Atomistic simulation of carbohydrate-protein complex formation: Hevein-32 domain

AbstractInteractions between proteins and their small molecule ligands are of great importance for the process of drug design. Here we report an unbiased molecular dynamics simulation of systems containing hevein domain (HEV32) with N-acetylglucosamine mono-, di- or trisaccharide. Carbohydrate molecules were placed outside the binding site. Three of six simulations (6 × 2 μs) led to binding of a carbohydrate ligand into the binding mode in agreement with the experimentally determined structure. Unbinding was observed in one simulation (monosaccharide). There were no remarkable intermediates of binding for mono and disaccharide. Trisaccharide binding was initiated by formation of carbohydrate-aromatic CH/π interactions. Our results indicate that binding of ligands followed the model of conformational selection because the conformation of the protein ready for ligand binding was observed before the binding. This study extends the concept of docking by dynamics on carbohydrate-protein interactions.

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Faculty Opinions recommendation of Role of cholesterol and polyunsaturated chains in lipid-protein interactions: molecular dynamics simulation of rhodopsin in a realistic membrane environment.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.1025182.297783 ◽

2005 ◽

Author(s):

Tetsuji Okada

Keyword(s):

Molecular Dynamics ◽

Molecular Dynamics Simulation ◽

Protein Interactions ◽

Dynamics Simulation ◽

Lipid Protein Interactions

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Computational Investigations on the Binding Mode of Ligands for the Cannabinoid-Activated G Protein-Coupled Receptor GPR18

Biomolecules ◽

10.3390/biom10050686 ◽

2020 ◽

Vol 10 (5) ◽

pp. 686 ◽

Cited By ~ 3

Author(s):

Alexander Neumann ◽

Viktor Engel ◽

Andhika B. Mahardhika ◽

Clara T. Schoeder ◽

Vigneshwaran Namasivayam ◽

...

Keyword(s):

Molecular Dynamics ◽

Molecular Dynamics Simulation ◽

G Protein ◽

Phenyl Ring ◽

Binding Mode ◽

Dynamics Simulation ◽

Simulation Studies ◽

Binding Modes ◽

G Protein Coupled Receptor ◽

G Protein Coupled

GPR18 is an orphan G protein-coupled receptor (GPCR) expressed in cells of the immune system. It is activated by the cannabinoid receptor (CB) agonist ∆9-tetrahydrocannabinol (THC). Several further lipids have been proposed to act as GPR18 agonists, but these results still require unambiguous confirmation. In the present study, we constructed a homology model of the human GPR18 based on an ensemble of three GPCR crystal structures to investigate the binding modes of the agonist THC and the recently reported antagonists which feature an imidazothiazinone core to which a (substituted) phenyl ring is connected via a lipophilic linker. Docking and molecular dynamics simulation studies were performed. As a result, a hydrophobic binding pocket is predicted to accommodate the imidazothiazinone core, while the terminal phenyl ring projects towards an aromatic pocket. Hydrophobic interaction of Cys251 with substituents on the phenyl ring could explain the high potency of the most potent derivatives. Molecular dynamics simulation studies suggest that the binding of imidazothiazinone antagonists stabilizes transmembrane regions TM1, TM6 and TM7 of the receptor through a salt bridge between Asp118 and Lys133. The agonist THC is presumed to bind differently to GPR18 than to the distantly related CB receptors. This study provides insights into the binding mode of GPR18 agonists and antagonists which will facilitate future drug design for this promising potential drug target.

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Cofilin and gelsolin segment-1: molecular dynamics simulation and biochemical analysis predict a similar actin binding mode

Journal of Molecular Biology ◽

10.1006/jmbi.1998.2048 ◽

1998 ◽

Vol 282 (5) ◽

pp. 921-932 ◽

Cited By ~ 49

Author(s):

Willy Wriggers ◽

Jay X. Tang ◽

Toshifumi Azuma ◽

Peter W. Marks ◽

Paul A. Janmey

Keyword(s):

Molecular Dynamics ◽

Molecular Dynamics Simulation ◽

Biochemical Analysis ◽

Binding Mode ◽

Dynamics Simulation ◽

Actin Binding

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Prediction of the binding mode between GSK3β and a peptide derived from GSKIP using molecular dynamics simulation

Biopolymers ◽

10.1002/bip.21603 ◽

2011 ◽

Vol 95 (7) ◽

pp. 461-471 ◽

Cited By ~ 10

Author(s):

Xu-Nan Tang ◽

Cheng-Wei Lo ◽

Yu-Chung Chuang ◽

Chao-Tung Chen ◽

Ying-Chieh Sun ◽

...

Keyword(s):

Molecular Dynamics ◽

Molecular Dynamics Simulation ◽

Binding Mode ◽

Dynamics Simulation

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Study on the binding mode of the integrase with DNA via steered molecular dynamics simulation

2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society ◽

10.1109/iembs.2009.5332821 ◽

2009 ◽

Author(s):

Cun Xin Wang ◽

Ming Liu ◽

Ping Li ◽

Xiao Jing Cong ◽

Jian Jun Tan ◽

...

Keyword(s):

Molecular Dynamics ◽

Molecular Dynamics Simulation ◽

Binding Mode ◽

Steered Molecular Dynamics ◽

Dynamics Simulation ◽

Steered Molecular Dynamics Simulation

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Prediction of the binding mode between BMS-378806 and HIV-1 gp120 by docking and molecular dynamics simulation

Biochimica et Biophysica Acta (BBA) - Proteins and Proteomics ◽

10.1016/j.bbapap.2005.12.017 ◽

2006 ◽

Vol 1764 (4) ◽

pp. 766-772 ◽

Cited By ~ 27

Author(s):

Ren Kong ◽

Jian Jun Tan ◽

Xiao Hui Ma ◽

Wei Zu Chen ◽

Cun Xin Wang

Keyword(s):

Molecular Dynamics ◽

Molecular Dynamics Simulation ◽

Binding Mode ◽

Dynamics Simulation ◽

Hiv 1

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

Current Drug Targets ◽

10.2174/1389450120666190906154412 ◽

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.

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