Electrostatic-Consistent Coarse-Grained Potentials for Molecular Simulations of Proteins.

We present a new generation of coarse-grained (CG) potentials that account for a simplified electrostatic description of soluble proteins. The treatment of permanent electrostatic dipoles of the backbone and polar side-chains allows to simulate proteins, preserving an excellent structural and dynamic agreement with respective reference structures and all-atom molecular dynamics simulations. Moreover, multiprotein complexes can be well described maintaining their molecular interfaces thanks to the ability of this scheme to better describe the actual electrostatics at a CG level of resolution.

Combining cellular automata and Lattice Boltzmann method to model multiscale avascular tumor growth coupled with nutrient diffusion and immune competition.

In the last decades the Lattice Boltzmann method (LB) has been successfully used to simulate a variety of processes. The LB model describes the microscopic processes occurring at the cellular level and the macroscopic processes occurring at the continuum level with a unique function, the probability distribution function. Recently, it has been tried to couple deterministic approaches with probabilistic cellular automata (probabilistic CA) methods with the aim to model temporal evolution of tumor growths and three dimensional spatial evolution, obtaining hybrid methodologies.

Metal flux through consuming interfaces in ligand mixtures: boundary conditions do not influence the lability and relative contributions of metal species.

In a mixture of metal ions and complexes, it is difficult to predict ecological risk without understanding the contribution of each metal species to biouptake. For microorganisms, the rate of uptake (internalization flux) has not only a major influence on the total metal flux but also on the bioavailability of the various metal species and their relative contributions to the total flux. In this paper, the microorganism is considered as a consuming interface, which interacts with the metal ion, M, via the Michaelis-Menten boundary conditions.

ImmunoGrid: towards agent-based simulations of the human immune system at a natural scale.

The ultimate aim of the EU-funded ImmunoGrid project is to develop a natural-scale model of the human immune system-that is, one that reflects both the diversity and the relative proportions of the molecules and cells that comprise it-together with the grid infrastructure necessary to apply this model to specific applications in the field of immunology. These objectives present the ImmunoGrid Consortium with formidable challenges in terms of complexity of the immune system, our partial understanding about how the immune system works, the lack of reliable data and the scale of computational resources required. In this paper, we explain the key challenges and the approaches adopted to overcome them.

A Nonradial Coarse-Grained Potential for Proteins Produces Naturally Stable Secondary Structure Elements.

We introduce a nonradial potential term for coarse-grained (CG) molecular simulations of proteins. This term mimics the backbone dipole-dipole interactions and accounts for the needed directionality to form stable folded secondary structure elements. We show that α-helical and β-sheet peptide chains are correctly described in dynamics without the need of introducing any a priori bias potentials or ad hoc parametrizations, which limit broader applicability of CG simulations for proteins.

ImmunoGrid, an integrative environment for large-scale simulation of the immune system for vaccine discovery, design and optimization.

Vaccine research is a combinatorial science requiring computational analysis of vaccine components, formulations and optimization. We have developed a framework that combines computational tools for the study of immune function and vaccine development. This framework, named ImmunoGrid combines conceptual models of the immune system, models of antigen processing and presentation, system-level models of the immune system, Grid computing, and database technology to facilitate discovery, formulation and optimization of vaccines.

Metal flux and dynamic speciation at (bio)interfaces. Part IV: MHEDYN, a general code for metal flux computation; application to particulate complexants and their mixtures with the other natural ligands.

Metal flux at consuming interfaces (e.g., sensors or microorganisms) is simulated in environmental multiligand systems using a new numerical code, MHEDYN (Multispecies HEterogeneous DYNamics), based on the lattice Boltzmann method.

Metal flux and dynamic speciation at (bio)interfaces. Part III: MHEDYN, a general code for metal flux computation; application to simple and fulvic complexants.

Metal flux at consuming interfaces (e.g., sensors or microorganisms) is simulated in environmental multiligand systems using a new numerical code, MHEDYN (Multispecies HEterogeneous DYNamics), based on the lattice Boltzmann method.

Metal flux and dynamic speciation at (bio)interfaces. Part II: Evaluation and compilation of physicochemical parameters for complexes with particles and aggregates.

The computation of metal flux in aquatic systems at consuming surfaces like organism membranes must consider the diffusion processes of metal ions, ligands, and complex species, as well as the kinetic and thermodynamic aspects of their chemical interactions. Many natural ligands, however, have complicated properties (formation of successive complexes for simple ligands, polyelectrolytic properties and chemical heterogeneity for macromolecular ligands, large size distribution and fractal structure for suspended aggregates). These properties should be properly modeled to get the correct values of the chemical rate constants and diffusion coefficients required for flux computations.

Two grid refinement methods in the lattice Boltzmann framework for reaction-diffusion processes in complex systems.

This paper studies the optimisation of a numerical model and a computer code to solve numerically reaction-diffusion processes in environmental or biological systems with complicated geometries and mixtures of reactions including time and spatial scales extending over several order of magnitude. In particular, we consider different grid refinement techniques in the framework of a lattice Boltzmann solver for reaction-diffusion systems. Two new grid refinement methods are proposed, which are both quantitatively good.

LBGK method coupled to time splitting technique for solving reaction-diffusion processes in complex systems.

A new approach to numerically solve a reaction-diffusion system is given, specifically developed for complex systems including many reacting/diffusing species with broad ranges of rate constants and diffusion coefficients, as well as complicated geometry of reacting interfaces. The approach combines a Lattice Boltzmann (LB) method with a splitting time technique. In the present work, the proposed approach is tested by focusing on the typical reaction process between a metal ion M and a ligand L, to form a complex ML with M being consumed at an electrode.