MOLECULAR DYNAMICS SIMULATIONS OF BIOMOLECULES: Long-Range Electrostatic Effects

Abstract

Current computer simulations of biomolecules typically make use of classical molecular dynamics methods, as a very large number (tens to hundreds of thousands) of atoms are involved over timescales of many nanoseconds. The methodology for treating short-range bonded and van der Waals interactions has matured. However, long-range electrostatic interactions still represent a bottleneck in simulations. In this article, we introduce the basic issues for an accurate representation of the relevant electrostatic interactions. In spite of the huge computational time demanded by most biomolecular systems, it is no longer necessary to resort to uncontrolled approximations such as the use of cutoffs. In particular, we discuss the Ewald summation methods, the fast particle mesh methods, and the fast multipole methods. We also review recent efforts to understand the role of boundary conditions in systems with long-range interactions, and conclude with a short perspective on future trends.

Computational Methods for Biomolecular Electrostatics

“…Popular methods for understanding electrostatic interactions in these systems can be loosely classified into two categories (see Fig. 1): explicit solvent methods (Burkert and Allinger, 1982;Jorgensen et al, 1983;Sagui and Darden, 1999;Ponder and Case, 2003;Horn et al, 2004), which treat the solvent in full atomic detail, and implicit solvent methods (Davis and McCammon, 1990b;Honig and Nicholls, 1995;Roux and Simonson, 1999;Baker, 2005b;Baker et al, 2006), which represent the solvent through its average effect on solute.…”

Systematic comparison of force fields for microscopic simulations of NaCl in aqueous solutions: Diffusion, free energy of hydration, and structural properties

“…In the past, there has been much work to include the effects of Coulombic interactions [5,6,7,8,9,10,11,12] without performing the computationally costly Ewald summations. Present day computational resources allow one to treat electrostatics properly [13] and in, e.g., the case of lipid bilayers, this is a very important matter [14].…”

Effect of computational methodology on the conformational dynamics of the protein photosensor LOV1 from Chlamydomonas reinhardtii

“…a short-ranged part that sums quickly in real space and a long-ranged part that sums quickly in Fourier space, in addition to a constant self-energy correction contribution. The particle mesh-based approaches [27] all attempt to accelerate the solution of Poisson's equation under periodic boundary conditions using the advantages of the fast Fourier transform for calculating discrete Fourier transforms. However, they differ in how they transform the continuous charge density, due to the sum of compensating Gaussians, onto a regular three-dimensional grid and in how they compensate for the loss of accuracy introduced in this process.…”

“…Although LS and RF methods rely on more or less reasonable approximations for dealing with the long-range component of the electrostatic interactions, some dependence of the calculated properties on the cutoff distance or system size has also been evidenced for these methods [25,26,[48][49][50][51][52]. Moreover, it has been stated in several works that the long-range periodicity of the Ewald boundary conditions can artificially stabilize local equilibrium structures of peptides and small proteins by inhibiting conformational fluctuations [27]. For example, Lins and Röthlisberger [24] performed a series of MD simulations to investigate the influence of the long-range electrostatics on the folding of the N-terminal H4-histone tail peptide.…”

“…The importance of electrostatics on influencing peptide or small protein conformations has been demonstrated in several recent computer simulation studies. For example, the commonly used particle-mesh Ewald (PME) technique has been suspected to lead to a structural stabilization of the secondary structure [24][25][26][27], whereas the computationally cheap cutoff techniques have been found to result in a structural destabilization [28,29]. Here we will test the reliability of these methods for treating large heterogeneous protein systems, typically containing a multitude of different length and time scales [30].…”