Evidence map›Paper›PMID 25392414›Full record

ArticleNucleic acids research2015

Mechismo: predicting the mechanistic impact of mutations and modifications on molecular interactions.

Matthew J Betts, Qianhao Lu, YingYing Jiang, Armin Drusko, Oliver Wichmann, Mathias Utz, Ilse A Valtierra-Gutiérrez, Matthias Schlesner, Natalie Jaeger, David T Jones and 8 more

Abstract read
In one paragraph

Article in Nucleic acids research, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 50 papers.

0numbers the graph read from it
0cells of the map it votes in
50citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

50 citing papers in PubMed.

  1. Article
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  4. Molecular Tweezers Block the Functional Pore of a Protein Machine.Journal of the American Chemical Society · 2025
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

18 authors.

Matthew J BettsCell Networks, University of Heidelberg, Im Neuenheimer Feld 267, 69120 Heidelberg, Germany Bioquant, University of Heidelberg, Im Neuenheimer Feld 267, 69120 Heidelberg, Germany.
Qianhao LuCell Networks, University of Heidelberg, Im Neuenheimer Feld 267, 69120 Heidelberg, Germany Bioquant, University of Heidelberg, Im Neuenheimer Feld 267, 69120 Heidelberg, Germany.
YingYing JiangCell Networks, University of Heidelberg, Im Neuenheimer Feld 267, 69120 Heidelberg, Germany Bioquant, University of Heidelberg, Im Neuenheimer Feld 267, 69120 Heidelberg, Germany.
Armin DruskoCell Networks, University of Heidelberg, Im Neuenheimer Feld 267, 69120 Heidelberg, Germany Bioquant, University of Heidelberg, Im Neuenheimer Feld 267, 69120 Heidelberg, Germany.
Oliver WichmannCell Networks, University of Heidelberg, Im Neuenheimer Feld 267, 69120 Heidelberg, Germany Bioquant, University of Heidelberg, Im Neuenheimer Feld 267, 69120 Heidelberg, Germany.
Mathias UtzCell Networks, University of Heidelberg, Im Neuenheimer Feld 267, 69120 Heidelberg, Germany Bioquant, University of Heidelberg, Im Neuenheimer Feld 267, 69120 Heidelberg, Germany.
Ilse A Valtierra-GutiérrezCell Networks, University of Heidelberg, Im Neuenheimer Feld 267, 69120 Heidelberg, Germany Bioquant, University of Heidelberg, Im Neuenheimer Feld 267, 69120 Heidelberg, Germany.
Matthias SchlesnerDeutsches Krebsforschungszentrum, Im Neuenheimer Feld 280, 69120 Heidelberg, Germany.
Natalie JaegerDeutsches Krebsforschungszentrum, Im Neuenheimer Feld 280, 69120 Heidelberg, Germany.
David T JonesDeutsches Krebsforschungszentrum, Im Neuenheimer Feld 280, 69120 Heidelberg, Germany.
Stefan PfisterDeutsches Krebsforschungszentrum, Im Neuenheimer Feld 280, 69120 Heidelberg, Germany.
Peter LichterDeutsches Krebsforschungszentrum, Im Neuenheimer Feld 280, 69120 Heidelberg, Germany.
Roland EilsBioquant, University of Heidelberg, Im Neuenheimer Feld 267, 69120 Heidelberg, Germany Deutsches Krebsforschungszentrum, Im Neuenheimer Feld 280, 69120 Heidelberg, Germany Department for Bioinformatics and Functional Genomics, Institute for Pharmacy and Molecular Biotechnology (IPMB), University of Heidelberg, Heidelberg, Germany.
Reiner SiebertInstitut für Humangenetik, Universitätsklinikum Schleswig-Holstein, Christian-Albrechts-Universität zu Kiel, Arnold Heller Straße 3, 24105 Kiel, Germany.
Peer BorkEMBL, Meyerhofstrasse 1, 69117 Heidelberg, Germany.
Gordana ApicCell Networks, University of Heidelberg, Im Neuenheimer Feld 267, 69120 Heidelberg, Germany Bioquant, University of Heidelberg, Im Neuenheimer Feld 267, 69120 Heidelberg, Germany Cambridge Cell Networks Ltd, St John's Innovation Centre, Cowley Road, CB3 0WS, Cambridge, UK.
Anne-Claude GavinEMBL, Meyerhofstrasse 1, 69117 Heidelberg, Germany.
Robert B RussellCell Networks, University of Heidelberg, Im Neuenheimer Feld 267, 69120 Heidelberg, Germany Bioquant, University of Heidelberg, Im Neuenheimer Feld 267, 69120 Heidelberg, Germany robertbrucerussell@gmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

Databases, ProteinMutationHigh-Throughput Nucleotide SequencingHumansNeoplasmsProtein ConformationProtein Interaction MappingProteinsProteomicsProteins

Identifiers

PMID25392414
PMCPMC4333368

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.