Protein ScienceBioinformaticsPeer-reviewed journal article
Computational Structure Prediction Provides a Plausible Mechanism for Electron Transfer by the Outer Membrane Protein Cyc2 from Acidithiobacillus ferrooxidans
Abstract
Cyc2 is the key protein in the outer membrane of Acidithiobacillus ferrooxidans that mediates electron transfer between extracellular inorganic iron and the intracellular central metabolism. This cytochrome c is specific for iron and interacts with periplasmic proteins to complete a reversible electron transport chain. A structure of Cyc2 has not yet been characterized experimentally. Here we describe a structural model of Cyc2, and associated proteins, to highlight a plausible mechanism for the ferrous iron electron transfer chain. A comparative modeling protocol specific for trans membrane beta barrel (TMBB) proteins in acidophilic conditions (pH ~2) was applied to the primary sequence of Cyc2. The proposed structure has three main regimes: extracellular loops exposed to low-pH conditions, a TMBB, and a N-terminal cytochrome-like region within the periplasmic space. The Cyc2 model was further refined by identifying likely iron and heme docking sites. This represents the first computational model of Cyc2 that accounts for the membrane microenvironment and the acidity in the extracellular matrix. This approach can be used to model other TMBBs which can be critical for chemolithotrophic microbial growth. Importance of workAcidithiobacillus ferrooxidans can oxidize both iron and reduced sulfur compounds and plays a key role in metal sulfide ore bioleaching used for the industrial recovery of metals. A. ferrooxidans has also been explored as a potential organism for emerging technologies such as e-waste recycling and biofuel production. Synthetic biology efforts are hampered by lack of knowledge about the mechanisms of iron oxidation and reduction, which is mediated by the Cyc2 transmembrane beta barrel (TMBB) protein.
- organism: bacteria (other)
- assay: protein structure
- research focus: protein structure prediction
- approach: statistical model
- Citations
- 28
- FWCI
- 1.33
- Field percentile
- top 20%
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