Evidence map›Paper›PMID 28472524›Full record

ArticleNucleic acids research2017

I-TASSER-MR: automated molecular replacement for distant-homology proteins using iterative fragment assembly and progressive sequence truncation.

Yan Wang, Jouko Virtanen, Zhidong Xue, Yang Zhang

Abstract read
In one paragraph

Article in Nucleic acids research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing 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

24 citing papers in PubMed.

  1. Review
  2. Accelerating crystal structure determination with iterative AlphaFold prediction.Acta crystallographica. Section D, Structural biology · 2023
    Article
  3. Review
  4. Implications of AlphaFold2 for crystallographic phasing by molecular replacement.Acta crystallographica. Section D, Structural biology · 2022
    Review
  5. Article
  6. Article
  7. Article
  8. The coordination of major events in CScientific reports · 2021
    Article
  9. Article
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  11. TheInternational journal of molecular sciences · 2020
    Article
  12. Article
  13. Article
  14. Computational Analysis ofCancer informatics · 2020
    Article
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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

4 authors.

Yan WangKey Laboratory of Molecular Biophysics of the Ministry of Education, School of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China.
Jouko VirtanenDepartment of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA.
Zhidong XueDepartment of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA.
Yang ZhangDepartment of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA.

Funding

I-TASSER based atomic-level protein structure predictionR01GM083107 · NIGMS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI ZHANG, YANG · 2008 to 2019
$3.5M
Template-based docking refinement approach to protein-protein structure modelingR01GM116960 · NIGMS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI ZHANG, YANG · 2016 to 2019
$1.4M
National Science Foundation DBI1564756NIGMS NIH HHS R01 GM083107NIGMS NIH HHS R01 GM116960
6 · The paper itself

Abstract

Molecular replacement (MR) is one of the most common techniques used for solving the phase problem in X-ray crystal diffraction. The success rate of MR however drops quickly when the sequence identity between query and templates is reduced, while the I-TASSER-MR server is designed to solve the phase problem for proteins that lack close homologous templates. Starting from a sequence, it first generates full-length models using I-TASSER by iterative structural fragment reassembly. A progressive sequence truncation procedure is then used for editing the models based on local variations of the structural assembly simulations. Next, the edited models are submitted to MR-REX to search for optimal placements in the crystal unit-cells through replica-exchange Monte Carlo simulations, with the phasing results used by CNS for final atomic model refinement and selection. The I-TASSER-MR algorithm was tested in large-scale benchmark datasets and solved 36% more targets compared to using the best threading templates. The server takes primary sequence and raw crystal diffraction data as input, with output containing annotated phase information and refined structure models. It also allows users to choose between different methods for setting B-factors and the number of models used for phasing. The online server is freely available at http://zhanglab.ccmb.med.umich.edu/I-TASSER-MR.

Indexed as

Crystallography, X-RayModels, MolecularProtein ConformationSoftwareInternetSequence Analysis, Protein

Identifiers

PMID28472524
PMCPMC5793832

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.