CAVER Analyst

CAVER Analyst analyzes and quantifies tunnels, channels, and cavities in protein structures to characterize transport pathways for ligands, solvents, and ions.


Key Features:

  • Quantitative Analysis: Computes quantitative metrics of tunnels, channels, and cavities that influence transport pathways within protein structures.
  • Temporal Visualization: Visualizes spatiotemporal behavior of tunnels and channels across static structures and molecular dynamics trajectories.
  • Advanced Inspection Techniques: Provides techniques for detailed analysis of structural dynamics in large protein complexes and molecular dynamics simulations.
  • Efficient Data Analysis: Implements integrated algorithms for efficient analysis and data reduction of large datasets from static and dynamic protein structures.

Scientific Applications:

  • Biological Function Analysis: Studies transport paths to elucidate mechanisms underlying protein function and interactions.
  • Protein Engineering: Informs design and modification of proteins by characterizing structural features that affect transport pathways.
  • Molecular Dynamics Studies: Analyzes dynamic behavior of protein tunnels and channels within molecular dynamics simulations.

Methodology:

Employs integrated algorithms to perform efficient analysis and data reduction on large datasets derived from static and dynamic protein structures and to handle molecular dynamics simulations.

Topics

Collections

Details

License:
Proprietary
Maturity:
Mature
Cost:
Free of charge (with restrictions)
Tool Type:
desktop application
Operating Systems:
Linux, Windows, Mac
Programming Languages:
Java
Added:
11/7/2015
Last Updated:
11/24/2024

Operations

Publications

Jurcik A, Bednar D, Byska J, Marques SM, Furmanova K, Daniel L, Kokkonen P, Brezovsky J, Strnad O, Stourac J, Pavelka A, Manak M, Damborsky J, Kozlikova B. CAVER Analyst 2.0: analysis and visualization of channels and tunnels in protein structures and molecular dynamics trajectories. Bioinformatics. 2018;34(20):3586-3588. doi:10.1093/bioinformatics/bty386. PMID:29741570. PMCID:PMC6184705.

PMID: 29741570
PMCID: PMC6184705
Funding: - Czech Science Foundation: 16-06096S, 17-07690S - Ministry of Education: LM2015047, LM2015055, LO1214, LO1506, LQ1605 - PhysioIllustration research: 218023 - National Science Centre, Poland: 2017/25/B/NZ1/01307 - Czech Republic: LM2015042 - CERIT-Scientific Cloud: LM2015085

Documentation

Downloads

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