In contrast to ordinary polymers, the vast majority of biological macromolecules adopt highly ordered three-dimensional structures that define their functions. The key to folding of a biopolymer into a unique 3D structure or to assembly of several biopolymers into a functional unit is a delicate balance between the attractive and repulsive forces that also makes such self-assembly reversible under physiological conditions. The all-atom molecular dynamics (MD) method has emerged as a powerful tool for studies of individual biomolecules and their functional assemblies, encompassing systems of ever increasing complexity. However, advances in parallel computing technology have outpaced development of the underlying theoretical models—the molecular force fields, pushing the MD method into untested territory. Recent tests of the MD method have found the most commonly used molecular force fields to be out of balance, overestimating attractive interactions between charged and hydrophobic groups, which can promote artificial aggregation in MD simulations of multi-component protein, nucleic acid, and lipid systems. One route to improving the force fields is through the NBFIX corrections method, in which the intermolecular forces are calibrated against experimentally measured quantities such as osmotic pressure by making atom pair-specific adjustments to the non-bonded interactions. In this article, we review development of the NBFIX corrections to the AMBER and CHARMM force fields and discuss their implications for MD simulations of electrolyte solutions, dense DNA systems, Holliday junctions, protein folding, and lipid bilayer membranes.

Over the past decades, molecular dynamics (MD) simulations of biomolecules have become a mainstream biophysics technique. As the length and time scales amenable to the MD method increase, shortcomings of the empirical force fields, which have been developed and validated using relatively short simulations of small molecules, become apparent. One common artifact is aggregation of water-soluble biomolecules driven by artificially strong charge–charge interactions. Here, we report a systematic atom pair-specific refinement of Lennard-Jones parameters (NBFIX) describing amine–carboxylate and amine–phosphate interactions, which bring MD simulations of basic peptide-mediated nucleic acid assemblies and lipid bilayer membranes into better agreement with experimental data. As our refinement does not affect the existing parametrization of bonded interactions or alter the solvation free energies, it improves the realism of an MD simulation without introducing additional artifacts.

Atomic-scale modeling of compacted nucleic acids has the ability to reveal the inner workings of spectacular biomolecular machines, yet the outcome of such modeling efforts sensitively depends on the accuracy of the underlying computational models. Our molecular dynamics simulations of an array of 64 parallel duplex DNA revealed considerable artifacts of cation−DNA phosphate interactions in CHARMM and AMBER parameter sets: both the DNA arrangement and the pressure inside the DNA arrays were found to be in considerable disagreement with experiment. To improve the models, we fine-tuned van der Waals interaction parameters for specific ion pairs to reproduce experimental osmotic pressure of binary electrolyte solutions of biologically relevant ions. Repeating the DNA array simulations using our parameters produced results consistent with experiment. Our improved parametrization can be directly applied to molecular dynamics simulations of various charged biomolecular systems, including nucleic acids, proteins, and lipid bilayer membranes.