Defining the scope for altering rice leaf anatomy to improve photosynthesis: a modelling approach

Leaf structure plays an important role in photosynthesis. However, the causal relationship and the quantitative importance of any single structural parameter to the overall photosynthetic performance of a leaf remains open to debate. In this paper, we report on a mechanistic model, eLeaf, which successfully captures rice leaf photosynthetic performance under varying environmental conditions of light and CO2. We developed a 3D reaction-diffusion model for leaf photosynthesis parameterised using a range of imaging data and biochemical measurements from plants grown under ambient and elevated CO2 and then interrogated the model to quantify the importance of these elements. The model successfully captured leaf-level photosynthetic performance in rice. Photosynthetic metabolism underpinned the majority of the increased carbon assimilation rate observed under elevated CO2 levels, with a range of structural elements making positive and negative contributions. Mesophyll porosity could be varied without any major outcome on photosynthetic performance, providing a theoretical underpinning for experimental data. eLeaf allows quantitative analysis of the influence of morphological and biochemical properties on leaf photosynthesis. The analysis highlights a degree of leaf structural plasticity with respect to photosynthesis of significance in the context of attempts to improve crop photosynthesis

Development of a Novel Virtual Screening Cascade Protocol to Identify Potential Trypanothione Reductase Inhibitors

The implementation of a novel sequential computational approach that can be used effectively for virtual screening and identification of prospective ligands that bind to trypanothione reductase (TryR) is reported. The multistep strategy combines a ligand-based virtual screening for building an enriched library of small molecules with a docking protocol (AutoDock, X-Score) for screening against the TryR target. Compounds were ranked by an exhaustive conformational consensus scoring approach that employs a rank-by-rank strategy by combining both scoring functions. Analysis of the predicted ligand-protein interactions highlights the role of bulky quaternary amine moieties for binding affinity. The scaffold hopping (SHOP) process derived from this computational approach allowed the identification of several chemotypes, not previously reported as antiprotozoal agents, which includes dibenzothiepine, dibenzooxathiepine, dibenzodithiepine, and polycyclic cationic structures like thiaazatetracyclo-nonadeca-hexaen-3-ium. Assays measuring the inhibiting effect of these compounds on T. cruzi and T. brucei TryR confirm their potential for further rational optimization

A theoretical entropy score as a single value to express inhibitor selectivity

<p>Abstract</p> <p>Background</p> <p>Designing maximally selective ligands that act on individual targets is the dominant paradigm in drug discovery. Poor selectivity can underlie toxicity and side effects in the clinic, and for this reason compound selectivity is increasingly monitored from very early on in the drug discovery process. To make sense of large amounts of profiling data, and to determine when a compound is sufficiently selective, there is a need for a proper quantitative measure of selectivity.</p> <p>Results</p> <p>Here we propose a new theoretical entropy score that can be calculated from a set of IC₅₀data. In contrast to previous measures such as the 'selectivity score', Gini score, or partition index, the entropy score is non-arbitary, fully exploits IC₅₀data, and is not dependent on a reference enzyme. In addition, the entropy score gives the most robust values with data from different sources, because it is less sensitive to errors. We apply the new score to kinase and nuclear receptor profiling data, and to high-throughput screening data. In addition, through analyzing profiles of clinical compounds, we show quantitatively that a more selective kinase inhibitor is not necessarily more drug-like.</p> <p>Conclusions</p> <p>For quantifying selectivity from panel profiling, a theoretical entropy score is the best method. It is valuable for studying the molecular mechanisms of selectivity, and to steer compound progression in drug discovery programs.</p

Nature of the bonding in metal-silane σ-complexes

The nature of metal silane σ-bond interaction has been investigated in several key systems by a range of experimental and computational techniques. The structure of [Cp′Mn(CO)2(η2-HSiHPh2)] 1 has been determined by single crystal neutron diffraction, and the geometry at the Si atom is shown to approximate a trigonal bipyramid; salient bond distances and angles are Mn−H(1) 1.575(14), Si−H(1) 1.806(14), Si−H(2) 1.501(13) Å, and H(1)−Si−H(2) 148.5(8)°. This complex is similar to [Cp′Mn(CO)2(η2-HSiFPh2)] 2, whose structure and bonding characteristics have recently been determined by charge density studies based on high-resolution X-ray and neutron diffraction data. The geometry at the Si atom in these σ-bond complexes is compared with that in other systems containing hypercoordinate silicon. The Mn−H distances for 1 and 2 in solution have been estimated using NMR T1 relaxation measurements, giving a value of 1.56(3) Å in each case, in excellent agreement with the distances deduced from neutron diffraction. Density functional theory calculations have been employed to explore the bonding in the Mn−H−Si unit in 1 and 2 and in the related system [Cp′Mn(CO)2(η2-HSiCl3)] 3. These studies support the idea that the oxidative addition of a silane ligand to a transition metal center may be described as an asymmetric process in which the Mn−H bond is formed at an early stage, while both the establishment of the Mn−Si bond and also the activation of the η2-coordinated Si−H moiety are controlled by the extent of Mn → σ*(X−Si−H) back-donation, which increases with increasing electron-withdrawing character of the X substituent trans to the metal-coordinated Si−H bond. This delocalized molecular orbital (MO) approach is complemented and supported by combined experimental and theoretical charge density studies: the source function S(r,Ω), which provides a measure of the relative importance of each atom’s contribution to the density at a specific reference point r, clearly shows that all three atoms of the Mn(η2-SiH) moiety contribute to a very similar extent to the density at the Mn−Si bond critical point, in pleasing agreement with the MO model. Hence, we advance a consistent and unifying concept which accounts for the degree of Si−H activation in these silane σ-bond complexes