Structural Analysis of an Octameric Resorcinarene Self-Assembly in Toluene and its Morphological Transition by Temperature

The effect of water in THF/water mixtures on CMC, aggregation sizes, and fluorescence quenching of a new calix[4]resorcinarene macrocycle

This study explores how water content modulates the self-assembly and fluorescence behavior of a novel calixarene, C1. C1 forms large, flattened structures in pure THF, but water addition triggers a transition to smaller, unimodal clusters. A critical micellar concentration (CMC) is identified, decreasing with increasing water content. Fluorescence quenching is observed upon water addition, attributed to nonradiative deactivation. These findings highlight water as a key regulator of C1's assembly and fluorescence, paving the way for further development of water-responsive calixarene systems.

Characterization of mRNA Lipid Nanoparticles by Electron Density Mapping Reconstruction: X-ray Scattering with Density from Solution Scattering (DENSS) Algorithm

PURPOSE

This study aimed to test the feasibility of using Small Angle X-ray Scattering (SAXS) coupled with Density from Solution Scattering (DENSS) algorithm to characterize the internal architecture of messenger RNA-containing lipid nanoparticles (mRNA-LNPs).

METHODS

The DENSS algorithm was employed to construct a three-dimensional model of average individual mRNA-LNP. The reconstructed models were cross validated with cryogenic transmission electron microscopy (cryo-TEM), and dynamic light scattering (DLS) to assess size, morphology, and internal structure.

RESULTS

Cryo-TEM and DLS complemented SAXS, revealed a core-shell mRNA-LNP structure with electron-rich mRNA-rich region at the core, surrounded by lipids. The reconstructed model, utilizing the DENSS algorithm, effectively distinguishes mRNA and lipids via electron density mapping. Notably, DENSS accurately models the morphology of the mRNA-LNPs as an ellipsoidal shape with a "bleb" architecture or a two-compartment structure with contrasting electron densities, corresponding to mRNA-filled and empty lipid compartments, respectively. Finally, subtle changes in the LNP structure after three freeze-thaw cycles were detected by SAXS, demonstrating an increase in radius of gyration (Rg) associated with mRNA leakage.

CONCLUSION

Analyzing SAXS profiles based on DENSS algorithm to yield a reconstructed electron density based three-dimensional model can be a useful physicochemical characterization method in the toolbox to study mRNA-LNPs and facilitate their development.

Solvent and Substituent Size Influence on the Cyclochiral Rigidity of Aminomethylene Derivatives of Resorcin[4]arene

Resorcin[4]arenes (R[4]A) are a group of macrocyclic compounds whose peculiar feature is the presence of eight hydroxyl groups in their structure. The directional formation of intramolecular hydrogen bonds with their participation leads to the formation of a cyclochiral racemic mixture of these compounds. Their stability strongly depends on the substituent and especially the environment in which they are located. The paper discusses the cyclochiral nature of aminomethylene derivatives of R[4]A (AMD-R[4]A). Their cyclochiral rigidity in non-polar solvents has been shown. The influence of the size of the alkyl groups in the amino substituents of AMD-R[4]A on their cyclochiral nature was noted. To calculate the reaction paths for their racemization, the nudged elastic band (NEB) method was employed using the semi-empirical DFT (GFN1-xTB) approach. The calculated activation barrier energies for their racemization in chloroform, obtained through various semi-empirical quantum chemical methods (SE), Hartree-Fock (HF), and density functionals theory (DFT), show good correlation with experimental observations. Among the tested methods, the B38LYP-D4 method is highly recommended due to its fast computational speed and accuracy, which is comparable to the time-consuming double-hybrid DH-revDSD-PBEP86 approach.

Diffusion NMR Reveals the Structures of the Molecular Aggregates of Resorcin[4]arenes and Pyrogallol[4]arenes in Aromatic and Chlorinated Solvents

The hexameric assemblies of resorcinarenes and pyrogallolarenes are fascinating structures that can serve as nanoreactors in which new chemistry and catalysis occur. Recently, it was suggested based on SANS or SAXS that C₁₁-resorcin[4]arene (1) forms octameric aggregates of a micellar rather than capsular structure in toluene. Here, using NMR spectroscopy, diffusion NMR, and DOSY performed on solutions of C₁₁-resorcin[4]arene (1), C₁₁-pyrogallol[4]arene (2), and mixtures thereof in protonated and deuterated solvents, we found that, in benzene and toluene, 1 primarily formed hexameric capsules accompanied by a minor product with diffusion characteristics consistent with an octameric assembly. In chloroform, 1 formed hexameric capsules. In toluene, 2D NMR revealed two populations of encapsulated toluene molecules in the same capsule of 1. The addition of tetrahexylammonium bromide to the assemblies of 1 in aromatic solvents drove the equilibrium toward the formation of the hexameric capsules. Interestingly, 2 formed only hexameric capsules in all solvents tested.

Reconstruction of 3D density from solution scattering

Ab initio modeling methods have proven to be powerful means of interpreting solution scattering data. In the absence of atomic models, or complementary to them, ab initio modeling approaches can be used for generating low-resolution particle envelopes using only solution scattering profiles. Recently, a new ab initio reconstruction algorithm has been introduced to the scientific community, called DENSS. DENSS is unique among ab initio modeling algorithms in that it solves the inverse scattering problem, i.e., the 1D scattering intensities are directly used to determine the 3D particle density. The reconstruction of particle density has several advantages over conventional uniform density modeling approaches, including the ability to reconstruct a much wider range of particle types and the ability to visualize low-resolution density fluctuations inside the particle envelope. In this chapter we will discuss the theory behind this new approach, how to use DENSS, and how to interpret the results. Several examples with experimental and simulated data will be provided.