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CAVER Analyst 2.0: analysis and visualization of channels and tunnels in protein structures and molecular dynamics trajectories

MOTIVATION: Studying the transport paths of ligands, solvents, or ions in transmembrane proteins and proteins with buried binding sites is fundamental to the understanding of their biological function. A detailed analysis of the structural features influencing the transport paths is also important f...

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Detalles Bibliográficos
Autores principales: Jurcik, Adam, Bednar, David, Byska, Jan, Marques, Sergio M, Furmanova, Katarina, Daniel, Lukas, Kokkonen, Piia, Brezovsky, Jan, Strnad, Ondrej, Stourac, Jan, Pavelka, Antonin, Manak, Martin, Damborsky, Jiri, Kozlikova, Barbora
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6184705/
https://www.ncbi.nlm.nih.gov/pubmed/29741570
http://dx.doi.org/10.1093/bioinformatics/bty386
Descripción
Sumario:MOTIVATION: Studying the transport paths of ligands, solvents, or ions in transmembrane proteins and proteins with buried binding sites is fundamental to the understanding of their biological function. A detailed analysis of the structural features influencing the transport paths is also important for engineering proteins for biomedical and biotechnological applications. RESULTS: CAVER Analyst 2.0 is a software tool for quantitative analysis and real-time visualization of tunnels and channels in static and dynamic structures. This version provides the users with many new functions, including advanced techniques for intuitive visual inspection of the spatiotemporal behavior of tunnels and channels. Novel integrated algorithms allow an efficient analysis and data reduction in large protein structures and molecular dynamic simulations. AVAILABILITY AND IMPLEMENTATION: CAVER Analyst 2.0 is a multi-platform standalone Java-based application. Binaries and documentation are freely available at www.caver.cz. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.