Evidence map›Paper›PMID 25954868›Full record

ArticleBiophysical journal2015

Multidomain Assembler (MDA) Generates Models of Large Multidomain Proteins.

Samuel Hertig, Thomas D Goddard, Graham T Johnson, Thomas E Ferrin

Abstract read
In one paragraph

Article in Biophysical journal, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. A novelOphthalmic genetics · 2020
    Article
  8. Article
  9. Homology modeling in the time of collective and artificial intelligence.Computational and structural biotechnology journal · 2020
    Review
  10. Article
  11. Article
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.

Samuel HertigDepartment of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, California; Resource for Biocomputing, Visualization, and Informatics, University of California, San Francisco, San Francisco, California.
Thomas D GoddardDepartment of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, California; Resource for Biocomputing, Visualization, and Informatics, University of California, San Francisco, San Francisco, California.
Graham T JohnsonDepartment of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, California; Resource for Biocomputing, Visualization, and Informatics, University of California, San Francisco, San Francisco, California; California Institute for Quantitative Biosciences (QB3), University of California, San Francisco, San Francisco, California.
Thomas E FerrinDepartment of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, California; Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, California; Resource for Biocomputing, Visualization, and Informatics, University of California, San Francisco, San Francisco, California; California Institute for Quantitative Biosciences (QB3), University of California, San Francisco, San Francisco, California. Electronic address: tef@cgl.ucsf.edu.

Funding

Resource for Biocomputing Visualization and InformaticsP41GM103311 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI FERRIN, THOMAS E · 2012 to 2017
$8.2M
NIGMS NIH HHS P41 GM103311NIGMS NIH HHS P41-GM103311
6 · The paper itself

Abstract

Homology modeling predicts protein structures using known structures of related proteins as templates. We developed MULTIDOMAIN ASSEMBLER (MDA) to address the special problems that arise when modeling proteins with large numbers of domains, such as fibronectin with 30 domains, as well as cases with hundreds of templates. These problems include how to spatially arrange nonoverlapping template structures, and how to get the best template coverage when some sequence regions have hundreds of available structures while other regions have a few distant homologs. MDA automates the tasks of template searching, visualization, and selection followed by multidomain model generation, and is part of the widely used molecular graphics package UCSF CHIMERA (University of California, San Francisco). We demonstrate applications and discuss MDA's benefits and limitations.

Indexed as

Sequence HomologySoftwareProtein Structure, TertiarySequence AlignmentSequence Analysis, Protein

Identifiers

PMID25954868
PMCPMC4423039

What OpenQuestion holds

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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.