SDM: a server for predicting effects of mutations on protein stability

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/sdm2Gates HIT-TB and the EU MM4TB [Project ID: 260872 to A.P.P. and T.L.B.]; Bill & Melinda Gates Foundation [RG60453 to B.O.M.]; Jack Brockhoff Foundation [JBF 4186, 2016 to D.B.A.]; C.J. Martin Research Fellowship from the National Health and Medical Research Council of Australia [APP1072476]; Wellcome Trust Programme Grant [093167/Z/10/Z to D.B.A., T.L.B.]; Newton Fund RCUK-CONFAP Grant awarded by The Medical Research Council (MRC) [MR/M026302/1]. Funding for open access charge: Bill & Melinda Gates Foundation [RG60453] Gates HIT-TB; Wellcome Trust Programme Grant [093167/Z/10/Z]; Newton Fund RCUK-CONFAP Grant awarded by the Medical Research Council (MRC) [MR/M026302/1