Statistical inference and quantum mechanical measurement

We analyze the quantum mechanical measuring process from the standpoint of information theory. Statistical inference is used in order to define the most likely state of the measured system that is compatible with the readings of the measuring instrument and the a priori information about the correlations between the system and the instrument. This approach has the advantage that no reference to the time evolution of the combined system need be made. It must, however, be emphasized that the result is to be interpreted as the statistically inferred state of the original system rather than the state of the system after measurement. The phenomenon of “reduction of states” appears in this light as a consequence of incomplete information rather than the physical interaction between measured system and measuring instrument.     

Electrospray ionization mass spectrometric detection of self-assembly of a crown ether complex directed by π-stacking interactions

The self-assembly of ligand-metal-ligand sandwich complexes involving a novel quinoxaline-containing crown ether, 1, was studied by electrospray ionization mass spectrometry (ESI-MS). Donor-acceptor π-stacking interactions between the electron-poor quinoxaline group of 1 and electron-rich benzene groups from benzo- or dibenzo-18-crown-6 were found to significantly enhance the formation of mixed-ligand sandwich complexes with a free energy gain of up to 17 kJ/mol relative to sandwich formation involving macrocycles without such aromatic functionalities. The relative intensities of the sandwich complexes were greatest with the alkali metals Na⁺, K⁺, and Rb⁺ as well as with the ammonium ion in equimolar concentrations with the macrocycles. The preferential formation of the mixed-ligand sandwich complexes demonstrated that donor-acceptor π-stacking interactions contribute to the assembly of molecular structures and can be monitored by ESI-MS.     

Studying variations in the PCDD/PCDF profile across various food products using multivariate statistical analysis

Polychlorinated dibenzo-p-dioxins (PCDD) and polychlorinated dibenzofurans (PCDF) are widely recognized by the scientific community as persistent organic pollutants due to their toxicity and adverse effects on wildlife and human health. The actual regulation dedicated to the monitoring of dioxins in food is based on the measurement of 17 congener concentrations. The final result is reported as a toxic equivalent value that takes into account the relative toxicity of each congener. This procedure can minimize the qualitative information available from the abundances of each PCDD/PCDF congener: the characteristic contamination profile of the sample. Multivariate statistical techniques, such as principal component analysis (PCA) or linear discriminant analysis (LDA), represent an interesting way to investigate this qualitative information. Nevertheless, they have only been applied to the analysis of contamination data from food products and biological matrices infrequently. The objective of the present study was to analyze a large data set from dioxin analyses performed on various food products of animal origin. The results demonstrate the existence of differences in congener-specific patterns between the analyzed samples. Variability was first demonstrated in terms of the food type (fish, meat, milk, fatty products). Then a variability was observed that was related to the specific animal species for meat and milk samples (bovine, ovine, porcine, caprine and poultry). Some practical applications of these results are discussed. The origin(s) of the observed differences, as well as their significance, now remain to be investigated, both in terms of environmental factors and transfer through living organisms. A better knowledge of the relation between a contamination profile and its specific source and/or food product should be of great interest to scientists working in the fields of contaminant analysis, toxicology and metabolism, as well as to regulatory bodies and risk assessors in charge of final decisions regarding the eventual hazards associated with theses substances.     

Sharp transition for single polarons in the one-dimensional Su-Schrieffer-Heeger model

We study a single polaron in the Su-Schrieffer-Heeger (SSH) model using four different techniques (three numerical and one analytical). Polarons show a smooth crossover from weak to strong coupling, as a function of the electron-phonon coupling strength λ, in all models where this coupling depends only on phonon momentum q. In the SSH model the coupling also depends on the electron momentum k; we find it has a sharp transition, at a critical coupling strength λ(c), between states with zero and nonzero momentum of the ground state. All other properties of the polaron are also singular at λ=λ(c). This result is representative of all polarons with coupling depending on k and q, and will have important experimental consequences (e.g., in angle-resolved photoemission spectroscopy and conductivity experiments).     

Thermodynamic vs. kinetic control in the Diels-Alder cycloaddition of cyclopentadiene to 2,3-dicyano-p-benzoquinone

Diels-Alder cycloaddition of cyclopentadiene (1a) to 2,3-dicyano-p-benzoquinone (2a), when performed in methanol solvent at ambient temperature, proceeds with kinetic control to afford 1,4,4a,8a-tetrahydro-5,8-dioxo-1,4-methanonaphthalene-4a,8a-dicarbonitrile (7, 77% yield). However, when this cycloaddition is performed by refluxing an equimolar solution of1a and2a in benzene for 3 h, the product of thermodynamic control, i.e., 1,4,4a,8a-tetrahydro-5,8-dioxo-1,4-methanonaphthalene-6,7-dicarbonitrile (3a) is obtained in 64% yield. The structure of3a was confirmed by an analysis of the reduced intramolecular photocyclization product,9.     

Nucleophilic additions of primary and secondary amines to pentacyclo[5.4.0.02,6.03,10.05,9]undecane-8,11-dione

The crystal structures of three compounds formedvia nucleophilic attack of a heterocyclic secondary amine on PCU-8,11-dione, with the concomitant intramolecular attack of one keto oxygen on the carbon of the other ketone, are presented. In all three compounds, the bridging oxygen contains substantial p-character, and the bonds to the attacking nitrogen are significantly shorter than would be expected.     

The structure of 11,12-bis[spiro(cyclopropyl)]-1,4,4a,5,8,8a,9a,10a-octahydro-1,4∶5,8-dimethano-9,10-anthraquinone

In the solid state the 21 Diels-Alder adduct between spiro[4.2]hepta-1,3-diene and p-benzoquinone has a planar cyclohexadione ring with a center of symmetry. Both planar and boat conformations have been observed in similar systems, and the relative stability of the two conformers is of interest. The adduct in the gas phase should contain a mirror plane perpendicular to the cyclohexadione ring; however, a data set collected on a crystal in a capillary resulted in a structure where some bond lengths related by this mirror plane differed by more than 4 in the solid state. Molecular mechanics, MOPAC, and the Cambridge Structural Data Base were used to investigate the factors influencing the conformation of the cyclohexadione ring and the asymmetry across the noncrystallographic mirror plane. The energy differences between the planar and nonplanar ring system is small, and the conformation is determined by crystal packing. No reason for the bond length asymmetry could be found, and a recollection of data on a crystal exposed to the environment led to a structure with statistically equivalent bond lengths.     

Predicting the affinity of Farnesoid X Receptor ligands through a hierarchical ranking protocol: a D3R Grand Challenge 2 case study

The Drug Design Data Resource (D3R) Grand Challenges are blind contests organized to assess the state-of-the-art methods accuracy in predicting binding modes and relative binding free energies of experimentally validated ligands for a given target. The second stage of the D3R Grand Challenge 2 (GC2) was focused on ranking 102 compounds according to their predicted affinity for Farnesoid X Receptor. In this task, our workflow was ranked 5th out of the 77 submissions in the structure-based category. Our strategy consisted in (1) a combination of molecular docking using AutoDock 4.2 and manual edition of available structures for binding poses generation using SeeSAR, (2) the use of HYDE scoring for pose selection, and (3) a hierarchical ranking using HYDE and MM/GBSA. In this report, we detail our pose generation and ligands ranking protocols and provide guidelines to be used in a prospective computer aided drug design program.