429 research outputs found
Building Water Models, A Different Approach
Simplified, classical models of water are an integral part of atomistic
molecular simulations, especially in biology and chemistry where hydration
effects are critical. Yet, despite several decades of effort, these models are
still far from perfect. Presented here is an alternative approach to
constructing point charge water models - currently, the most commonly used
type. In contrast to the conventional approach, we do not impose any geometry
constraints on the model other than symmetry. Instead, we optimize the
distribution of point charges to best describe the "electrostatics" of the
water molecule, which is key to many unusual properties of liquid water. The
search for the optimal charge distribution is performed in 2D parameter space
of key lowest multipole moments of the model, to find best fit to a small set
of bulk water properties at room temperature. A virtually exhaustive search is
enabled via analytical equations that relate the charge distribution to the
multipole moments. The resulting "optimal" 3-charge, 4-point rigid water model
(OPC) reproduces a comprehensive set of bulk water properties significantly
more accurately than commonly used rigid models: average error relative to
experiment is 0.76%. Close agreement with experiment holds over a wide range of
temperatures, well outside the ambient conditions at which the fit to
experiment was performed. The improvements in the proposed water model extend
beyond bulk properties: compared to the common rigid models, predicted
hydration free energies of small molecules in OPC water are uniformly closer to
experiment, root-mean-square error < 1kcal/mol
Accurate Evaluation of Charge Asymmetry in Aqueous Solvation
Charge hydration asymmetry (CHA)--a characteristic dependence of hydration
free energy on the sign of the solute charge--quantifies the asymmetric
response of water to electric field at microscopic level. Accurate estimates of
CHA are critical for understanding hydration effects ubiquitous in chemistry
and biology. However, measuring hydration energies of charged species is
fraught with significant difficulties, which lead to unacceptably large (up to
300%) variation in the available estimates of the CHA effect. We circumvent
these difficulties by developing a framework which allows us to extract and
accurately estimate the intrinsic propensity of water to exhibit CHA from
accurate experimental hydration free energies of neutral polar molecules.
Specifically, from a set of 504 small molecules we identify two pairs that are
analogous, with respect to CHA, to the K+/F- pair--a classical probe for the
effect. We use these "CHA-conjugate" molecule pairs to quantify the intrinsic
charge-asymmetric response of water to the microscopic charge perturbations:
the asymmetry of the response is strong, ~50% of the average hydration free
energy of these molecules. The ability of widely used classical water models to
predict hydration energies of small molecules correlates with their ability to
predict CHA
Heat conductivity of DNA double helix
Thermal conductivity of isolated single molecule DNA fragments is of
importance for nanotechnology, but has not yet been measured experimentally.
Theoretical estimates based on simplified (1D) models predict anomalously high
thermal conductivity. To investigate thermal properties of single molecule DNA
we have developed a 3D coarse-grained (CG) model that retains the realism of
the full all-atom description, but is significantly more efficient. Within the
proposed model each nucleotide is represented by 6 particles or grains; the
grains interact via effective potentials inferred from classical molecular
dynamics (MD) trajectories based on a well-established all-atom potential
function. Comparisons of 10 ns long MD trajectories between the CG and the
corresponding all-atom model show similar root-mean-square deviations from the
canonical B-form DNA, and similar structural fluctuations. At the same time,
the CG model is 10 to 100 times faster depending on the length of the DNA
fragment in the simulation. Analysis of dispersion curves derived from the CG
model yields longitudinal sound velocity and torsional stiffness in close
agreement with existing experiments. The computational efficiency of the CG
model makes it possible to calculate thermal conductivity of a single DNA
molecule not yet available experimentally. For a uniform (polyG-polyC) DNA, the
estimated conductivity coefficient is 0.3 W/mK which is half the value of
thermal conductivity for water. This result is in stark contrast with estimates
of thermal conductivity for simplified, effectively 1D chains ("beads on a
spring") that predict anomalous (infinite) thermal conductivity. Thus, full 3D
character of DNA double-helix retained in the proposed model appears to be
essential for describing its thermal properties at a single molecule level.Comment: 16 pages, 12 figure
Accuracy comparison of several common implicit solvent models and their implementations in the context of protein-ligand binding.
In this study several commonly used implicit solvent models are compared with respect to their accuracy of estimating solvation energies of small molecules and proteins, as well as desolvation penalty in protein-ligand binding. The test set consists of 19 small proteins, 104 small molecules, and 15 protein-ligand complexes. We compared predicted hydration energies of small molecules with their experimental values; the results of the solvation and desolvation energy calculations for small molecules, proteins and protein-ligand complexes in water were also compared with Thermodynamic Integration calculations based on TIP3P water model and Amber12 force field. The following implicit solvent (water) models considered here are: PCM (Polarized Continuum Model implemented in DISOLV and MCBHSOLV programs), GB (Generalized Born method implemented in DISOLV program, S-GB, and GBNSR6 stand-alone version), COSMO (COnductor-like Screening Model implemented in the DISOLV program and the MOPAC package) and the Poisson-Boltzmann model (implemented in the APBS program). Different parameterizations of the molecules were examined: we compared MMFF94 force field, Amber12 force field and the quantum-chemical semi-empirical PM7 method implemented in the MOPAC package. For small molecules, all of the implicit solvent models tested here yield high correlation coefficients (0.87-0.93) between the calculated solvation energies and the experimental values of hydration energies. For small molecules high correlation (0.82-0.97) with the explicit solvent energies is seen as well. On the other hand, estimated protein solvation energies and protein-ligand binding desolvation energies show substantial discrepancy (up to 10kcal/mol) with the explicit solvent reference. The correlation of polar protein solvation energies and protein-ligand desolvation energies with the corresponding explicit solvent results is 0.65-0.99 and 0.76-0.96 respectively, though this difference in correlations is caused more by different parameterization and less by methods and indicates the need for further improvement of implicit solvent models parameterization. Within the same parameterization, various implicit methods give practically the same correlation with results obtained in explicit solvent model for ligands and proteins: e.g. correlation values of polar ligand solvation energies and the corresponding energies in the frame of explicit solvent were 0.953-0.966 for the APBS program, the GBNSR6 program and all models used in the DISOLV program. The DISOLV program proved to be on a par with the other used programs in the case of proteins and ligands solvation energy calculation. However, the solution of the Poisson-Boltzmann equation (APBS program) and Generalized Born method (implemented in the GBNSR6 program) proved to be the most accurate in calculating the desolvation energies of complexes
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