OxyB is a cytochrome P450 enzyme that catalyzes the first phenol coupling reaction during the biosynthesis of vancomycin-like glycopeptide antibiotics. The phenol coupling reaction occurs on a linear peptide intermediate linked as a C-terminal thioester to a peptide carrier protein (PCP) domain within the multidomain glycopeptide nonribosomal peptide synthetase (NRPS). Using model peptides with the sequence (R)(NMe)Leu-(R)Tyr-(S)Asn-(R)Hpg-(R)Hpg-(S)Tyr-S-PCP and (R)(NMe)Leu-(R)Tyr-(S)Asn-(R)Hpg-(R)Hpg-(S)Tyr-(S)Dpg-S-PCP (where Hpg = 4-hydroxyphenylglycine, and Dpg = 3,5-dihydroxyphenylglycine), or containing (R)Leu instead of (R)(NMe)Leu, attached to recombinant PCPs derived from modules-6 and -7 in the vancomycin NRPS, we show that cross-linking of Hpg4 and Tyr6 by OxyB can occur in both hexapeptide- and heptapeptide-PCP conjugates. Thus, whereas OxyB may act preferentially on a hexapeptide still linked to the PCP-6 in NRPS subunit-2, it is possible that a linear heptapeptide intermediate linked to PCP-7 in NRPS subunit-3 may also be transformed into monocyclic product. For turnover, OxyB requires electrons, which in vitro can be supplied by spinach ferredoxin and E. coli flavodoxin reductase. Turnover is also dependent upon the presence of molecular oxygen. The model substrate (R)(NMe)Leu-(R)Tyr-(S)Asn-(R)Hpg-(R)Hpg-(S)Tyr-S-PCP is transformed into cross-linked product by OxyB with a kcat of 0.1 s-1 and Km in the range 4-13 muM. Equilibrium binding of this substrate to OxyB, monitored by UV-vis, is accompanied by a typical low-to-high spin state change in the heme, characterized with a Kd of 17 +/- 5 muM.

The polypyrimidine tract binding protein (PTB) is a 58 kDa protein involved in many aspects of RNA metabolism. In this study, we focused our attention on the structure of the two C-terminal RNA recognition motifs (RRM3 and RRM4) of PTB. In a previous study, it was found that the two RRMs are independent in the free state. We recently determined the structure of the same fragment in complex with RNA and found that the two RRMs interact extensively. This difference made us re-evaluate in detail the free protein structure and in particular the interdomain interface. We used a combination of NMR spectroscopy and segmental isotopic labeling to unambiguously study and characterize the interdomain interactions. An improved segmental isotopic labeling protocol was used, enabling us to unambiguously identify 130 interdomain NOEs between the two RRMs and to calculate a very precise structure. The structure reveals a large interdomain interface, resulting in a very unusual positioning of the two RRM domains relative to one another.

Gene-inactivation studies point to the involvement of OxyB in catalyzing the first oxidative phenol coupling reaction during glycopeptide antibiotic biosynthesis. The oxyB gene has been cloned and sequenced from the vancomycin producer Amycolatopsis orientalis, and the hemoprotein has been produced in Escherichia coli, crystallized, and its structure determined to 1.7-Å resolution. OxyB gave UV-visible spectra characteristic of a P450-like hemoprotein in the low spin ferric state. After reduction to the ferrous state by dithionite or by spinach ferredoxin and ferredoxin reductase, the CO-ligated form gave a 450-nm peak in a UV-difference spectrum. Addition of putative heptapeptide substrates to resting OxyB produced type I changes to the UV spectrum, but no turnover was observed in the presence of ferredoxin and ferredoxin reductase, showing that either the peptides or the reduction system, or both, are insufficient to support a full catalytic cycle. OxyB exhibits the typical P450-fold, with helix L containing the signature sequence FGHGXHXCLG and Cys 347 being the proximal axial thiolate ligand of the heme iron. The structural similarity of OxyB is highest to P450nor, P450terp, CYP119, and P450eryF. In OxyB, the F and G helices are rotated out of the active site compared with P450nor, resulting in a much more open active site, consistent with the larger size of the presumed heptapeptide substrate.

In recent years, high-throughput sequencing technologies provide unprecedented opportunity to depict cancer samples at multiple molecular levels. The integration and analysis of these multi-omics datasets is a crucial and critical step to gain actionable knowledge in a precision medicine framework. This paper explores recent data-driven methodologies that have been developed and applied to respond major challenges of stratified medicine in oncology, including patients' phenotyping, biomarker discovery, and drug repurposing. We systematically retrieved peer-reviewed journals published from 2014 to 2019, select and thoroughly describe the tools presenting the most promising innovations regarding the integration of heterogeneous data, the machine learning methodologies that successfully tackled the complexity of multi-omics data, and the frameworks to deliver actionable results for clinical practice. The review is organized according to the applied methods: Deep learning, Network-based methods, Clustering, Features Extraction, and Transformation, Factorization. We provide an overview of the tools available in each methodological group and underline the relationship among the different categories. Our analysis revealed how multi-omics datasets could be exploited to drive precision oncology, but also current limitations in the development of multi-omics data integration.