The Optimal Permeation of Cyclic Boronates to Cross the Outer Membrane via the Porin Pathway

The Effect of Lipopolysaccharides on the Electrostatic Properties of Gram-Negative General Porins from Enterobacteriaceae

We investigated, by using all-atom molecular dynamics simulations, the effect of the outer membrane of Gram-negative bacteria, composed in the outer leaflet by polar/charged lipopolysaccharides (LPS), on the electrostatic properties of general porins from the Enterobacteriaceae family. General porins constitute the main path for the facilitated diffusion of polar antibiotics through the outer membrane. As model system we selected OmpK36 from Klebsiella pneumoniae, the ortholog of OmpC from Escherichia coli. This species presents high variability of amino acid composition of porins, with the effect to increase its resistance to the penetration of antibiotics. The various properties we analyzed seem to indicate that LPS acts as an independent layer without affecting the internal electrostatic properties of OmpK36. The only apparent effect on the microsecond time scale we sampled is the appearance of calcium ions, when present at moderate concentration in solution, inside the pore. However, we noticed increased fluctuations of the polarization density and only minor changes on its average value.

Machine Learning Prediction of Small Molecule Accumulation in Escherichia Coli Enhanced with Descriptor Statistics

Antibiotic resistance, particularly among Gram-negative bacteria, poses a significant healthcare challenge due to their ability to evade antibiotic action through various mechanisms. In this study, we explore the prediction of small molecule accumulation in Gram-negative bacteria by using machine learning techniques enhanced with statistical descriptors derived from molecular dynamics simulations. We begin by identifying a minimal set of molecular descriptors that maximize the model's predictive power while preserving human interpretability. We optimize model accuracy, precision, and the area under the receiver operating characteristic curve through an iterative process. We demonstrate that the inclusion of statistical descriptors significantly improves model performance across various prediction metrics. Particularly, the addition of statistical descriptors related to dipole moment and minimum projection radius enhances the model's predictive capabilities, shedding light on the physicochemical properties crucial for small molecule accumulation. Our findings highlight the importance of considering statistical moments beyond mean values in predictive modeling and suggest avenues for future research. Overall, our study provides insights into the complex dynamics of antibiotic accumulation in Escherichia coli bacterial cells, generalizable to other Gram-negative species, offering a promising approach for the discovery of effective antibacterial agents, identifying new hits, and improving them to define effective lead agents.

Enantiopure β-isocyano-boronic esters: synthesis and exploitation in isocyanide-based multicomponent reactions

Various boron-containing isocyanides have been efficiently synthesized from the corresponding enantiopure β-substituted β-amino boronic acid pinacol esters, without need for protecting group interconversion, through a two-step, purification-free procedure. They were employed in a variety of isocyanide-based multicomponent reactions, proving to be reliable components for all of them and allowing the efficient synthesis of unprecedented, boron-containing peptidomimetics and heteroatom-rich small molecules, including biologically relevant cyclic boronates. Jointing together the β-amido boronic acid moiety, deriving from the isocyanide component, with prominent pharmacophoric rings emerging from the multicomponent process, a successful application of the molecular hybridization concept could be realized.