Rationalising Supramolecular Hydrogelation of Bis‐Urea‐Based Gelators through a Multiscale Approach

Abstract

The current approach to designing low‐molecular‐weight gelators relies on a laborious trial‐and‐error process, mainly because of the lack of an accurate description of the noncovalent interactions crucial for supramolecular gelation. In this work, we report a multiscale bottom‐up approach composed of several computational techniques to unravel the key interactions in a library of synthesized bis‐urea‐based gelators and rationalize their experimentally observed hydrogelation performance. In addition to density functional theory calculations and molecular dynamics, the noncovalent interaction index is applied as a tool to visualise and identify the different types of noncovalent interactions. Interestingly, as well as hydrogen bonds between urea moieties, hydrogen bonds between a urea moiety and a pyridine ring were shown to play a detrimental role in the early aggregation phase. These findings enabled us to explain the hydrogelation performance observed in a library of twelve bis‐urea derivatives, which were synthesized with 58–95 % yields. From this library, three compounds were discovered to effectively gel water, with the most efficient hydrogelator only requiring a concentration of 0.2 w/v%.

Molecular dynamics based descriptors for predicting supramolecular gelation

“…Some LMWGs were previously reported by other research groups (1, 2, 3, 4 and 5), while other compounds were recently synthesized by our group (6, 7, 8, 9, 10 and 11). 7,[17][18][19][20][21] The compounds were selected on the basis of two criteria. First, the molecule should contain at least one urea moiety.…”

“…In our previous work on the rationalization of supramolecular hydrogelation through a multiscale computational approach, we have showed that all-atom molecular dynamics simulations, emerge as a unique tool to provide insight into the aggregation phase during supramolecular gelation. 7 Similarly, in the pioneering work of Tuttle and Ulijn, 11 coarse grained molecular dynamics was applied to obtain their AP H score and predict the hydrogelation performance of tripeptides. Herein, molecular dynamics simulations are performed to obtain a set of descriptors, which we envisioned to have predictive ability value in supramolecular gelation.…”

“…25,26 This force eld was already shown to accurately describe urea based interactions, which are key during the supramolecular gelation of urea containing compounds. 7,27 Before production, an energy minimization and temperature/ pressure equilibration step was performed to ensure steric clashes or inadequate equilibration of the NPT-ensemble would not affect the production simulation. The V-rescale thermostat and Parrinello-Rahman barostat were used with the temperature set at 300 K and the pressure at 1.0 bar.…”

“…In our previous work, we showed how the end-to-end distance is a valuable descriptor to dene the shape of a single gelator molecule. 7 To assess the effect that the solvent environment, other gelator molecules and intramolecular interactions have on the shape of the gelator molecule, a relative end-to-end distance (rH) is dened, which is computed by measuring the average distance between the most distant atoms of the backbone over time in all gelator molecules present in the simulation ( R) and dividing this value with the maximum end-to-end distance, obtained by measuring the distance between the respective atoms of a corresponding fully extended molecule (R max ) ( Fig. 3C).…”

“…[4][5][6] In this context, multiscale computational methodologies have the potential to provide a better understanding of the underlying relationship between the molecular structure and the gelation ability. 7 However, besides post-rationalization, the ability to predict supramolecular gelation by means of computational methods has been scarcely explored.…”