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A Force Balanced Fragmentation Method for ab Initio Molecular Dynamic Simulation of Protein

Overview of attention for article published in Frontiers in Chemistry, May 2018
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Title
A Force Balanced Fragmentation Method for ab Initio Molecular Dynamic Simulation of Protein
Published in
Frontiers in Chemistry, May 2018
DOI 10.3389/fchem.2018.00189
Pubmed ID
Authors

Mingyuan Xu, Tong Zhu, John Z. H. Zhang

Abstract

A force balanced generalized molecular fractionation with conjugate caps (FB-GMFCC) method is proposed for ab initio molecular dynamic simulation of proteins. In this approach, the energy of the protein is computed by a linear combination of the QM energies of individual residues and molecular fragments that account for the two-body interaction of hydrogen bond between backbone peptides. The atomic forces on the caped H atoms were corrected to conserve the total force of the protein. Using this approach, ab initio molecular dynamic simulation of an Ace-(ALA)9-NME linear peptide showed the conservation of the total energy of the system throughout the simulation. Further a more robust 110 ps ab initio molecular dynamic simulation was performed for a protein with 56 residues and 862 atoms in explicit water. Compared with the classical force field, the ab initio molecular dynamic simulations gave better description of the geometry of peptide bonds. Although further development is still needed, the current approach is highly efficient, trivially parallel, and can be applied to ab initio molecular dynamic simulation study of large proteins.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 9 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 9 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 3 33%
Student > Bachelor 2 22%
Other 1 11%
Student > Master 1 11%
Researcher 1 11%
Other 0 0%
Unknown 1 11%
Readers by discipline Count As %
Chemistry 4 44%
Biochemistry, Genetics and Molecular Biology 2 22%
Agricultural and Biological Sciences 1 11%
Computer Science 1 11%
Unknown 1 11%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 30 May 2018.
All research outputs
#21,709,675
of 24,226,848 outputs
Outputs from Frontiers in Chemistry
#3,076
of 6,382 outputs
Outputs of similar age
#294,585
of 335,410 outputs
Outputs of similar age from Frontiers in Chemistry
#94
of 163 outputs
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