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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 DhaA p1 tunnel.(A) Evolution of the p1 tunnel bottleneck radius over time. The dotted orange lines indicate bottleneck radii of the p1 tunnel in DhaA crystal structures with added hydrogen atoms: PDB-IDs 1BN6 and 1BN7 (bottleneck radius 1.2 Å) and 1CQW (1.3 Å). The four green circles indicate bottleneck radii of the p1 tunnel from the 2.76 ns (bottleneck radius 1.4 Å), 5.85 ns (2.3 Å), 7.57 ns (0.9 Å) and the 7.72 ns (0.9 Å) snapshots from the molecular dynamics simulation of DhaA. (B) The p1 tunnel identified in DhaA crystal structures with added hydrogen atoms (PDB-IDs 1CQW, 1BN6, 1BN7). (C) The p1 tunnel identified in the 2.76 ns, 5.85 ns, 7.57 ns and 7.72 ns snapshots of the MD trajectory of DhaA.
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pcbi-1002708-g004: Time evolution of the DhaA p1 tunnel.(A) Evolution of the p1 tunnel bottleneck radius over time. The dotted orange lines indicate bottleneck radii of the p1 tunnel in DhaA crystal structures with added hydrogen atoms: PDB-IDs 1BN6 and 1BN7 (bottleneck radius 1.2 Å) and 1CQW (1.3 Å). The four green circles indicate bottleneck radii of the p1 tunnel from the 2.76 ns (bottleneck radius 1.4 Å), 5.85 ns (2.3 Å), 7.57 ns (0.9 Å) and the 7.72 ns (0.9 Å) snapshots from the molecular dynamics simulation of DhaA. (B) The p1 tunnel identified in DhaA crystal structures with added hydrogen atoms (PDB-IDs 1CQW, 1BN6, 1BN7). (C) The p1 tunnel identified in the 2.76 ns, 5.85 ns, 7.57 ns and 7.72 ns snapshots of the MD trajectory of DhaA.

Mentions: The capability of CAVER 3.0 to analyze dynamical systems is essential for the identification of biochemically relevant tunnels. All previously known DhaA tunnels were reliably identified by the analysis of the 10 ns MD simulation snapshots, while only two of them—p1 and p2ab—were found in the crystal structures of DhaA (PDB-IDs 1CQW, 1BN7 and 1BN6) under the same calculation settings (Protocol S4). By decreasing the probe radius from 0.9 Å to 0.8 Å, more than ten potential tunnels were identified in each crystal structure, including the p1 variants (p1a, p1a′ and p1b), p2ab and p3 tunnels (Table S3). The p2c tunnel was not observed. While the p1 tunnel was clearly wider and had higher throughput than all other tunnels in all three crystal structures, the remaining tunnels (with the exception of p2a and p2b in the structure PDB-ID 1BN6) had very similar characteristics to one another (Table S3), demonstrating that it is difficult to identify the biochemically relevant tunnels by analyzing the static crystal structures only. Such analysis may easily overlook relevant tunnels that are temporarily closed, and/or identify tunnels whose relevancy is disputable. In contrast, tunnel characteristics obtained from the analysis of MD simulation, such as the frequency of tunnel identification, the frequency of tunnel opening or the bottleneck radius fluctuation, may be used as indicators of the tunnel's functional relevancy (Table S2). This can be demonstrated on the exemplary analysis of the time evolution of the p1 tunnel bottleneck. In all three available crystal structures of DhaA with added hydrogen atoms, the value of the bottleneck radius 1.2 Å (PDB-IDs 1BN6, 1BN7) and 1.3 Å (PDB-ID 1CQW) indicates that the p1 tunnel may not be relevant, considering the usual probe radius of 1.4 Å. In the MD simulation, however, the p1 tunnel was open in a large number of snapshots (bottleneck radius wider than 1.4 Å), suggesting the importance of the tunnel for enzyme function (Figure 3 and Figure 4). The maximum radius of the p1 tunnel bottleneck in the MD simulation was 2.3 Å (Figure 4 and Table S4).


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 DhaA p1 tunnel.(A) Evolution of the p1 tunnel bottleneck radius over time. The dotted orange lines indicate bottleneck radii of the p1 tunnel in DhaA crystal structures with added hydrogen atoms: PDB-IDs 1BN6 and 1BN7 (bottleneck radius 1.2 Å) and 1CQW (1.3 Å). The four green circles indicate bottleneck radii of the p1 tunnel from the 2.76 ns (bottleneck radius 1.4 Å), 5.85 ns (2.3 Å), 7.57 ns (0.9 Å) and the 7.72 ns (0.9 Å) snapshots from the molecular dynamics simulation of DhaA. (B) The p1 tunnel identified in DhaA crystal structures with added hydrogen atoms (PDB-IDs 1CQW, 1BN6, 1BN7). (C) The p1 tunnel identified in the 2.76 ns, 5.85 ns, 7.57 ns and 7.72 ns snapshots of the MD trajectory of DhaA.
© Copyright Policy
Related In: Results  -  Collection

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

pcbi-1002708-g004: Time evolution of the DhaA p1 tunnel.(A) Evolution of the p1 tunnel bottleneck radius over time. The dotted orange lines indicate bottleneck radii of the p1 tunnel in DhaA crystal structures with added hydrogen atoms: PDB-IDs 1BN6 and 1BN7 (bottleneck radius 1.2 Å) and 1CQW (1.3 Å). The four green circles indicate bottleneck radii of the p1 tunnel from the 2.76 ns (bottleneck radius 1.4 Å), 5.85 ns (2.3 Å), 7.57 ns (0.9 Å) and the 7.72 ns (0.9 Å) snapshots from the molecular dynamics simulation of DhaA. (B) The p1 tunnel identified in DhaA crystal structures with added hydrogen atoms (PDB-IDs 1CQW, 1BN6, 1BN7). (C) The p1 tunnel identified in the 2.76 ns, 5.85 ns, 7.57 ns and 7.72 ns snapshots of the MD trajectory of DhaA.
Mentions: The capability of CAVER 3.0 to analyze dynamical systems is essential for the identification of biochemically relevant tunnels. All previously known DhaA tunnels were reliably identified by the analysis of the 10 ns MD simulation snapshots, while only two of them—p1 and p2ab—were found in the crystal structures of DhaA (PDB-IDs 1CQW, 1BN7 and 1BN6) under the same calculation settings (Protocol S4). By decreasing the probe radius from 0.9 Å to 0.8 Å, more than ten potential tunnels were identified in each crystal structure, including the p1 variants (p1a, p1a′ and p1b), p2ab and p3 tunnels (Table S3). The p2c tunnel was not observed. While the p1 tunnel was clearly wider and had higher throughput than all other tunnels in all three crystal structures, the remaining tunnels (with the exception of p2a and p2b in the structure PDB-ID 1BN6) had very similar characteristics to one another (Table S3), demonstrating that it is difficult to identify the biochemically relevant tunnels by analyzing the static crystal structures only. Such analysis may easily overlook relevant tunnels that are temporarily closed, and/or identify tunnels whose relevancy is disputable. In contrast, tunnel characteristics obtained from the analysis of MD simulation, such as the frequency of tunnel identification, the frequency of tunnel opening or the bottleneck radius fluctuation, may be used as indicators of the tunnel's functional relevancy (Table S2). This can be demonstrated on the exemplary analysis of the time evolution of the p1 tunnel bottleneck. In all three available crystal structures of DhaA with added hydrogen atoms, the value of the bottleneck radius 1.2 Å (PDB-IDs 1BN6, 1BN7) and 1.3 Å (PDB-ID 1CQW) indicates that the p1 tunnel may not be relevant, considering the usual probe radius of 1.4 Å. In the MD simulation, however, the p1 tunnel was open in a large number of snapshots (bottleneck radius wider than 1.4 Å), suggesting the importance of the tunnel for enzyme function (Figure 3 and Figure 4). The maximum radius of the p1 tunnel bottleneck in the MD simulation was 2.3 Å (Figure 4 and Table S4).

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