Evidence map›Paper›PMID 35298864›Full record

ArticleThe FEBS journal2023

Integrative structure determination of histones H3 and H4 using genetic interactions.

Ignacia Echeverria, Hannes Braberg, Nevan J Krogan, Andrej Sali

Open access · hybridAbstract read
In one paragraph

Article in The FEBS journal, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.4field-weighted citation impact, top 43% 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

0 citing papers in PubMed, 5 citations in OpenAlex.

No citing paper in PubMed yet.

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

4 authors at 1 institution in 1 country.

Ignacia EcheverriaDepartment of Cellular and Molecular Pharmacology, University of California, San Francisco, CA, USA.ORCID 0000-0003-4717-1467
Hannes BrabergDepartment of Cellular and Molecular Pharmacology, University of California, San Francisco, CA, USA.ORCID 0000-0002-7070-2257
Nevan J KroganDepartment of Cellular and Molecular Pharmacology, University of California, San Francisco, CA, USA.ORCID 0000-0003-4902-337X
Andrej SaliQuantitative Biosciences Institute, University of California, San Francisco, CA, USA.ORCID 0000-0003-0435-6197
QB3 · US

Funding

RESEARCH PROJECT 2U19AI135990 · NIAID · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Melanie Maria Ott · 2018 to 2026
$21.4M
Rewiring Therapeutic Cells: User-Controlled T Cells and Stem CellsP50GM081879 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI LIM, WENDELL A · 2010 to 2017
$19.0M
TR&D Project 4. The Imaging Stage: Multiscale Spatiotemporal Modeling of Macromolecular Systems in Cellular NeighborhoodsP41GM109824 · NIGMS · ROCKEFELLER UNIVERSITY · PI ROUT, MICHAEL P · 2014 to 2023
$18.8M
X-ray Screening and Rapid Structure DeterminationP50AI150476 · NIAID · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI KROGAN, NEVAN J · 2019 to 2021
$14.4M
IMP: Software for Hybrid Determination of Macromolecular Assembly StructuresR01GM083960 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI SALI, ANDREJ · 2008 to 2024
$5.2M
Comparative Analysis of Genetic Interaction NetworksR01GM084279 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI IDEKER, TREY, KROGAN, NEVAN J · 2008 to 2017
$3.9M
Genetic Analysis of the Nucleosome and RNA Polymerase II: A Systems ApproachR01GM084448 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI KROGAN, NEVAN J · 2008 to 2012
$2.3M
Integrating computation and genetics to quantify specificity in protein networksR01GM098101 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI KORTEMME, TANJA, KROGAN, NEVAN J · 2011 to 2014
$1.7M
High Performance Computer for Computational BiosciencesS10OD021596 · OD · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI SALI, ANDREJ · 2016 to 2016
$443k
NIAID NIH HHS P50 AI150476NIAID NIH HHS U19 AI135990NIGMS NIH HHS P41 GM109824NIGMS NIH HHS P50 GM081879NIGMS NIH HHS R01 GM083960NIGMS NIH HHS R01 GM084279NIGMS NIH HHS R01 GM084448NIGMS NIH HHS R01 GM098101NIH HHS S10 OD021596
6 · The paper itself

Abstract

Integrative structure modeling is increasingly used for determining the architectures of biological assemblies, especially those that are structurally heterogeneous. Recently, we reported on how to convert in vivo genetic interaction measurements into spatial restraints for structural modeling: first, phenotypic profiles are generated for each point mutation and thousands of gene deletions or environmental perturbations. Following, the phenotypic profile similarities are converted into distance restraints on the pairs of mutated residues. We illustrate the approach by determining the structure of the histone H3-H4 complex. The method is implemented in our open-source IMP program, expanding the structural biology toolbox by allowing structural characterization based on in vivo data without the need to purify the target system. We compare genetic interaction measurements to other sources of structural information, such as residue coevolution and deep-learning structure prediction of complex subunits. We also suggest that determining genetic interactions could benefit from new technologies, such as CRISPR-Cas9 approaches to gene editing, especially for mammalian cells. Finally, we highlight the opportunity for using genetic interactions to determine recalcitrant biomolecular structures, such as those of disordered proteins, transient protein assemblies, and host-pathogen protein complexes.

Indexed as

HistonesMammalsAnimalsHistonesgenetic interactionsintegrative structure modelingin vivo data

Identifiers

PMID35298864
PMCPMC9481981
OpenAlexW4220740908

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

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.