Dynamic diversity of synthetic supramolecular polymers in water as revealed by hydrogen/deuterium exchange

Lou, Xianwen; Lafleur, René P. M.; Leenders, Christianus M. A.; Schoenmakers, Sandra M. C.; Matsumoto, Nicholas M.; Baker, Matthew B.; Dongen, Joost L. J. van; Palmans, Anja R. A.; Meijer, E. W.

doi:10.1038/ncomms15420

Cited by 64 publications

(81 citation statements)

References 38 publications

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“…[24] Remarkably,t he exchange dynamics of both monomers are slowed down upon copolymerization, ar esult that is seconded by molecular dynamics simulations. We apply hydrogen-deuterium exchange mass spectrometry (HDX-MS) to monitor the exchange dynamics of supramolecular polymers and copolymers,asithas recently been proved to be apowerful label-free method to elucidate dynamic processes in supramolecular polymers.…”

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confidence: 87%

Supramolecular Copolymerization as a Strategy to Control the Stability of Self‐Assembled Nanofibers

et al. 2018

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A major challenge in supramolecular polymerization is controlling the stability of the polymers formed, that is, controlling the rate of monomer exchange in the equilibrium between monomer and polymer. The exchange dynamics of supramolecular polymers based on benzene-1,3,5-tricarboxamide (BTA) can be regulated by copolymerizing molecules with dendronized (dBTA) and linear (nBTA) ethylene glycol-based water-soluble side chains. Whereas nBTAs form long nanofibers in water, dBTAs do not polymerize, forming instead small spherical aggregates. The copolymerization of the two BTAs results in long nanofibers. The exchange dynamics of both the BTA monomers in the copolymer are significantly slowed down in the mixed systems, leading to a more stable copolymer, while the morphology and spectroscopic signature of the copolymers are identical to that of nBTA homopolymer. This copolymerization is the supramolecular counterpart of styrene/ maleic anhydride copolymerization.

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confidence: 87%

Supramolecular Copolymerization as a Strategy to Control the Stability of Self‐Assembled Nanofibers

et al. 2018

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“…From the 1 HNMR spectrum of BTTPAi n[ D 6 ]DMSO with D 2 O ( Figure S7), the protonp eak of amide bonds cannotb ed etected because of the H-D exchange, suggesting water contacted with the amide bonds and may influence the packing. [23] Based on the optimized results (Scheme S2), at high water content, the BTTPAd imer was stabilized by water molecules through NÀH···O and OÀH···O hydrogen bonds, and an overlapped structure was obtained. However,a tl ow water content, there are too few water molecules available to form sufficient numberso fh ydrogen bonds to sustain such overlapped structure, leading to as lipped structure.…”

Section: Packing Modes In the Gel Statementioning

confidence: 99%

Fluorescence Regulation and Photoresponsivity in AIEE Supramolecular Gels Based on a Cyanostilbene Modified Benzene‐1,3,5‐Tricarboxamide Derivative

Ding

Shang

et al. 2018

Chemistry A European J

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Supramolecular interactions play an important role in regulating the optical properties of molecular materials. Different arrangements of identical molecules can afford a more straightforward insight into the contributions of supramolecular interactions. Herein, a novel gelator, BTTPA, composed of a benzene‐1,3,5‐tricarboxamide (BTA) central unit functionalized with three cyanostilbenes is designed, which forms two kinds of gels in DMSO/water mixtures. Depending on the water volume content, the gels exhibit quite different aggregation‐induced emission enhancement (AIEE) properties, with one emitting a green emission (G‐gel), and the second emitting a blue emission (B‐gel). The main reason for this difference is that water affects H‐bonding and π–π interactions, further resulting in disparate packing modes of gelators. In addition, only the G‐gel displays gel‐to‐sol transition accompanied with fluorescence switching according to the trans‐cis photoisomerization of cyanostilbene under UV light irradiation. The B‐gel does not exhibit any change because of its tight hexagonal packing arrangement. Such packing modes restricted the space in which molecules were located and inhibited the transformation of configuration of cyanostilbene. These phenomena underline the incomparable status of packing modes and molecular configuration in regulating fluorescence properties and photoresponse behavior in organic solid‐state luminescent materials.

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“…Such a structural and dynamic diversity within fiber (2) is consistent with recent experimental and computational observations that revealed that these water-soluble assemblies are way more dynamic and less ordered than expected. 21,32 On the other hand, fiber (1) appears as a nearly perfect stack of monomers (similar to the cartoons of ideal fibers often used in the literature).…”

Section: Automatic Comparison Of Defects In Different Supramolecular mentioning

confidence: 84%

A Complete Structural and Dynamic Characterization of Supramolecular Polymers via Automatic Learning of Defects

Gasparotto¹,

Bochicchio²,

Ceriotti³

et al. 2019

Preprint

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A central paradigm of self-assembly is to create ordered structures starting from molecular monomers that spontaneously recognize and interact with each other via noncovalent interactions. In the recent years, great efforts have been directed toward reaching the perfection in the design of a variety of supramolecular polymers and materials with different architectures. The resulting structures are often thought of as ideally perfect, defect-free supramolecular fibers, micelles, vesicles, etc., having an intrinsic dynamic character, which are typically studied at the level of statistical ensembles to assess their average properties. However, high-resolution molecular simulations recently demonstrated that local defects that may be present or may form in these assemblies, and which are poorly captured by conventional approaches, are key to controlling their dynamic behavior and properties. The study of these defects poses considerable challenges, as the flexible/dynamic nature of these soft systems makes it difficult to identify what effectively constitutes a defect, and to characterize its stability and evolution. Here, we demonstrate the power of unsupervised machine learning techniques to systematically identify and compare defects in supramolecular polymer variants in different conditions, using as a benchmark high-resolution molecular simulations of a family of supramolecular polymers. We shot that this approach allows a complete data-driven characterization of the internal structure and dynamics of these complex assemblies and of the dynamic pathways for defects formation and resorption. This provides a useful, generally applicable approach to unambiguously identify defects in these dynamic self-assembled materials and to classify them based on their structure, stability and dynamics.

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Dynamic diversity of synthetic supramolecular polymers in water as revealed by hydrogen/deuterium exchange

Cited by 64 publications

References 38 publications

Supramolecular Copolymerization as a Strategy to Control the Stability of Self‐Assembled Nanofibers

Supramolecular Copolymerization as a Strategy to Control the Stability of Self‐Assembled Nanofibers

Fluorescence Regulation and Photoresponsivity in AIEE Supramolecular Gels Based on a Cyanostilbene Modified Benzene‐1,3,5‐Tricarboxamide Derivative

A Complete Structural and Dynamic Characterization of Supramolecular Polymers via Automatic Learning of Defects

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