Mathematical Aspects of Phylogenetic Groves

The inference of new information on the relatedness of species by phylogenetic trees based on DNA data is one of the main challenges of modern biology. But despite all technological advances, DNA sequencing is still a time-consuming and costly process. Therefore, decision criteria would be desirable to decide a priori which data might contribute new information to the supertree which is not explicitly displayed by any input tree. A new concept, the so-called groves, to identify taxon sets with the potential to construct such informative supertrees was suggested by Ané et al. in 2009. But the important conjecture that maximal groves can easily be identified in a database remained unproved and was published on the Isaac Newton Institute’s list of open phylogenetic problems. In this paper, we show that the conjecture does not generally hold, but also introduce a new concept, namely, the 2-overlap groves, which overcomes this problem.     

Protic ionic liquids based on phosphonium cations: comparison with ammonium analogues

Novel protic ionic liquids (PILs) based on a tributyl phosphonium cation have been synthesised and characterised, revealing that the phosphonium based ILs show high thermal stability, high ionic conductivity and facile proton reduction compared to the corresponding ammonium based ILs.     

Inference and Learning in a Latent Variable Model for Beta Distributed Interval Data

Latent Variable Models (LVMs) are well established tools to accomplish a range of different data processing tasks. Applications exploit the ability of LVMs to identify latent data structure in order to improve data (e.g., through denoising) or to estimate the relation between latent causes and measurements in medical data. In the latter case, LVMs in the form of noisy-OR Bayes nets represent the standard approach to relate binary latents (which represent diseases) to binary observables (which represent symptoms). Bayes nets with binary representation for symptoms may be perceived as a coarse approximation, however. In practice, real disease symptoms can range from absent over mild and intermediate to very severe. Therefore, using diseases/symptoms relations as motivation, we here ask how standard noisy-OR Bayes nets can be generalized to incorporate continuous observables, e.g., variables that model symptom severity in an interval from healthy to pathological. This transition from binary to interval data poses a number of challenges including a transition from a Bernoulli to a Beta distribution to model symptom statistics. While noisy-OR-like approaches are constrained to model how causes determine the observables’ mean values, the use of Beta distributions additionally provides (and also requires) that the causes determine the observables’ variances. To meet the challenges emerging when generalizing from Bernoulli to Beta distributed observables, we investigate a novel LVM that uses a maximum non-linearity to model how the latents determine means and variances of the observables. Given the model and the goal of likelihood maximization, we then leverage recent theoretical results to derive an Expectation Maximization (EM) algorithm for the suggested LVM. We further show how variational EM can be used to efficiently scale the approach to large networks. Experimental results finally illustrate the efficacy of the proposed model using both synthetic and real data sets. Importantly, we show that the model produces reliable results in estimating causes using proofs of concepts and first tests based on real medical data and on images.     

Deconstructing Covalent Organocatalysis

Modern organocatalysis has rapidly evolved into an essential component of contemporary organic synthesis. One of the most distinctive aspects of organocatalytic processes is the biomimetic nature in which the catalyst engages the substrate, often forming covalently bound intermediates in a manner reminiscent of enzyme catalysis. Indeed, the process of intramolecularization is often accompanied by a conformational change of the catalyst scaffold, further accentuating this analogy with biological systems. The isolation and study of these catalytic intermediates facilitate the rapid generation of conformation and reactivity profiles to assist in organocatalytic reaction development and/or clarify reaction outcomes. Emulating the formative advances that have derived from studying reaction intermediates in mechanistic organometallic and enzymatic catalysis, the deconstruction of covalently bound organocatalysis intermediates is gaining momentum as a design strategy.     

Molecular recognition at the active site of factor Xa: cation-π interactions, stacking on planar peptide surfaces, and replacement of structural water

Factor Xa, a serine protease from the blood coagulation cascade, is an ideal enzyme for molecular recognition studies, as its active site is highly shape-persistent and features distinct, concave sub-pockets. We developed a family of non-peptidic, small-molecule inhibitors with a central tricyclic core orienting a neutral heterocyclic substituent into the S1 pocket and a quaternary ammonium ion into the aromatic box in the S4 pocket. The substituents were systematically varied to investigate cation-π interactions in the S4 pocket, optimal heterocyclic stacking on the flat peptide walls lining the S1 pocket, and potential water replacements in both the S1 and the S4 pockets. Structure-activity relationships were established to reveal and quantify contributions to the binding free enthalpy, resulting from single-atom replacements or positional changes in the ligands. A series of high-affinity ligands with inhibitory constants down to K(i)=2 nM were obtained and their proposed binding geometries confirmed by X-ray co-crystal structures of protein-ligand complexes.     

Measuring the range of plasmonic interaction

When gold nanoparticles are covered with nanometric layers of transparent polyelectrolytes, the plasmon absorption spectrum A(λ) increases by a factor of approximately three and shifts to the red. These modifications of dissipative experimental observables stop when the cover layer thickness approaches the particle diameter. Spectral modifications of dispersive parameters like the reflection R, however, keep changing with increasing cover layer thickness. The shift of the plasmon resonance caused by two interacting particle layers is studied as a function of the separating distance between the two layers. We discuss these observations in the context of an effective medium theory and conclude that it can only be applied for a layer thickness on the order of the particle diameter.     

Stabilisation of water-soluble platinum nanoparticles by phosphonic acid derivatives

Sodium 2-(diphenylphosphino)ethyl phosphonate (1) was investigated as a stabilising agent for platinum nanoparticles (Pt-NPs) in aqueous solution. This phosphino phosphonate is known to stabilise rhodium nanoparticles (NPs) in water. Here we report that in the case of Pt-NPs this ligand is indirectly involved in the stabilisation mechanism and the actual stabilisation agent is the platinum complex Na(2)[Pt(1)(2)] (2). The reduction of platinum(II) salts in the presence of the phosphonates 1, 2, sodium 2-(diphenylphosphoryl)ethyl phosphonate (3) and 3,3,3-triphenylpropyl phosphonate (4) leads to stable platinum NPs with a remarkably narrow particle size distribution. These platinum NPs show high catalytic activity in the hydrogenation of 1-hexene and 1-chloro-3-nitrobenzene under biphasic as well as heterogeneous (supported on charcoal) conditions. The activity of the supported NPs was 30 times higher than the commercially available catalyst Pt(0) EnCat?. Furthermore, the single-crystal X-ray structures of (1)(MeOH)(2)(H(2)O)(2), (3)(H(2)O)(4), and (4)(2)(H(2)O)(17) have been determined.     

Importance of Intermolecular Hydrogen Bonding for the Stereochemical Control of Allene–Enone (3+2) Annulations Catalyzed by a Bifunctional,Amino Acid Derived Phosphine Catalyst

The origin of stereoselectivity in the (3+2) annulation of allenes and enones catalyzed by an amino acid derived phosphine catalyst has been investigated by the use of dispersion‐corrected density functional theory. An intermolecular hydrogen bond between the intermediate zwitterion and the enone was found to be the key interaction in the two enantiomeric transition states. Additional stabilization is provided by intermolecular hydrogen‐bonding interactions between acidic positions on the catalyst backbone and the substrate. Enantioselectivity occurs because the intermolecular hydrogen bond in the transition state leading to the minor enantiomer is only possible at the expense of reactant distortion.