Nonbonded Force Field Parameters Research Articles

Nonbonded Force Field Parameters from MBIS Partitioning of the Molecular Electron Density Improve Thermophysical Properties Prediction of Organic Liquids

Nonbonded Force Field Parameters from MBIS Partitioning of the Molecular Electron Density Improve Thermophysical Properties Prediction of Organic Liquids

Nonbonded Force Field Parameters from MBIS Partitioning of the Molecular Electron Density Improve Binding Affinity Predictions of the T4-Lysozyme Double Mutant.

The use of computer simulation for binding affinity prediction is growing in drug discovery. However, its wider use is constrained by the accuracy of the free energy calculations. The key sources of error are the force fields used to depict molecular interactions and insufficient sampling of the configurational space. To improve the quality of the force field, we developed a Python-based computational workflow. The workflow described here uses the minimal basis iterative stockholder (MBIS) method to determine atomic charges and Lennard-Jones parameters from the polarized molecular density. This is done by performing electronic structure calculations on various configurations of the ligand when it is both bound and unbound. In addition, we validated a simulation procedure that accounts for the protein and ligand degrees of freedom to precisely calculate binding free energies. This was achieved by comparing the self-adjusted mixture sampling and nonequilibrium thermodynamic integration methods using various protein and ligand conformations. The accuracy of predicting binding affinity is improved by using MBIS-derived force field parameters and a validated simulation procedure. This improvement surpasses the chemical precision for the eight aromatic ligands, reaching a root-mean-square error of 0.7 kcal/mol.

Nonbonded Force Field Parameters from Minimal Basis Iterative Stockholder Partitioning of the Molecular Electron Density Improve CB7 Host-Guest Affinity Predictions.

Binding affinity prediction by means of computer simulation has been increasingly incorporated in drug discovery projects. Its wide application, however, is limited by the prediction accuracy of the free energy calculations. The main error sources are force fields used to describe molecular interactions and incomplete sampling of the configurational space. Organic host-guest systems have been used to address force field quality because they share similar interactions found in ligands and receptors, and their rigidity facilitates configurational sampling. Here, we test the binding free energy prediction accuracy for 14 guests with an aromatic or adamantane core and the CB7 host using molecular electron density derived nonbonded force field parameters. We developed a computational workflow written in Python to derive atomic charges and Lennard-Jones parameters with the Minimal Basis Iterative Stockholder method using the polarized electron density of several configurations of each guest in the bound and unbound states. The resulting nonbonded force field parameters improve binding affinity prediction, especially for guests with an adamantane core in which repulsive exchange and dispersion interactions to the host dominate.

Supplementary Data: Non-bonded force field parameters from MBIS partitioning of the molecular electron density improve CB7 host-guest affinity predictions

Supplementary Data: Non-bonded force field parameters from MBIS partitioning of the molecular electron density improve CB7 host-guest affinity predictions

Development and Validation of the Quantum Mechanical Bespoke Protein Force Field.

Molecular mechanics force field parameters for macromolecules, such as proteins, are traditionally fit to reproduce experimental properties of small molecules, and thus, they neglect system-specific polarization. In this paper, we introduce a complete protein force field that is designed to be compatible with the quantum mechanical bespoke (QUBE) force field by deriving nonbonded parameters directly from the electron density of the specific protein under study. The main backbone and sidechain protein torsional parameters are rederived in this work by fitting to quantum mechanical dihedral scans for compatibility with QUBE nonbonded parameters. Software is provided for the preparation of QUBE input files. The accuracy of the new force field, and the derived torsional parameters, is tested by comparing the conformational preferences of a range of peptides and proteins with experimental measurements. Accurate backbone and sidechain conformations are obtained in molecular dynamics simulations of dipeptides, with NMR J coupling errors comparable to the widely used OPLS force field. In simulations of five folded proteins, the secondary structure is generally retained, and the NMR J coupling errors are similar to standard transferable force fields, although some loss of the experimental structure is observed in certain regions of the proteins. With several avenues for further development, the use of system-specific nonbonded force field parameters is a promising approach for next-generation simulations of biological molecules.

Application of advanced sampling and analysis methods to predict the structure of adsorbed protein on a material surface.

The use of standard molecular dynamics simulation methods to predict the interactions of a protein with a material surface have the inherent limitations of lacking the ability to determine the most likely conformations and orientations of the adsorbed protein on the surface and to determine the level of convergence attained by the simulation. In addition, standard mixing rules are typically applied to combine the nonbonded force field parameters of the solution and solid phases the system to represent interfacial behavior without validation. As a means to circumvent these problems, the authors demonstrate the application of an efficient advanced sampling method (TIGER2A) for the simulation of the adsorption of hen egg-white lysozyme on a crystalline (110) high-density polyethylene surface plane. Simulations are conducted to generate a Boltzmann-weighted ensemble of sampled states using force field parameters that were validated to represent interfacial behavior for this system. The resulting ensembles of sampled states were then analyzed using an in-house-developed cluster analysis method to predict the most probable orientations and conformations of the protein on the surface based on the amount of sampling performed, from which free energy differences between the adsorbed states were able to be calculated. In addition, by conducting two independent sets of TIGER2A simulations combined with cluster analyses, the authors demonstrate a method to estimate the degree of convergence achieved for a given amount of sampling. The results from these simulations demonstrate that these methods enable the most probable orientations and conformations of an adsorbed protein to be predicted and that the use of our validated interfacial force field parameter set provides closer agreement to available experimental results compared to using standard CHARMM force field parameterization to represent molecular behavior at the interface.

Further Efforts Toward a Molecular Dynamics Force Field for Simulations of Peptides in 40% Trifluoroethanol–Water

A set of force field parameters for trifluoroethanol (TFE) was shown in earlier work from this lab to give a good accounting of system density, translational diffusion coefficients, and the solvent fluorine-solute hydrogen NMR cross-relaxation parameter (∑HF) for acetate dissolved in 40% TFE-water. It has since been found that this parameter set performs poorly when used to predict ∑HF for interactions of TFE with the hydrogens of an octapeptide, [val(5)]angiotensin. In the present work, adjustment of nonbonded force field parameters for interactions of fluorine with hydrogen was explored with the goal of improving these predictions. Six sets of TFE parameters were examined. When used in conjunction with the TIP5PE water model, all gave values for system density, translational diffusion coefficients, and ∑HF for acetate-TFE interactions that were similar to experimental results. Increasing the Lennard-Jones σHF for fluorine-hydrogen interactions by 10% led to calculated solvent-solute cross-relaxation parameters that are in better agreement with experiment for many of the peptide hydrogens. Changing the Lennard-Jones εHF parameters for the same interactions had little effect on calculated ∑HF values. There was no discernible influence of the TFE model used on the radius of gyration of the peptide or on the backbone conformational angles of the peptide, implying that the conformational properties of the peptide are not strongly influenced by changes in the force field description of TFE in 40% TFE-water. A recent parameter set for TFE proposed by Vymetal and Vondrasek (2014), which reproduces well various physical properties of neat TFE and TFE-water mixtures, was shown to predict cross-relaxation terms for this system poorly.

Unraveling Cellulose Microfibrils: A Twisted Tale

Molecular dynamics (MD) simulations of cellulose microfibrils are pertinent to the paper, textile, and biofuels industries for their unique capacity to characterize dynamic behavior and atomic-level interactions with solvent molecules and cellulase enzymes. While high-resolution crystallographic data have established a solid basis for computational analysis of cellulose, previous work has demonstrated a tendency for modeled microfibrils to diverge from the linear experimental structure and adopt a twisted conformation. Here, we investigate the dependence of this twisting behavior on computational approximations and establish the theoretical basis for its occurrence. We examine the role of solvent, the effect of nonbonded force field parameters [partial charges and van der Waals (vdW) contributions], and the use of explicitly modeled oxygen lone pairs in both the solute and solvent. Findings suggest that microfibril twisting is favored by vdW interactions, and counteracted by both intrachain hydrogen bonds and solvent effects at the microfibril surface.

Simulation of multiphase systems utilizing independent force fields to control intraphase and interphase behavior

Fixed-charge empirical force fields have been developed and widely used over the past three decades for all-atom molecular simulations. Most simulation programs providing these methods enable only one set of force field parameters to be used for the entire system. Whereas this is generally suitable for single-phase systems, the molecular environment at the interface between two phases may be sufficiently different from the individual phases to require a different set of parameters to be used to accurately represent the system. Recently published simulations of peptide adsorption to material surfaces using the CHARMM force field have clearly demonstrated this issue by revealing that calculated values of adsorption free energy substantially differ from experimental results. Whereas nonbonded parameters could be adjusted to correct this problem, this cannot be done without also altering the conformational behavior of the peptide in solution, for which CHARMM has been carefully tuned. We have developed a dual-force-field approach (Dual-FF) to address this problem and implemented it in the CHARMM simulation package. This Dual-FF method provides the capability to use two separate sets of nonbonded force field parameters within the same simulation: one set to represent intraphase interactions and a separate set to represent interphase interactions. Using this approach, we show that interfacial parameters can be adjusted to correct errors in peptide adsorption free energy without altering peptide conformational behavior in solution. This program thus provides the capability to enable both intraphase and interphase molecular behavior to be accurately and efficiently modeled in the same simulation.

Development of a Polarizable Force Field for Molecular Dynamics Simulations of Poly (Ethylene Oxide) in Aqueous Solution.

We have developed a quantum chemistry-based polarizable potential for poly(ethylene oxide) (PEO) in aqueous solution based on the APPLE&P polarizable ether and the SWM4-DP polarizable water models. Ether-water interactions were parametrized to reproduce the binding energy of water with 1,2-dimethoxyethane (DME) determined from high-level quantum chemistry calculations. Simulations of DME-water and PEO-water solutions at room temperature using the new polarizable potentials yielded thermodynamic properties in good agreement with experimental results. The predicted miscibility of PEO and water as a function of the temperature was found to be strongly correlated with the predicted free energy of solvation of DME. The developed nonbonded force field parameters were found to be transferrable to poly(propylene oxide) (PPO), as confirmed by capturing, at least qualitatively, the miscibility of PPO in water as a function of the molecular weight.

Derivation of Class II Force Fields. 7. Nonbonded Force Field Parameters for Organic Compounds

A set of nonbonded force field parameters consisting of atomic partial charges and van der Waals parameters has been derived by fitting experimental data for a broad set of organic compounds. The compounds in the fit spanned 11 functional groups: alcohols, aldehydes, amides, amines, carboxylic acids, esters, ethers, N-heterocycles, hydrocarbons, ketones, and sulfur compounds. The data consist of 136 crystal structures, 34 sublimation energies, and 63 gas-phase dipole moments. The nonbonded potential function is of the “9-6” form and is used in our class II CFF force field. This paper describes the fitting procedure and the quality of the fit as measured by comparing computed and experimental gas-phase dipole moments and crystal lattice energies. As a further test, each crystal structure was optimized. We report the accuracy of the computed crystal structures, including results obtained with force fields derived using two different combination rules. A summary is presented of the accuracy and consistency of predicted crystal lattice vectors and the lattice energies at the computed crystal structures. The results are discussed separately for each of the functional groups.