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Deriving Force-Field Parameters from First Principles Using a Polarizable and Higher Order Dispersion Model.

ABSTRACT: In this work we propose a strategy based on quantum mechanical (QM) calculations to parametrize a polarizable force field for use in molecular dynamics (MD) simulations. We investigate the use of multiple atoms-in-molecules (AIM) strategies to partition QM determined molecular electron densities into atomic subregions. The partitioned atomic densities are subsequently used to compute atomic dispersion coefficients from effective exchange-hole-dipole moment (XDM) calculations. In order to derive values for the repulsive van der Waals parameters from first principles, we use a simple volume relation to scale effective atomic radii. Explicit inclusion of higher order dispersion coefficients was tested for a series of alkanes, and we show that combining C₆ and C₈ attractive terms together with a C₁₁ repulsive potential yields satisfying models when used in combination with our van der Waals parameters and electrostatic and bonded parameters as directly obtained from quantum calculations as well. This result highlights that explicit inclusion of higher order dispersion terms could be viable in simulation, and it suggests that currently available QM analysis methods allow for first-principles parametrization of molecular mechanics models.

SUBMITTER: Visscher KM

PROVIDER: S-EPMC6581419 | biostudies-literature | 2019 Mar

REPOSITORIES: biostudies-literature

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Project description:Previously, we reported development of a fast polarizable force field and software named POSSIM (POlarizable Simulations with Second order Interaction Model). The second-order approximation permits the speed up of the polarizable component of the calculations by ca. an order of magnitude. We have now expanded the POSSIM framework to include a complete polarizable force field for proteins. Most of the parameter fitting was done to high-level quantum mechanical data. Conformational geometries and energies for dipeptides have been reproduced within average errors of ca. 0.5 kcal/mol for energies of the conformers (for the electrostatically neutral residues) and 9.7° for key dihedral angles. We have also validated this force field by running Monte Carlo simulations of collagen-like proteins in water. The resulting geometries were within 0.94 Å root-mean-square deviation (RMSD) from the experimental data. We have performed additional validation by studying conformational properties of three oligopeptides relevant in the context of N-glycoprotein secondary structure. These systems have been previously studied with combined experimental and computational methods, and both POSSIM and benchmark OPLS-AA simulations that we carried out produced geometries within ca. 0.9 Å RMSD of the literature structures. Thus, the performance of POSSIM in reproducing the structures is comparable with that of the widely used OPLS-AA force field. Furthermore, our fitting of the force field parameters for peptides and proteins has been streamlined compared with the previous generation of the complete polarizable force field and relied more on transferability of parameters for nonbonded interactions (including the electrostatic component). The resulting deviations from the quantum mechanical data are similar to those achieved with the previous generation; thus, the technique is robust, and the parameters are transferable. At the same time, the number of parameters used in this work was noticeably smaller than that of the previous generation of our complete polarizable force field for proteins; thus, the transferability of this set can be expected to be greater, and the danger of force field fitting artifacts is lower. Therefore, we believe that this force field can be successfully applied in a wide variety of applications to proteins and protein-ligand complexes.

Project description:Molecular dynamics (MD) simulations based on atomic models play an important role in the drug-discovery process to screen molecules, estimate binding free energies, and optimize lead compounds in chemical space. Accurate computations of thermodynamic and kinetic properties using MD simulations are highly dependent on the accuracy of the underlying atomic force field. In this context, going beyond the nonpolarizable fixed-charge model by accounting explicitly for induced polarization is highly desirable. The CHARMM polarizable force field based on classical Drude oscillators, in which an auxiliary charged particle is attached via a harmonic spring to its parent nucleus, offers both a computationally convenient and rigorous framework to model explicitly induced electronic polarization in MD simulations. For any molecule of interest, electrostatic partial charges, atomic polarizabilities, and Thole shielding factors, as well as bonded parameters can either be determined from ab initio calculations or ascribed from the knowledge-based library of the CHARMM Generalized force field. While this approach is fairly reliable in general, it is well understood that the overall accuracy of the models with respect to thermodynamic properties such as bulk density, enthalpies, and solvation free energies is particularly sensitive to the nonbonded Lennard-Jones (LJ) parameters. In the present study, we systematically refined the set of LJ parameters for the atom types available in the Drude force field to best match the experimental thermodynamic properties for 416 small druglike organic molecules. To further test the transferability of the optimized parameters, the hydration free energy of 372 molecules was computed. The calculations resulted in a small average error of 0.46 kcal/mol and a Pearson R of 0.9, representing a significant improvement over the additive GAFF force field in our previous study, where an average error of ∼2 kcal/mol was obtained. Such an improvement is consistent with the ability of the polarizable Drude model to more accurately model interactions in different environments. The effort provides a roadmap for the global optimization of force field parameters using experimental data. It is hoped that the present effort will further the application of the Drude polarizable force field in molecular simulations including drug design and discovery.

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Deriving Force-Field Parameters from First Principles Using a Polarizable and Higher Order Dispersion Model.

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