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Modeling functional changes to Escherichia coli thymidylate synthase upon single residue replacements: a structure-based approach
Escherichia coli thymidylate synthase (TS) is an enzyme that is indispensable to DNA synthesis and cell division, as it provides the only de novo source of dTMP by catalyzing the reductive methylation of dUMP, thus making it a key target for chemotherapeutic agents. High resolution X-ray crystallogr...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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PeerJ Inc.
2015
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4304848/ https://www.ncbi.nlm.nih.gov/pubmed/25648456 http://dx.doi.org/10.7717/peerj.721 |
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author | Masso, Majid |
author_facet | Masso, Majid |
author_sort | Masso, Majid |
collection | PubMed |
description | Escherichia coli thymidylate synthase (TS) is an enzyme that is indispensable to DNA synthesis and cell division, as it provides the only de novo source of dTMP by catalyzing the reductive methylation of dUMP, thus making it a key target for chemotherapeutic agents. High resolution X-ray crystallographic structures are available for TS and, owing to its relatively small size, successful experimental mutagenesis studies have been conducted on the enzyme. In this study, an in silico mutagenesis technique is used to investigate the effects of single amino acid substitutions in TS on enzymatic activity, one that employs the TS protein structure as well as a knowledge-based, four-body statistical potential. For every single residue TS variant, this approach yields both a global structural perturbation score and a set of local environmental perturbation scores that characterize the mutated position as well as all structurally neighboring residues. Global scores for the TS variants are capable of uniquely characterizing groups of residue positions in the enzyme according to their physicochemical, functional, or structural properties. Additionally, these global scores elucidate a statistically significant structure–function relationship among a collection of 372 single residue TS variants whose activity levels have been experimentally determined. Predictive models of TS variant activity are subsequently trained on this dataset of experimental mutants, whose respective feature vectors encode information regarding the mutated position as well as its six nearest residue neighbors in the TS structure, including their environmental perturbation scores. |
format | Online Article Text |
id | pubmed-4304848 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | PeerJ Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-43048482015-02-03 Modeling functional changes to Escherichia coli thymidylate synthase upon single residue replacements: a structure-based approach Masso, Majid PeerJ Bioinformatics Escherichia coli thymidylate synthase (TS) is an enzyme that is indispensable to DNA synthesis and cell division, as it provides the only de novo source of dTMP by catalyzing the reductive methylation of dUMP, thus making it a key target for chemotherapeutic agents. High resolution X-ray crystallographic structures are available for TS and, owing to its relatively small size, successful experimental mutagenesis studies have been conducted on the enzyme. In this study, an in silico mutagenesis technique is used to investigate the effects of single amino acid substitutions in TS on enzymatic activity, one that employs the TS protein structure as well as a knowledge-based, four-body statistical potential. For every single residue TS variant, this approach yields both a global structural perturbation score and a set of local environmental perturbation scores that characterize the mutated position as well as all structurally neighboring residues. Global scores for the TS variants are capable of uniquely characterizing groups of residue positions in the enzyme according to their physicochemical, functional, or structural properties. Additionally, these global scores elucidate a statistically significant structure–function relationship among a collection of 372 single residue TS variants whose activity levels have been experimentally determined. Predictive models of TS variant activity are subsequently trained on this dataset of experimental mutants, whose respective feature vectors encode information regarding the mutated position as well as its six nearest residue neighbors in the TS structure, including their environmental perturbation scores. PeerJ Inc. 2015-01-08 /pmc/articles/PMC4304848/ /pubmed/25648456 http://dx.doi.org/10.7717/peerj.721 Text en © 2015 Masso http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited. |
spellingShingle | Bioinformatics Masso, Majid Modeling functional changes to Escherichia coli thymidylate synthase upon single residue replacements: a structure-based approach |
title | Modeling functional changes to Escherichia coli thymidylate synthase upon single residue replacements: a structure-based approach |
title_full | Modeling functional changes to Escherichia coli thymidylate synthase upon single residue replacements: a structure-based approach |
title_fullStr | Modeling functional changes to Escherichia coli thymidylate synthase upon single residue replacements: a structure-based approach |
title_full_unstemmed | Modeling functional changes to Escherichia coli thymidylate synthase upon single residue replacements: a structure-based approach |
title_short | Modeling functional changes to Escherichia coli thymidylate synthase upon single residue replacements: a structure-based approach |
title_sort | modeling functional changes to escherichia coli thymidylate synthase upon single residue replacements: a structure-based approach |
topic | Bioinformatics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4304848/ https://www.ncbi.nlm.nih.gov/pubmed/25648456 http://dx.doi.org/10.7717/peerj.721 |
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