Evidence map›Paper›PMID 33654096›Full record

ArticleNature communications2021

Large-scale discovery of protein interactions at residue resolution using co-evolution calculated from genomic sequences.

Anna G Green, Hadeer Elhabashy, Kelly P Brock, Rohan Maddamsetti, Oliver Kohlbacher, Debora S Marks

Open access · goldAbstract read
In one paragraph

Article in Nature communications, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 63 papers.

0numbers the graph read from it
0cells of the map it votes in
63citing papers in PubMed
8.7field-weighted citation impact, top 1% of its field
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

63 citing papers in PubMed, 131 citations in OpenAlex.

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  16. Recent progress and future challenges in structure-based protein-protein interaction prediction.Molecular therapy : the journal of the American Society of Gene Therapy · 2025
    Review
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3 more citing papers are in PubMed but not listed here.

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

6 authors at 3 institutions in 2 countries.

Anna G Green *Department of Systems Biology, Harvard Medical School, Boston, MA, 02115, USA.ORCID 0000-0001-7548-3682
Hadeer Elhabashy *Biomolecular Interactions, Max Planck Institute for Developmental Biology, 72076, Tübingen, Germany.
Kelly P BrockDepartment of Systems Biology, Harvard Medical School, Boston, MA, 02115, USA.
Rohan MaddamsettiDepartment of Systems Biology, Harvard Medical School, Boston, MA, 02115, USA.ORCID 0000-0003-3370-092X
Oliver KohlbacherBiomolecular Interactions, Max Planck Institute for Developmental Biology, 72076, Tübingen, Germany. oliver.kohlbacher@uni-tuebingen.de.ORCID 0000-0003-1739-4598
Debora S MarksInstitute for Bioinformatics and Medical Informatics, University of Tübingen, Sand 14, 72076, Tübingen, Germany. debbie@hms.harvard.edu.ORCID 0000-0001-9388-2281
Harvard University · USMax Planck Institute for Developmental Biology · DEBroad Institute · US

Funding

RESEARCH TRAINING-MEDICAL INFORMATICS 90T15LM007092 · NLM · HARVARD UNIVERSITY (SCH OF PUBLIC HLTH) · PI Nils Gehlenborg · 1992 to 2026
$32.8M
Orchestra: A high performance biomedical supercomputing collaborativeS10RR028832 · NCRR · HARVARD MEDICAL SCHOOL · PI DANUSER, GAUDENZ · 2010 to 2010
$3.7M
NCRR NIH HHS S10 RR028832NLM NIH HHS T15 LM007092
6 · The paper itself

Abstract

Increasing numbers of protein interactions have been identified in high-throughput experiments, but only a small proportion have solved structures. Recently, sequence coevolution-based approaches have led to a breakthrough in predicting monomer protein structures and protein interaction interfaces. Here, we address the challenges of large-scale interaction prediction at residue resolution with a fast alignment concatenation method and a probabilistic score for the interaction of residues. Importantly, this method (EVcomplex2) is able to assess the likelihood of a protein interaction, as we show here applied to large-scale experimental datasets where the pairwise interactions are unknown. We predict 504 interactions de novo in the E. coli membrane proteome, including 243 that are newly discovered. While EVcomplex2 does not require available structures, coevolving residue pairs can be used to produce structural models of protein interactions, as done here for membrane complexes including the Flagellar Hook-Filament Junction and the Tol/Pal complex.

Indexed as

Evolution, MolecularGenome, BacterialProtein Interaction MappingAmino AcidsBacterial ProteinsBase SequenceEscherichia coliEukaryotic CellsMembrane ProteinsMolecular Docking SimulationProtein BindingProteomeAmino AcidsBacterial ProteinsMembrane ProteinsProteome

Identifiers

PMID33654096
PMCPMC7925567
OpenAlexW3133793061

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.