Home > Publications database > Mechismo: predicting the mechanistic impact of mutations and modifications on molecular interactions. > print

001     126138
005     20240228140810.0
024 7 _ |a 10.1093/nar/gku1094
|2 doi
024 7 _ |a pmid:25392414
|2 pmid
024 7 _ |a pmc:PMC4333368
|2 pmc
024 7 _ |a 0261-3166
|2 ISSN
024 7 _ |a 0305-1048
|2 ISSN
024 7 _ |a 1362-4962
|2 ISSN
024 7 _ |a 1746-8272
|2 ISSN
024 7 _ |a altmetric:2878961
|2 altmetric
037 _ _ |a DKFZ-2017-02253
041 _ _ |a eng
082 _ _ |a 540
100 1 _ |a Betts, Matthew J
|b 0
245 _ _ |a Mechismo: predicting the mechanistic impact of mutations and modifications on molecular interactions.
260 _ _ |a Oxford
|c 2015
|b Oxford Univ. Press44364
336 7 _ |a article
|2 DRIVER
336 7 _ |a Output Types/Journal article
|2 DataCite
336 7 _ |a Journal Article
|b journal
|m journal
|0 PUB:(DE-HGF)16
|s 1508399112_6846
|2 PUB:(DE-HGF)
336 7 _ |a ARTICLE
|2 BibTeX
336 7 _ |a JOURNAL_ARTICLE
|2 ORCID
336 7 _ |a Journal Article
|0 0
|2 EndNote
520 _ _ |a 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.
536 _ _ |a 312 - Functional and structural genomics (POF3-312)
|0 G:(DE-HGF)POF3-312
|c POF3-312
|f POF III
|x 0
588 _ _ |a Dataset connected to CrossRef, PubMed,
650 _ 7 |a Proteins
|2 NLM Chemicals
700 1 _ |a Lu, Qianhao
|b 1
700 1 _ |a Jiang, YingYing
|b 2
700 1 _ |a Drusko, Armin
|b 3
700 1 _ |a Wichmann, Oliver
|b 4
700 1 _ |a Utz, Mathias
|b 5
700 1 _ |a Valtierra-Gutiérrez, Ilse A
|b 6
700 1 _ |a Schlesner, Matthias
|0 P:(DE-He78)f2a782242acf94a3114d75c45dc75b37
|b 7
|u dkfz
700 1 _ |a Jaeger, Natalie
|0 P:(DE-HGF)0
|b 8
700 1 _ |a Jones, David
|0 P:(DE-He78)551bb92841f634070997aa168d818492
|b 9
|u dkfz
700 1 _ |a Pfister, Stefan
|0 P:(DE-He78)f746aa965c4e1af518b016de3aaff5d9
|b 10
|u dkfz
700 1 _ |a Lichter, Peter
|0 P:(DE-He78)e13b4363c5fe858044ef8a39c02c870c
|b 11
|u dkfz
700 1 _ |a Eils, Roland
|0 P:(DE-He78)78b6aa82148e60b4d91e3a37a6d3d9a0
|b 12
|u dkfz
700 1 _ |a Siebert, Reiner
|b 13
700 1 _ |a Bork, Peer
|b 14
700 1 _ |a Apic, Gordana
|b 15
700 1 _ |a Gavin, Anne-Claude
|b 16
700 1 _ |a Russell, Robert B
|b 17
773 _ _ |a 10.1093/nar/gku1094
|g Vol. 43, no. 2, p. e10 - e10
|0 PERI:(DE-600)2205588-5
|n 2
|p e10 - e10
|t Nucleic acids symposium series
|v 43
|y 2015
|x 1362-4962
909 C O |o oai:inrepo02.dkfz.de:126138
|p VDB
910 1 _ |a Deutsches Krebsforschungszentrum
|0 I:(DE-588b)2036810-0
|k DKFZ
|b 7
|6 P:(DE-He78)f2a782242acf94a3114d75c45dc75b37
910 1 _ |a Deutsches Krebsforschungszentrum
|0 I:(DE-588b)2036810-0
|k DKFZ
|b 8
|6 P:(DE-HGF)0
910 1 _ |a Deutsches Krebsforschungszentrum
|0 I:(DE-588b)2036810-0
|k DKFZ
|b 9
|6 P:(DE-He78)551bb92841f634070997aa168d818492
910 1 _ |a Deutsches Krebsforschungszentrum
|0 I:(DE-588b)2036810-0
|k DKFZ
|b 10
|6 P:(DE-He78)f746aa965c4e1af518b016de3aaff5d9
910 1 _ |a Deutsches Krebsforschungszentrum
|0 I:(DE-588b)2036810-0
|k DKFZ
|b 11
|6 P:(DE-He78)e13b4363c5fe858044ef8a39c02c870c
910 1 _ |a Deutsches Krebsforschungszentrum
|0 I:(DE-588b)2036810-0
|k DKFZ
|b 12
|6 P:(DE-He78)78b6aa82148e60b4d91e3a37a6d3d9a0
913 1 _ |a DE-HGF
|l Krebsforschung
|1 G:(DE-HGF)POF3-310
|0 G:(DE-HGF)POF3-312
|2 G:(DE-HGF)POF3-300
|v Functional and structural genomics
|x 0
|4 G:(DE-HGF)POF
|3 G:(DE-HGF)POF3
|b Gesundheit
914 1 _ |y 2015
915 _ _ |a Allianz-Lizenz / DFG
|0 StatID:(DE-HGF)0400
|2 StatID
915 _ _ |a Nationallizenz
|0 StatID:(DE-HGF)0420
|2 StatID
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0200
|2 StatID
|b SCOPUS
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0300
|2 StatID
|b Medline
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0310
|2 StatID
|b NCBI Molecular Biology Database
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0501
|2 StatID
|b DOAJ Seal
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0500
|2 StatID
|b DOAJ
915 _ _ |a JCR
|0 StatID:(DE-HGF)0100
|2 StatID
|b NUCLEIC ACIDS RES : 2015
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0199
|2 StatID
|b Thomson Reuters Master Journal List
915 _ _ |a WoS
|0 StatID:(DE-HGF)0110
|2 StatID
|b Science Citation Index
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0150
|2 StatID
|b Web of Science Core Collection
915 _ _ |a WoS
|0 StatID:(DE-HGF)0111
|2 StatID
|b Science Citation Index Expanded
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1030
|2 StatID
|b Current Contents - Life Sciences
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1050
|2 StatID
|b BIOSIS Previews
915 _ _ |a IF >= 5
|0 StatID:(DE-HGF)9905
|2 StatID
|b NUCLEIC ACIDS RES : 2015
920 1 _ |0 I:(DE-He78)B080-20160331
|k B080
|l Theoretische Bioinformatik
|x 0
920 1 _ |0 I:(DE-He78)B062-20160331
|k B062
|l Pädiatrische Neuroonkologie
|x 1
920 1 _ |0 I:(DE-He78)B060-20160331
|k B060
|l Molekulare Genetik
|x 2
980 _ _ |a journal
980 _ _ |a VDB
980 _ _ |a I:(DE-He78)B080-20160331
980 _ _ |a I:(DE-He78)B062-20160331
980 _ _ |a I:(DE-He78)B060-20160331
980 _ _ |a UNRESTRICTED

LibraryCollectionCLSMajorCLSMinorLanguageAuthor
Marc 21