SDM: a server for predicting effects of mutations on protein stability. Issue Volume 45:Issue W1(2017) (19th May 2017)

• Record Type: Journal Article
• Authors: Pandurangan, Arun Prasad; Ochoa-Montaño, Bernardo; Ascher, David B.; Blundell, Tom L.
• Is Part Of: Nucleic acids research. Volume 45:Issue W1(2017)
• Page Start: W229
• Page End: W235
• Publication Date: 2017-05-19
• Subjects: Nucleic acids -- Periodicals; Molecular biology -- Periodicals; 572.805
• DOI: 10.1093/nar/gkx439
• Languages: English
• ISSNs: 0305-1048

Abstract

Abstract: Here, we report a webserver for the improved SDM, used for predicting the effects of mutations on protein stability. As a pioneering knowledge-based approach, SDM has been highlighted as the most appropriate method to use in combination with many other approaches. We have updated the environment-specific amino-acid substitution tables based on the current expanded PDB (a 5-fold increase in information), and introduced new residue-conformation and interaction parameters, including packing density and residue depth. The updated server has been extensively tested using a benchmark containing 2690 point mutations from 132 different protein structures. The revised method correlates well against the hypothetical reverse mutations, better than comparable methods built using machine-learning approaches, highlighting the strength of our knowledge-based approach for identifying stabilising mutations. Given a PDB file (a Protein Data Bank file format containing the 3D coordinates of the protein atoms), and a point mutation, the server calculates the stability difference score between the wildtype and mutant protein. The server is available at http://structure.bioc.cam.ac.uk/sdm2