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EC-PSI: Associating Enzyme Commission Numbers with Pfam Domains

Seyed Alborzi 1 Marie-Dominique Devignes 1 David Ritchie 1
1 CAPSID - Computational Algorithms for Protein Structures and Interactions
Inria Nancy - Grand Est, LORIA - AIS - Department of Complex Systems, Artificial Intelligence & Robotics
Abstract : With the growing number of protein structures in the protein data bank (PDB), there is a need to annotate these structures at the domain level in order to relate protein structure to protein function. Thanks to the SIFTS database, many PDB chains are now cross-referenced with Pfam domains and enzyme commission (EC) numbers. However, these annotations do not include any explicit relationship between individual Pfam domains and EC numbers. This article presents a novel statistical training-based method called EC-PSI that can automatically infer high confidence associations between EC numbers and Pfam domains directly from EC-chain associations from SIFTS and from EC-sequence associations from the SwissProt, and TrEMBL databases. By collecting and integrating these existing EC-chain/sequence annotations, our approach is able to infer a total of 8,329 direct EC-Pfam associations with an overall F-measure of 0.819 with respect to the manually curated InterPro database, which we treat here as a " gold standard " reference dataset. Thus, compared to the 1,493 EC-Pfam associations in InterPro, our approach provides a way to find over six times as many high quality EC-Pfam associations completely automatically.
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https://hal.inria.fr/hal-01216743
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Submitted on : Friday, October 16, 2015 - 7:13:37 PM
Last modification on : Sunday, January 3, 2021 - 5:00:06 PM
Long-term archiving on: : Thursday, April 27, 2017 - 7:02:28 AM

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Seyed Alborzi, Marie-Dominique Devignes, David Ritchie. EC-PSI: Associating Enzyme Commission Numbers with Pfam Domains. JOBIM 2015, Jul 2015, Clermont-Ferrand, France. ⟨10.1101/022343⟩. ⟨hal-01216743⟩

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