From sequence to enzyme mechanism using multi-label machine learning.

ABSTRACT:

Background

In this work we predict enzyme function at the level of chemical mechanism, providing a finer granularity of annotation than traditional Enzyme Commission (EC) classes. Hence we can predict not only whether a putative enzyme in a newly sequenced organism has the potential to perform a certain reaction, but how the reaction is performed, using which cofactors and with susceptibility to which drugs or inhibitors, details with important consequences for drug and enzyme design. Work that predicts enzyme catalytic activity based on 3D protein structure features limits the prediction of mechanism to proteins already having either a solved structure or a close relative suitable for homology modelling.

Results

In this study, we evaluate whether sequence identity, InterPro

SUBMITTER: De Ferrari L 

PROVIDER: S-EPMC4229970 | biostudies-literature | 2014 May

REPOSITORIES: biostudies-literature