scholarly journals Homology modeling and molecular dynamics simulation of human prothrombin fragment 1

1995 ◽  
Vol 4 (11) ◽  
pp. 2341-2348 ◽  
Author(s):  
Leping Li ◽  
Tom Darden ◽  
Charles Foley ◽  
Richard Hiskey ◽  
Lee Pedersen
Keyword(s):  
Molecular Dynamics ◽  
Molecular Dynamics Simulation ◽  
Homology Modeling ◽  
Dynamics Simulation ◽  
Prothrombin Fragment

scholarly journals Homology Modeling and Molecular Dynamics Simulation Studies of the human resistin protein

2009 ◽  
Vol 96 (3) ◽  
pp. 652a-653a
Author(s):  
Chilamakuri C. Sekhar Reddy ◽  
Ramanathan Sowdhamini ◽  
Bernard Offmann
Keyword(s):  
Molecular Dynamics ◽  
Molecular Dynamics Simulation ◽  
Homology Modeling ◽  
Dynamics Simulation ◽  
Simulation Studies ◽  
Human Resistin

scholarly journals Binding interactions of epididymal protease inhibitor and semenogelin-1: a homology modeling, docking and molecular dynamics simulation study

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e7329 ◽  
Author(s):  
Changyu Shan ◽  
Hongwei Li ◽  
Yuping Zhang ◽  
Yuyan Li ◽  
Yingchun Chen ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Molecular Dynamics Simulation ◽  
Homology Modeling ◽  
Protease Inhibitor ◽  
Hormonal Contraceptive ◽  
Dynamics Simulation ◽  
Binding Interaction ◽  
Binding Interactions ◽  
C Terminus ◽  
N Terminus

Epididymal protease inhibitor (EPPIN) that is located on the sperm surface and specific to the male reproductive system is a non-hormonal contraceptive target, since the binding of EPPIN with the seminal plasma protein semenogelin-1 (SEMG1) causes a loss of sperm function. Here, we investigated the binding interactions between EPPIN and SEMG1 by homology modeling, docking and molecular dynamics simulation. Since no crystal structure was reported for EPPIN, its 3D structure was constructed by homology modeling and refined by dynamics simulation, illustrating the C-terminus domain of EPPIN could bind with its N-terminus domain through the residues 30–32 and 113–116. The binding interaction of SEMG110-8 peptide and EPPIN was investigated by Z-DOCK and dynamics simulation. After evaluating the models according to the calculated binding free energies, we demonstrated that C-terminus domain of EPPIN was important for the binding of SEMG1 via residues Tyr107, Gly112, Asn116, Gln118 and Asn122, while residue Arg32 in N-terminus domain also had contribution for their binding interaction. Additionally, the binding pocket of EPPIN was defined according to these key residues and verified by molecular docking with reported inhibitor EP055, suggesting that the pocket formed by Arg32, Asn114, Asn116, Phe117 and Asn122 could be important for the design of new ligands. This study might be helpful for the understanding of biological function of EPPIN and would encourage the discovery of non-hormonal contraceptive leads/drugs in the future.

Computational Approaches for Elucidating Protein-Protein Interactions in Cation Channel Signaling

2020 ◽  
Vol 21 (2) ◽  
pp. 179-192
Author(s):  
Baichun Hu ◽  
Xiaoming Zheng ◽  
Ying Wang ◽  
Jian Wang ◽  
Fengjiao Zhang
Keyword(s):  
Molecular Dynamics ◽  
Molecular Dynamics Simulation ◽  
Homology Modeling ◽  
Protein Interactions ◽  
Protein Docking ◽  
Cation Channel ◽  
Dynamics Simulation ◽  
Protein Protein Interactions ◽  
Molecular Graphics ◽  
Computational Approaches

Background: The lipid bilayer of the plasma membrane is impermeable to ions, yet changes in the flux of ions across the cell membrane are critical regulatory events in cells. Because of their regulatory roles in a range of physiological processes, such as electrical signaling in muscles and neurons, to name a few, these proteins are one of the most important drug targets. Objective: This review mainly focused on the computational approaches for elucidating proteinprotein interactions in cation channel signaling. Discussion: Due to continuously advanced facilities and technologies in computer sciences, the physical contacts of macromolecules of channel structures have been virtually visualized. Indeed, techniques like protein-protein docking, homology modeling, and molecular dynamics simulation are valuable tools for predicting the protein complex and refining channels with unreleased structures. Undoubtedly, these approaches will greatly expand the cation channel signaling research, thereby speeding up structure-based drug design and discovery. Conclusion: We introduced a series of valuable computational tools for elucidating protein-protein interactions in cation channel signaling, including molecular graphics, protein-protein docking, homology modeling, and molecular dynamics simulation.

TOWARD A BLUEPRINT FOR β-PRIMEVEROSIDASE FROM TEA LEAVES STRUCTURE/FUNCTION PROPERTIES: HOMOLOGY MODELING STUDY

2006 ◽  
Vol 05 (spec01) ◽  
pp. 433-446 ◽  
Author(s):  
WEI-WEI HAN ◽  
ZE-SHENG LI ◽  
QING-CHUAN ZHENG ◽  
CHIA-CHUNG SUN
Keyword(s):  
Molecular Dynamics ◽  
Molecular Dynamics Simulation ◽  
Homology Modeling ◽  
Active Site ◽  
3D Model ◽  
Dynamics Simulation ◽  
Experimental Investigations ◽  
Refined Model ◽  
Tea Leaves ◽  
Final Model

By means of the Homology modeling and the known structure of cyannogenic β-glycosidase from white clover (1CBG, EC 3.2.1.21), we construct a 3D model of the β-primeverosidase (EC 3.2.1.149) and search for the binding site of substrate. The 3D model is then refined by using molecular mechanics (optimization and molecular dynamics) simulation. Finally, the refined model is further assessed by Profile-3D and PROCHECK, and the results showed that the final model is reliable. Furthermore, the docking of the substrates into the active site of the protein indicates that β-primeverosidase is able to hydrolyze β-primeverosides, but not act on 2-phenylethyl β-D-glucopyranoside. These results suggest that β-primeverosidase shows broad substrate specificity with respect to the disaccharide glycon moiety (subsite -2). This is consistent with the experimental observation. Thr271 and Thr415 play important roles in subsite -2 of β-primeverosidase. Our results may be helpful for further experimental investigations.

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