In order to increase the accuracy of classical computer simulations, existing methodologies may need to be adapted. Hitherto, most force fields employ a truncated potential function to model van der Waals interactions, sometimes augmented with an analytical correction. Although such corrections are accurate for homogeneous systems with a long cutoff, they should not be used in inherently inhomogeneous systems such as biomolecular and interface systems. For such cases, a variant of the particle mesh Ewald algorithm (Lennard-Jones PME) was already proposed 20 years ago (Essmann et al. J. Chem. Phys. 1995, 103, 8577-8593), but it was implemented only recently (Wennberg et al. J. Chem. Theory Comput. 2013, 9, 3527-3537) in a major simulation code (GROMACS). The availability of this method allows surface tensions of liquids as well as bulk properties to be established, such as density and enthalpy of vaporization, without approximations due to truncation. Here, we report on simulations of ≈150 liquids (taken from a force field benchmark: Caleman et al. J. Chem. Theory Comput. 2012, 8, 61-74) using three different force fields and compare simulations with and without explicit long-range van der Waals interactions. We find that the density and enthalpy of vaporization increase for most liquids using the generalized Amber force field (GAFF, Wang et al. J. Comput. Chem. 2004, 25, 1157-1174) and the Charmm generalized force field (CGenFF, Vanommeslaeghe et al. J. Comput. Chem. 2010, 31, 671-690) but less so for OPLS/AA (Jorgensen and Tirado-Rives, Proc. Natl. Acad. Sci. U.S.A. 2005, 102, 6665-6670), which was parametrized with an analytical correction to the van der Waals potential. The surface tension increases by ≈10(-2) N/m for all force fields. These results suggest that van der Waals attractions in force fields are too strong, in particular for the GAFF and CGenFF. In addition to the simulation results, we introduce a new version of a web server, http://virtualchemistry.org, aimed at facilitating sharing and reuse of input files for molecular simulations.

The accurate calculation of the binding free energy for arbitrary ligand–protein pairs is a considerable challenge in computer-aided drug discovery. Recently, it has been demonstrated that current state-of-the-art molecular dynamics (MD) based methods are capable of making highly accurate predictions. Conventional MD-based approaches rely on the first principles of statistical mechanics and assume equilibrium sampling of the phase space. In the current work we demonstrate that accurate absolute binding free energies (ABFE) can also be obtained via theoretically rigorous non-equilibrium approaches. Our investigation of ligands binding to bromodomains and T4 lysozyme reveals that both equilibrium and non-equilibrium approaches converge to the same results. The non-equilibrium approach achieves the same level of accuracy and convergence as an equilibrium free energy perturbation (FEP) method enhanced by Hamiltonian replica exchange. We also compare uni- and bi-directional non-equilibrium approaches and demonstrate that considering the work distributions from both forward and reverse directions provides substantial accuracy gains. In summary, non-equilibrium ABFE calculations are shown to yield reliable and well-converged estimates of protein–ligand binding affinity.

The hydration free energy (HFE) is a critical property for predicting and understanding chemical and biological processes in aqueous solution. There are a number of computational methods to derive HFE, generally classified into the equilibrium or non-equilibrium methods, based on the type of calculations used. In the present study, we compute the hydration free energies of 34 small, neutral, organic molecules with experimental HFE between +2 and −16 kcal/mol. The one-sided non-equilibrium methods Jarzynski Forward (JF) and Backward (JB), the two-sided non-equilibrium methods Jarzynski mean based on the average of JF and JB, Crooks Gaussian Intersection (CGI), and the Bennett Acceptance Ratio (BAR) are compared to the estimates from the two-sided equilibrium method Multistate Bennett Acceptance Ratio (MBAR), which is considered as the reference method for HFE calculations, and experimental data from the literature. Our results show that the estimated hydration free energies from all the methods are consistent with MBAR results, and all methods provide a mean absolute error of ∼0.8 kcal/mol and root mean square error of ∼1 kcal for the 34 organic molecules studied. In addition, the results show that one-sided methods JF and JB result in systematic deviations that cannot be corrected entirely. The statistical efficiency ε of the different methods can be expressed as the one over the simulation time times the average variance in the HFE. From such an analysis, we conclude that ε(MBAR) > ε(BAR) ≈ ε(CGI) > ε(JX), where JX is any of the Jarzynski methods. In other words, the non-equilibrium methods tested here for the prediction of HFE have lower computational efficiency than the MBAR method.

The structural, elastic, electronic, optical, and vibrational properties of the orthorhombic Pd 2 Ga compound are investigated using the norm-conserving pseudopotentials within the local density approximation in the frame of density functional theory. The calculated lattice parameters have been compared with the experimental values and found to be in good agreement with these results. The second-order elastic constants and the other relevant quantities, such as the Young's modulus, shear modulus, Poisson's ratio, anisotropy factor, sound velocity, and Debye temperature, have been calculated. It is shown that this compound is mechanically stable after analysing the calculated elastic constants. Furthermore, the real and imaginary parts of the dielectric function and the optical constants, such as the optical dielectric constant and the effective number of electrons per unit cell, are calculated and presented. The phonon dispersion curves are derived using the direct method. The present results demonstrate that this compound is dynamically stable.

Identification of correlated residues in proteins is very important for many areas of protein research such as drug design, protein domain classification, signal transmission, allostery and mutational studies. Pairwise residue correlations in proteins can be obtained from experimental and theoretical ensembles. Since it is difficult to obtain proteins in various conformational states experimentally, theoretical methods such as all-atom molecular dynamics simulations and normal-mode analysis are commonly used methods to obtain protein ensembles and, therefore, pairwise residue correlations. The extent of agreement for the correlations obtained with all-atom molecular dynamics and elastic network model based normal-mode analysis is an important issue to investigate due to orders of magnitude computational advantage in terms of wall time for normal-mode based calculation. We performed multiple microsecond long equilibrium classical molecular dynamics simulations for six proteins. We calculated normalized dynamical cross-correlations and linear mutual information as pairwise residue correlations from the trajectories of these simulations. Then, we calculated the same pairwise residue correlations with two elastic network model based normal-mode analysis methods and compared our results with the former. The results show that elastic network model based normal-mode analysis can provide a fast and accurate estimation of linear correlations within proteins. Finally, we observed that only a subset of modes is sufficient to obtain linear correlations in proteins. This conclusion has crucial implications for understanding correlations within very large protein assemblies such as viral capsids.