Enzymes are widely used in the food industry. Their use as a supplement to the raw material for animal feed is a current research topic. Although there are several studies on the application of enzyme additives in the animal feed industry, it is necessary to search for new enzymes, as well as to utilize bioinformatics tools for the design of specific enzymes that work in certain environmental conditions and substrates. This will allow the improvement of the productive parameters in animals, reducing costs and making the processes more efficient. Technological needs have considered these catalysts as essential in many industrial sectors and research is constantly being carried out to optimize their use in those processes. This review describes the enzymes used in animal nutrition, their mode of action, their production and new sources of production as well as studies on different animal models to evaluate their effect on the productive performance intended for the production of animal feed.

In this paper, the amino acid sequence of the β-xylanase SRXL1 of Sporisorium reilianum, which is a pathogenic fungus of maize was used as a model protein to find its phylogenetic relationship with other xylanases of Ascomycetes and Basidiomycetes and the information obtained allowed to establish a hypothesis of monophyly and of biological role. 84 amino acid sequences of β-xylanase obtained from the GenBank database was used. Groupings analysis of higher-level in the Pfam database allowed to determine that the proteins under study were classified into the GH10 and GH11 families, based on the regions of highly conserved amino acids, 233–318 and 180–193 respectively, where glutamate residues are responsible for the catalysis.

This chapter deals with the topic of bioinformatics, computational, mathematics, and statistics tools applied to biology, essential for the analysis and characterization of biological molecules, in particular proteins, which play an important role in all cellular and evolutionary processes of the organisms. In recent decades, with the next generation sequencing technologies and bioinformatics, it has facilitated the collection and analysis of a large amount of genomic, transcriptomic, proteomic, and metabolomic data from different organisms that have allowed predictions on the regulation of expression, transcription, translation, structure, and mechanisms of action of proteins as well as homology, mutations, and evolutionary processes that generate structural and functional changes over time. Although the information in the databases is greater every day, all bioinformatics tools continue to be constantly modified to improve performance that leads to more accurate predictions regarding protein functionality, which is why bioinformatics research remains a great challenge.