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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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Detalles Bibliográficos
Autores principales: Flores, David I., Sotelo-Mundo, Rogerio R., Brizuela, Carlos A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4182483/
https://www.ncbi.nlm.nih.gov/pubmed/25268770
http://dx.doi.org/10.1371/journal.pone.0108513
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author Flores, David I.
Sotelo-Mundo, Rogerio R.
Brizuela, Carlos A.
author_facet Flores, David I.
Sotelo-Mundo, Rogerio R.
Brizuela, Carlos A.
author_sort Flores, David I.
collection PubMed
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.
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spelling pubmed-41824832014-10-07 A Simple Extension to the CMASA Method for the Prediction of Catalytic Residues in the Presence of Single Point Mutations Flores, David I. Sotelo-Mundo, Rogerio R. Brizuela, Carlos A. PLoS One Research Article 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. Public Library of Science 2014-09-30 /pmc/articles/PMC4182483/ /pubmed/25268770 http://dx.doi.org/10.1371/journal.pone.0108513 Text en © 2014 Flores 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.
spellingShingle Research Article
Flores, David I.
Sotelo-Mundo, Rogerio R.
Brizuela, Carlos A.
A Simple Extension to the CMASA Method for the Prediction of Catalytic Residues in the Presence of Single Point Mutations
title 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_short 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
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4182483/
https://www.ncbi.nlm.nih.gov/pubmed/25268770
http://dx.doi.org/10.1371/journal.pone.0108513
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