Thermodynamic measurements of the solvation of salts and electrolytes are relatively straightforward, but it is not possible to separate total solvation free energies into distinct cation and anion contributions without reference to an additional extrathermodynamic assumption. The present work attempts to resolve this difficulty using molecular dynamics simulations with the AMOEBA polarizable force field and perturbation techniques to directly compute absolute solvation free energies for potassium, sodium, and chloride ions in liquid water and formamide. Corresponding calculations are also performed with two widely used nonpolarizable force fields. The simulations with the polarizable force field accurately reproduce in vacuo quantum mechanical results, experimental ion-cluster solvation enthalpies, and experimental solvation free energies for whole salts, while the other force fields do not. The results indicate that calculations with a polarizable force field can capture the thermodynamics of ion solvation and that the solvation free energies of the individual ions differ by several kilocalories from commonly cited values.

Growing computing capacity and algorithmic advances have facilitated the study of increasingly large biomolecular systems at longer timescales. However, with these larger, more complex systems come questions about the quality of sampling and statistical convergence. What size systems can be sampled fully? If a system is not fully sampled, can certain “fast variables” be considered well-converged? How can one determine the statistical significance of observed results? The present review describes statistical tools and the underlying physical ideas necessary to address these questions. Basic definitions and ready-to-use analyses are provided, along with explicit recommendations. Such statistical analyses are of paramount importance in establishing the reliability of simulation data in any given study.

The alkaline earth metals calcium and magnesium are critically involved in many biomolecular processes. To understand the hydration thermodynamics of these ions, we have performed molecular dynamics simulations using a polarizable potential. Particle-mesh Ewald for point multipoles has been applied to the calculation of electrostatic interactions. The parameters in this model have been determined from an ab initio quantum mechanical calculation of dimer interactions between ions and water. Two methods for ion solvation free energy calculation, free energy perturbation, and the Bennett acceptance ratio have been compared. Both predict results consistent with other theoretical estimations while the Bennett approach leads to a much smaller statistical error. Based on the Born theory and the ion-oxygen radial distribution functions, we estimate the effective size of the ions in solution, concluding that K(+) > Na(+) congruent with Ca(2+) > Mg(2+). There appears to be much stronger perturbation in water structure, dynamics, and dipole moment around the divalent cations than the monovalent K(+) and Na(+). The average water coordination numbers for Ca(2+) and Mg(2+) are 7.3 and 6, respectively. The lifetime of water molecules in the first solvation shell of Mg(2+) is on the order of hundreds of picoseconds, in contrast to only few picoseconds for Ca(2+), K(+), or Na(+).

Rhodopsin, the G protein-coupled receptor primarily responsible for sensing light, is found in an environment rich in polyunsaturated lipid chains and cholesterol. Biophysical experiments have shown that lipid unsaturation and cholesterol both have significant effects on rhodopsin's stability and function; -3 polyunsaturated chains, such as docosahexaenoic acid (DHA), destabilize rhodopsin and enhance the kinetics of the photocycle, whereas cholesterol has the opposite effect. Here, we use molecular dynamics simulations to investigate the possibility that polyunsaturated chains modulate rhodopsin stability and kinetics via specific direct interactions. By analyzing the results of 26 independent 100-ns simulations of dark-adapted rhodopsin, we found that DHA routinely forms tight associations with the protein in a small number of specific locations qualitatively different from the nonspecific interactions made by saturated chains and cholesterol. Furthermore, the presence of tightly packed DHA molecules tends to weaken the interhelical packing. These results are consistent with recent NMR work, which proposes that rhodopsin binds DHA, and they suggest a molecular rationale for DHA's effects on rhodopsin stability and kinetics.cholesterol ͉ molecular dynamics ͉ fatty acid ͉ protein-lipid interactions R hodopsin, the primary light receptor in the visual system, is an integral membrane protein belonging to the G proteincoupled receptor (GPCR) superfamily. GPCRs, the largest known protein superfamily, are critically important in a wide variety of biological signaling processes (1). As a result, half of all current drug targets belong to this family (2). Moreover, rhodopsin is the only GPCR whose structure is known to atomic resolution (3-7), making it important both in its own right and as a template for understanding GPCR function in general (1,8).Rhodopsin is found in the rod outer-disk membranes in the photoreceptor cells of vertebrates and invertebrates (9). These membranes are highly enriched in -3 polyunsaturated fatty acids (10, 11); the cholesterol content is very high in newly formed disk membranes and drops as they mature (12). The presence of lipids with polyunsaturated chains destabilizes the native state of rhodopsin and speeds the kinetics of the photocycle (13, 14), whereas cholesterol stabilizes rhodopsin and slows its kinetics (13-15). Although these experiments deepen our understanding, the molecular-level details of how the membrane environment modulates rhodopsin's structure and function are unknown.Molecular dynamics simulations can be a powerful tool to advance our understanding of protein-lipid biophysics. In recent years, a number of groups have published simulations of rhodopsin in monounsaturated (16-19) and polyunsaturated membranes (20, 21). Recent work from our group focused on the interactions between polyunsaturated lipids, cholesterol, and rhodopsin (20). In that work, we observed two docosahexaenoic acid (DHA) chains forming contacts deep in the protein interior, suggesting that DHA's...

The cannabinoid receptors belong to the class A (rhodopsin family) of G protein-coupled receptors (GPCRs).2 The second cannabinoid receptor subtype, CB2 (2), is highly expressed throughout the immune system (3, 4) and has been described in the central nervous system under both pathological (5) and physiological conditions (6). All known CB2 ligands are highly lipophilic. In fact, the CB2 endogenous cannabinoid, sn-2-arachidonoylglycerol (2-AG) (7,8), is synthesized on demand from the lipid bilayer itself in a two-step process in which phospholipase C-␤ hydrolyzes phosphatidylinositol 4,5-bisphosphate to generate diacylglycerol, which is then hydrolyzed by diacylglycerol lipase to yield 2-AG (9, 10). After 2-AG interaction with the membraneembedded CB receptor, it is hydrolyzed to arachidonic acid and glycerol by a membrane-associated enzyme, monoacylglycerol lipase (11). As revealed by the crystal structures of rhodopsin (12-15), the ␤ 2 -adrenergic receptor (AR) (16 -18), ␤ 1 -AR (19), and adenosine A2A receptor (20), the general topology of a GPCR includes the following: 1) an extracellular (EC) N terminus; 2) seven transmembrane ␣-helices (TMHs) arranged to form a closed bundle; 3) loops connecting TMHs that extend intra-and extracellularly; and 4) an intracellular (IC) C terminus that begins with a short helical segment (helix 8) oriented parallel to the membrane surface. Agonists bind inside the crevice formed by the TMH bundle and produce conformational changes on the IC face of the receptor that uncover previously masked G protein-binding sites (21), which then lead to G protein coupling. Biophysical studies using a variety of techniques indicate that ligand-induced receptor activation produces the following changes: 1) a conformational change in the W6.48 "toggle switch" within the ligand binding pocket (22); 2) a change in the relative orientations of TMH3 and -6 that breaks an IC "ionic lock" (23-28), with the intracellular end of TMH6 moving away from TMH3 by hinging and moving up toward lipid (27); 3) the uptake of two protons (29); and 4) an influx of water (30).Recent isothiocyanate covalent labeling studies have suggested that a classical cannabinoid, AM841, enters the CB2 receptor via the lipid bilayer (1). However, the sequence of steps involved in such a lipid pathway entry has not yet been elucidated. We report here microsecond time scale unbiased