Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/15024
Title: In silico identification of rescue sites by double force scanning
Authors: Tiberti, M
Pandini, A
Fraternali, F
Fornili, A
Issue Date: 2017
Citation: Bioinformatics, 2017
Abstract: Motivation: A deleterious amino acid change in a protein can be compensated by a second-site rescue mutation. These compensatory mechanisms can be mimicked by drugs. In particular, the location of rescue mutations can be used to identify protein regions that can be targeted by small molecules to reactivate a damaged mutant. Results: We present the first general computational method to detect rescue sites. By mimicking the effect of mutations through the application of forces, the Double Force Scanning (DFS) method identifies the second-site residues that make the protein structure most resilient to the effect of pathogenic mutations. We tested DFS predictions against two datasets containing experimentally validated and putative evolutionary-related rescue sites. A remarkably good agreement was found between predictions and experimental data. Indeed, almost half of the rescue sites in p53 was correctly predicted by DFS, with 65% of remaining sites in contact with DFS predictions. Similar results were found for other proteins in the evolutionary dataset.
URI: http://bura.brunel.ac.uk/handle/2438/15024
DOI: http://dx.doi.org/10.1093/bioinformatics/btx515
ISSN: 1367-4803
Appears in Collections:Dept of Computer Science Research Papers

Files in This Item:
File Description SizeFormat 
FullText.pdf996.44 kBAdobe PDFView/Open


Items in BURA are protected by copyright, with all rights reserved, unless otherwise indicated.