Evidence map›Paper›PMID 31839598›Full record

ArticleMolecular & cellular proteomics : MCP2020

MaXLinker: Proteome-wide Cross-link Identifications with High Specificity and Sensitivity.

Kumar Yugandhar, Ting-Yi Wang, Alden King-Yung Leung, Michael Charles Lanz, Ievgen Motorykin, Jin Liang, Elnur Elyar Shayhidin, Marcus Bustamante Smolka, Sheng Zhang, Haiyuan Yu

Abstract read
In one paragraph

Article in Molecular & cellular proteomics : MCP, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing 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

25 citing papers in PubMed.

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  17. Protein interaction landscapes revealed by advanced in vivo cross-linking-mass spectrometry.Proceedings of the National Academy of Sciences of the United States of America · 2021
    Article
  18. Article
  19. Article
  20. Crosslinking mass spectrometry: A link between structural biology and systems biology.Protein science : a publication of the Protein Society · 2021
    Review
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

10 authors.

Kumar YugandharDepartment of Computational Biology, Cornell University, Ithaca, New York,14853; Weill Institute for Cell and Molecular Biology, Cornell University, Ithaca, New York, 14853.
Ting-Yi WangDepartment of Computational Biology, Cornell University, Ithaca, New York,14853; Weill Institute for Cell and Molecular Biology, Cornell University, Ithaca, New York, 14853.
Alden King-Yung LeungDepartment of Computational Biology, Cornell University, Ithaca, New York,14853; Weill Institute for Cell and Molecular Biology, Cornell University, Ithaca, New York, 14853.
Michael Charles LanzWeill Institute for Cell and Molecular Biology, Cornell University, Ithaca, New York, 14853; Department of Molecular Biology and Genetics, Cornell University, Ithaca, New York 14853.
Ievgen MotorykinMass Spectrometry and Proteomics Facility, Institute of Biotechnology, Cornell University, Ithaca, New York,14853.
Jin LiangDepartment of Computational Biology, Cornell University, Ithaca, New York,14853; Weill Institute for Cell and Molecular Biology, Cornell University, Ithaca, New York, 14853.
Elnur Elyar ShayhidinDepartment of Computational Biology, Cornell University, Ithaca, New York,14853; Weill Institute for Cell and Molecular Biology, Cornell University, Ithaca, New York, 14853.
Marcus Bustamante SmolkaWeill Institute for Cell and Molecular Biology, Cornell University, Ithaca, New York, 14853; Department of Molecular Biology and Genetics, Cornell University, Ithaca, New York 14853.
Sheng ZhangMass Spectrometry and Proteomics Facility, Institute of Biotechnology, Cornell University, Ithaca, New York,14853.
Haiyuan YuDepartment of Computational Biology, Cornell University, Ithaca, New York,14853; Weill Institute for Cell and Molecular Biology, Cornell University, Ithaca, New York, 14853. Electronic address: haiyuan.yu@cornell.edu.

Funding

Cellular Responses to DNA Replication StressR01GM097272 · NIGMS · CORNELL UNIVERSITY · PI SMOLKA, MARCUS · 2011 to 2020
$2.7M
Quantifying molecular consequences of human missense variants with large-scale interactome perturbation studiesR01GM125639 · NIGMS · CORNELL UNIVERSITY · PI ALEXOV, EMIL GEORGIEV, CLARK, ANDREW G · 2018 to 2021
$2.6M
Towards a comprehensive multiscale 3D human interactome networkR01GM124559 · NIGMS · CORNELL UNIVERSITY · PI YU, HAIYUAN · 2017 to 2020
$1.5M
Acquisition of a Hybrid Quadrupole Time of Flight LC-MS/MS System for the CornellS10OD017992 · OD · CORNELL UNIVERSITY · PI ZHANG, SHENG · 2014 to 2014
$600k
NIGMS NIH HHS R01 GM097272NIGMS NIH HHS R01 GM124559NIGMS NIH HHS R01 GM125639NIH HHS S10 OD017992
6 · The paper itself

Abstract

Protein-protein interactions play a vital role in nearly all cellular functions. Hence, understanding their interaction patterns and three-dimensional structural conformations can provide crucial insights about various biological processes and underlying molecular mechanisms for many disease phenotypes. Cross-linking mass spectrometry (XL-MS) has the unique capability to detect protein-protein interactions at a large scale along with spatial constraints between interaction partners. The inception of MS-cleavable cross-linkers enabled the MS2-MS3 XL-MS acquisition strategy that provides cross-link information from both MS2 and MS3 level. However, the current cross-link search algorithm available for MS2-MS3 strategy follows a "MS2-centric" approach and suffers from a high rate of mis-identified cross-links. We demonstrate the problem using two new quality assessment metrics ["fraction of mis-identifications" (FMI) and "fraction of interprotein cross-links from known interactions" (FKI)]. We then address this problem, by designing a novel "MS3-centric" approach for cross-link identification and implementing it as a search engine named MaXLinker. MaXLinker outperforms the currently popular search engine with a lower mis-identification rate, and higher sensitivity and specificity. Moreover, we performed human proteome-wide cross-linking mass spectrometry using K562 cells. Employing MaXLinker, we identified a comprehensive set of 9319 unique cross-links at 1% false discovery rate, comprising 8051 intraprotein and 1268 interprotein cross-links. Finally, we experimentally validated the quality of a large number of novel interactions identified in our study, providing a conclusive evidence for MaXLinker's robust performance.

Indexed as

HumansK562 CellsMass SpectrometryPeptidesProtein Interaction MappingProteomeProteomicsSensitivity and SpecificityPeptidesProteomecomputational biologymass spectrometryProtein cross-linkingprotein-protein interactionssystems biology

Identifiers

PMID31839598
PMCPMC7050104

What OpenQuestion holds

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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.