The PHA Depolymerase Engineering Database: A systematic analysis tool for the diverse family of polyhydroxyalkanoate (PHA) depolymerases

Michael Knoll,Virginia Martinez,Florian Wagner,Thomas M Hamm,Jürgen Pleiss

doi:10.1186/1471-2105-10-89

Michael Knoll, Virginia Martinez + Show 3 more

Open Access

https://doi.org/10.1186/1471-2105-10-89

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Journal: BMC bioinformatics	Publication Date: Mar 18, 2009
Citations: 163	License type: cc-by

Affiliation: University of Stuttgart

Abstract

BackgroundPolyhydroxyalkanoates (PHAs) can be degraded by many microorganisms using intra- or extracellular PHA depolymerases. PHA depolymerases are very diverse in sequence and substrate specificity, but share a common α/β-hydrolase fold and a catalytic triad, which is also found in other α/β-hydrolases.ResultsThe PHA Depolymerase Engineering Database (DED, ) has been established as a tool for systematic analysis of this enzyme family. The DED contains sequence entries of 587 PHA depolymerases, which were assigned to 8 superfamilies and 38 homologous families based on their sequence similarity. For each family, multiple sequence alignments and profile hidden Markov models are provided, and functionally relevant residues are annotated.ConclusionThe DED is a valuable tool which can be applied to identify new PHA depolymerase sequences from complete genomes in silico, to classify PHA depolymerases, to predict their biochemical properties, and to design enzyme variants with improved properties.

Highlights

Polyhydroxyalkanoates (PHAs) can be degraded by many microorganisms using intra- or extracellular PHA depolymerases
The Depolymerase Engineering Database (DED) contains sequence entries of 587 PHA depolymerases, which were assigned to 8 superfamilies and 38 homologous families based on their sequence similarity
The DED is a valuable tool which can be applied to identify new PHA depolymerase sequences from complete genomes in silico, to classify PHA depolymerases, to predict their biochemical properties, and to design enzyme variants with improved properties

Summary

Results

The PHA Depolymerase Engineering Database (DED, http://www.ded.uni-stuttgart.de) has been established as a tool for systematic analysis of this enzyme family. The DED contains sequence entries of 587 PHA depolymerases, which were assigned to 8 superfamilies and 38 homologous families based on their sequence similarity. Multiple sequence alignments and profile hidden Markov models are provided, and functionally relevant residues are annotated

Background

Utility and discussion

Conclusion

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