Coenzyme Q Biosynthesis: Evidence for a Substrate Access Channel in the FAD-Dependent Monooxygenase Coq6.

Coq6 is an enzyme involved in the biosynthesis of coenzyme Q, a polyisoprenylated benzoquinone lipid essential to the function of the mitochondrial respiratory chain. In the yeast Saccharomyces cerevisiae, this putative flavin-dependent monooxygenase is proposed to hydroxylate the benzene ring of coenzyme Q (ubiquinone) precursor at position C5. We show here through biochemical studies that Coq6 is a flavoprotein using FAD as a cofactor. Homology models of the Coq6-FAD complex are constructed and studied through molecular dynamics and substrate docking calculations of 3-hexaprenyl-4-hydroxyphenol (4-HP6), a bulky hydrophobic model substrate. We identify a putative access channel for Coq6 in a wild type model and propose in silico mutations positioned at its entrance capable of partially (G248R and L382E single mutations) or completely (a G248R-L382E double-mutation) blocking access to the channel for the substrate. Further in vivo assays support the computational predictions, thus explaining the decreased activities or inactivation of the mutated enzymes. This work provides the first detailed structural information of an important and highly conserved enzyme of ubiquinone biosynthesis.

ubiI, a new gene in Escherichia coli coenzyme Q biosynthesis, is involved in aerobic C5-hydroxylation.

Coenzyme Q (ubiquinone or Q) is a redox-active lipid found in organisms ranging from bacteria to mammals in which it plays a crucial role in energy-generating processes. Q biosynthesis is a complex pathway that involves multiple proteins. In this work, we show that the uncharacterized conserved visC gene is involved in Q biosynthesis in Escherichia coli, and we have renamed it ubiI. Based on genetic and biochemical experiments, we establish that the UbiI protein functions in the C5-hydroxylation reaction. A strain deficient in ubiI has a low level of Q and accumulates a compound derived from the Q biosynthetic pathway, which we purified and characterized. We also demonstrate that UbiI is only implicated in aerobic Q biosynthesis and that an alternative enzyme catalyzes the C5-hydroxylation reaction in the absence of oxygen. We have solved the crystal structure of a truncated form of UbiI. This structure shares many features with the canonical FAD-dependent para-hydroxybenzoate hydroxylase and represents the first structural characterization of a monooxygenase involved in Q biosynthesis. Site-directed mutagenesis confirms that residues of the flavin binding pocket of UbiI are important for activity. With our identification of UbiI, the three monooxygenases necessary for aerobic Q biosynthesis in E. coli are known.

An integrative computational model for large-scale identification of metalloproteins in microbial genomes: a focus on iron-sulfur cluster proteins.

Metalloproteins represent a ubiquitous group of molecules which are crucial to the survival of all living organisms. While several metal-binding motifs have been defined, it remains challenging to confidently identify metalloproteins from primary protein sequences using computational approaches alone. Here, we describe a comprehensive strategy based on a machine learning approach to design and assess a penalized generalized linear model. We used this strategy to detect members of the iron-sulfur cluster protein family. A new category of descriptors, whose profile is based on profile hidden Markov models, encoding structural information was combined with public descriptors into a linear model. The model was trained and tested on distinct datasets composed of well-characterized iron-sulfur protein sequences, and the resulting model provided higher sensitivity compared to a motif-based approach, while maintaining a good level of specificity. Analysis of this linear model allows us to detect and quantify the contribution of each descriptor, providing us with a better understanding of this complex protein family along with valuable indications for further experimental characterization. Two newly-identified proteins, YhcC and YdiJ, were functionally validated as genuine iron-sulfur proteins, confirming the prediction. The computational model was then applied to over 550 prokaryotic genomes to screen for iron-sulfur proteomes; the results are publicly available at: . This study represents a proof-of-concept for the application of a penalized linear model to identify metalloprotein superfamilies on a large-scale. The application employed here, screening for iron-sulfur proteomes, provides new candidates for further biochemical and structural analysis as well as new resources for an extensive exploration of iron-sulfuromes in the microbial world.