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. 2011:2011:743782.
doi: 10.1155/2011/743782. Epub 2011 Mar 29.

ModEnzA: Accurate Identification of Metabolic Enzymes Using Function Specific Profile HMMs with Optimised Discrimination Threshold and Modified Emission Probabilities

Dhwani K Desai  1 , Soumyadeep Nandi, Prashant K Srivastava, Andrew M Lynn
Affiliations

ModEnzA: Accurate Identification of Metabolic Enzymes Using Function Specific Profile HMMs with Optimised Discrimination Threshold and Modified Emission Probabilities

Dhwani K Desai et al. Adv Bioinformatics. 2011.

Abstract

Various enzyme identification protocols involving homology transfer by sequence-sequence or profile-sequence comparisons have been devised which utilise Swiss-Prot sequences associated with EC numbers as the training set. A profile HMM constructed for a particular EC number might select sequences which perform a different enzymatic function due to the presence of certain fold-specific residues which are conserved in enzymes sharing a common fold. We describe a protocol, ModEnzA (HMM-ModE Enzyme Annotation), which generates profile HMMs highly specific at a functional level as defined by the EC numbers by incorporating information from negative training sequences. We enrich the training dataset by mining sequences from the NCBI Non-Redundant database for increased sensitivity. We compare our method with other enzyme identification methods, both for assigning EC numbers to a genome as well as identifying protein sequences associated with an enzymatic activity. We report a sensitivity of 88% and specificity of 95% in identifying EC numbers and annotating enzymatic sequences from the E. coli genome which is higher than any other method. With the next-generation sequencing methods producing a huge amount of sequence data, the development and use of fully automated yet accurate protocols such as ModEnzA is warranted for rapid annotation of newly sequenced genomes and metagenomic sequences.

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Figures

Figure 1
Figure 1
Flow diagram of the ModEnzA protocol.
Figure 2
Figure 2
ROC curves for genome-wide enzyme identification using the ModEnzA profiles. The classification of the complete genomes of the four organisms is shown in (a). A fraction of the EC number profiles (284 out of 2075 Tier I ModEnzA profiles) were retrained with an older version of the ENZYME database and compared to PRIAM and MetaShark (b). ModEnzA-RT-Retrained ModEnzA profiles.
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