1er Escuela de verano
Avances en Simulaciones Computacionales

It is not known how the multidomain Gag protein selects HIV-1’s genomic RNA (gRNA) for packaging into virions, sorting it out from a great excess of cellular mRNA molecules in the cytoplasm of infected cells. Gag interacts with the cell’s plasma membrane, viral gRNA, host’s tRNA and mRNA, as well as with itself and other Gag copies.

Gag is compact when in solution but assumes an extended conformation when assembled within the immature HIV-1 virion: using molecular dynamics simulations, we found two specific sites in Gag that can stabilize its compact state (preventing too-early capsid assembly) and characterized their potential of mean force.

In addition, we discuss a model for the assembly of the HIV-1 virion that couples the kinetics of the single virion nucleation and growth on the plasma membrane with kinetics of Gag synthesis and virion budding. Numerical solution of the associated set of differential equations reproduces the experimentally observed kinetics of cytoplasmic Gag accumulation, virion nucleation on plasma membrane, as well as growth and release in the infected cells. We also predict new effects on the gRNA packaging selectivity of various cellular and viral factors that can be used to test our model experimentally.

Coarse grained simulation approaches provide powerful tools for the prediction of the equilibrium properties of polymeric systems. However, common coarse-grained methodologies fail to capture the dynamics of entangled polymers. In this talk, I will present our efforts to develop a model capable of predicting the equilibrium and non-equilibrium behavior of entangled polymeric materials. We show that this model is capable of reproducing several key aspects of the linear response and rheology of polymer melts at quantitative level.

The great flexibility of the Monte Carlo method and the increase in available computing power position it as one of the most essential tools of the actual physicist. Moreover, we shouldn't forget that mathematical advances in physics can be applied to other areas.

In this talk, the objective is to show how we can fuse these two ideas to generate instruments that help us understand actual problems. I will talk about the development of Mocareps, an epidemiological simulator, and its application to model the actual COVID-19 epidemic.

Nanoparticle (NP) self-assembly in liquid crystals (LCs) depends on the elasticity of the material to form arrays with crystalline symmetry. These arrays can be tuned via the anchoring of the NP, and the orientation of the director field, effectively using the defects around the NP as sites for assembly. Additionally, confinement and hydrodynamic fields can also be used to control the assembly. Scenarios often consider one, two, or three NPs under various flow regimes and in moderate confinement. The simulations presented here use the Stark-Lubensky formalism, where the Landau-de Gennes free energy functional is coupled with the momentum balance through a Poisson-bracket formulation. To describe NP-LC suspensions, a transient three-dimensional Galerkin finite element framework was implemented to achieve a numerical solution. We show that, independent of NP anchoring, defects are displaced in the up-stream direction, ultimately forming a hedgehog defect. The assembly mechanism for a pair of NPs is modified in the large Ericksen regime, where the NPs show an unexpected non-monotonic tendency to aggregate. The modifications to the defect structure and the free energy landscape open a new avenue to the directed assembly of NPs immersed in LC under conditions far from equilibrium.