Predicting Protein Folds with Fold-Specific PSSM Libraries

Accurately assigning folds for divergent protein sequences is a major obstacle to structural studies. Herein, we outline an effective method for fold recognition using sets of PSSMs, each of which is constructed for different protein folds. Our analyses demonstrate that FSL (Fold-specific Position S...

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Main Authors:	Hong, Yoojin, Chintapalli, Sree Vamsee, Ko, Kyung Dae, Bhardwaj, Gaurav, Zhang, Zhenhai, van Rossum, Damian, Patterson, Randen L.
Format:	Online
Language:	English
Published:	Public Library of Science 2011
Online Access:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3116844/

id	pubmed-3116844
recordtype	oai_dc
spelling	pubmed-31168442011-06-22 Predicting Protein Folds with Fold-Specific PSSM Libraries Hong, Yoojin Chintapalli, Sree Vamsee Ko, Kyung Dae Bhardwaj, Gaurav Zhang, Zhenhai van Rossum, Damian Patterson, Randen L. Research Article Accurately assigning folds for divergent protein sequences is a major obstacle to structural studies. Herein, we outline an effective method for fold recognition using sets of PSSMs, each of which is constructed for different protein folds. Our analyses demonstrate that FSL (Fold-specific Position Specific Scoring Matrix Libraries) can predict/relate structures given only their amino acid sequences of highly divergent proteins. This ability to detect distant relationships is dependent on low-identity sequence alignments obtained from FSL. Results from our experiments demonstrate that FSL perform well in recognizing folds from the “twilight-zone” SABmark dataset. Further, this method is capable of accurate fold prediction in newly determined structures. We suggest that by building complete PSSM libraries for all unique folds within the Protein Database (PDB), FSL can be used to rapidly and reliably annotate a large subset of protein folds at proteomic level. The related programs and fold-specific PSSMs for our FSL are publicly available at: http://ccp.psu.edu/download/FSLv1.0/. Public Library of Science 2011-06-16 /pmc/articles/PMC3116844/ /pubmed/21698189 http://dx.doi.org/10.1371/journal.pone.0020557 Text en Hong et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
repository_type	Open Access Journal
institution_category	Foreign Institution
institution	US National Center for Biotechnology Information
building	NCBI PubMed
collection	Online Access
language	English
format	Online
author	Hong, Yoojin Chintapalli, Sree Vamsee Ko, Kyung Dae Bhardwaj, Gaurav Zhang, Zhenhai van Rossum, Damian Patterson, Randen L.
spellingShingle	Hong, Yoojin Chintapalli, Sree Vamsee Ko, Kyung Dae Bhardwaj, Gaurav Zhang, Zhenhai van Rossum, Damian Patterson, Randen L. Predicting Protein Folds with Fold-Specific PSSM Libraries
author_facet	Hong, Yoojin Chintapalli, Sree Vamsee Ko, Kyung Dae Bhardwaj, Gaurav Zhang, Zhenhai van Rossum, Damian Patterson, Randen L.
author_sort	Hong, Yoojin
title	Predicting Protein Folds with Fold-Specific PSSM Libraries
title_short	Predicting Protein Folds with Fold-Specific PSSM Libraries
title_full	Predicting Protein Folds with Fold-Specific PSSM Libraries
title_fullStr	Predicting Protein Folds with Fold-Specific PSSM Libraries
title_full_unstemmed	Predicting Protein Folds with Fold-Specific PSSM Libraries
title_sort	predicting protein folds with fold-specific pssm libraries
description	Accurately assigning folds for divergent protein sequences is a major obstacle to structural studies. Herein, we outline an effective method for fold recognition using sets of PSSMs, each of which is constructed for different protein folds. Our analyses demonstrate that FSL (Fold-specific Position Specific Scoring Matrix Libraries) can predict/relate structures given only their amino acid sequences of highly divergent proteins. This ability to detect distant relationships is dependent on low-identity sequence alignments obtained from FSL. Results from our experiments demonstrate that FSL perform well in recognizing folds from the “twilight-zone” SABmark dataset. Further, this method is capable of accurate fold prediction in newly determined structures. We suggest that by building complete PSSM libraries for all unique folds within the Protein Database (PDB), FSL can be used to rapidly and reliably annotate a large subset of protein folds at proteomic level. The related programs and fold-specific PSSMs for our FSL are publicly available at: http://ccp.psu.edu/download/FSLv1.0/.
publisher	Public Library of Science
publishDate	2011
url	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3116844/
_version_	1611460305292886016

Predicting Protein Folds with Fold-Specific PSSM Libraries

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