thermodynamic equilibrium behavior of the system. Here, we initiate such a task by considering a mixture of monomeric proteins and the corresponding aggregates in the disordered form (micelles) and in the fibrillar form (amyloid fibrils). Starting with a model on the respective binding free energies for these species, we calculate their concentrations at thermal equilibrium. We then discuss how the incorporation of the disordered structure furthers our understanding on the various amyloid promoting factors observed empirically, and on the kinetics of fibrilization.
We argue that the first order folding transitions of proteins observed at physiological chemical conditions end in a critical point for a given temperature and chemical potential of the surrounding water. We investigate this critical point using a hierarchical Hamiltonian and determine its universality class. This class differs qualitatively from those of other known models.
In this review we discuss recent advances in the self-assembly of self-propelled colloidal particles and highlight some of the most exciting results in this field with a specific focus on dry active matter. We explore this phenomenology through the lens of the complexity of the colloidal building blocks. We begin by considering the behavior of isotropic spherical particles. We then discuss the case of amphiphilic and dipolar Janus particles. Finally, we show how the geometry of the colloids and/or the directionality of their interactions can be used to control the physical properties of the assembled active aggregates, and suggest possible strategies on how to exploit activity as a tunable driving force for self-assembly. The unique properties of active colloids lend promise for the design of the next generation of functional, environment-sensing microstructures able to perform specific tasks in an autonomous and targeted manner.
Starting from a microscopic lattice model, we investigate clustering, micellization and micelle ordering in semi-dilute solutions of AB diblock copolymers in a selective solvent. To bridge the gap in length scales, from monomers to ordered micellar structures, we implement a two-step coarse graining strategy, whereby the AB copolymers are mapped onto ``ultrasoft dumbells with monomer-averaged effective interactions between the centres of mass of the blocks. Monte Carlo simulations of this coarse-grained model yield clear-cut evidence for self-assembly into micelles with a mean aggregation number n of roughly 100 beyond a critical concentration. At a slightly higher concentration the micelles spontaneously undergo a disorder-order transition to a cubic phase. We determine the effective potential between these micelles from first principles.
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