The B-form of DNA can populate two different backbone conformations: BI and BII, defined by the difference between the torsion angles ε and ζ (BI = ε-ζ < 0 and BII = ε-ζ > 0). BI is the most populated state, but the population of the BII state, which is sequence dependent, is significant and accumulating evidence shows that BII affects the overall structure of DNA, and thus influences protein-DNA recognition. This work presents a reparametrization of the CHARMM27 additive nucleic acid force field to increase the sampling of the BII form in MD simulations of DNA. In addition, minor modifications of sugar puckering were introduced to facilitate sampling of the A form of DNA under the appropriate environmental conditions. Parameter optimization was guided by quantum mechanical data on model compounds, followed by calculations on several DNA duplexes in the condensed phase. The selected optimized parameters were then validated against a number of DNA duplexes, with the most extensive tests performed on the EcoRI dodecamer, including comparative calculations using the Amber Parm99bsc0 force field. The new CHARMM model better reproduces experimentally observed sampling of the BII conformation, including sampling as a function of sequence. In addition, the model reproduces the A form of the 1ZF1 duplex in 75 % ethanol, and yields a stable Z-DNA conformation of duplex (GTACGTAC) in its crystal environment. The resulting model, in combination with a recent reoptimization of the CHARMM27 force field for RNA, will be referred to as CHARMM36.

Protein-protein interactions are at the heart of regulatory and signaling processes in the cell. In many interactions, one or both proteins are disordered before association. However, this disorder in the unbound state does not prevent many of these proteins folding to a well-defined, ordered structure in the bound state. Here we examine a typical system, where a small disordered protein (PUMA, p53 upregulated modulator of apoptosis) folds to an α-helix when bound to a groove on the surface of a folded protein (MCL-1, induced myeloid leukemia cell differentiation protein). We follow the association of these proteins using rapid-mixing stopped flow, and examine how the kinetic behavior is perturbed by denaturant and carefully chosen mutations. We demonstrate the utility of methods developed for the study of monomeric protein folding, including β-Tanford values, Leffler α, Φ-value analysis, and coarse-grained simulations, and propose a self-consistent mechanism for binding. Folding of the disordered protein before binding does not appear to be required and few, if any, specific interactions are required to commit to association. The majority of PUMA folding occurs after the transition state, in the presence of MCL-1. We also examine the role of the side chains of folded MCL-1 that make up the binding groove and find that many favor equilibrium binding but, surprisingly, inhibit the association process.Protein folding | stopped flow | coarse-grained simulation | protein-protein interactions | BCL-2

Lennard-Jones (LJ) parameters for a variety of model compounds have previously been optimized within the CHARMM Drude polarizable force field to reproduce accurately pure liquid phase thermodynamic properties as well as additional target data. While the polarizable force field resulting from this optimization procedure has been shown to satisfactorily reproduce a wide range of experimental reference data across numerous series of small molecules, a slight but systematic overestimate of the hydration free energies has also been noted. Here, the reproduction of experimental hydration free energies is greatly improved by the introduction of pair-specific LJ parameters between solute heavy atoms and water oxygen atoms that override the standard LJ parameters obtained from combining rules. The changes are small and a systematic protocol is developed for the optimization of pair-specific LJ parameters and applied to the development of pair-specific LJ parameters for alkanes, alcohols and ethers. The resulting parameters not only yield hydration free energies in good agreement with experimental values, but also provide a framework upon which other pair-specific LJ parameters can be added as new compounds are parametrized within the CHARMM Drude polarizable force field. Detailed analysis of the contributions to the hydration free energies reveals that the dispersion interaction is the main source of the systematic errors in the hydration free energies. This information suggests that the systematic error may result from problems with the LJ combining rules and is combined with analysis of the pair-specific LJ parameters obtained in this work to identify a preliminary improved combining rule.

Molecular dynamics simulations are well established for the study of biomolecular systems. Within these simulations, energy functions known as force fields are used to determine the forces acting on atoms and molecules. While these force fields have been very successful, they contain a number of approximations, included to overcome limitations in computing power. One of the most important of these approximations is the omission of polarizability, the process by which the charge distribution in a molecule changes in response to its environment. Since polarizability is known to be important in many biochemical situations, and since advances in computer hardware have reduced the need for approximations within force fields, there is major interest in the use of force fields that include an explicit representation of polarizability. As such, a number of polarizable force fields have been under development: these have been largely experimental, and their use restricted to specialized researchers. This situation is now changing. Parameters for fully optimized polarizable force fields are being published, and associated code incorporated into standard simulation software. Simulations on the hundred-nanosecond timescale are being reported, and are now within reach of all simulation scientists. In this overview, I examine the polarizable force fields available for the simulation of biomolecules, the systems to which they have been applied, and the benefits and challenges that polarizability can bring. In considering future directions for development of polarizable force fields, I examine lessons learnt from non-polarizable force fields, and highlight issues that remain to be addressed.