Full QM Calculation of RNA Energy Using Electrostatically Embedded Generalized Molecular Fractionation with Conjugate Caps Method

Jin, Xinsheng; Zhang, John Z. H.; He, Xiao

doi:10.1021/acs.jpca.7b00859

Cited by 22 publications

(43 citation statements)

References 79 publications

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“…The electrostatically embedded generalized molecular fractionation with conjugate caps (EE-GMFCC) method was employed to perform full QM calculations of electric field in KSI. The detailed description of the EE-GMFCC method can be found in our previous works [ 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 ]. The calculations of the electrostatic potential by the EE-GMFCC method are the same as our previous work [ 16 ].…”

Section: Computational Approachesmentioning

confidence: 99%

An Ab Initio QM/MM Study of the Electrostatic Contribution to Catalysis in the Active Site of Ketosteroid Isomerase

Wang

2018

Molecules

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The electric field in the hydrogen-bond network of the active site of ketosteroid isomerase (KSI) has been experimentally measured using vibrational Stark effect (VSE) spectroscopy, and utilized to study the electrostatic contribution to catalysis. A large gap was found in the electric field between the computational simulation based on the Amber force field and the experimental measurement. In this work, quantum mechanical (QM) calculations of the electric field were performed using an ab initio QM/MM molecular dynamics (MD) simulation and electrostatically embedded generalized molecular fractionation with conjugate caps (EE-GMFCC) method. Our results demonstrate that the QM-derived electric field based on the snapshots from QM/MM MD simulation could give quantitative agreement with the experiment. The accurate calculation of the electric field inside the protein requires both the rigorous sampling of configurations, and a QM description of the electrostatic field. Based on the direct QM calculation of the electric field, we theoretically confirmed that there is a linear correlation relationship between the activation free energy and the electric field in the active site of wild-type KSI and its mutants (namely, D103N, Y16S, and D103L). Our study presents a computational protocol for the accurate simulation of the electric field in the active site of the protein, and provides a theoretical foundation that supports the link between electric fields and enzyme catalysis.

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Section: Computational Approachesmentioning

confidence: 99%

An Ab Initio QM/MM Study of the Electrostatic Contribution to Catalysis in the Active Site of Ketosteroid Isomerase

Wang

2018

Molecules

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“…Our previous studies on proteins and RNAs have demonstrated that the calculated total energy by EE‐GMFCC is not very sensitive to the embedding charge models. Another study by Liu and Herbert also found that the variations of protein total energies using three different embedding charge models, namely, Mulliken ChElPG and NPA charges, are also very small based on their pp‐GMBE (pair–pair approximation to the generalized many‐body expansion) approach.…”

Section: Computational Approachesmentioning

confidence: 99%

“…Theoretical approaches employing molecular mechanical (MM) force fields have achieved great success in describing biomolecular motion and interaction energies, but traditional nonpolarized force fields are lack of quantum mechanical (QM) effects, such as electronic polarization, many‐body QM interactions, charge transfer and so on . Previous studies have demonstrated that the electronic polarization plays a critical role in accurate description of the binding affinities for protein–ligand complexes and other complex systems …”

Section: Introductionmentioning

confidence: 99%

Fragment‐based quantum mechanical calculation of protein–protein binding affinities

Wang

Liu

et al. 2018

J Comput Chem

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The electrostatically embedded generalized molecular fractionation with conjugate caps (EE-GMFCC) method has been successfully utilized for efficient linear-scaling quantum mechanical (QM) calculation of protein energies. In this work, we applied the EE-GMFCC method for calculation of binding affinity of Endonuclease colicin-immunity protein complex. The binding free energy changes between the wild-type and mutants of the complex calculated by EE-GMFCC are in good agreement with experimental results. The correlation coefficient (R) between the predicted binding energy changes and experimental values is 0.906 at the B3LYP/6-31G*-D level, based on the snapshot whose binding affinity is closest to the average result from the molecular mechanics/Poisson-Boltzmann surface area (MM/PBSA) calculation. The inclusion of the QM effects is important for accurate prediction of protein-protein binding affinities. Moreover, the self-consistent calculation of PB solvation energy is required for accurate calculations of protein-protein binding free energies. This study demonstrates that the EE-GMFCC method is capable of providing reliable prediction of relative binding affinities for protein-protein complexes. © 2018 Wiley Periodicals, Inc.

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“…In our previous studies, we combined fragment methods with the MD engine and performed AIMD simulations for large molecular systems including protein, RNA, and hydration of metal ions [ 20 , 34 , 35 ]. In this study, a fragment-based AIMD (FB-AIMD) for combustion is developed, and its performance on the calculation of potential energies, atomic forces, and AIMD simulation of methane combustion are systematically investigated.…”

Section: Introductionmentioning

confidence: 99%

Fragment-Based Ab Initio Molecular Dynamics Simulation for Combustion

Cao

Zeng

et al. 2021

Molecules

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We develop a fragment-based ab initio molecular dynamics (FB-AIMD) method for efficient dynamics simulation of the combustion process. In this method, the intermolecular interactions are treated by a fragment-based many-body expansion in which three- or higher body interactions are neglected, while two-body interactions are computed if the distance between the two fragments is smaller than a cutoff value. The accuracy of the method was verified by comparing FB-AIMD calculated energies and atomic forces of several different systems with those obtained by standard full system quantum calculations. The computational cost of the FB-AIMD method scales linearly with the size of the system, and the calculation is easily parallelizable. The method is applied to methane combustion as a benchmark. Detailed reaction network of methane reaction is analyzed, and important reaction species are tracked in real time. The current result of methane simulation is in excellent agreement with known experimental findings and with prior theoretical studies.

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Full QM Calculation of RNA Energy Using Electrostatically Embedded Generalized Molecular Fractionation with Conjugate Caps Method

Cited by 22 publications

References 79 publications

An Ab Initio QM/MM Study of the Electrostatic Contribution to Catalysis in the Active Site of Ketosteroid Isomerase

An Ab Initio QM/MM Study of the Electrostatic Contribution to Catalysis in the Active Site of Ketosteroid Isomerase

Fragment‐based quantum mechanical calculation of protein–protein binding affinities

Fragment-Based Ab Initio Molecular Dynamics Simulation for Combustion

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