DENSITY FUNCTIONAL CALCULATIONS OF BACKBONE 15N CHEMICAL SHIELDINGS IN PEPTIDES AND PROTEINS

In this dissertation, we describe computational and theoretical study of backbone 15N chemical shieldings in peptides and proteins. Comprehensive density functional calculations have been performed on systems of different complexity, ranging from model dipeptides to real proteins and protein complexes. We begin with examining the effects of solvation, hydrogen bonding, backbone conformation, and the side chain identity on 15N chemical shielding in proteins by density functional calculations. N-methylacetamide (NMA) and N-formyl-alanyl-X (with X being one of the 19 naturally occurring amino acids excluding proline) were used as model systems for this purpose. The conducting polarizable continuum model was employed to include the effect of solvent in the calculations. We show that the augmentation of the polarizable continuum model with the explicit water molecules in the first solvation shell has a significant influence on isotropic 15N chemical shift but not as much on the chemical shift anisotropy. The difference in the isotropic chemical shift between the standard &beta-sheet and standard &alpha-helical conformations ranges from 0.8 ppm to 6.2 ppm depending on the residue type, with the mean of 2.7 ppm. This is in good agreement with the experimental chemical shifts averaged over a database of 36 proteins containing >6100 amino acid residues. The orientation of the 15N chemical shielding tensor as well as its anisotropy and asymmetry are also in the range of values experimentally observed for peptides and proteins. Having applied density functional calculation successfully to model peptides, we develop a computationally efficient methodology to include most of the important effects in the calculation of chemical shieldings of backbone 15N in a protein. We present the application to selected &alpha-helical and &beta-sheet residues of protein G. The role of long-range intra-protein electrostatic interactions by comparing models with different complexity in vacuum and in charge field is analyzed. We show that the dipole moment of the &alpha-helix can cause significant deshielding of 15N; therefore, it needs to be considered when calculating 15N chemical shielding. We emphasize the importance of including interactions with the side chains that are close in space when the charged form for ionizable side chains is adopted in the calculation. We also illustrate how the ionization state of these side chains can affect the chemical shielding tensor elements. For &alpha-helical residues, chemical shielding calculations using a 8-residue fragment model in vacuum and adopting the charged form of ionizable side chains yield a generally good agreement with experimental data. We also performed computational modeling of the chemical shift perturbations occurring upon protein-protein or protein-ligand binding. We show that the chemical shift perturbations in ubiquitin upon dimer formation can be explained qualitatively through computation. This dissertation hence demonstrates that quantum chemical calculations can be successfully used to obtain a fundamental understanding of the relationship between chemical shielding and the surrounding protein environment for the elusive case of 15N and therefore enhance the role of 15N chemical shift measurements in the analysis of protein structure and dynamics

Rethinking Item Importance in Session-based Recommendation

Session-based recommendation aims to predict users' based on anonymous sessions. Previous work mainly focuses on the transition relationship between items during an ongoing session. They generally fail to pay enough attention to the importance of the items in terms of their relevance to user's main intent. In this paper, we propose a Session-based Recommendation approach with an Importance Extraction Module, i.e., SR-IEM, that considers both a user's long-term and recent behavior in an ongoing session. We employ a modified self-attention mechanism to estimate item importance in a session, which is then used to predict user's long-term preference. Item recommendations are produced by combining the user's long-term preference and current interest as conveyed by the last interacted item. Experiments conducted on two benchmark datasets validate that SR-IEM outperforms the start-of-the-art in terms of Recall and MRR and has a reduced computational complexity

Characterisation of de-structured starch and its interactions in whey protein isolate gels : a thesis submitted in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Food Technology at Massey University, Palmerston North, New Zealand

Permission from Elsevier was granted for the re-use of four articles published in Food Hydrocolloids. Figures 2-2, 2-4, 2-5, 2-6, 2-8, 2-9, 2-12, 2-14, 2-16, 3-7, 3-8, 3-9, 3-19, 3-20 & 3-22 are also re-used with permission. Figures 2-3, 2-7 & 2.10 are re-used under a Creative Commons CC-BY license.Starch serves as an important additive to enhance the physico-chemical properties of many food products. With the increased pursuit of natural products, there is an increasing demand for “clean-label” starches. In this study, waxy potato starch was physically-modified at elevated temperatures of 120–150 °C for 30 min at 300 rpm, in a pressurised reactor. The treatment converted native starch granules into their macromolecular chains (denoted as de-structured waxy potato starch, DWPS). This doctoral thesis presents the: (i) method of modifying starch (i.e., the de-structuring process), (ii) the mechanism of starch de-structuring, (iii) the rheological changes in DWPS samples and the shear-thickening mechanism, and (iv) the interactions of these DWPS ingredients with whey protein isolate (WPI) in a protein-based gel system, at different pH and ionic strength. The molar mass (Mᵥᵥ), particle size, rheological properties, degree of branching (DB) and side-chain length distribution of DWPS samples were characterised to elucidate the starch de-structuring mechanism. DWPS treated at 120 °C DWPS showed similar Mᵥᵥ (~3.6 × 10⁸ Da) as its native form (~3.7 × 10⁸ Da) indicating that the treatment at 120 °C resulted in the disassembly of starch granules into their macromolecular chains. Reduction in viscosity, Mᵥᵥ and particle size was observed with an increase in temperature from 120 to 150 °C, suggesting a cleavage in amylopectin chains. The DB and side-chain distribution data suggest that the reduction in Mᵥᵥ is likely due to the cleavage at α-1,4 linkages near the middle of the main amylopectin backbone. Particle size analysis by laser diffraction measurements revealed the presence of large fragment particles (> 1 µm) in DWPS samples, indicating that the starch de-structuring process into its macromolecules was incomplete even at 150 °C for 30 min. The DWPS (5% w/w) samples were found to exhibit a wide range of rheological properties—Newtonian, shear-thinning, shear-thickening and anti-thixotropy behaviours—depending on their treatment temperature (120–150 °C). In particular, 120 °C DWPS exhibited interesting shear-thickening, anti-thixotropy and shear-induced gelation. These rheological properties are different from the shear-thinning and thixotropy behaviours observed in most conventionally gelatinised waxy potato starches treated at 95 °C. The complex shear-induced structures of 120 °C DWPS were attributed to a two-step process: (i) upon shear at the critical shear rate (~10–20 s⁻¹), the shear stress caused a size reduction in the starch fragments and (ii) the increased number of small fragments together with the amylopectin chains in very close proximity could lead to the formation of a complex network probably consisting of amylopectin chains and a large number of fragments (2–20 μm). Shear thickening properties were attributed largely to these soft fragment particles colliding and sliding past each other during shear. The data from this study has also shown that the hydrogen bonding, electrostatic, hydrophobic interactions, or the combination of these interactions did not cause the shear-thickening behaviour. The influence of 4% w/w DWPS on 13% w/w WPI gels was studied by characterising the phase stability of the liquid mixtures, and mechanical properties, microstructure, and water-immersion stability of fine-stranded polymeric and coarse-stranded particulate protein gels at pH 7 and pH 5, respectively. At neutral pH, synergistic gel hardness of WPI was obtained with the incorporation of 140 °C DWPS. The increased gel strength was attributed to the enhanced density of a very fine-stranded gel network. The ability of the gel to retain its shape when immersed in water for 40 h was most noticeable for the composite gels containing either gelatinised starch or DWPS samples (swollen gels but with intact shape). In contrast, pure WPI gel and composite gel containing maltodextrin turned into very weak fluid-like and disintegrated gels, respectively. At pH 5, WPI formed particulate gels. The addition of gelatinised starch or DWPS weakened the particulate protein gels, likely due to phase separation and interrupted protein network with starch polymers acting as inactive fillers. The effects of NaCl and CaCl₂ (i.e., type of salts and ionic strength) on the mechanical and microstructural properties of composite gels containing 13% w/w WPI and 4% w/w 140 °C DWPS were also evaluated. Thermodynamic incompatibility between WPI and 140 °C DWPS was observed upon the addition of NaCl (~75 mM) or CaCl₂ (10–75 mM). The combined effects of such thermodynamic incompatibility with the changes in protein connectivity induced by varied ionic strength led to the formation of distinctive gel structures (inhomogeneous self-supporting gels with a liquid centre and weak gels with paste-like consistency) that were different from thermodynamic compatible homogeneous self-supporting gels (pure WPI and WPI + maltodextrin gels). At ≥ 250 mM NaCl, instead of a paste-like texture, a recovered soft self-supporting gel structure was observed when using 140 °C DWPS. The ability to generate a range of textures in WPI gelation-based foods by using 140 °C DWPS under different ionic conditions, is a feasible strategy for structuring high-protein foods for dysphagia—aimed to be either thickened fluids or soft solids. Additionally, this acquired knowledge is also relevant when formulating food gels for 3-D printing. The desirable rheological properties of DWPS samples and their ability to alter WPI gel structure signify the potential of DWPS as a clean-label ingredient to structure foods of specific needs (e.g., whipping cream for enhanced structure upon shear and high-protein foods for dysphagia sufferers)

A Deep Reinforcement Learning Framework for Rebalancing Dockless Bike Sharing Systems

Bike sharing provides an environment-friendly way for traveling and is booming all over the world. Yet, due to the high similarity of user travel patterns, the bike imbalance problem constantly occurs, especially for dockless bike sharing systems, causing significant impact on service quality and company revenue. Thus, it has become a critical task for bike sharing systems to resolve such imbalance efficiently. In this paper, we propose a novel deep reinforcement learning framework for incentivizing users to rebalance such systems. We model the problem as a Markov decision process and take both spatial and temporal features into consideration. We develop a novel deep reinforcement learning algorithm called Hierarchical Reinforcement Pricing (HRP), which builds upon the Deep Deterministic Policy Gradient algorithm. Different from existing methods that often ignore spatial information and rely heavily on accurate prediction, HRP captures both spatial and temporal dependencies using a divide-and-conquer structure with an embedded localized module. We conduct extensive experiments to evaluate HRP, based on a dataset from Mobike, a major Chinese dockless bike sharing company. Results show that HRP performs close to the 24-timeslot look-ahead optimization, and outperforms state-of-the-art methods in both service level and bike distribution. It also transfers well when applied to unseen areas

Crystal structure of 3-benzyl-2,3-dihydro-2-thioxoquinazolin-4(1H)-one, C15H12N2OS

Abstract C15H12N2OS, triclinic, P1̅ (no. 2), a = 6.4172(6) Å, b = 9.7237(10) Å, c = 10.5031(10) Å, α = 84.838(2)°, β = 87.561(2)°, γ = 78.557(2)°, V = 639.54(11) Å3, Z = 2, R gt(F) = 0.0362, wR ref(F 2) = 0.0934, T = 296 K