TY - JOUR
AU - Betts, Matthew J
AU - Lu, Qianhao
AU - Jiang, YingYing
AU - Drusko, Armin
AU - Wichmann, Oliver
AU - Utz, Mathias
AU - Valtierra-Gutiérrez, Ilse A
AU - Schlesner, Matthias
AU - Jaeger, Natalie
AU - Jones, David
AU - Pfister, Stefan
AU - Lichter, Peter
AU - Eils, Roland
AU - Siebert, Reiner
AU - Bork, Peer
AU - Apic, Gordana
AU - Gavin, Anne-Claude
AU - Russell, Robert B
TI - Mechismo: predicting the mechanistic impact of mutations and modifications on molecular interactions.
JO - Nucleic acids symposium series
VL - 43
IS - 2
SN - 1362-4962
CY - Oxford
PB - Oxford Univ. Press44364
M1 - DKFZ-2017-02253
SP - e10 - e10
PY - 2015
AB - Systematic interrogation of mutation or protein modification data is important to identify sites with functional consequences and to deduce global consequences from large data sets. Mechismo (mechismo.russellab.org) enables simultaneous consideration of thousands of 3D structures and biomolecular interactions to predict rapidly mechanistic consequences for mutations and modifications. As useful functional information often only comes from homologous proteins, we benchmarked the accuracy of predictions as a function of protein/structure sequence similarity, which permits the use of relatively weak sequence similarities with an appropriate confidence measure. For protein-protein, protein-nucleic acid and a subset of protein-chemical interactions, we also developed and benchmarked a measure of whether modifications are likely to enhance or diminish the interactions, which can assist the detection of modifications with specific effects. Analysis of high-throughput sequencing data shows that the approach can identify interesting differences between cancers, and application to proteomics data finds potential mechanistic insights for how post-translational modifications can alter biomolecular interactions.
KW - Proteins (NLM Chemicals)
LB - PUB:(DE-HGF)16
C6 - pmid:25392414
C2 - pmc:PMC4333368
DO - DOI:10.1093/nar/gku1094
UR - https://inrepo02.dkfz.de/record/126138
ER -