Double Force Scanning (DFS) is a computational method to predict rescue sites in proteins.
DFS uses external forces applied to (first-site,second-site) pairs of residues to mimic the effect of a pathogenic mutation (first site) and a candidate rescue mutation (second site). The effect of forces on the protein structure is calculated using the Linear Response Theory combined with the Anisotropic Network Model. The compensatory effect is quantified through a rescuability index, which is > 0 when the structural perturbation induced by the forces at the two sites is smaller than the one produced by a single force at the first site. The rescuability indices of a given second site are combined to generate an overall estimate of its compensatory power, which can be used to predict if the residue is a rescue site.
The program is made available under the GNU Public License for academic scientific purposes and under the condition that proper acknowledgement is made to the authors of the program in publications resulting from the use of the program. Please see the LICENSE file for details.
DFS is available on GitHub. The distribution includes a Python module (dfsutils) that comprises the main classes and functions, as well as the following scripts:
A summary help can be obtained with the –help option, e.g.:
The latest release of the dfs package is available here
Please refer to the INSTALL file in the distribution.
A test directory is also provided to check your installation.
Please refer to the doc directory in the distribution.
A step-by-step tutorial is included, together with a user manual.
If you publish results produced with the DFS or develop methods based on the DFS code, please cite the following paper:
M. Tiberti, A. Pandini, F. Fraternali, A. Fornili, "In silico identification of rescue sites by double force scanning", Bioinformatics, accepted