A multipole-based water potential with implicit polarization for biomolecular simulations

Non-covalent interactions from a Quantum Chemical Topology perspective

About half a century after its little-known beginnings, the quantum topological approach called QTAIM has grown into a widespread, but still not mainstream, methodology of interpretational quantum chemistry. Although often confused in textbooks with yet another population analysis, be it perhaps an elegant but somewhat esoteric one, QTAIM has been enriched with about a dozen other research areas sharing its main mathematical language, such as Interacting Quantum Atoms (IQA) or Electron Localisation Function (ELF), to form an overarching approach called Quantum Chemical Topology (QCT). Instead of reviewing the latter's role in understanding non-covalent interactions, we propose a number of ideas emerging from the full consequences of the space-filling nature of topological atoms, and discuss how they (will) impact on interatomic interactions, including non-covalent ones. The architecture of a force field called FFLUX, which is based on these ideas, is outlined. A new method called Relative Energy Gradient (REG) is put forward, which is able, by computation, to detect which fragments of a given molecular assembly govern the energetic behaviour of this whole assembly. This method can offer insight into the typical balance of competing atomic energies both in covalent and non-covalent case studies. A brief discussion on so-called bond critical points is given, highlighting concerns about their meaning, mainly in the arena of non-covalent interactions.

The Use of Anisotropic Potentials in Modeling Water and Free Energies of Hydration

We propose a novel, anisotropic rigid-body intermolecular potential model to predict the properties of water and the hydration free energies of neutral organic solutes. The electrostatic interactions of water and the solutes are modeled using atomic multipole moments up to hexadecapole; these are obtained from distributed multipole analysis of the quantum mechanically computed charge densities and include average polarization effects in solution. The repulsion-dispersion water-water interactions are modeled with a three-site, exp-6 model fitted to the experimental liquid water density and oxygen-oxygen radial distribution function at ambient conditions. The proposed water model reproduces well several water properties not used in its parametrization, including vapor-liquid coexistence densities, the maximum in liquid water density at atmospheric pressure, the structure of ordered ice polymorphs, and the liquid water heat capacity. The model is used to compute the hydration free energy of 10 neutral organic solutes using explicit-solvent free energy perturbation. The solute-solute repulsion-dispersion intermolecular potential is obtained from previous parametrizations on organic crystal structures. In order to calculate the free energies of hydration, water-solute repulsion-dispersion interactions are modeled using Lorenz-Berthelot combining rules. The root-mean-square error of the predicted hydration free energies is 1.5 kcal mol(-1), which is comparable to the error found using a continuum mean-field quantum mechanical approach parametrized using experimental free energy of hydration data. The results are also contrasted with explicit-solvent hydration free energies obtained with an atomic charge representation of the solute's charge density computed at the same level of theory used to compute the distributed multipoles. Replacing the multipole description of the solute's charge density with an atomic charge model changes the free energy of hydration by as much as 3 kcal mol(-1) and provides an estimate for the effect of the modeling quality of the intermolecular electrostatic forces in free energy of solvation calculations.

Electronic properties of a graphene device with peptide adsorption: insight from simulation

In this work, to explain doping behavior of single-layer graphene upon HSSYWYAFNNKT (P1) and HSSAAAAFNNKT (P1-3A) adsorption in field-effect transistors (GFETs), we applied a combined computational approach, whereby peptide adsorption was modeled by molecular dynamics simulations, and the lowest energy configuration was confirmed by density functional theory calculations. On the basis of the resulting structures of the hybrid materials, electronic structure and transport calculations were investigated. We demonstrate that π-π stacking of the aromatic residues and proximate peptide backbone to the graphene surface in P1 have a role in the p-doping. These results are consistent with our experimental observation of the GFET's p-doping even after a 24-h annealing procedure. Upon substitution of three of the aromatic residues to Ala in (P1-3A), a considerable decrease from p-doping is observed experimentally, demonstrating n-doping as compared to the nonadsorbed device, yet not explained based on the atomistic MD simulation structures. To gain a qualitative understanding of P1-3A's adsorption over a longer simulation time, which may differ from aromatic amino acid residues' swift anchoring on the surface, we analyzed equilibrated coarse-grain simulations performed for 500 ns. Desorption of the Ala residues from the surface was shown computationally, which could in turn affect charge transfer, yet a full explanation of the mechanism of n-doping will require elucidation of differences between various aromatic residues as dependent on peptide composition, and inclusion of effects of the substrate and environment, to be considered in future work.

Point charges optimally placed to represent the multipole expansion of charge distributions

We propose an approach for approximating electrostatic charge distributions with a small number of point charges to optimally represent the original charge distribution. By construction, the proposed optimal point charge approximation (OPCA) retains many of the useful properties of point multipole expansion, including the same far-field asymptotic behavior of the approximate potential. A general framework for numerically computing OPCA, for any given number of approximating charges, is described. We then derive a 2-charge practical point charge approximation, PPCA, which approximates the 2-charge OPCA via closed form analytical expressions, and test the PPCA on a set of charge distributions relevant to biomolecular modeling. We measure the accuracy of the new approximations as the RMS error in the electrostatic potential relative to that produced by the original charge distribution, at a distance 2x the extent of the charge distribution--the mid-field. The error for the 2-charge PPCA is found to be on average 23% smaller than that of optimally placed point dipole approximation, and comparable to that of the point quadrupole approximation. The standard deviation in RMS error for the 2-charge PPCA is 53% lower than that of the optimal point dipole approximation, and comparable to that of the point quadrupole approximation. We also calculate the 3-charge OPCA for representing the gas phase quantum mechanical charge distribution of a water molecule. The electrostatic potential calculated by the 3-charge OPCA for water, in the mid-field (2.8 Å from the oxygen atom), is on average 33.3% more accurate than the potential due to the point multipole expansion up to the octupole order. Compared to a 3 point charge approximation in which the charges are placed on the atom centers, the 3-charge OPCA is seven times more accurate, by RMS error. The maximum error at the oxygen-Na distance (2.23 Å) is half that of the point multipole expansion up to the octupole order.

Limiting assumptions in molecular modeling: electrostatics

Molecular mechanics attempts to represent intermolecular interactions in terms of classical physics. Initial efforts assumed a point charge located at the atom center and coulombic interactions. It is been recognized over multiple decades that simply representing electrostatics with a charge on each atom failed to reproduce the electrostatic potential surrounding a molecule as estimated by quantum mechanics. Molecular orbitals are not spherically symmetrical, an implicit assumption of monopole electrostatics. This perspective reviews recent evidence that requires use of multipole electrostatics and polarizability in molecular modeling.

Overview of computational methods employed in early-stage drug discovery

BACKGROUND

The understanding of biomolecular interactions ultimately depends on knowledge about the structural and dynamic details of the interacting system. Rational structure-based drug design implements computational methodology in this rationale.

DISCUSSION

Together with increasing throughput of structural biology, molecular modeling has progressively contributed to rational drug design and elucidation of nontoxic and patient-tailored interventions, helping to make drug development more cost-efficient. But in this challenging time for the pharmaceutical industry, the successful discovery of novel therapeutics should rely on integration of computational modeling with experimentation when it comes to ligand-binding energetics, system flexibility and genetic diversity/heterogeneity of the target. Moreover, it appears that many drugs--even those for which specific receptors have been identified--intercalate in biological membranes, which could also become the actual target.

CONCLUSIONS

Understanding the drug-target and drug-unwanted-target interactions at the atomic level is fundamental in the initial phases of the drug development process. Molecular dynamics simulations and complementary computational methods are already contributing in this endeavor for the soluble pharmacological targets and show an increasing importance in the understanding of membrane-ligand interactions.

Polarization effects in molecular mechanical force fields

The focus here is on incorporating electronic polarization into classical molecular mechanical force fields used for macromolecular simulations. First, we briefly examine currently used molecular mechanical force fields and the current status of intermolecular forces as viewed by quantum mechanical approaches. Next, we demonstrate how some components of quantum mechanical energy are effectively incorporated into classical molecular mechanical force fields. Finally, we assess the modeling methods of one such energy component-polarization energy-and present an overview of polarizable force fields and their current applications. Incorporating polarization effects into current force fields paves the way to developing potentially more accurate, though more complex, parameterizations that can be used for more realistic molecular simulations.