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Rapid Catalytic Template Searching as an Enzyme Function Prediction Procedure
We present an enzyme protein function identification algorithm, Catalytic Site Identification (CatSId), based on identification of catalytic residues. The method is optimized for highly accurate template identification across a diverse template library and is also very efficient in regards to time a...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3651201/ https://www.ncbi.nlm.nih.gov/pubmed/23675414 http://dx.doi.org/10.1371/journal.pone.0062535 |
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author | Nilmeier, Jerome P. Kirshner, Daniel A. Wong, Sergio E. Lightstone, Felice C. |
author_facet | Nilmeier, Jerome P. Kirshner, Daniel A. Wong, Sergio E. Lightstone, Felice C. |
author_sort | Nilmeier, Jerome P. |
collection | PubMed |
description | We present an enzyme protein function identification algorithm, Catalytic Site Identification (CatSId), based on identification of catalytic residues. The method is optimized for highly accurate template identification across a diverse template library and is also very efficient in regards to time and scalability of comparisons. The algorithm matches three-dimensional residue arrangements in a query protein to a library of manually annotated, catalytic residues – The Catalytic Site Atlas (CSA). Two main processes are involved. The first process is a rapid protein-to-template matching algorithm that scales quadratically with target protein size and linearly with template size. The second process incorporates a number of physical descriptors, including binding site predictions, in a logistic scoring procedure to re-score matches found in Process 1. This approach shows very good performance overall, with a Receiver-Operator-Characteristic Area Under Curve (AUC) of 0.971 for the training set evaluated. The procedure is able to process cofactors, ions, nonstandard residues, and point substitutions for residues and ions in a robust and integrated fashion. Sites with only two critical (catalytic) residues are challenging cases, resulting in AUCs of 0.9411 and 0.5413 for the training and test sets, respectively. The remaining sites show excellent performance with AUCs greater than 0.90 for both the training and test data on templates of size greater than two critical (catalytic) residues. The procedure has considerable promise for larger scale searches. |
format | Online Article Text |
id | pubmed-3651201 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-36512012013-05-14 Rapid Catalytic Template Searching as an Enzyme Function Prediction Procedure Nilmeier, Jerome P. Kirshner, Daniel A. Wong, Sergio E. Lightstone, Felice C. PLoS One Research Article We present an enzyme protein function identification algorithm, Catalytic Site Identification (CatSId), based on identification of catalytic residues. The method is optimized for highly accurate template identification across a diverse template library and is also very efficient in regards to time and scalability of comparisons. The algorithm matches three-dimensional residue arrangements in a query protein to a library of manually annotated, catalytic residues – The Catalytic Site Atlas (CSA). Two main processes are involved. The first process is a rapid protein-to-template matching algorithm that scales quadratically with target protein size and linearly with template size. The second process incorporates a number of physical descriptors, including binding site predictions, in a logistic scoring procedure to re-score matches found in Process 1. This approach shows very good performance overall, with a Receiver-Operator-Characteristic Area Under Curve (AUC) of 0.971 for the training set evaluated. The procedure is able to process cofactors, ions, nonstandard residues, and point substitutions for residues and ions in a robust and integrated fashion. Sites with only two critical (catalytic) residues are challenging cases, resulting in AUCs of 0.9411 and 0.5413 for the training and test sets, respectively. The remaining sites show excellent performance with AUCs greater than 0.90 for both the training and test data on templates of size greater than two critical (catalytic) residues. The procedure has considerable promise for larger scale searches. Public Library of Science 2013-05-10 /pmc/articles/PMC3651201/ /pubmed/23675414 http://dx.doi.org/10.1371/journal.pone.0062535 Text en © 2013 Nilmeier 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 Nilmeier, Jerome P. Kirshner, Daniel A. Wong, Sergio E. Lightstone, Felice C. Rapid Catalytic Template Searching as an Enzyme Function Prediction Procedure |
title | Rapid Catalytic Template Searching as an Enzyme Function Prediction Procedure |
title_full | Rapid Catalytic Template Searching as an Enzyme Function Prediction Procedure |
title_fullStr | Rapid Catalytic Template Searching as an Enzyme Function Prediction Procedure |
title_full_unstemmed | Rapid Catalytic Template Searching as an Enzyme Function Prediction Procedure |
title_short | Rapid Catalytic Template Searching as an Enzyme Function Prediction Procedure |
title_sort | rapid catalytic template searching as an enzyme function prediction procedure |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3651201/ https://www.ncbi.nlm.nih.gov/pubmed/23675414 http://dx.doi.org/10.1371/journal.pone.0062535 |
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