4.8 Article

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

Journal

NUCLEIC ACIDS RESEARCH
Volume 45, Issue W1, Pages W229-W235

Publisher

OXFORD UNIV PRESS
DOI: 10.1093/nar/gkx439

Keywords

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Funding

  1. Gates HIT-TB
  2. EU MM4TB [260872]
  3. Bill & Melinda Gates Foundation [RG60453]
  4. Jack Brockhoff Foundation [JBF 4186]
  5. C.J. Martin Research Fellowship from the National Health and Medical Research Council of Australia [APP1072476]
  6. Wellcome Trust [093167/Z/10/Z]
  7. Newton Fund RCUK-CONFAP Grant - Medical Research Council (MRC) [MR/M026302/1]
  8. Wellcome Trust [093167/Z/10/Z] Funding Source: Wellcome Trust
  9. Medical Research Council [MR/M026302/1, MR/N501864/1] Funding Source: researchfish
  10. MRC [MR/N501864/1, MR/M026302/1] Funding Source: UKRI

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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

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