A simple extension to the CMASA method for the prediction of catalytic residues in the presence of single point mutations.

The automatic identification of catalytic residues still remains an important challenge in structural bioinformatics. Sequence-based methods are good alternatives when the query shares a high percentage of identity with a well-annotated enzyme. However, when the homology is not apparent, which occur...

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Autores principales:	David I Flores, Rogerio R Sotelo-Mundo, Carlos A Brizuela
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2014
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/b68ebddc94044c42a0df55b7aee49602
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spelling	oai:doaj.org-article:b68ebddc94044c42a0df55b7aee496022021-11-25T05:58:35ZA simple extension to the CMASA method for the prediction of catalytic residues in the presence of single point mutations.1932-620310.1371/journal.pone.0108513https://doaj.org/article/b68ebddc94044c42a0df55b7aee496022014-01-01T00:00:00Zhttps://doi.org/10.1371/journal.pone.0108513https://doaj.org/toc/1932-6203The automatic identification of catalytic residues still remains an important challenge in structural bioinformatics. Sequence-based methods are good alternatives when the query shares a high percentage of identity with a well-annotated enzyme. However, when the homology is not apparent, which occurs with many structures from the structural genome initiative, structural information should be exploited. A local structural comparison is preferred to a global structural comparison when predicting functional residues. CMASA is a recently proposed method for predicting catalytic residues based on a local structure comparison. The method achieves high accuracy and a high value for the Matthews correlation coefficient. However, point substitutions or a lack of relevant data strongly affect the performance of the method. In the present study, we propose a simple extension to the CMASA method to overcome this difficulty. Extensive computational experiments are shown as proof of concept instances, as well as for a few real cases. The results show that the extension performs well when the catalytic site contains mutated residues or when some residues are missing. The proposed modification could correctly predict the catalytic residues of a mutant thymidylate synthase, 1EVF. It also successfully predicted the catalytic residues for 3HRC despite the lack of information for a relevant side chain atom in the PDB file.David I FloresRogerio R Sotelo-MundoCarlos A BrizuelaPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 9, Iss 9, p e108513 (2014)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q David I Flores Rogerio R Sotelo-Mundo Carlos A Brizuela A simple extension to the CMASA method for the prediction of catalytic residues in the presence of single point mutations.
description	The automatic identification of catalytic residues still remains an important challenge in structural bioinformatics. Sequence-based methods are good alternatives when the query shares a high percentage of identity with a well-annotated enzyme. However, when the homology is not apparent, which occurs with many structures from the structural genome initiative, structural information should be exploited. A local structural comparison is preferred to a global structural comparison when predicting functional residues. CMASA is a recently proposed method for predicting catalytic residues based on a local structure comparison. The method achieves high accuracy and a high value for the Matthews correlation coefficient. However, point substitutions or a lack of relevant data strongly affect the performance of the method. In the present study, we propose a simple extension to the CMASA method to overcome this difficulty. Extensive computational experiments are shown as proof of concept instances, as well as for a few real cases. The results show that the extension performs well when the catalytic site contains mutated residues or when some residues are missing. The proposed modification could correctly predict the catalytic residues of a mutant thymidylate synthase, 1EVF. It also successfully predicted the catalytic residues for 3HRC despite the lack of information for a relevant side chain atom in the PDB file.
format	article
author	David I Flores Rogerio R Sotelo-Mundo Carlos A Brizuela
author_facet	David I Flores Rogerio R Sotelo-Mundo Carlos A Brizuela
author_sort	David I Flores
title	A simple extension to the CMASA method for the prediction of catalytic residues in the presence of single point mutations.
title_short	A simple extension to the CMASA method for the prediction of catalytic residues in the presence of single point mutations.
title_full	A simple extension to the CMASA method for the prediction of catalytic residues in the presence of single point mutations.
title_fullStr	A simple extension to the CMASA method for the prediction of catalytic residues in the presence of single point mutations.
title_full_unstemmed	A simple extension to the CMASA method for the prediction of catalytic residues in the presence of single point mutations.
title_sort	simple extension to the cmasa method for the prediction of catalytic residues in the presence of single point mutations.
publisher	Public Library of Science (PLoS)
publishDate	2014
url	https://doaj.org/article/b68ebddc94044c42a0df55b7aee49602
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A simple extension to the CMASA method for the prediction of catalytic residues in the presence of single point mutations.

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