Insights from semi-oriented EPR spectroscopy studies into the interaction of lytic polysaccharide monooxygenases with cellulose

Probing the detailed interaction between lytic polysaccharide monooxygenases (LPMOs) and their polysaccharide substrates is key to revealing further insights into the mechanism of action of this class of enzymes on recalcitrant biomass. This investigation is somewhat hindered, however, by the insoluble nature of the substrates, which precludes the use of most optical spectroscopic techniques. Herein, we report a new semi-oriented EPR method which evaluates directly the binding of cellulose-active LPMOs to crystalline cellulose. We make use of the intrinsic order of cellulose fibres in Apium graveolens (celery) to orient the LPMO with respect to the magnetic field of an EPR spectrometer. The subsequent angle-dependent changes observed in the EPR spectra can then be related to the orientation of the g matrix principal directions with respect to the magnetic field of the spectrometer and, hence, to the binding of the enzyme onto the cellulose fibres. This method, which does not require specific modification of standard CW-EPR equipment, can be used as a general procedure to investigate LPMO–cellulose interactions

Structural and functional insight into human O-GlcNAcase

O-GlcNAc hydrolase (OGA) removes O-linked N-acetylglucosamine (O-GlcNAc) from a myriad of nucleocytoplasmic proteins. Through co-expression and assembly of OGA fragments, we determined the three-dimensional structure of human OGA, revealing an unusual helix-exchanged dimer that lays a structural foundation for an improved understanding of substrate recognition and regulation of OGA. Structures of OGA in complex with a series of inhibitors define a precise blueprint for the design of inhibitors that have clinical value

Structural and functional insight into human O-GlcNAcase.

O-GlcNAc hydrolase (OGA) removes O-linked N-acetylglucosamine (O-GlcNAc) from a myriad of nucleocytoplasmic proteins. Through co-expression and assembly of OGA fragments, we determined the three-dimensional structure of human OGA, revealing an unusual helix-exchanged dimer that lays a structural foundation for an improved understanding of substrate recognition and regulation of OGA. Structures of OGA in complex with a series of inhibitors define a precise blueprint for the design of inhibitors that have clinical value

Recovering Biological Electron Transfer Reaction Parameters from Multiple Protein Film Voltammetric Techniques Informed by Bayesian Inference

Deciphering the mechanism, kinetics and energetics of biological electron-transfer reactions requires a robust, rapid and reproducible protein-film voltammetry information recovery process. Here we describe a semi-automated computational approach for inferring the chemical reaction parameters for a simple protein system, a bacterial cytochrome domain from Cellvibrio japonicus that displays reversible one-electron redox chemistry. Despite the relative simplicity of the experimental system, developing a robust data analysis approach to find the global optimum in 13-dimensional parameter space is a challenging task because the Faradaic-to-background current ratio in such experiments is often low. We describe how a multiple-technique approach, whereby data from three voltammetry techniques (direct-current, pure sinusoidal and Fourier transform alternating current voltammetry) is combined, ultimately enables the automatic extraction of both (i) quantitative “best-fit” redox reaction parameter point values that are robust across multiple experiments performed on different protein-electrode films, and (ii) a statistical description of parameter correlation relationships, along with uncertainty in the individual parameter values, obtained using Bayesian inference. It is the latter achievement which is particularly important as it represents a method for visualising the possible limitations in the mathematical model of the experimental system. Our multi-voltammetry analysis approach enables such powerful insight because of the complementarity between the information content, simulation-speed and parameter sensitivity of the current-time data generated by the different techniques, illustrating the value of adding purely sinusoidal voltammetry to the bioelectrochemistry measurement toolkit