Table 2 Comparison between different methods to analyse the dynamical behaviour of proteins and their inter-residue communication
From: Dissecting protein architecture with communication blocks and communicating segment pairs
COMMA | Bio3D [11] | GSATools [16] | PyInteraph [10] | PSN-ENM [20] | Taylor et al. [17] | |
|---|---|---|---|---|---|---|
Software availability | ✓ | ✓ | ✓ | ✓ | - | - |
Open source | ✓ | ✓ | ✓ | ✓ | - | - |
Dependencies | MDtraj, Eigen and Numpy python packages | R, Muscle | GNU, Scientific Library, GROMACS | Python, Pymol | - | - |
Programming language | C++, Python | R | C | Python | - | - |
Input trajectory formats | AMBER, GROMACS, NAMD, CHARMM... | GROMACS (.dcd) | GROMACS | AMBER, GROMACS, NAMD, CHARMM... | - | - |
Dynamical properties: | ||||||
non-covalent interactions | ✓ | - | - | ✓ | ✓ | ✓ |
inter-residue distances | ✓ | - | - | - | - | ✓ |
secondary structures | ✓ | - | - | - | - | - |
dynamical correlations | ✓(PCA, LFA, CP) | ✓(ENM-NMA, PCA) | ✓(between frames) | - | ✓(ENM-NMA) | ✓(MI) |
Description levels: | ||||||
residue | ✓ | - | ✓ | ✓ | ✓ | ✓ |
secondary structure | ✓ | - | - | - | - | - |
region/domain | ✓ | ✓ | ✓ | - | - | ✓ |
protein | ✓ | ✓ | ✓ | ✓ | ✓ | ✓ |
Outputs: | ||||||
protein network | ✓ | - | ✓ | ✓ | ✓ | ✓ |
communicating regions | ✓(pathway- and clique-based blocks) | ✓(dynamic domain, correlation network) | ✓(functional fragments) | - | - | ✓(communities) |
communicating segment pairs | ✓ | - | - | - | - | - |
functional domains | - | - | ✓ | - | - | ✓ |
pathways | ✓ | - | ✓ | ✓ | ✓ | ✓ |