Mutational and structural analysis of an ancestral fungal dye-decolorizing peroxidase.
Ulises A ZitareMohamed H HabibHenriette RozeboomMaria L MascottiSmilja TodorovicMarco W FraaijePublished in: The FEBS journal (2021)
Dye-decolorizing peroxidases (DyPs) constitute a superfamily of heme-containing peroxidases that are related neither to animal nor to plant peroxidase families. These are divided into four classes (types A, B, C, and D) based on sequence features. The active site of DyPs contains two highly conserved distal ligands, an aspartate and an arginine, the roles of which are still controversial. These ligands have mainly been studied in class A-C bacterial DyPs, largely because no effective recombinant expression systems have been developed for the fungal (D-type) DyPs. In this work, we employ ancestral sequence reconstruction (ASR) to resurrect a D-type DyP ancestor, AncDyPD-b1. Expression of AncDyPD-b1 in Escherichia coli results in large amounts of a heme-containing soluble protein and allows for the first mutagenesis study on the two distal ligands of a fungal DyP. UV-Vis and resonance Raman (RR) spectroscopic analyses, in combination with steady-state kinetics and the crystal structure, reveal fine pH-dependent details about the heme active site structure and show that both the aspartate (D222) and the arginine (R390) are crucial for hydrogen peroxide reduction. Moreover, the data indicate that these two residues play important but mechanistically different roles on the intraprotein long-range electron transfer process. DATABASE: Structural data are available in the PDB database under the accession number 7ANV.
Keyphrases
- hydrogen peroxide
- nitric oxide
- crystal structure
- poor prognosis
- amino acid
- escherichia coli
- electron transfer
- electronic health record
- cell wall
- binding protein
- big data
- aqueous solution
- highly efficient
- molecular docking
- transcription factor
- small molecule
- energy transfer
- machine learning
- artificial intelligence
- pseudomonas aeruginosa
- single cell
- emergency department
- cystic fibrosis
- dna methylation
- label free
- visible light
- deep learning
- molecular dynamics simulations