Quantum Fragment Based ab Initio Molecular Dynamics for Proteins

被引:55
|
作者
Liu, Jinfeng [1 ]
Zhu, Tong [1 ,2 ]
Wang, Xianwei [3 ]
He, Xiao [1 ,2 ]
Zhang, John Z. H. [1 ,2 ,4 ]
机构
[1] E China Normal Univ, Inst Theoret & Computat Sci, State Key Lab Precis Spect, Shanghai 200062, Peoples R China
[2] NYU Shanghai, NYU ECNU Ctr Computat Chem, Shanghai 200062, Peoples R China
[3] Zhejiang Univ Technol, Coll Sci, Ctr Opt & Optoelect Res, Hangzhou 310023, Zhejiang, Peoples R China
[4] NYU, Dept Chem, New York, NY 10003 USA
基金
中国国家自然科学基金;
关键词
MULTIPOLAR EWALD METHODS; CHARGE-TRANSFER; FORCE-FIELD; ELECTROSTATIC POLARIZATION; MECHANICAL CALCULATION; DENSITY FUNCTIONALS; CONJUGATE CAPS; FREE-ENERGY; SIMULATION; FRACTIONATION;
D O I
10.1021/acs.jctc.5b00558
中图分类号
O64 [物理化学(理论化学)、化学物理学];
学科分类号
070304 ; 081704 ;
摘要
Developing ab initio molecular dynamics (AIMD) methods for practical application in protein dynamics is of significant interest. Due to the large size of biomolecules, applying standard quantum chemical methods to compute energies for dynamic simulation is computationally prohibitive. In this work, a fragment based ab initio molecular dynamics approach is presented for practical application in protein dynamics study. In this approach, the energy and forces of the protein are calculated by a recently developed electrostatically embedded generalized molecular fractionation with conjugate caps (EE-GMFCC) method. For simulation in explicit solvent, mechanical embedding is introduced to treat protein interaction with explicit water molecules. This AIMD approach has been applied to MD simulations of a small benchmark protein Trpcage (with 20 residues and 304 atoms) in both the gas phase and in solution. Comparison to the simulation result using the AMBER force field shows that the AIMD gives a more stable protein structure in the simulation, indicating that quantum chemical energy is more reliable. Importantly, the present fragment-based AIMD simulation captures quantum effects including electrostatic polarization and charge transfer that are missing in standard classical MD simulations. The current approach is linear-scaling, trivially parallel, and applicable to performing the AIMD simulation of proteins with a large size.
引用
收藏
页码:5897 / 5905
页数:9
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