Evidence map›Paper›PMID 17900341›Full record

ArticleBMC structural biology2007

Identification of DNA-binding protein target sequences by physical effective energy functions: free energy analysis of lambda repressor-DNA complexes.

Elisabetta Moroni, Michele Caselle, Federico Fogolari

Open access · hybridAbstract read
In one paragraph

Article in BMC structural biology, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
0.1field-weighted citation impact, top 47% 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

7 citing papers in PubMed, 10 citations in OpenAlex.

  1. Article
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  6. Review
  7. Direct inference of protein-DNA interactions using compressed sensing methods.Proceedings of the National Academy of Sciences of the United States of America · 2011
    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

3 authors at 3 institutions in 1 country.

Elisabetta MoroniDipartimento di Fisica Teorica, Universià di Torino and INFN, Via P, Giuria 1, 10125 Torino, Italy. moroni@to.infn.it
Michele Caselle
Federico Fogolari
Istituto Nazionale di Fisica Nucleare, Sezione di Torino · ITUniversity of Milan · ITUniversity of Udine · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSpecific binding of proteins to DNA is one of the most common ways gene expression is controlled. Although general rules for the DNA-protein recognition can be derived, the ambiguous and complex nature of this mechanism precludes a simple recognition code, therefore the prediction of DNA target sequences is not straightforward. DNA-protein interactions can be studied using computational methods which can complement the current experimental methods and offer some advantages. In the present work we use physical effective potentials to evaluate the DNA-protein binding affinities for the lambda repressor-DNA complex for which structural and thermodynamic experimental data are available.

resultsThe binding free energy of two molecules can be expressed as the sum of an intermolecular energy (evaluated using a molecular mechanics forcefield), a solvation free energy term and an entropic term. Different solvation models are used including distance dependent dielectric constants, solvent accessible surface tension models and the Generalized Born model. The effect of conformational sampling by Molecular Dynamics simulations on the computed binding energy is assessed; results show that this effect is in general negative and the reproducibility of the experimental values decreases with the increase of simulation time considered. The free energy of binding for non-specific complexes, estimated using the best energetic model, agrees with earlier theoretical suggestions. As a results of these analyses, we propose a protocol for the prediction of DNA-binding target sequences. The possibility of searching regulatory elements within the bacteriophage lambda genome using this protocol is explored. Our analysis shows good prediction capabilities, even in absence of any thermodynamic data and information on the naturally recognized sequence.

conclusionThis study supports the conclusion that physics-based methods can offer a completely complementary methodology to sequence-based methods for the identification of DNA-binding protein target sequences.

Indexed as

Base SequenceBinding SitesComputer SimulationDNADNA-Binding ProteinsModels, BiologicalModels, MolecularProtein BindingProtein Structure, TertiaryRepressor ProteinsThermodynamicsViral Regulatory and Accessory ProteinsDNADNA-Binding Proteinsphage repressor proteinsRepressor ProteinsViral Regulatory and Accessory Proteins

Identifiers

PMID17900341
PMCPMC2194778
OpenAlexW2041057543

What OpenQuestion holds

Textmetadata
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.