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CAVER 3.0: a tool for the analysis of transport pathways in dynamic protein structures.

Chovancova E, Pavelka A, Benes P, Strnad O, Brezovsky J, Kozlikova B, Gora A, Sustr V, Klvana M, Medek P, Biedermannova L, Sochor J, Damborsky J - PLoS Comput. Biol. (2012)

Bottom Line: CAVER 3.0 safely identified and reliably estimated the importance of all previously published DhaA tunnels, including the tunnels closed in DhaA crystal structures.Obtained results clearly demonstrate that analysis of molecular dynamics simulation is essential for the estimation of pathway characteristics and elucidation of the structural basis of the tunnel gating.CAVER 3.0 paves the way for the study of important biochemical phenomena in the area of molecular transport, molecular recognition and enzymatic catalysis.

View Article: PubMed Central - PubMed

Affiliation: Loschmidt Laboratories, Department of Experimental Biology and Research Centre for Toxic Compounds in the Environment, Faculty of Science, Masaryk University, Brno, Czech Republic.

ABSTRACT
Tunnels and channels facilitate the transport of small molecules, ions and water solvent in a large variety of proteins. Characteristics of individual transport pathways, including their geometry, physico-chemical properties and dynamics are instrumental for understanding of structure-function relationships of these proteins, for the design of new inhibitors and construction of improved biocatalysts. CAVER is a software tool widely used for the identification and characterization of transport pathways in static macromolecular structures. Herein we present a new version of CAVER enabling automatic analysis of tunnels and channels in large ensembles of protein conformations. CAVER 3.0 implements new algorithms for the calculation and clustering of pathways. A trajectory from a molecular dynamics simulation serves as the typical input, while detailed characteristics and summary statistics of the time evolution of individual pathways are provided in the outputs. To illustrate the capabilities of CAVER 3.0, the tool was applied for the analysis of molecular dynamics simulation of the microbial enzyme haloalkane dehalogenase DhaA. CAVER 3.0 safely identified and reliably estimated the importance of all previously published DhaA tunnels, including the tunnels closed in DhaA crystal structures. Obtained results clearly demonstrate that analysis of molecular dynamics simulation is essential for the estimation of pathway characteristics and elucidation of the structural basis of the tunnel gating. CAVER 3.0 paves the way for the study of important biochemical phenomena in the area of molecular transport, molecular recognition and enzymatic catalysis. The software is freely available as a multiplatform command-line application at http://www.caver.cz.

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Time evolution of the bottleneck radii of DhaA tunnels identified by CAVER 3.0.The color map ranges from very narrow (green) to wide (red) bottlenecks. White color indicates that no pathway with bottleneck radius ≥0.9 Å was identified for the given pathway cluster in the given snapshot.
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pcbi-1002708-g003: Time evolution of the bottleneck radii of DhaA tunnels identified by CAVER 3.0.The color map ranges from very narrow (green) to wide (red) bottlenecks. White color indicates that no pathway with bottleneck radius ≥0.9 Å was identified for the given pathway cluster in the given snapshot.

Mentions: We found a good agreement between the results of CAVER 3.0 and the previous MD and RAMD study of DhaA product release pathways [15] (Text S2): (i) all five previously proposed DhaA pathways were reliably identified by CAVER 3.0, with estimated relative importance p1≫p2b≫p2a>p2c∼p3; (ii) the p1 tunnel was found to be the dominant transport pathway—it was the most frequently identified collective pathway, had by far the highest maximum and mean radii of bottlenecks and was frequently open for water molecules (Table 1, Figure 3); (iii) based on all studied characteristics, the p2b and p2a tunnels were found to be the second and the third most important, respectively; (iv) the p2c and p3 pathways were only rarely identified, however, compared to other possible tunnels ranked at lower places, the p2c and p3 pathways were still significantly more frequent and showed a considerable widening of the bottlenecks in some snapshots (up to 1.2 Å, Table S2).


CAVER 3.0: a tool for the analysis of transport pathways in dynamic protein structures.

Chovancova E, Pavelka A, Benes P, Strnad O, Brezovsky J, Kozlikova B, Gora A, Sustr V, Klvana M, Medek P, Biedermannova L, Sochor J, Damborsky J - PLoS Comput. Biol. (2012)

Time evolution of the bottleneck radii of DhaA tunnels identified by CAVER 3.0.The color map ranges from very narrow (green) to wide (red) bottlenecks. White color indicates that no pathway with bottleneck radius ≥0.9 Å was identified for the given pathway cluster in the given snapshot.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3475669&req=5

pcbi-1002708-g003: Time evolution of the bottleneck radii of DhaA tunnels identified by CAVER 3.0.The color map ranges from very narrow (green) to wide (red) bottlenecks. White color indicates that no pathway with bottleneck radius ≥0.9 Å was identified for the given pathway cluster in the given snapshot.
Mentions: We found a good agreement between the results of CAVER 3.0 and the previous MD and RAMD study of DhaA product release pathways [15] (Text S2): (i) all five previously proposed DhaA pathways were reliably identified by CAVER 3.0, with estimated relative importance p1≫p2b≫p2a>p2c∼p3; (ii) the p1 tunnel was found to be the dominant transport pathway—it was the most frequently identified collective pathway, had by far the highest maximum and mean radii of bottlenecks and was frequently open for water molecules (Table 1, Figure 3); (iii) based on all studied characteristics, the p2b and p2a tunnels were found to be the second and the third most important, respectively; (iv) the p2c and p3 pathways were only rarely identified, however, compared to other possible tunnels ranked at lower places, the p2c and p3 pathways were still significantly more frequent and showed a considerable widening of the bottlenecks in some snapshots (up to 1.2 Å, Table S2).

Bottom Line: CAVER 3.0 safely identified and reliably estimated the importance of all previously published DhaA tunnels, including the tunnels closed in DhaA crystal structures.Obtained results clearly demonstrate that analysis of molecular dynamics simulation is essential for the estimation of pathway characteristics and elucidation of the structural basis of the tunnel gating.CAVER 3.0 paves the way for the study of important biochemical phenomena in the area of molecular transport, molecular recognition and enzymatic catalysis.

View Article: PubMed Central - PubMed

Affiliation: Loschmidt Laboratories, Department of Experimental Biology and Research Centre for Toxic Compounds in the Environment, Faculty of Science, Masaryk University, Brno, Czech Republic.

ABSTRACT
Tunnels and channels facilitate the transport of small molecules, ions and water solvent in a large variety of proteins. Characteristics of individual transport pathways, including their geometry, physico-chemical properties and dynamics are instrumental for understanding of structure-function relationships of these proteins, for the design of new inhibitors and construction of improved biocatalysts. CAVER is a software tool widely used for the identification and characterization of transport pathways in static macromolecular structures. Herein we present a new version of CAVER enabling automatic analysis of tunnels and channels in large ensembles of protein conformations. CAVER 3.0 implements new algorithms for the calculation and clustering of pathways. A trajectory from a molecular dynamics simulation serves as the typical input, while detailed characteristics and summary statistics of the time evolution of individual pathways are provided in the outputs. To illustrate the capabilities of CAVER 3.0, the tool was applied for the analysis of molecular dynamics simulation of the microbial enzyme haloalkane dehalogenase DhaA. CAVER 3.0 safely identified and reliably estimated the importance of all previously published DhaA tunnels, including the tunnels closed in DhaA crystal structures. Obtained results clearly demonstrate that analysis of molecular dynamics simulation is essential for the estimation of pathway characteristics and elucidation of the structural basis of the tunnel gating. CAVER 3.0 paves the way for the study of important biochemical phenomena in the area of molecular transport, molecular recognition and enzymatic catalysis. The software is freely available as a multiplatform command-line application at http://www.caver.cz.

Show MeSH