NDLI: CAVER: algorithms for analyzing dynamics of tunnels in macromolecules

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IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB) : Volume 13

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CAVER: algorithms for analyzing dynamics of tunnels in macromolecules

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CAVER: algorithms for analyzing dynamics of tunnels in macromolecules

Content Provider	ACM Digital Library
Author	Sebestova, Eva Kozlikova, Barbora Sochor, Jiri Damborsky, Jiri Brezovsky, Jan Pavelka, Antonin
Copyright Year	2016
Description	Author Affiliation: Faculty of Informatics, Botanicka, Brno, Czech Republic(Damborsky, Jiri; Brezovsky, Jan; Masaryk university, Kamenice, Brno, Czech Republic (Sebestova, Eva; Sochor, Jiri); Kozlikova, Barbora; Pavelka, Antonin)
Abstract	The biological function of a macromolecule often requires that a small molecule or ion is transported through its structure. The transport pathway often leads through void spaces in the structure. The properties of transport pathways change significantly in time; therefore, the analysis of a trajectory from molecular dynamics rather than of a single static structure is needed for understanding the function of pathways. The identification and analysis of transport pathways are challenging because of the high complexity and diversity of macromolecular shapes, the thermal motion of their atoms, and the large amount of conformations needed to properly describe conformational space of protein structure. In this paper, we describe the principles of the CAVER 3.0 algorithms for the identification and analysis of properties of transport pathways both in static and dynamic structures. Moreover, we introduce the improved clustering solution for finding tunnels in macromolecules, which is included in the latest CAVER 3.02 version. Voronoi diagrams are used to identify potential pathways in each snapshot of a molecular dynamics trajectory and clustering is then used to find the correspondence between tunnels from different snapshots. Furthermore, the geometrical properties of pathways and their evolution in time are computed and visualized.
Starting Page	505
Ending Page	517
Page Count	13
File Format	PDF
ISSN	15455963
Volume Number	13
Issue Number	3
Journal	IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2016-05-01
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	CAVER Delaunay triangulation Voronoi diagram Average link hierarchical clustering Channel Macromolecule Molecular dynamics Pathway Pore Tunnel
Content Type	Text
Resource Type	Article
Subject	Genetics Biotechnology Applied Mathematics

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CAVER: Algorithms for Analyzing Dynamics of Tunnels in Macromolecules.

Algorithm 772: STRIPACK: Delaunay triangulation and Voronoi diagram on the surface of a sphere

Bregman Voronoi Diagrams: Properties, Algorithms and Applications

Visualizing the Connection Among Convex Hull, Voronoi Diagram and Delaunay Triangulation

Voronoi diagrams and delaunay triangulations (1995).

Fully dynamic delaunay triangulation in logarithmic expected time per operation (1992).

Vector weighted voronoi diagrams and delaunay triangulations (2007).

Computability of partial delaunay triangulation and voronoi diagram (extended abstract) (2002).

Facial Feature Location with Delaunay Triangulation/Voronoi Diagram Calculation

CAVER: algorithms for analyzing dynamics of tunnels in macromolecules

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CAVER: Algorithms for Analyzing Dynamics of Tunnels in Macromolecules.

Algorithm 772: STRIPACK: Delaunay triangulation and Voronoi diagram on the surface of a sphere

Bregman Voronoi Diagrams: Properties, Algorithms and Applications

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Fully dynamic delaunay triangulation in logarithmic expected time per operation (1992).

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CAVER: algorithms for analyzing dynamics of tunnels in macromolecules