Channel identification software tools | Protein structure data analysis

An online tool that locates and measures pockets and voids on 3D protein structures. CASTp includes annotated functional information of specific residues on the protein structure. The annotations are derived from the Protein Data Bank (PDB), Swiss-Prot, as well as Online Mendelian Inheritance in Man (OMIM), the latter contains information on the variant single nucleotide polymorphisms (SNPs) that are known to cause disease.

Provides rapid, accurate and fully automated calculation of tunnels and channels in static structures. The molecules amendable to analysis of CAVER include proteins, nucleic acids or inorganic materials. CAVER can be used either as PyMol plugin or independent application CAVER Analyst. CAVER Analyst has been designed for easy set-up of calculation, visualization of results and efficient data analysis. It can be used for both static structures and molecular ensembles from molecular dynamic simulations or NMR.

A fully automated method designed to detect and characterise transmembrane protein channels from their 3D structure. A stepwise procedure is followed in which the pore centre and pore axis are first identified and optimised using geometric criteria, and then the biggest and longest cavity through the channel is detected. Finally, pore features, including diameter profiles, pore-lining residues, size, shape and regularity of the pore are calculated, providing a quantitative and visual characterization of the channel.

A tool for the identification of high clearance pathways or corridors which represent molecular channels in the complement space of proteins. MolAxis is extremely efficient because it samples the medial axis of the complement of the molecule, reducing the problem dimension to two, since the medial axis is composed of surface patches. It is designed to analyze proteins channels, calculate pore dimensions and analyze atom accessibility.

Finds protein cavities throughout Molecular Dynamics (MD) simulation trajectories. trj_cavity can analyse the solvent occupancy of the cavities identified. This tool is implemented within the GROMACS framework for the rapid identification and characterization of cavities detected within MD trajectories. It is also optimized for usability and computational efficiency and is applicable to the time-dependent analysis of any cavity topology, and optional specialized descriptors can be used to characterize, protein channels.