Evidence map›Paper›PMID 33937764›Full record

ArticleNAR genomics and bioinformatics2021

On the use of direct-coupling analysis with a reduced alphabet of amino acids combined with super-secondary structure motifs for protein fold prediction.

Bernat Anton, Mireia Besalú, Oriol Fornes, Jaume Bonet, Alexis Molina, Ruben Molina-Fernandez, Gemma De Las Cuevas, Narcis Fernandez-Fuentes, Baldo Oliva

Open access · goldAbstract read
In one paragraph

Article in NAR genomics and bioinformatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.2field-weighted citation impact, top 52% 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

1 citing paper in PubMed, 3 citations in OpenAlex.

  1. Review
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

9 authors at 6 institutions in 5 countries.

Bernat AntonStructural Bioinformatics Lab (GRIB-IMIM), Department of Experimental and Health Science, University Pompeu Fabra, Barcelona 08005, Catalonia, Spain.
Mireia BesalúDepartament de Genètica, Microbiologia i Estadística, Universitat de Barcelona, Barcelona 08028, Catalonia, Spain.
Oriol FornesStructural Bioinformatics Lab (GRIB-IMIM), Department of Experimental and Health Science, University Pompeu Fabra, Barcelona 08005, Catalonia, Spain.ORCID https://orcid.org/0000-0002-5969-3054
Jaume BonetStructural Bioinformatics Lab (GRIB-IMIM), Department of Experimental and Health Science, University Pompeu Fabra, Barcelona 08005, Catalonia, Spain.
Alexis MolinaElectronic and Atomic Protein Modeling, Life Sciences, Barcelona Supercomputing Center, Barcelona 08034, Catalonia, Spain.
Ruben Molina-FernandezStructural Bioinformatics Lab (GRIB-IMIM), Department of Experimental and Health Science, University Pompeu Fabra, Barcelona 08005, Catalonia, Spain.
Gemma De Las CuevasInstitut für Theoritische Physik, School of Mathematics, Computer Science and Physics, Universität Innsbruck. A-6020 Innsbruck, Austria.
Narcis Fernandez-FuentesInstitute of Biological, Environmental and Rural Sciences, Aberystwyth University, SY233EB Aberystwyth, United Kingdom.
Baldo OlivaStructural Bioinformatics Lab (GRIB-IMIM), Department of Experimental and Health Science, University Pompeu Fabra, Barcelona 08005, Catalonia, Spain.ORCID https://orcid.org/0000-0003-0702-0250
Universitat Pompeu Fabra · ESBarcelona Supercomputing Center · ESUniversitat de Barcelona · ESUniversitat de Vic - Universitat Central de Catalunya · ESUniversität Innsbruck · ATUniversity of British Columbia · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Direct-coupling analysis (DCA) for studying the coevolution of residues in proteins has been widely used to predict the three-dimensional structure of a protein from its sequence. We present RADI/raDIMod, a variation of the original DCA algorithm that groups chemically equivalent residues combined with super-secondary structure motifs to model protein structures. Interestingly, the simplification produced by grouping amino acids into only two groups (polar and non-polar) is still representative of the physicochemical nature that characterizes the protein structure and it is in line with the role of hydrophobic forces in protein-folding funneling. As a result of a compressed alphabet, the number of sequences required for the multiple sequence alignment is reduced. The number of long-range contacts predicted is limited; therefore, our approach requires the use of neighboring sequence-positions. We use the prediction of secondary structure and motifs of super-secondary structures to predict local contacts. We use RADI and raDIMod, a fragment-based protein structure modelling, achieving near native conformations when the number of super-secondary motifs covers >30-50% of the sequence. Interestingly, although different contacts are predicted with different alphabets, they produce similar structures.

Identifiers

PMID33937764
PMCPMC8061457
OpenAlexW3158876629

What OpenQuestion holds

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LicenceCC BY-NC
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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.