DockVis: Visual Analysis of Molecular Docking Trajectories
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Date
2020Author
Furmanová, Katarína
Vávra, Ondřej
Kozlíková, Barbora
Damborský, Jiří
Vonásek, Vojtěch
Bednář, David
Byška, Jan
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Computation of trajectories for ligand binding and unbinding via protein tunnels and channels is important for predicting possible protein–ligand interactions. These highly complex processes can be simulated by several software tools, which provide biochemists with valuable information for drug design or protein engineering applications. This paper focuses on aiding this exploration process by introducing the DockVis visual analysis tool. DockVis operates with the multivariate output data from one of the latest available tools for the prediction of ligand transport, CaverDock. DockVis provides the users with several linked views, combining the 2D abstracted depictions of ligands and their surroundings and properties with the 3D view. In this way, we enable the users to perceive the spatial configurations of ligand passing through the protein tunnel. The users are initially visually directed to the most relevant parts of ligand trajectories, which can be then explored in higher detail by the follow‐up analyses. DockVis was designed in tight collaboration with protein engineers developing the CaverDock tool. However, the concept of DockVis can be extended to any other tool predicting ligand pathways by the molecular docking. DockVis will be made available to the wide user community as part of the Caver Analyst 3.0 software package ().
BibTeX
@article {10.1111:cgf.14048,
journal = {Computer Graphics Forum},
title = {{DockVis: Visual Analysis of Molecular Docking Trajectories}},
author = {Furmanová, Katarína and Vávra, Ondřej and Kozlíková, Barbora and Damborský, Jiří and Vonásek, Vojtěch and Bednář, David and Byška, Jan},
year = {2020},
publisher = {© 2020 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd},
ISSN = {1467-8659},
DOI = {10.1111/cgf.14048}
}
journal = {Computer Graphics Forum},
title = {{DockVis: Visual Analysis of Molecular Docking Trajectories}},
author = {Furmanová, Katarína and Vávra, Ondřej and Kozlíková, Barbora and Damborský, Jiří and Vonásek, Vojtěch and Bednář, David and Byška, Jan},
year = {2020},
publisher = {© 2020 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd},
ISSN = {1467-8659},
DOI = {10.1111/cgf.14048}
}