Research Article

The use of bioinformatics tools to characterize a hypothetical protein from Penicillium rubens

Published: June 30, 2020
Genet. Mol. Res. 19(2): GMR18574 DOI: https://doi.org/10.4238/gmr18574
Cite this Article:
F.F. Silva, D.B. Gonçalves, D.O. Lopes (2020). The use of bioinformatics tools to characterize a hypothetical protein from Penicillium rubens. Genet. Mol. Res. 19(2): GMR18574. https://doi.org/10.4238/gmr18574
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Abstract

Advances in biotechnology and molecular biology fields have allowed the sequencing of species genomes to improve the understanding of their genetics. As a consequence of the large number of whole genome sequencing projects, various DNA and protein sequences predicted by bioinformatics still without an identified function and are annotated in data banks as hypothetical proteins (HPs). Approximately 30% of the genome of recently sequenced organisms is composed of HPs, and these proteins are not included in functional studies due to the inexistence of full annotation. The characterization of HPs through bioinformatics is an important step to improve the understanding of genes and proteins and aims to assign some information to these sequences. Here, we used bioinformatics tools to predict the function of a hypothetical protein using as a model a protein from the filamentous fungus Penicillium rubens (XP_002569027.1). This fungus has been extensively studied due its ability to produce a wide range of natural products, many of them with biotechnological and pharmaceutical applications. The first step was to characterize the physicochemical properties of this HP. This protein has a molecular weight of 79.4 kDa and a theoretical pI of 5.06; 44.1% of its sequence is composed of hydrophilic amino acid residues and it was predicted as an extracellular protein. Prediction of 3D structure showed 42.21% of this sequence with an alpha galactosidase from Geobacillus stearothermophilus. In addition, XP_002569027.1 showed the presence of a glycosylase domain and most important amino acids residues in a catalytic site. Thus, we characterized a HP from P. rubens using computational tools and were able to produce useful information for future in vivo and in vitro studies, highlighting the importance of bioinformatics as a preliminary tool for functional studies.

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