Genome-scaled Prediction of Substrate-specific Enzymes

The code for the paper: Sun J, Xia Y and Ming D (2020) Whole-Genome Sequencing and Bioinformatics Analysis of Apiotrichum mycotoxinivorans: Predicting Putative Zearalenone-Degradation Enzymes. Front. Microbiol. 11:1866. doi: 10.3389/fmicb.2020.01866 have been moved to the v1 directory.

In the post-genomic era, genome mining has been one of the most powerful tools leading to the discovery of new enzymes with properties of interest, and the combination of biological features like thermophilic and the sequence-based method like BLAST is the dominant approach. In this way, numerous enzymes have been found out and some of them have industrial applications. Also, with the development of structure-related computational methods involving docking and modeling, rational design and even de novo design of new enzymes have become a reality.

The accumulation of sequences ensures us unlimited biomineral and the development of structure-related computational methods endue us powerful tools to mine more effectively and completely.