Evidence map›Paper›PMID 22750985›Full record

ArticleJournal of biosciences2012

Prediction of DNA-binding specificity in zinc finger proteins.

Sumedha Roy, Shayoni Dutta, Kanika Khanna, Shruti Singla, Durai Sundar

Abstract read
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Article in Journal of biosciences, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Review
  2. Article
  3. Improving key enzyme activities and quality of rice under various methods of zinc application.Physiology and molecular biology of plants : an international journal of functional plant biology · 2015
    Article
  4. 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

5 authors.

Sumedha RoyDepartment of Biochemical Engineering and Biotechnology, Indian Institute of Technology Delhi, New Delhi 110 016, India.
Shayoni Dutta
Kanika Khanna
Shruti Singla
Durai Sundar

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Zinc finger proteins interact via their individual fingers to three base pair subsites on the target DNA. The four key residue positions -1, 2, 3 and 6 on the alpha-helix of the zinc fingers have hydrogen bond interactions with the DNA. Mutating these key residues enables generation of a plethora of combinatorial possibilities that can bind to any DNA stretch of interest. Exploiting the binding specificity and affinity of the interaction between the zinc fingers and the respective DNA can help to generate engineered zinc fingers for therapeutic purposes involving genome targeting. Exploring the structure-function relationships of the existing zinc finger-DNA complexes can aid in predicting the probable zinc fingers that could bind to any target DNA. Computational tools ease the prediction of such engineered zinc fingers by effectively utilizing information from the available experimental data. A study of literature reveals many approaches for predicting DNA-binding specificity in zinc finger proteins. However, an alternative approach that looks into the physico-chemical properties of these complexes would do away with the difficulties of designing unbiased zinc fingers with the desired affinity and specificity. We present a physico-chemical approach that exploits the relative strengths of hydrogen bonding between the target DNA and all combinatorially possible zinc fingers to select the most optimum zinc finger protein candidate.

Indexed as

AnimalsBase SequenceComputer SimulationDNADNA-Binding ProteinsHumansHydrogen BondingMarkov ChainsModels, MolecularOnline SystemsProtein BindingProtein EngineeringSoftwareSupport Vector MachineZinc FingersDNADNA-Binding Proteins

Identifiers

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Registered trials

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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.