Computational protein design: validation and possible relevance as a tool for homology searching and fold recognition.

<h4>Background</h4>Protein fold recognition usually relies on a statistical model of each fold; each model is constructed from an ensemble of natural sequences belonging to that fold. A complementary strategy may be to employ sequence ensembles produced by computational protein design. D...

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Autores principales:	Marcel Schmidt Am Busch, Audrey Sedano, Thomas Simonson
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2010
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/dbb0df8140b242edb0a97ccd5983ce2f
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spelling	oai:doaj.org-article:dbb0df8140b242edb0a97ccd5983ce2f2021-12-02T20:21:53ZComputational protein design: validation and possible relevance as a tool for homology searching and fold recognition.1932-620310.1371/journal.pone.0010410https://doaj.org/article/dbb0df8140b242edb0a97ccd5983ce2f2010-05-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/20463972/?tool=EBIhttps://doaj.org/toc/1932-6203<h4>Background</h4>Protein fold recognition usually relies on a statistical model of each fold; each model is constructed from an ensemble of natural sequences belonging to that fold. A complementary strategy may be to employ sequence ensembles produced by computational protein design. Designed sequences can be more diverse than natural sequences, possibly avoiding some limitations of experimental databases.<h4>Methodology/principal findings</h4>WE EXPLORE THIS STRATEGY FOR FOUR SCOP FAMILIES: Small Kunitz-type inhibitors (SKIs), Interleukin-8 chemokines, PDZ domains, and large Caspase catalytic subunits, represented by 43 structures. An automated procedure is used to redesign the 43 proteins. We use the experimental backbones as fixed templates in the folded state and a molecular mechanics model to compute the interaction energies between sidechain and backbone groups. Calculations are done with the Proteins@Home volunteer computing platform. A heuristic algorithm is used to scan the sequence and conformational space, yielding 200,000-300,000 sequences per backbone template. The results confirm and generalize our earlier study of SH2 and SH3 domains. The designed sequences ressemble moderately-distant, natural homologues of the initial templates; e.g., the SUPERFAMILY, profile Hidden-Markov Model library recognizes 85% of the low-energy sequences as native-like. Conversely, Position Specific Scoring Matrices derived from the sequences can be used to detect natural homologues within the SwissProt database: 60% of known PDZ domains are detected and around 90% of known SKIs and chemokines. Energy components and inter-residue correlations are analyzed and ways to improve the method are discussed.<h4>Conclusions/significance</h4>For some families, designed sequences can be a useful complement to experimental ones for homologue searching. However, improved tools are needed to extract more information from the designed profiles before the method can be of general use.Marcel Schmidt Am BuschAudrey SedanoThomas SimonsonPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 5, Iss 5, p e10410 (2010)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Marcel Schmidt Am Busch Audrey Sedano Thomas Simonson Computational protein design: validation and possible relevance as a tool for homology searching and fold recognition.
description	<h4>Background</h4>Protein fold recognition usually relies on a statistical model of each fold; each model is constructed from an ensemble of natural sequences belonging to that fold. A complementary strategy may be to employ sequence ensembles produced by computational protein design. Designed sequences can be more diverse than natural sequences, possibly avoiding some limitations of experimental databases.<h4>Methodology/principal findings</h4>WE EXPLORE THIS STRATEGY FOR FOUR SCOP FAMILIES: Small Kunitz-type inhibitors (SKIs), Interleukin-8 chemokines, PDZ domains, and large Caspase catalytic subunits, represented by 43 structures. An automated procedure is used to redesign the 43 proteins. We use the experimental backbones as fixed templates in the folded state and a molecular mechanics model to compute the interaction energies between sidechain and backbone groups. Calculations are done with the Proteins@Home volunteer computing platform. A heuristic algorithm is used to scan the sequence and conformational space, yielding 200,000-300,000 sequences per backbone template. The results confirm and generalize our earlier study of SH2 and SH3 domains. The designed sequences ressemble moderately-distant, natural homologues of the initial templates; e.g., the SUPERFAMILY, profile Hidden-Markov Model library recognizes 85% of the low-energy sequences as native-like. Conversely, Position Specific Scoring Matrices derived from the sequences can be used to detect natural homologues within the SwissProt database: 60% of known PDZ domains are detected and around 90% of known SKIs and chemokines. Energy components and inter-residue correlations are analyzed and ways to improve the method are discussed.<h4>Conclusions/significance</h4>For some families, designed sequences can be a useful complement to experimental ones for homologue searching. However, improved tools are needed to extract more information from the designed profiles before the method can be of general use.
format	article
author	Marcel Schmidt Am Busch Audrey Sedano Thomas Simonson
author_facet	Marcel Schmidt Am Busch Audrey Sedano Thomas Simonson
author_sort	Marcel Schmidt Am Busch
title	Computational protein design: validation and possible relevance as a tool for homology searching and fold recognition.
title_short	Computational protein design: validation and possible relevance as a tool for homology searching and fold recognition.
title_full	Computational protein design: validation and possible relevance as a tool for homology searching and fold recognition.
title_fullStr	Computational protein design: validation and possible relevance as a tool for homology searching and fold recognition.
title_full_unstemmed	Computational protein design: validation and possible relevance as a tool for homology searching and fold recognition.
title_sort	computational protein design: validation and possible relevance as a tool for homology searching and fold recognition.
publisher	Public Library of Science (PLoS)
publishDate	2010
url	https://doaj.org/article/dbb0df8140b242edb0a97ccd5983ce2f
work_keys_str_mv	AT marcelschmidtambusch computationalproteindesignvalidationandpossiblerelevanceasatoolforhomologysearchingandfoldrecognition AT audreysedano computationalproteindesignvalidationandpossiblerelevanceasatoolforhomologysearchingandfoldrecognition AT thomassimonson computationalproteindesignvalidationandpossiblerelevanceasatoolforhomologysearchingandfoldrecognition
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Computational protein design: validation and possible relevance as a tool for homology searching and fold recognition.

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