<?xml version="1.0" encoding="UTF-8"?><?xml-stylesheet type="text/xsl" href="static/style.xsl"?><OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd"><responseDate>2026-04-17T05:43:58Z</responseDate><request verb="GetRecord" identifier="oai:www.recercat.cat:10230/48806" metadataPrefix="qdc">https://recercat.cat/oai/request</request><GetRecord><record><header><identifier>oai:recercat.cat:10230/48806</identifier><datestamp>2025-12-20T16:44:18Z</datestamp><setSpec>com_2072_6</setSpec><setSpec>col_2072_452952</setSpec></header><metadata><qdc:qualifieddc xmlns:qdc="http://dspace.org/qualifieddc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:dcterms="http://purl.org/dc/terms/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:doc="http://www.lyncode.com/xoai" xsi:schemaLocation="http://purl.org/dc/elements/1.1/ http://dublincore.org/schemas/xmls/qdc/2006/01/06/dc.xsd http://purl.org/dc/terms/ http://dublincore.org/schemas/xmls/qdc/2006/01/06/dcterms.xsd http://dspace.org/qualifieddc/ http://www.ukoln.ac.uk/metadata/dcmi/xmlschema/qualifieddc.xsd">
   <dc:title>On the use of direct-coupling analysis with a reduced alphabet of amino acids combined with super-secondary structure motifs for protein fold prediction</dc:title>
   <dc:creator>Anton, Bernat</dc:creator>
   <dc:creator>Besalú, Mireia</dc:creator>
   <dc:creator>Fornés Crespo, Oriol, 1983-</dc:creator>
   <dc:creator>Bonet Martínez, Jaume, 1982-</dc:creator>
   <dc:creator>Molina, Alexis</dc:creator>
   <dc:creator>Molina Fernández, Rubén</dc:creator>
   <dc:creator>Cuevas, Gemma de las</dc:creator>
   <dc:creator>Fernández Fuentes, Narcís</dc:creator>
   <dc:creator>Oliva Miguel, Baldomero</dc:creator>
   <dcterms: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 &amp;gt;30-50% of the sequence. Interestingly, although different contacts are predicted with different alphabets, they produce similar structures.</dcterms:abstract>
   <dcterms:abstract>Spanish Ministry of Economy MINECO [BIO2014-57518-R, BIO2017-83591-R (FEDER, UE), BIO2017-85329-R (FEDER, UE)]; Generalitat de Catalunya [SGR17-1020].</dcterms:abstract>
   <dcterms:issued>2021-10-26T05:58:10Z</dcterms:issued>
   <dcterms:issued>2021-10-26T05:58:10Z</dcterms:issued>
   <dcterms:issued>2021</dcterms:issued>
   <dc:type>info:eu-repo/semantics/article</dc:type>
   <dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
   <dc:relation>NAR Genom Bioinform. 2021;3(2):lqab027</dc:relation>
   <dc:relation>info:eu-repo/grantAgreement/ES/1PE/BIO2014-57518-R</dc:relation>
   <dc:relation>info:eu-repo/grantAgreement/ES/2PE/BIO2017-85329-R</dc:relation>
   <dc:relation>info:eu-repo/grantAgreement/ES/2PE/BIO2017-83591-R</dc:relation>
   <dc:rights>© The Author(s) 2021. Published by Oxford University Press on behalf of NAR Genomics and Bioinformatics. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com</dc:rights>
   <dc:rights>http://creativecommons.org/licenses/by-nc/4.0/</dc:rights>
   <dc:rights>info:eu-repo/semantics/openAccess</dc:rights>
   <dc:publisher>Oxford University Press</dc:publisher>
</qdc:qualifieddc></metadata></record></GetRecord></OAI-PMH>