In Silico and In Vitro Analysis of MAP3773c Protein from Mycobacterium avium subsp. Paratuberculosis .
Esteban Hernández-GuevaraJosé A Gutiérrez-PabelloKaina Quintero-ChávezMirna Del Carmen Brito-PereaLilia Angélica Hurtado-AyalaGerman Ibarra-MolinaOmar Cortez-HernándezDulce Liliana Dueñas-MenaÁngela Fernández-OtalMaría F FillatBertha Landeros-SánchezPublished in: Biology (2022)
Paratuberculosis is a disease caused by Mycobacterium avium subsp. paratuberculosis (MAP). It is of great interest to better understand the proteins involved in the pathogenicity of this organism in order to be able to identify potential therapeutic targets and design new vaccines. The protein of interest-MAP3773c-was investigated, and molecular modeling in silico, docking, cloning, expression, purification, and partial characterization of the recombinant protein were achieved. In the in silico study, it was shown that MAP3773c of MAP has 34% sequence similarity with Mycobacterium tuberculosis (MTB) FurB, which is a zinc uptake regulator (Zur) protein. The docking data showed that MAP3773c exhibits two metal-binding sites. The presence of structural Zn 2+ in the purified protein was confirmed by SDS-PAGE PAR staining. The purification showed one band that corresponded to a monomer, which was confirmed by liquid chromatography-mass spectrometry (LC-MS). The presence of a monomer was verified by analyzing the native protein structure through BN-SDS-PAGE (Native Blue (BN) Two-Dimensional Electrophoresis) and BN-Western blotting. The MAP3773c protein contains structural zinc. In conclusion, our results show that MAP3773c displays the features of a Fur-type protein with two metal-binding sites, one of them coordinating structural Zn 2+ .
Keyphrases
- mycobacterium tuberculosis
- protein protein
- mass spectrometry
- amino acid
- liquid chromatography
- binding protein
- small molecule
- poor prognosis
- staphylococcus aureus
- molecular dynamics
- transcription factor
- electronic health record
- machine learning
- molecular dynamics simulations
- pulmonary tuberculosis
- high performance liquid chromatography
- big data
- human health
- oxide nanoparticles