Structural Reconstruction of E. coli Ubi Metabolon Using an AlphaFold2-Based Computational Framework.

Ubiquinone (UQ) is a redox polyisoprenoid lipid found in the membranes of bacteria and eukaryotes that has important roles, notably one in respiratory metabolism, which sustains cellular bioenergetics. In Escherichia coli, several steps of the UQ biosynthesis take place in the cytosol. To perform these reactions, a supramolecular assembly called Ubi metabolon is involved. This latter is composed of seven proteins (UbiE, UbiG, UbiF, UbiH, UbiI, UbiJ, and UbiK), and its structural organization is unknown as well as its protein stoichiometry. In this study, a computational framework has been designed to predict the structure of this macromolecular assembly. In several successive steps, we explored the possible protein interactions as well as the protein stoichiometry, to finally obtain a structural organization of the complex. The use of AlphaFold2-based methods combined with evolutionary information enabled us to predict several models whose quality and confidence were further analyzed using different metrics and scores. Our work led to the identification of a "core assembly" that will guide functional and structural characterization of the Ubi metabolon.

Towards Molecular Understanding of the Functional Role of UbiJ-UbiK2 Complex in Ubiquinone Biosynthesis by Multiscale Molecular Modelling Studies.

Ubiquinone (UQ) is a polyisoprenoid lipid found in the membranes of bacteria and eukaryotes. UQ has important roles, notably in respiratory metabolisms which sustain cellular bioenergetics. Most steps of UQ biosynthesis take place in the cytosol of E. coli within a multiprotein complex called the Ubi metabolon, that contains five enzymes and two accessory proteins, UbiJ and UbiK. The SCP2 domain of UbiJ was proposed to bind the hydrophobic polyisoprenoid tail of UQ biosynthetic intermediates in the Ubi metabolon. How the newly synthesised UQ might be released in the membrane is currently unknown. In this paper, we focused on better understanding the role of the UbiJ-UbiK2 heterotrimer forming part of the metabolon. Given the difficulties to gain functional insights using biophysical techniques, we applied a multiscale molecular modelling approach to study the UbiJ-UbiK2 heterotrimer. Our data show that UbiJ-UbiK2 interacts closely with the membrane and suggests possible pathways to enable the release of UQ into the membrane. This study highlights the UbiJ-UbiK2 complex as the likely interface between the membrane and the enzymes of the Ubi metabolon and supports that the heterotrimer is key to the biosynthesis of UQ8 and its release into the membrane of E. coli.

DockNmine, a Web Portal to Assemble and Analyse Virtual and Experimental Interaction Data.

Scientists have to perform multiple experiments producing qualitative and quantitative data to determine if a compound is able to bind to a given target. Due to the large diversity of the potential ligand chemical space, the possibility of experimentally exploring a lot of compounds on a target rapidly becomes out of reach. Scientists therefore need to use virtual screening methods to determine the putative binding mode of ligands on a protein and then post-process the raw docking experiments with a dedicated scoring function in relation with experimental data. Two of the major difficulties for comparing docking predictions with experiments mostly come from the lack of transferability of experimental data and the lack of standardisation in molecule names. Although large portals like PubChem or ChEMBL are available for general purpose, there is no service allowing a formal expert annotation of both experimental data and docking studies. To address these issues, researchers build their own collection of data in flat files, often in spreadsheets, with limited possibilities of extensive annotations or standardisation of ligand descriptions allowing cross-database retrieval. We have conceived the dockNmine platform to provide a service allowing an expert and authenticated annotation of ligands and targets. First, this portal allows a scientist to incorporate controlled information in the database using reference identifiers for the protein (Uniprot ID) and the ligand (SMILES description), the data and the publication associated to it. Second, it allows the incorporation of docking experiments using forms that automatically parse useful parameters and results. Last, the web interface provides a lot of pre-computed outputs to assess the degree of correlations between docking experiments and experimental data.

A functional mini-GDE transgene corrects impairment in models of glycogen storage disease type III.

Glycogen storage disease type III (GSDIII) is a rare inborn error of metabolism affecting liver, skeletal muscle, and heart due to mutations of the AGL gene encoding for the glycogen debranching enzyme (GDE). No curative treatment exists for GSDIII. The 4.6 kb GDE cDNA represents the major technical challenge toward the development of a single recombinant adeno-associated virus-derived (rAAV-derived) vector gene therapy strategy. Using information on GDE structure and molecular modeling, we generated multiple truncated GDEs. Among them, an N-terminal-truncated mutant, ΔNter2-GDE, had a similar efficacy in vivo compared with the full-size enzyme. A rAAV vector expressing ΔNter2-GDE allowed significant glycogen reduction in heart and muscle of Agl-/- mice 3 months after i.v. injection, as well as normalization of histology features and restoration of muscle strength. Similarly, glycogen accumulation and histological features were corrected in a recently generated Agl-/- rat model. Finally, transduction with rAAV vectors encoding ΔNter2-GDE corrected glycogen accumulation in an in vitro human skeletal muscle cellular model of GSDIII. In conclusion, our results demonstrated the ability of a single rAAV vector expressing a functional mini-GDE transgene to correct the muscle and heart phenotype in multiple models of GSDIII, supporting its clinical translation to patients with GSDIII.

Modeling Protein Complexes and Molecular Assemblies Using Computational Methods.

Many biological molecules are assembled into supramolecular complexes that are necessary to perform functions in the cell. Better understanding and characterization of these molecular assemblies are thus essential to further elucidate molecular mechanisms and key protein-protein interactions that could be targeted to modulate the protein binding affinity or develop new binders. Experimental access to structural information on these supramolecular assemblies is often hampered by the size of these systems that make their recombinant production and characterization rather difficult. Computational methods combining both structural data, molecular modeling techniques, and sequence coevolution information can thus offer a good alternative to gain access to the structural organization of protein complexes and assemblies. Herein, we present some computational methods to predict structural models of the protein partners, to search for interacting regions using coevolution information, and to build molecular assemblies. The approach is exemplified using a case study to model the succinate-quinone oxidoreductase heterocomplex.