Search

Uptake of acetaldehyde on ice surfaces has been investigated over the temperature range 203−253 K using a coated wall flow tube coupled to a mass spectrometric detection. The experiments were conducted on pure ice surfaces and on liquid/solid ice mixture both doped with nitric acid (0.063, 0.63, and 6.3 wt %). Uptake of acetaldehyde on these surfaces was always found to be totally reversible whatever the experimental conditions were. The number of acetaldehyde molecules adsorbed per surface unit was conventionally plotted as a function of acetaldehyde concentration in the gas phase. Although the amounts of acetaldehyde adsorbed on solid ice surfaces (pure and HNO3-doped ice) were approximately similar and rather limited, the number of acetaldehyde molecules taken up on the HNO3-doped solid ice/liquid mixtures are significantly higher, up to 1 or 2 orders of magnitudes compared to pure ice surfaces. At 213 K for example and for low concentrations of acetaldehyde (<1 × 1013molecule cm−3), the amount of acetaldehyde molecules taken up on solid/liquid doped surfaces is 3.3 and 8.8 times higher than those measured on pure ice respectively for 0.063 and 0.63 wt % of HNO3. The huge quantities of acetaldehyde taken up by liquid-/solid-doped mixtures are likely dissolved in the nonhomogeneous liquid part of the surfaces according to the Henry’s law equilibrium. As a consequence, up to about 10% of acetaldehyde may be scavenged by supercooled liquid droplets of convective clouds in the upper troposphere. [ABSTRACT FROM AUTHOR]

The RNA virus influenza A is a serious public health problem, with epidemics resulting in more than 250 000 deaths every year. A protein cavity was identified on the HA2 subunit of the hemagglutinin responsible for the entry of the virus into the host cell by endocytosis. The binding of a ligand in this zone rich in invariant residues and synthetic lethal couples could prevent therapeutic escape and inhibit the conformational change at pH = 5 which is necessary to initiate the membrane fusion in the endosome. Two pentapeptides, a linear peptide (EQRRS) and a cyclic peptide (DQRRD), have been proposed as potential ligands. Complex stability and the interactions between the ligand and the protein have been studied with the help of molecular dynamics and quantum chemistry methods. A high stability of the interactions has been obtained for these two ligands at both pH = 7 and pH = 5. Indeed, these two peptides present two cooperative modes of action that should prevent the conformational change at the origin of the spring-loaded mechanism at pH = 5, (1) mechanical because they are docked on HA2 and (2) electronic because they modify the protonation states of key residues in the loop. This study thus paves the way toward the development of peptide ligands that can inhibit the membrane fusion process.

Predicting protein druggability is a key interest in the target identification phase of drug discovery. Here, we assess the pocket estimation methods' influence on druggability predictions by comparing statistical models constructed from pockets estimated using different pocket estimation methods: a proximity of either 4 or 5.5 Å to a cocrystallized ligand or DoGSite and fpocket estimation methods. We developed PockDrug, a robust pocket druggability model that copes with uncertainties in pocket boundaries. It is based on a linear discriminant analysis from a pool of 52 descriptors combined with a selection of the most stable and efficient models using different pocket estimation methods. PockDrug retains the best combinations of three pocket properties which impact druggability: geometry, hydrophobicity, and aromaticity. It results in an average accuracy of 87.9% ± 4.7% using a test set and exhibits higher accuracy (∼5-10%) than previous studies that used an identical apo set. In conclusion, this study confirms the influence of pocket estimation on pocket druggability prediction and proposes PockDrug as a new model that overcomes pocket estimation variability.

Adsorption study of benzaldehyde on ice surfaces is performed by combining experimental and theoretical approaches. The experiments are conducted over the temperature range 233-253 K using a coated wall flow tube coupled to a mass spectrometric detector. Besides the experimental way, the adsorption isotherm is also determined by performing a set of grand canonical Monte Carlo simulations at 233 K. The experimental and calculated adsorption isotherms show a very good agreement within the corresponding errors. Besides, both experimental and theoretical studies permit us to derive the enthalpy of adsorption of benzaldehyde on ice surfaces DeltaH(ads), which are in excellent agreement: DeltaH(ads) = -61.4 +/- 9.7 kJ/mol (experimental) and DeltaH(ads) = -59.4 +/- 5.1 kJ/mol (simulation). The obtained results indicate a much stronger ability of benzaldehyde of being adsorbed at the surface of ice than that of small aliphatic aldehydes, such as formaldehyde or acetaldehyde. At low surface coverages the adsorbed molecules exclusively lie parallel with the ice surface. With increasing surface coverage, however, the increasing competition of the adsorbed molecules for the surface area to be occupied leads to the appearance of two different perpendicular orientations relative to the surface. In the first orientation, the benzaldehyde molecule turns its aldehyde group toward the ice phase, and, similarly to the molecules in the lying orientation, forms a hydrogen bond with a surface water molecule. In the other perpendicular orientation the aldehyde group turns to the vapor phase, and its O atom interacts with the delocalized pi system of the benzene ring of a nearby lying benzaldehyde molecule of the second molecular layer. In accordance with this observed scenario, the saturated adsorption layer, being stable in a roughly 1 kJ/mol broad range of chemical potentials, contains, besides the first molecular layer, also traces of the second molecular layer of adsorbed benzaldehyde.

An algorithm is presented, which exhibits a computed number of rigid conformers of an input small molecule, covering the geometric diversity in the conformational space, with minimal structural redundancy. The algorithm calls a conformer generator, then performs an agglomerative hierarchical clustering with the modified clustering gain as the stop criterion. The number of classes is computed without an arbitrary parameter. A representative conformer is selected in each class, and nonrepresentative conformers are discarded. For illustration, the algorithm has been applied on a database containing 70 ligands of the cytochrome CYP 3A4, showing that the structural flexibility of each ligand is indeed handled via a small number of its representative conformers. The method is valid for all small molecules.

We introduce the principles and the architecture of a user-friendly software named MOLDIA (Molecular Diversity Analysis) which aims to the comparison of diverse molecular data sets through an XML structured database of predefined fragments. The MOLDIA descriptors are composed of complex fingerprint-like structures, which enclose not only structural information but also physicochemical property data. The system architecture includes the use of customizable weights on molecular descriptors and different choices of similarity/diversity measures to analyze the given data sets. Intermolecular comparisons using Ullmann's algorithm were optimized by the use of fuzzy logic, generic atoms, and a whole system of chemical graph analysis. We have found that customizing the similarity/diversity computation using structural and/or properties weights and choosing the level of fuzziness of the molecular comparison allow the user to adapt the tool to particular needs and increases the possibilities of MolDiA applications. The implementation of XML Web technologies has proven to improve and ease the extraction, processing, and analysis of chemical information.

A general mathematical proof of a formula proposed and used by Fan et al. for calculating the number of the smallest rings in their smallest set of the smallest rings search algorithm is reported. This proof generalizes this formula to all connected cyclic graphs.