Dataset Information

Polarizable Force Field for CO₂ in M-MOF-74 Derived from Quantum Mechanics.

ABSTRACT: On the short term, carbon capture is a viable solution to reduce human-induced CO₂ emissions, which requires an energy efficient separation of CO₂. Metal-organic frameworks (MOFs) may offer opportunities for carbon capture and other industrially relevant separations. Especially, MOFs with embedded open metal sites have been shown to be promising. Molecular simulation is a useful tool to predict the performance of MOFs even before the synthesis of the material. This reduces the experimental effort, and the selection process of the most suitable MOF for a particular application can be accelerated. To describe the interactions between open metal sites and guest molecules in molecular simulation is challenging. Polarizable force fields have potential to improve the description of such specific interactions. Previously, we tested the applicability of polarizable force fields for CO₂ in M-MOF-74 by verifying the ability to reproduce experimental measurements. Here, we develop a predictive polarizable force field for CO₂ in M-MOF-74 (M = Co, Fe, Mg, Mn, Ni, Zn) without the requirement of experimental data. The force field is derived from energies predicted from quantum mechanics. The procedure is easily transferable to other MOFs. To incorporate explicit polarization, the induced dipole method is applied between the framework and the guest molecule. Atomic polarizabilities are assigned according to the literature. Only the Lennard-Jones parameters of the open metal sites are parameterized to reproduce energies from quantum mechanics. The created polarizable force field for CO₂ in M-MOF-74 can describe the adsorption well and even better than that in our previous work.

SUBMITTER: Becker TM

PROVIDER: S-EPMC6369669 | biostudies-literature | 2018 Oct

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Polarizable Force Field for CO2 in M-MOF-74 Derived from Quantum Mechanics.

Becker Tim M TM Lin Li-Chiang LC Dubbeldam David D Vlugt Thijs J H TJH

The journal of physical chemistry. C, Nanomaterials and interfaces 20181009 42

On the short term, carbon capture is a viable solution to reduce human-induced CO2 emissions, which requires an energy efficient separation of CO2. Metal-organic frameworks (MOFs) may offer opportunities for carbon capture and other industrially relevant separations. Especially, MOFs with embedded open metal sites have been shown to be promising. Molecular simulation is a useful tool to predict the performance of MOFs even before the synthesis of the material. This reduces ...[more]

PMID: 30774742

Similar Datasets

Project description:Electronic polarization effects have been suggested to play an important role in proton binding to titratable residues in proteins. In this work, we describe a new computational method for pKa calculations, using Monte Carlo (MC) simulations to sample protein protonation states with the Drude polarizable force field and Poisson-Boltzmann (PB) continuum electrostatic solvent model. While the most populated protonation states at the selected pH, corresponding to residues that are half-protonated at that pH, are sampled using the exact relative free energies computed with Drude particles optimized in the field of the PB implicit solvation model, we introduce an approximation for the protein polarization of low-populated protonation states to reduce the computational cost. The highly populated protonation states used to compute the polarization and pKa's are then iteratively improved until convergence. It is shown that for lysozyme, when considering 9 of the 18 titratable residues, the new method converged within two iterations with computed pKa's differing only by 0.02 pH units from pKa's estimated with the exact approach. Application of the method to predict pKa's of 94 titratable side chains in 8 proteins shows the Drude-PB model to produce physically more correct results as compared to the additive CHARMM36 (C36) force field (FF). With a dielectric constant of two assigned to the protein interior the Root Mean Square (RMS) deviation between computed and experimental pKa's is 2.07 and 3.19 pH units with the Drude and C36 models, respectively, and the RMS deviation using the Drude-PB model is relatively insensitive to the choice of the internal dielectric constant in contrast to the additive C36 model. At the higher internal dielectric constant of 20, pKa's computed with the additive C36 model converge to the results obtained with the Drude polarizable force field, indicating the need to artificially overestimate electrostatic screening in a nonphysical way with the additive FF. In addition, inclusion of both syn and anti orientations of the proton in the neutral state of acidic groups is shown to yield improved agreement with experiment. The present work, which is the first example of the use of a polarizable model for the prediction of pKa's in proteins, shows that the use of a polarizable model represents a more physically correct model for the treatment of electrostatic contributions to pKa shifts in proteins.

Dataset Information

Polarizable Force Field for CO₂ in M-MOF-74 Derived from Quantum Mechanics.

Publications

Polarizable Force Field for CO<sub>2</sub> in M-MOF-74 Derived from Quantum Mechanics.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets