Mapping Functionally Important and Stabilising Regions in Biotherapeutic Proteins, using NMR and Mutagenesis

Structure-function relationships in proteins refer to a trade-off between stability and bioactivity, moulded by evolution of the molecule. Identifying which protein amino acid residues jeopardise global or local stability for the benefit of bioactivity would reveal residues pivotal to this structure-function trade-off. Demonstrated here is the use of varied-temperature 15N-1H heteronuclear single quantum coherence (HSQC) nuclear magnetic resonance (NMR) spectroscopy to probe the microenvironment and dynamics of residues in granulocyte-colony stimulating factor (G-CSF). This experimental approach was also used to investigate (de-) stabilising mechanisms of action for previously studied excipients with G-CSF. Combining NMR with in silico analysis revealed four structural clusters that are subject to localised conformational changes (some of which are key to bioactivity) or partial unfolding prior to global unfolding at higher temperatures. Mechanisms by which excipients influence these important structural changes and implement their own structural clusters reflects their impact on stability and function. This approach was leveraged for semi-rational mutant/formulation design. These mutants were tested for fitness with respect to thermostability and functionality. The Mutants P65V and E45Q were constructed to elicit mutation-excipient interactions, and presented the largest impact on the respective fitness. Hence, this study proposes an approach to profile residues, thus highlighting their roles in stability and bioactivity while exposing potential mutation-excipient interactions. This permits a semi-rational protein engineering approach to optimise desirable protein fitness characteristics

Opening the Black Box of the Radiation Belt Machine Learning Model

Many Machine Learning (ML) systems, especially neural networks, are fundamentally regarded as black boxes since it is difficult to grasp how they function once they have been trained. Here, we tackle the issue of the interpretability of a high-accuracy ML model created to model the flux of Earth's radiation belt electrons. The Outer RadIation belt Electron Neural net model (ORIENT) uses only solar wind conditions and geomagnetic indices as input. Using the Deep SHAPley additive explanations (DeepSHAP) method, we show that the `black box' ORIENT model can be successfully explained. Two significant electron flux enhancement events observed by Van Allen Probes during the storm interval of 17 to 18 March 2013 and non storm interval of 19 to 20 September 2013 are investigated using the DeepSHAP method. The results show that the feature importances calculated from the purely data driven ORIENT model identify physically meaningful behavior consistent with current physical understanding.Comment: Under revie

Wave-induced loss of ultra-relativistic electrons in the Van Allen radiation belts.

The dipole configuration of the Earth's magnetic field allows for the trapping of highly energetic particles, which form the radiation belts. Although significant advances have been made in understanding the acceleration mechanisms in the radiation belts, the loss processes remain poorly understood. Unique observations on 17 January 2013 provide detailed information throughout the belts on the energy spectrum and pitch angle (angle between the velocity of a particle and the magnetic field) distribution of electrons up to ultra-relativistic energies. Here we show that although relativistic electrons are enhanced, ultra-relativistic electrons become depleted and distributions of particles show very clear telltale signatures of electromagnetic ion cyclotron wave-induced loss. Comparisons between observations and modelling of the evolution of the electron flux and pitch angle show that electromagnetic ion cyclotron waves provide the dominant loss mechanism at ultra-relativistic energies and produce a profound dropout of the ultra-relativistic radiation belt fluxes

e-VLBI observations of GHz-Peaked Spectrum (GPS) radio sources in nearby galaxies from the AT20G survey

GHz-peaked spectrum (GPS) radio sources are thought to be young objects which later evolve into FR-I and FR-II radio galaxies. We have used the Australia Telescope 20GHz (AT20G) survey catalogue to select a uniform sample of GPS sources with spectral peaks above 5GHz, which should represent the youngest members of this class. In this paper, we present e-VLBI observations of ten such objects which are associated with nearby (z<0.15) galaxies and so represent a new population of local, low--power GPS sources. Our e-VLBI observations were carried out at 4.8GHz with the Australia Telescope Long Baseline Array (LBA) using a real--time software correlator. All ten sources were detected, and were unresolved on scales of ~100mas, implying that they are typically less than 100pc in linear size.Comment: 7 pages, 7 figures, 3 table

NMR Reveals Functionally Relevant Thermally Induced Structural Changes within the Native Ensemble of G-CSF.

Structure-function relationships in proteins refer to a trade-off between stability and bioactivity, molded by evolution of the molecule. Identifying which protein amino acid residues jeopardize global or local stability for the benefit of bioactivity would reveal residues pivotal to this structure-function trade-off. Here, we use 15N-1H heteronuclear single quantum coherence (HSQC) nuclear magnetic resonance (NMR) spectroscopy to probe the microenvironment and dynamics of residues in granulocyte colony-stimulating factor (G-CSF) through thermal perturbation. From this analysis, we identified four residues (G4, A6, T133, and Q134) that we classed as significant to global stability, given that they all experienced large environmental and dynamic changes and were closely correlated to each other in their NMR characteristics. Additionally, we observe that roughly four structural clusters are subject to localized conformational changes or partial unfolding prior to global unfolding at higher temperature. Combining NMR observables with structure relaxation methods reveals that these structural clusters concentrate around loop AB (binding site III inclusive). This loop has been previously implicated in conformational changes that result in an aggregation prone state of G-CSF. Residues H43, V48, and S63 appear to be pivotal to an opening motion of loop AB, a change that is possibly also important for function. Hence, we present here an approach to profiling residues in order to highlight their potential roles in the two vital characteristics of proteins: stability and bioactivity

Modeling Field Line Curvature Scattering Loss of 1–10 MeV Protons During Geomagnetic Storms

The proton radiation belt contains high fluxes of adiabatically trapped protons varying in energy from ∼one to hundreds of megaelectron volts (MeV). At large radial distances, magnetospheric field lines become stretched on the nightside of Earth and exhibit a small radius of curvature RC near the equator. This leads protons to undergo field line curvature (FLC) scattering, whereby changes to the first adiabatic invariant accumulate as field strength becomes nonuniform across a gyroorbit. The outer boundary of the proton belt at a given energy corresponds to the range of magnetic L shell over which this transition to nonadiabatic motion takes place, and is sensitive to the occurrence of geomagnetic storms. In this work, we first find expressions for nightside equatorial RC and field strength Be as functions of Dst and L* to fit the TS04 field model. We then apply the Tu et al. (2014, https://doi.org/10.1002/2014ja019864) condition for nonadiabatic onset to solve the outer boundary L*, and refine our expression for RC to achieve agreement with Van Allen Probes observations of 1–50 MeV proton flux over the 2014–2018 era. Finally, we implement this nonadiabatic onset condition into the British Antarctic Survey proton belt model (BAS-PRO) to solve the temporal evolution of proton fluxes at L ≤ 4. Compared with observations, BAS-PRO reproduces storm losses due to FLC scattering, but there is a discrepancy in mid-2017 that suggests a ∼5 MeV proton source not accounted for. Our work sheds light on outer zone proton belt variability at 1–10 MeV and demonstrates a useful tool for real-time forecasting