PAVELKA, Antonín, Eva ŠEBESTOVÁ, Barbora KOZLÍKOVÁ, Jan BREZOVSKÝ, Jiří SOCHOR and Jiří DAMBORSKÝ. CAVER: Algorithms for Analyzing Dynamics of Tunnels in Macromolecules. IEEE/ACM Transactions on Computational Biology and Bioinformatics, IEEE Computer Society, 2016, vol. 13, No 3, p. 505 - 517. ISSN 1545-5963. doi:10.1109/TCBB.2015.2459680.
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Basic information
Original name CAVER: Algorithms for Analyzing Dynamics of Tunnels in Macromolecules
Authors PAVELKA, Antonín (203 Czech Republic, guarantor, belonging to the institution), Eva ŠEBESTOVÁ (203 Czech Republic, belonging to the institution), Barbora KOZLÍKOVÁ (203 Czech Republic, belonging to the institution), Jan BREZOVSKÝ (203 Czech Republic, belonging to the institution), Jiří SOCHOR (203 Czech Republic, belonging to the institution) and Jiří DAMBORSKÝ (203 Czech Republic, belonging to the institution).
Edition IEEE/ACM Transactions on Computational Biology and Bioinformatics, IEEE Computer Society, 2016, 1545-5963.
Other information
Original language English
Type of outcome Article in a journal
Field of Study 10201 Computer sciences, information science, bioinformatics
Country of publisher United States of America
Confidentiality degree is not subject to a state or trade secret
WWW URL
Impact factor Impact factor: 1.955
RIV identification code RIV/00216224:14330/16:00089113
Organization unit Faculty of Informatics
Doi http://dx.doi.org/10.1109/TCBB.2015.2459680
UT WoS 000378528100010
Keywords in English tunnel; pore; channel; pathway; macromolecule; molecular dynamics; CAVER; Voronoi diagram; Delaunay triangulation; average link hierarchical clustering
Tags International impact, Reviewed
Changed by Changed by: RNDr. Pavel Šmerk, Ph.D., učo 3880. Changed: 27/4/2017 05:44.
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.
Links
EE2.3.30.0037, research and development projectName: Zaměstnáním nejlepších mladých vědců k rozvoji mezinárodní spolupráce
LM2010005, research and development projectName: Velká infrastruktura CESNET (Acronym: VI CESNET)
Investor: Ministry of Education, Youth and Sports of the CR, Large Infrastructures for Research, Development and Innovation
LO1214, research and development projectName: Centrum pro výzkum toxických látek v prostředí (Acronym: RECETOX)
Investor: Ministry of Education, Youth and Sports of the CR, National Feasibility Programme I
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