Cargando…

Identification and classification of small molecule kinases: insights into substrate recognition and specificity

BACKGROUND: Many prokaryotic kinases that phosphorylate small molecule substrates, such as antibiotics, lipids and sugars, are evolutionarily related to Eukaryotic Protein Kinases (EPKs). These Eukaryotic-Like Kinases (ELKs) share the same overall structural fold as EPKs, but differ in their modes o...

Descripción completa

Detalles Bibliográficos
Autores principales: Oruganty, Krishnadev, Talevich, Eric E., Neuwald, Andrew F., Kannan, Natarajan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4702295/
https://www.ncbi.nlm.nih.gov/pubmed/26738562
http://dx.doi.org/10.1186/s12862-015-0576-x
_version_ 1782408612224696320
author Oruganty, Krishnadev
Talevich, Eric E.
Neuwald, Andrew F.
Kannan, Natarajan
author_facet Oruganty, Krishnadev
Talevich, Eric E.
Neuwald, Andrew F.
Kannan, Natarajan
author_sort Oruganty, Krishnadev
collection PubMed
description BACKGROUND: Many prokaryotic kinases that phosphorylate small molecule substrates, such as antibiotics, lipids and sugars, are evolutionarily related to Eukaryotic Protein Kinases (EPKs). These Eukaryotic-Like Kinases (ELKs) share the same overall structural fold as EPKs, but differ in their modes of regulation, substrate recognition and specificity—the sequence and structural determinants of which are poorly understood. RESULTS: To better understand the basis for ELK specificity, we applied a Bayesian classification procedure designed to identify sequence determinants responsible for functional divergence. This reveals that a large and diverse family of aminoglycoside kinases, characterized members of which are involved in antibiotic resistance, fall into major sub-groups based on differences in putative substrate recognition motifs. Aminoglycoside kinase substrate specificity follows simple rules of alternating hydroxyl and amino groups that is strongly correlated with variations at the DFG + 1 position. CONCLUSIONS: Substrate specificity determining features in small molecule kinases are mostly confined to the catalytic core and can be identified based on quantitative sequence and crystal structure comparisons. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12862-015-0576-x) contains supplementary material, which is available to authorized users.
format Online
Article
Text
id pubmed-4702295
institution National Center for Biotechnology Information
language English
publishDate 2016
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-47022952016-01-07 Identification and classification of small molecule kinases: insights into substrate recognition and specificity Oruganty, Krishnadev Talevich, Eric E. Neuwald, Andrew F. Kannan, Natarajan BMC Evol Biol Research Article BACKGROUND: Many prokaryotic kinases that phosphorylate small molecule substrates, such as antibiotics, lipids and sugars, are evolutionarily related to Eukaryotic Protein Kinases (EPKs). These Eukaryotic-Like Kinases (ELKs) share the same overall structural fold as EPKs, but differ in their modes of regulation, substrate recognition and specificity—the sequence and structural determinants of which are poorly understood. RESULTS: To better understand the basis for ELK specificity, we applied a Bayesian classification procedure designed to identify sequence determinants responsible for functional divergence. This reveals that a large and diverse family of aminoglycoside kinases, characterized members of which are involved in antibiotic resistance, fall into major sub-groups based on differences in putative substrate recognition motifs. Aminoglycoside kinase substrate specificity follows simple rules of alternating hydroxyl and amino groups that is strongly correlated with variations at the DFG + 1 position. CONCLUSIONS: Substrate specificity determining features in small molecule kinases are mostly confined to the catalytic core and can be identified based on quantitative sequence and crystal structure comparisons. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12862-015-0576-x) contains supplementary material, which is available to authorized users. BioMed Central 2016-01-06 /pmc/articles/PMC4702295/ /pubmed/26738562 http://dx.doi.org/10.1186/s12862-015-0576-x Text en © Oruganty et al. 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Oruganty, Krishnadev
Talevich, Eric E.
Neuwald, Andrew F.
Kannan, Natarajan
Identification and classification of small molecule kinases: insights into substrate recognition and specificity
title Identification and classification of small molecule kinases: insights into substrate recognition and specificity
title_full Identification and classification of small molecule kinases: insights into substrate recognition and specificity
title_fullStr Identification and classification of small molecule kinases: insights into substrate recognition and specificity
title_full_unstemmed Identification and classification of small molecule kinases: insights into substrate recognition and specificity
title_short Identification and classification of small molecule kinases: insights into substrate recognition and specificity
title_sort identification and classification of small molecule kinases: insights into substrate recognition and specificity
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4702295/
https://www.ncbi.nlm.nih.gov/pubmed/26738562
http://dx.doi.org/10.1186/s12862-015-0576-x
work_keys_str_mv AT orugantykrishnadev identificationandclassificationofsmallmoleculekinasesinsightsintosubstraterecognitionandspecificity
AT talevicherice identificationandclassificationofsmallmoleculekinasesinsightsintosubstraterecognitionandspecificity
AT neuwaldandrewf identificationandclassificationofsmallmoleculekinasesinsightsintosubstraterecognitionandspecificity
AT kannannatarajan identificationandclassificationofsmallmoleculekinasesinsightsintosubstraterecognitionandspecificity