Seq2Enz: An application of mask BLAST methodology with a new chemical logic of amino acids for improved enzyme function prediction.

Biochim Biophys Acta Proteins Proteom

Department of Chemistry, Indian Institute of Technology, Hauz Khas, New Delhi 110016, India; Supercomputing Facility for Bioinformatics & Computational Biology, Indian Institute of Technology, Hauz Khas, New Delhi 110016, India; Kusuma School of Biological Sciences, Indian Institute of Technology, Hauz Khas, New Delhi 110016, India. Electronic address:

Published: January 2022

Seq2Enz method is a new way to identify whether a query protein sequence is an enzyme and to assign an enzyme class to the protein sequence. The method is based on mask BLAST fortified with some novel structural-chemical properties (NCL) of the building blocks of proteins. All available reviewed enyme sequences (267,276 in number) in Uniprot/SwissProt and most recent depositions (7062) not used for training in ECPred, a state of the art software for enzyme class prediction, are taken for assessment and the results are compared with those from conventional BLAST and ECPred respectively. Seq2Enz is seen to perform consistently better for all the enzyme classes to all the four levels. Seq2Enz methodology is converted into an easy to use web-server and made freely accessible at http://www.scfbio-iitd.res.in Seq2Enz/.

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Source
http://dx.doi.org/10.1016/j.bbapap.2021.140721DOI Listing

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