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Distribution and prediction of catalytic domains in 2-oxoglutarate dependent dioxygenases.

Kundu S - BMC Res Notes (2012)

Bottom Line: Access to this repository is by a web server that compares user defined unknown sequences to these pre-defined profiles and outputs a list of predicted catalytic domains.This work, will aid efforts by investigators to screen and characterize putative 2-OG dependent sequences.The profile database will be updated at regular intervals.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Biochemistry, Army College of Medical Sciences, Delhi Cantt., New Delhi 110010, India. siddharthakundu@theacms.in

ABSTRACT

Background: The 2-oxoglutarate dependent superfamily is a diverse group of non-haem dioxygenases, and is present in prokaryotes, eukaryotes, and archaea. The enzymes differ in substrate preference and reaction chemistry, a factor that precludes their classification by homology studies and electronic annotation schemes alone. In this work, I propose and explore the rationale of using substrates to classify structurally similar alpha-ketoglutarate dependent enzymes.

Findings: Differential catalysis in phylogenetic clades of 2-OG dependent enzymes, is determined by the interactions of a subset of active-site amino acids. Identifying these with existing computational methods is challenging and not feasible for all proteins. A clustering protocol based on validated mechanisms of catalysis of known molecules, in tandem with group specific hidden markov model profiles is able to differentiate and sequester these enzymes. Access to this repository is by a web server that compares user defined unknown sequences to these pre-defined profiles and outputs a list of predicted catalytic domains. The server is free and is accessible at the following URL (http://comp-biol.theacms.in/H2OGpred.html).

Conclusions: The proposed stratification is a novel attempt at classifying and predicting 2-oxoglutarate dependent function. In addition, the server will provide researchers with a tool to compare their data to a comprehensive list of HMM profiles of catalytic domains. This work, will aid efforts by investigators to screen and characterize putative 2-OG dependent sequences. The profile database will be updated at regular intervals.

Show MeSH
Outline of protocol used to predict catalytic domains in user-defined sequences. Salient features of H2OGpred: the HMM profiles used, formulation of the query required to search the database for suitable matches, and a summary of the profiles found in the sequence(s) of interest. Other details include (not shown): instructions for use, general scheme of the 2-OG dependent reaction, and detailed scores used by HMMER-3.0 for profile assignment.
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Figure 1: Outline of protocol used to predict catalytic domains in user-defined sequences. Salient features of H2OGpred: the HMM profiles used, formulation of the query required to search the database for suitable matches, and a summary of the profiles found in the sequence(s) of interest. Other details include (not shown): instructions for use, general scheme of the 2-OG dependent reaction, and detailed scores used by HMMER-3.0 for profile assignment.

Mentions: I coded the PERL scripts needed to interface the front- and back- ends of the server with HMMER-3.0 and perform other miscellaneous tasks. The GUI (Graphical User Interface) for input and the results page were coded and designed by me using HTML (Hyper Text Markup Language) and CSS (Cascading Style Sheets). A concise workflow, along with salient features of H2OGpred is presented (Figure‚ÄČ1).


Distribution and prediction of catalytic domains in 2-oxoglutarate dependent dioxygenases.

Kundu S - BMC Res Notes (2012)

Outline of protocol used to predict catalytic domains in user-defined sequences. Salient features of H2OGpred: the HMM profiles used, formulation of the query required to search the database for suitable matches, and a summary of the profiles found in the sequence(s) of interest. Other details include (not shown): instructions for use, general scheme of the 2-OG dependent reaction, and detailed scores used by HMMER-3.0 for profile assignment.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3475032&req=5

Figure 1: Outline of protocol used to predict catalytic domains in user-defined sequences. Salient features of H2OGpred: the HMM profiles used, formulation of the query required to search the database for suitable matches, and a summary of the profiles found in the sequence(s) of interest. Other details include (not shown): instructions for use, general scheme of the 2-OG dependent reaction, and detailed scores used by HMMER-3.0 for profile assignment.
Mentions: I coded the PERL scripts needed to interface the front- and back- ends of the server with HMMER-3.0 and perform other miscellaneous tasks. The GUI (Graphical User Interface) for input and the results page were coded and designed by me using HTML (Hyper Text Markup Language) and CSS (Cascading Style Sheets). A concise workflow, along with salient features of H2OGpred is presented (Figure‚ÄČ1).

Bottom Line: Access to this repository is by a web server that compares user defined unknown sequences to these pre-defined profiles and outputs a list of predicted catalytic domains.This work, will aid efforts by investigators to screen and characterize putative 2-OG dependent sequences.The profile database will be updated at regular intervals.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department of Biochemistry, Army College of Medical Sciences, Delhi Cantt., New Delhi 110010, India. siddharthakundu@theacms.in

ABSTRACT

Background: The 2-oxoglutarate dependent superfamily is a diverse group of non-haem dioxygenases, and is present in prokaryotes, eukaryotes, and archaea. The enzymes differ in substrate preference and reaction chemistry, a factor that precludes their classification by homology studies and electronic annotation schemes alone. In this work, I propose and explore the rationale of using substrates to classify structurally similar alpha-ketoglutarate dependent enzymes.

Findings: Differential catalysis in phylogenetic clades of 2-OG dependent enzymes, is determined by the interactions of a subset of active-site amino acids. Identifying these with existing computational methods is challenging and not feasible for all proteins. A clustering protocol based on validated mechanisms of catalysis of known molecules, in tandem with group specific hidden markov model profiles is able to differentiate and sequester these enzymes. Access to this repository is by a web server that compares user defined unknown sequences to these pre-defined profiles and outputs a list of predicted catalytic domains. The server is free and is accessible at the following URL (http://comp-biol.theacms.in/H2OGpred.html).

Conclusions: The proposed stratification is a novel attempt at classifying and predicting 2-oxoglutarate dependent function. In addition, the server will provide researchers with a tool to compare their data to a comprehensive list of HMM profiles of catalytic domains. This work, will aid efforts by investigators to screen and characterize putative 2-OG dependent sequences. The profile database will be updated at regular intervals.

Show MeSH