scholarly journals Molecular Model Construction and Evaluation of Jincheng Anthracite

ACS Omega ◽  
2020 ◽  
Vol 5 (19) ◽  
pp. 10663-10670
Author(s):  
Guochao Yan ◽  
Gang Ren ◽  
Longjian Bai ◽  
Jianping Feng ◽  
Zhiqiang Zhang
RSC Advances ◽  
2020 ◽  
Vol 10 (9) ◽  
pp. 5468-5477 ◽  
Author(s):  
Guan-qun Gong ◽  
Xin Yuan ◽  
Ying-jie Zhang ◽  
Ya-jun Li ◽  
Wei-xin Liu ◽  
...  

Fulvic acid (FA) is composed of many molecular units with similar characteristic structures. The characterization and molecular model construction of coal-based FA is the key for the scientific basis and applied science of FA.


2021 ◽  
Author(s):  
Qianzhen Shao ◽  
Yaoyukun Jiang ◽  
Zhongyue Yang

Molecular simulations, including quantum mechanics (QM), molecular mechanics (MM), and multiscale QM/MM modeling, have been extensively applied to understand the mechanism of enzyme catalysis and to design new enzymes. However, molecular simulations typically require specialized, manual operation ranging from model construction to post-analysis to complete the entire life-cycle of enzyme modeling. The dependence on manual operation makes it challenging to simulate enzymes and enzyme variants in a high-throughput fashion. In this work, we developed a Python software, EnzyHTP, to automate molecular model construction, QM, MM, and QM/MM computation, and analyses of modeling data for enzyme simulations. To test the EnzyHTP, we used fluoroacetate dehalogenase (FAcD) as a model system and simulated the enzyme interior electrostatics for 100 FAcD mutants with a random single amino acid substitution. For each enzyme mutant, the workflow involves structural model construction, 1 ns molecular dynamics simulations, and quantum mechnical calculations in 100 MD-sampled snapshots. The entire simulation workflow for 100 mutants was completed in 7 hours with 10 GPUs and 160 CPUs. EnzyHTP is expected to improve the efficiency and reproducibility of computational enzyme, facilitate the fundamental understanding of catalytic origins across enzyme families, and accelerate the optimization of biocatalysts for non-native substrate transformation.


2018 ◽  
Vol 32 (9) ◽  
pp. 9727-9737 ◽  
Author(s):  
Junqing Meng ◽  
Ruquan Zhong ◽  
Shichao Li ◽  
Feifei Yin ◽  
Baisheng Nie

2017 ◽  
Vol 31 (2) ◽  
pp. 1310-1317 ◽  
Author(s):  
Zhiqiang Zhang ◽  
Qiannan Kang ◽  
Shuai Wei ◽  
Tao Yun ◽  
Guochao Yan ◽  
...  

ACS Omega ◽  
2020 ◽  
Vol 5 (22) ◽  
pp. 13375-13383
Author(s):  
Lulu Lian ◽  
Zhihong Qin ◽  
Chunsheng Li ◽  
Jinglan Zhou ◽  
Qiang Chen ◽  
...  

Author(s):  
P.R. Smith ◽  
W.E. Fowler ◽  
U. Aebi

An understanding of the specific interactions of actin with regulatory proteins has been limited by the lack of information about the structure of the actin filament. Molecular actin has been studied in actin-DNase I complexes by single crystal X-ray analysis, to a resolution of about 0.6nm, and in the electron microscope where two dimensional actin sheets have been reconstructed to a maximum resolution of 1.5nm. While these studies have shown something of the structure of individual actin molecules, essential information about the orientation of actin in the filament is still unavailable.The work of Egelman & DeRosier has, however, suggested a method which could be used to provide an initial quantitative estimate of the orientation of actin within the filament. This method involves the quantitative comparison of computed diffraction data from single actin filaments with diffraction data derived from synthetic filaments constructed using the molecular model of actin as a building block. Their preliminary work was conducted using a model consisting of two juxtaposed spheres of equal size.


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