Experimental Charge Density Analysis of the Anti-inflammatory Drug Meloxicam [sodium 4-hydroxy-2-methyl-N-(5-methyl-1,3-thiazol-2-yl)-1,1-dioxo-1$l^{6},2-benzothiazine-3-carboxamide Monohydrate]

The charge density analysis of meloxicam sodium monohydrate [sodium 4-hydroxy-2-methyl-N-(5-methyl-1,3-thiazol-2-yl)-1,1-dioxo-1$l^{6},2-benzothiazine-3-carboxamide monohydrate] was performed with high-resolution X-ray diffraction data measured at low temperature (90 K). The experimental results were compared with those derived from the corresponding periodic theoretical calculations at the B3LYP/6-31G** level of theory. The multipolar charge-density analysis highlights the regions of meloxicam which are the most electronegative. These regions correspond to those forming short electrostatic interactions with the Na+ cation. The molecular conformation in the crystal is maintained by a strong intramolecular N−H…O=C hydrogen bond. The Na+ cation interacts with as much as five neighboring oxygen atoms. The strong hydrogen bonds N/O−H…O/N, the Na…O short contacts and hydrophobic aromatic stacking between the two aromatic cycles constitute the most represented and enriched contact types and act as the driving force in the crystal packing formation. The crystal packing presents several meloxicam anion dimers but also one Na+…Na+ repulsive interactions which are largely compensated by the electrostatic favorable attractions between anions and cations. This work is licensed under a Creative Commons Attribution 4.0 International License

Structure property relationships in halogenated aromatic amides and imides

The effect of halogens (X) and pyridine N atom substitution patterns on molecular structure and conformation is analyzed and discussed herein. Several series of 3 x 3 isomer grids (Scheme 1; Figs 1-3) of halo-N-(pyridyl)benzamides (Xxx) (C12H9N2OX, x = para-/meta-/ortho-) and their corresponding imides (Fig. 4) have been evaluated and correlated in terms of their structural relationships

Synthesis, structural elucidation, spectroscopic and Hirshfeld surface analysis of a new organic cyclohexaphosphate, (C12H19N2)4(Li)2(P6O18)(H2O)4

International audienc

Network Models of TEM β-Lactamase Mutations Coevolving under Antibiotic Selection Show Modular Structure and Anticipate Evolutionary Trajectories

Understanding how novel functions evolve (genetic adaptation) is a critical goal of evolutionary biology. Among asexual organisms, genetic adaptation involves multiple mutations that frequently interact in a non-linear fashion (epistasis). Non-linear interactions pose a formidable challenge for the computational prediction of mutation effects. Here we use the recent evolution of β-lactamase under antibiotic selection as a model for genetic adaptation. We build a network of coevolving residues (possible functional interactions), in which nodes are mutant residue positions and links represent two positions found mutated together in the same sequence. Most often these pairs occur in the setting of more complex mutants. Focusing on extended-spectrum resistant sequences, we use network-theoretical tools to identify triple mutant trajectories of likely special significance for adaptation. We extrapolate evolutionary paths (n = 3) that increase resistance and that are longer than the units used to build the network (n = 2). These paths consist of a limited number of residue positions and are enriched for known triple mutant combinations that increase cefotaxime resistance. We find that the pairs of residues used to build the network frequently decrease resistance compared to their corresponding singlets. This is a surprising result, given that their coevolution suggests a selective advantage. Thus, β-lactamase adaptation is highly epistatic. Our method can identify triplets that increase resistance despite the underlying rugged fitness landscape and has the unique ability to make predictions by placing each mutant residue position in its functional context. Our approach requires only sequence information, sufficient genetic diversity, and discrete selective pressures. Thus, it can be used to analyze recent evolutionary events, where coevolution analysis methods that use phylogeny or statistical coupling are not possible. Improving our ability to assess evolutionary trajectories will help predict the evolution of clinically relevant genes and aid in protein design

An in vivo platform for identifying inhibitors of protein aggregation

Protein aggregation underlies an array of human diseases, yet only one small molecule therapeutic has been successfully developed to date. Here, we introduce an in vivo system, based on a β-lactamase tripartite fusion construct, capable of identifying aggregation-prone sequences in the periplasm of Escherichia coli and inhibitors that prevent their aberrant self-assembly. We demonstrate the power of the system using a range of proteins, from small unstructured peptides (islet amyloid polypeptide and amyloid β) to larger, folded immunoglobulin domains. Configured in a 48-well format, the split β-lactamase sensor readily differentiates between aggregation-prone and soluble sequences. Performing the assay in the presence of 109 compounds enabled a rank ordering of inhibition and revealed a new inhibitor of IAPP aggregation. This platform can be applied to both amyloidogenic and other aggregation-prone systems, independent of sequence or size, and can identify small molecules or other factors able to ameliorate or inhibit protein aggregation