We describe a strategy of integrating quantum mechanical (QM), hybrid quantum mechanical/molecular mechanical (QM/MM) and MM simulations to analyze the physical properties of a solid/water interface. This protocol involves using a correlated ab initio (CCSD(T)) method to first calibrate Density Functional Theory (DFT) as the QM approach, which is then used in QM/MM simulations to compute relevant free energy quantities at the solid/water interface using a mean-field approximation of Yang et al. that decouples QM and MM thermal fluctuations; gas-phase QM/MM and periodic DFT calculations are used to determine the proper QM size in the QM/MM simulations. Finally, the QM/MM free energy results are compared with those obtained from MM simulations to directly calibrate the force field model for the solid/water interface. This protocol is illustrated by examining the orientations of an alkyl amine ligand at the gold/water interface, since the ligand conformation is expected to impact the chemical properties ( e.g. , charge) of the solid surface. DFT/MM and MM simulations using the INTERFACE force field lead to consistent results, suggesting that the effective gold/ligand interactions can be adequately described by a van der Waals model, while electrostatic and induction effects are largely quenched by solvation. The observed differences among periodic DFT, QM/MM and MM simulations, nevertheless, suggest that explicitly including electronic polarization and potentially charge transfer in the MM model can be important to the quantitative accuracy. The strategy of integrating multiple computational methods to cross-validate each other for complex interfaces is applicable to many problems that involve both inorganic/metallic and organic/biomolecular components, such as functionalized nanoparticles.
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Automation of AMOEBA polarizable force field for small molecules: Poltype 2
A next‐generation protocol (Poltype 2) has been developed which automatically generates AMOEBA polarizable force field parameters for small molecules. Both features and computational efficiency have been drastically improved. Notable advances include improved database transferability using SMILES, robust torsion fitting, non‐aromatic ring torsion parameterization, coupled torsion‐torsion parameterization, Van der Waals parameter refinement using ab initio dimer data and an intelligent fragmentation scheme that produces parameters with dramatically reduced ab initio computational cost. Additional improvements include better local frame assignment for atomic multipoles, automated formal charge assignment, Zwitterion detection, smart memory resource defaults, parallelized fragment job submission, incorporation of Psi4 quantum package, ab initio error handling, ionization state enumeration, hydration free energy prediction and binding free energy prediction. For validation, we have applied Poltype 2 to ~1000 FDA approved drug molecules from DrugBank. The ab initio molecular dipole moments and electrostatic potential values were compared with Poltype 2 derived AMOEBA counterparts. Parameters were further substantiated by calculating hydration free energy (HFE) on 40 small organic molecules and were compared with experimental data, resulting in an RMSE error of 0.59 kcal/mol. The torsion database has expanded to include 3543 fragments derived from FDA approved drugs. Poltype 2 provides a convenient utility for applications including binding free energy prediction for computational drug discovery. Further improvement will focus on automated parameter refinement by experimental liquid properties, expansion of the Van der Waals parameter database and automated parametrization of modified bio‐fragments such as amino and nucleic acids.
more » « less- Award ID(s):
- 1856173
- NSF-PAR ID:
- 10375629
- Publisher / Repository:
- Wiley Blackwell (John Wiley & Sons)
- Date Published:
- Journal Name:
- Journal of Computational Chemistry
- Volume:
- 43
- Issue:
- 23
- ISSN:
- 0192-8651
- Page Range / eLocation ID:
- p. 1530-1542
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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