In parallel with the increase in computational power, coarse-grained (CG) modelling of biomolecules allowed to perform simulations of large biological systems. In CG modelling, one should carefully choose which degrees of freedom can be eliminated without affecting properties of interest. Several coarse-graining levels can be reached depending on how “non-essential” degrees of freedom are treated [1]. Here we describe two approaches used to simplify the representation of biomacromolecules in order to perform large-scale simulations: 1. rigid bodies approximation, 2. “canonical” CG with supra-atomic beads. The first method uses Brownian dynamics to simulate the diffusional motion of macromolecules treated as rigid bodies with atomic details [2]. This method allows to simulate hundreds of macromolecules (~200 nm simulation box) for long timescales (10 μs) and can be used to accurately describe structural and dynamical properties of crowded macromolecular solutions [3]. The method and some applications will be shown. The second approach, “canonical” coarse graining, groups lumps of atoms into supra-atomic beads allowing to preserve the internal flexibility of the macromolecule at the cost of losing atomic details. Simulations here are performed by means of Langevin dynamics. We describe the development and some applications of a coarse-grained (one-bead per residue/base) model [4] that can be applied to proteins and DNA. Some fundamental issues in the coarse-graining process will be discussed in more details, such as the techniques that can be used for the parameterization and the ease of obtaining a CG model for the system of interest [5]. 

References.

1. Riniker, S., Allison, J. R., and Van Gunsteren, W. F. (2012). On developing coarse-grained models for biomolecular simulation: a review. Physical chemistry chemical physics : PCCP, 14(36), 12423–30.
2. Mereghetti, P., Gabdoulline, R. R., & Wade, R. C. (2010). Brownian dynamics simulation of protein solutions: structural and dynamical properties. Biophys. J., 99(11), 3782–91.
3. Mereghetti, P., Martinez, M., & Wade, R. C. (2014). Long range Debye-Hückel correction for computation of grid-based electrostatic forces between biomacromolecules. BMC Biophysics, 7(1), 4.
4. Tozzini, V., & McCammon, J. A. (2005). A coarse grained model for the dynamics of flap opening in HIV- 1 protease. Chemical Physics Letters, 413(1-3)
5. Mereghetti, P., Maccari, G., Spampinato G., Tozzini, V. AsParaGs. (2015). Assisted parameterization platform for coarse-grained models. PLOS comp. Biol. - submitted.