From Cooperative Self-Assembly to Water-Soluble Supramolecular Polymers Using Coarse-Grained Simulations

Multiscale computational simulation of pollutant behavior at water interfaces

The investigation of pollutant behavior at water interfaces is critical to understand pollution in aquatic systems. Computational methods allow us to overcome the limitations of experimental analysis, delivering valuable insights into the chemical mechanisms and structural characteristics of pollutant behavior at interfaces across a range of scales, from microscopic to mesoscopic. Quantum mechanics, all-atom molecular dynamics simulations, coarse-grained molecular dynamics simulations, and dissipative particle dynamics simulations represent diverse molecular interaction calculation methods that can effectively model pollutant behavior at environmental interfaces from atomic to mesoscopic scales. These methods provide a rich variety of information on pollutant interactions with water surfaces. This review synthesizes the advancements in applying typical computational methods to the formation, adsorption, binding, and catalytic conversion of pollutants at water interfaces. By drawing on recent advancements, we critically examine the current challenges and offer our perspective on future directions. This review seeks to advance our understanding of computational techniques for elucidating pollutant behavior at water interfaces, a critical aspect of water research.

Self-assembly of cyclic peptide monolayers by hydrophobic supramolecular hinges

Supramolecular polymerisation of two-dimensional (2D) materials requires monomers with non-covalent binding motifs that can control the directionality of both dimensions of growth. A tug of war between these propagation forces can bias polymerisation in either direction, ultimately determining the structure and properties of the final 2D ensemble. Deconvolution of the assembly dynamics of 2D supramolecular systems has been widely overlooked, making monomer design largely empirical. It is thus key to define new design principles for suitable monomers that allow the control of the direction and the dynamics of two-dimensional self-assembled architectures. Here, we investigate the sequential assembly mechanism of new monolayer architectures of cyclic peptide nanotubes by computational simulations and synthesised peptide sequences with selected mutations. Rationally designed cyclic peptide scaffolds are shown to undergo hierarchical self-assembly and afford monolayers of supramolecular nanotubes. The particular geometry, the rigidity and the planar conformation of cyclic peptides of alternating chirality allow the orthogonal orientation of hydrophobic domains that define lateral supramolecular contacts, and ultimately direct the propagation of the monolayers of peptide nanotubes. A flexible 'tryptophan hinge' at the hydrophobic interface was found to allow lateral dynamic interactions between cyclic peptides and thus maintain the stability of the tubular monolayer structure. These results unfold the potential of cyclic peptide scaffolds for the rational design of supramolecular polymerisation processes and hierarchical self-assembly across the different dimensions of space.

Stimuli-responsive viscosity modifiers

Stimuli responsive viscosity modifiers entail an important class of materials which allow for smart material formation utilizing various stimuli for switching such as pH, temperature, light and salinity. They have seen applications in the biomedical space including tissue engineering and drug delivery, wherein stimuli responsive hydrogels and polymeric vessels have been extensively applied. Applications have also been seen in other domains like the energy sector and automobile industry, in technologies such as enhanced oil recovery. The chemistry and microstructural arrangements of the aqueous morphologies of dissolved materials are usually sensitive to the aforementioned stimuli which subsequently results in rheological sensitivity as well. Herein, we overview different structures capable of viscosity modification as well as go over the rheological theory associated with classical systems studied in literature. A detailed analysis allows us to explore correlations between commonly discussed models such as molecular packing parameter, tube reptation and stress relaxation with structural and rheological changes. We then present five primary mechanisms corresponding to stimuli responsive viscosity modification: (i) packing parameter modification via functional group conditioning and (ii) via dynamic bond formation, (iii) mesh formation by interlinking of network nodes, (iv) viscosity modification by chain conformation changes and (v) viscosity modification by particle jamming. We also overview several recent examples from literature that employ the concepts discussed to create novel classes of intriguing stimuli responsive structures and their corresponding rheological properties. Furthermore, we also explore systems that are responsive to multiple stimuli which can provide enhanced functionality and versatility by providing multi-level and precise actuation. Such systems have been used for programmed site-specific drug delivery.

Salt-Induced Coil-Globule Transition of Sulfonate-Modified HPAM is Affected by the Branched Chain Length

Polymer flooding is a cheap and efficient method for tertiary oil recovery. However, the failure of partially hydrolyzed polyacrylamide (HPAM) molecules reduces the oil displacement efficiency under high salinity conditions. In this study, we modified HPAM molecules by sulfonic acid groups with different branched chain lengths, and we characterized the structures of these molecules in different salinity solutions through all-atoms molecular dynamics simulation. Compared with the acrylic group, the sulfonate group has excellent salt resistance because of its weak ability to attract cations. When using different lengths of branched linked branch sulfonates, increasing the length of the branched chain can improve the movement ability of sulfonates, so as to play a better salt resistance effect. However, excessive growth of branched chains can cause their association with each other and can lead to polymer folding. Therefore, we believe that the branched chain length of sulfonate should be moderately increased. These results are expected to provide theoretical support for the design and use of salt-resistant polymers..

Watching Molecular Nanotubes Self-Assemble in Real Time

Molecular self-assembly is a fundamental process in nature that can be used to develop novel functional materials for medical and engineering applications. However, their complex mechanisms make the short-lived stages of self-assembly processes extremely hard to reveal. In this article, we track the self-assembly process of a benchmark system, double-walled molecular nanotubes, whose structure is similar to that found in biological and synthetic systems. We selectively dissolved the outer wall of the double-walled system and used the inner wall as a template for the self-reassembly of the outer wall. The reassembly kinetics were followed in real time using a combination of microfluidics, spectroscopy, cryogenic transmission electron microscopy, molecular dynamics simulations, and exciton modeling. We found that the outer wall self-assembles through a transient disordered patchwork structure: first, several patches of different orientations are formed, and only on a longer time scale will the patches interact with each other and assume their final preferred global orientation. The understanding of patch formation and patch reorientation marks a crucial step toward steering self-assembly processes and subsequent material engineering.

Detecting dynamic domains and local fluctuations in complex molecular systems via timelapse neighbors shuffling

It is known that the behavior of many complex systems is controlled by local dynamic rearrangements or fluctuations occurring within them. Complex molecular systems, composed of many molecules interacting with each other in a Brownian storm, make no exception. Despite the rise of machine learning and of sophisticated structural descriptors, detecting local fluctuations and collective transitions in complex dynamic ensembles remains often difficult. Here, we show a machine learning framework based on a descriptor which we name Local Environments and Neighbors Shuffling (LENS), that allows identifying dynamic domains and detecting local fluctuations in a variety of systems in an abstract and efficient way. By tracking how much the microscopic surrounding of each molecular unit changes over time in terms of neighbor individuals, LENS allows characterizing the global (macroscopic) dynamics of molecular systems in phase transition, phases-coexistence, as well as intrinsically characterized by local fluctuations (e.g., defects). Statistical analysis of the LENS time series data extracted from molecular dynamics trajectories of, for example, liquid-like, solid-like, or dynamically diverse complex molecular systems allows tracking in an efficient way the presence of different dynamic domains and of local fluctuations emerging within them. The approach is found robust, versatile, and applicable independently of the features of the system and simply provided that a trajectory containing information on the relative motion of the interacting units is available. We envisage that "such a LENS" will constitute a precious basis for exploring the dynamic complexity of a variety of systems and, given its abstract definition, not necessarily of molecular ones.

Investigating the Hydrogen Bond-Induced Self-Assembly of Polysulfamides Using Molecular Simulations and Experiments

In this paper, we present a synergistic, experimental, and computational study of the self-assembly of N,N'-disubstituted polysulfamides driven by hydrogen bonds (H-bonds) between the H-bonding donor and acceptor groups present in repeating sulfamides as a function of the structural design of the polysulfamide backbone. We developed a coarse-grained (CG) polysulfamide model that captures the directionality of H-bonds between the sulfamide groups and used this model in molecular dynamics (MD) simulations to study the self-assembly of these polymers in implicit solvent. The CGMD approach was validated by reproducing experimentally observed trends in the extent of crystallinity for three polysulfamides synthesized with aliphatic and/or aromatic repeating units. After validation of our CGMD approach, we computationally predicted the effect of repeat unit bulkiness, length, and uniformity of segment lengths in the polymers on the extent of orientational and positional order among the self-assembled polysulfamide chains, providing key design principles for tuning the extent of crystallinity in polysulfamides in experiments. Those computational predictions were then experimentally tested through the synthesis and characterization of polysulfamide architectures.

Caught in Action: Visualizing Dynamic Nanostructures Within Supramolecular Systems Chemistry

Supramolecular systems chemistry has been an area of active research to develop nanomaterials with life-like functions. Progress in systems chemistry relies on our ability to probe the nanostructure formation in solution. Often visualizing the dynamics of nanostructures which transform over time is a formidable challenge. This necessitates a paradigm shift from dry sample imaging towards solution-based techniques. We review the application of state-of-the-art techniques for real-time, in situ visualization of dynamic self-assembly processes. We present how solution-based techniques namely optical super-resolution microscopy, solution-state atomic force microscopy, liquid-phase transmission electron microscopy, molecular dynamics simulations and other emerging techniques are revolutionizing our understanding of active and adaptive nanomaterials with life-like functions. This Review provides the visualization toolbox and futuristic vision to tap the potential of dynamic nanomaterials.

Supramolecular Semiconductivity through Emerging Ionic Gates in Ion-Nanoparticle Superlattices

The self-assembly of nanoparticles driven by small molecules or ions may produce colloidal superlattices with features and properties reminiscent of those of metals or semiconductors. However, to what extent the properties of such supramolecular crystals actually resemble those of atomic materials often remains unclear. Here, we present coarse-grained molecular simulations explicitly demonstrating how a behavior evocative of that of semiconductors may emerge in a colloidal superlattice. As a case study, we focus on gold nanoparticles bearing positively charged groups that self-assemble into FCC crystals via mediation by citrate counterions. In silico ohmic experiments show how the dynamically diverse behavior of the ions in different superlattice domains allows the opening of conductive ionic gates above certain levels of applied electric fields. The observed binary conductive/nonconductive behavior is reminiscent of that of conventional semiconductors, while, at a supramolecular level, crossing the "band gap" requires a sufficient electrostatic stimulus to break the intermolecular interactions and make ions diffuse throughout the superlattice's cavities.

Understanding of supramolecular solution polymerization and interfacial polymerization via forming multiple hydrogen bonds: a computer simulation study

By employing dissipative particle dynamics (DPD) simulations combined with stochastic polymerization models, we have conducted a detailed simulation study of supramolecular solution polymerization as well as interfacial polymerization employing a coarse-grained model which is closer to the real monomer structure. By adding bending angle potentials to coarse-grained models representing supramolecular reactive monomers, we achieved monomer model simulations for different kinds of multiple hydrogen bonds. Our simulation results indicated that for the interfacial polymerization system, the volume of the monomer caused a strong steric hindrance effect, which in turn led to a low average degree of polymerization of the product. Therefore, by appropriately reducing the volume of the reaction monomer (corresponding to different confinement ascribed to the multiple hydrogen bonds), the average polymerization degree, the degree of reaction and the polymerization rate of the monomer can be effectively improved. For the solution polymerization system and the interfacial polymerization system, a certain proportion of rigid monomers and flexible monomers (60% rigid monomers and 40% flexible monomers) are mixed. High molecular weight products can thus be obtained via the polymerization reaction. The simulation strategy proposed in this study can not only provide theoretical guidance for better design of new supramolecular systems, but also provide ideas for the further synthesis of higher molecular weight supramolecular polymers.

Modelling structural properties of cyanine dye nanotubes at coarse-grained level

Self-assembly is a ubiquitous process spanning from biomolecular aggregates to nanomaterials. Even though the resulting aggregates can be studied through experimental techniques, the dynamic pathways of the process and the molecular details of the final structures are not necessarily easy to resolve. Consequently, rational design of self-assembling aggregates and their properties remains extremely challenging. At the same time, modelling the self-assembly with computational methods is not trivial, because its spatio-temporal scales are usually beyond the limits of all-atom based simulations. The use of coarse-grained (CG) models can alleviate this limitation, but usually suffers from the lack of optimised parameters for the molecular constituents. In this work, we describe the procedure of parametrizing a CG Martini model for a cyanine dye (C8S3) that self-assembles into hollow double-walled nanotubes. First, we optimised the model based on quantum mechanics calculations and all-atom reference simulations, in combination with available experimental data. Then, we conducted random self-assembly simulations, and the performance of our model was tested on preformed assemblies. Our simulations provide information on the time-dependent local arrangement of this cyanine dye, when aggregates are being formed. Furthermore, we provide guidelines for designing and optimising parameters for similar self-assembling nanomaterials.

Classifying soft self-assembled materials via unsupervised machine learning of defects

Unlike molecular crystals, soft self-assembled fibers, micelles, vesicles, etc., exhibit a certain order in the arrangement of their constitutive monomers but also high structural dynamicity and variability. Defects and disordered local domains that continuously form-and-repair in their structures impart to such materials unique adaptive and dynamical properties, which make them, e.g., capable to communicate with each other. However, objective criteria to compare such complex dynamical features and to classify soft supramolecular materials are non-trivial to attain. Here we show a data-driven workflow allowing us to achieve this goal. Building on unsupervised clustering of Smooth Overlap of Atomic Position (SOAP) data obtained from equilibrium molecular dynamics simulations, we can compare a variety of soft supramolecular assemblies via a robust SOAP metric. This provides us with a data-driven "defectometer" to classify different types of supramolecular materials based on the structural dynamics of the ordered/disordered local molecular environments that statistically emerge within them.

Molecular communications in complex systems of dynamic supramolecular polymers

Supramolecular polymers are composed of monomers that self-assemble non-covalently, generating distributions of monodimensional fibres in continuous communication with each other and with the surrounding solution. Fibres, exchanging molecular species, and external environment constitute a sole complex system, which intrinsic dynamics is hard to elucidate. Here we report coarse-grained molecular simulations that allow studying supramolecular polymers at the thermodynamic equilibrium, explicitly showing the complex nature of these systems, which are composed of exquisitely dynamic molecular entities. Detailed studies of molecular exchange provide insights into key factors controlling how assemblies communicate with each other, defining the equilibrium dynamics of the system. Using minimalistic and finer chemically relevant molecular models, we observe that a rich concerted complexity is intrinsic in such self-assembling systems. This offers a new dynamic and probabilistic (rather than structural) picture of supramolecular polymer systems, where the travelling molecular species continuously shape the assemblies that statistically emerge at the equilibrium.

The dynamic structure of supramolecular polymers is challenging to determine both in experiments and in simulations. Here the authors use coarse-grained molecular models to provide a comprehensive analysis of the molecular communication in these complex molecular systems.

How the Choice of Force-Field Affects the Stability and Self-Assembly Process of Supramolecular CTA Fibers

In recent years, computational methods have become an essential element of studies focusing on the self-assembly process. Although they provide unique insights, they face challenges, from which two are the most often mentioned in the literature: the temporal and spatial scale of the self-assembly. A less often mentioned issue, but not less important, is the choice of the force-field. The repetitive nature of the supramolecular structure results in many similar interactions. Consequently, even a small deviation in these interactions can lead to significant energy differences in the whole structure. However, studies comparing different force-fields for self-assembling systems are scarce. In this article, we compare molecular dynamics simulations for trifold hydrogen-bonded fibers performed with different force-fields, namely GROMOS, CHARMM General Force Field (CGenFF), CHARMM Drude, General Amber Force-Field (GAFF), Martini, and polarized Martini. Briefly, we tested the force-fields by simulating: (i) spontaneous self-assembly (none form a fiber within 500 ns), (ii) stability of the fiber (observed for CHARMM Drude, GAFF, MartiniP), (iii) dimerization (observed for GROMOS, GAFF, and MartiniP), and (iv) oligomerization (observed for CHARMM Drude and MartiniP). This system shows that knowledge of the force-field behavior regarding interactions in oligomer and larger self-assembled structures is crucial for designing efficient simulation protocols for self-assembling systems.

Controlling the length of porphyrin supramolecular polymers via coupled equilibria and dilution-induced supramolecular polymerization

Multi-component systems often display convoluted behavior, pathway complexity and coupled equilibria. In recent years, several ways to control complex systems by manipulating the subtle balances of interaction energies between the individual components have been explored and thereby shifting the equilibrium between different aggregate states. Here we show the enantioselective chain-capping and dilution-induced supramolecular polymerization with a Zn²⁺-porphyrin-based supramolecular system when going from long, highly cooperative supramolecular polymers to short, disordered aggregates by adding a monotopic Mn³⁺-porphyrin monomer. When mixing the zinc and manganese centered monomers, the Mn³⁺-porphyrins act as chain-cappers for Zn²⁺-porphyrin supramolecular polymers, effectively hindering growth of the copolymer and reducing the length. Upon dilution, the interaction between chain-capper and monomers weakens as the equilibria shift and long supramolecular polymers form again. This dynamic modulation of aggregate morphology and length is achieved through enantioselectivity in the aggregation pathways and concentration-sensitive equilibria. All-atom and coarse-grained molecular simulations provide further insights into the mixing of the species and their exchange dynamics. Our combined experimental and theoretical approach allows for precise control of molecular self-assembly and chiral discrimination in complex systems.

Cyclic Photoisomerization of Azobenzene in Atomistic Simulations: Modeling the Effect of Light on Columnar Aggregates of Azo Stars

This computational study investigates the influence of light on supramolecular aggregates of three-arm azobenzene stars. Every star contains three azobenzene (azo) moieties, each able to undergo reversible photoisomerization. In solution, the azo stars build column-shaped supramolecular aggregates. Previous experimental works report severe morphological changes of these aggregates under UV-Vis light. However, the underlying molecular mechanisms are still debated. Here we aim to elucidate how light affects the structure and stability of the columnar stacks on the molecular scale. The system is investigated using fully atomistic molecular dynamics (MD) simulations. To implement the effects of light, we first developed a stochastic model of the cyclic photoisomerization of azobenzene. This model reproduces the collective photoisomerization kinetics of the azo stars in good agreement with theory and previous experiments. We then apply light of various intensities and wavelengths on an equilibrated columnar stack of azo stars in water. The simulations indicate that the aggregate does not break into separate fragments upon light irradiation. Instead, the stack develops defects in the form of molecular shifts and reorientations and, as a result, it eventually loses its columnar shape. The mechanism and driving forces behind this order-disorder structural transition are clarified based on the simulations. In the end, we provide a new interpretation of the experimentally observed morphological changes.

Columnar Aggregates of Azobenzene Stars: Exploring Intermolecular Interactions, Structure, and Stability in Atomistic Simulations

We present a simulation study of supramolecular aggregates formed by three-arm azobenzene (Azo) stars with a benzene-1,3,5-tricarboxamide (BTA) core in water. Previous experimental works by other research groups demonstrate that such Azo stars assemble into needle-like structures with light-responsive properties. Disregarding the response to light, we intend to characterize the equilibrium state of this system on the molecular scale. In particular, we aim to develop a thorough understanding of the binding mechanism between the molecules and analyze the structural properties of columnar stacks of Azo stars. Our study employs fully atomistic molecular dynamics (MD) simulations to model pre-assembled aggregates with various sizes and arrangements in water. In our detailed approach, we decompose the binding energies of the aggregates into the contributions due to the different types of non-covalent interactions and the contributions of the functional groups in the Azo stars. Initially, we investigate the origin and strength of the non-covalent interactions within a stacked dimer. Based on these findings, three arrangements of longer columnar stacks are prepared and equilibrated. We confirm that the binding energies of the stacks are mainly composed of π-π interactions between the conjugated parts of the molecules and hydrogen bonds formed between the stacked BTA cores. Our study quantifies the strength of these interactions and shows that the π-π interactions, especially between the Azo moieties, dominate the binding energies. We clarify that hydrogen bonds, which are predominant in BTA stacks, have only secondary energetic contributions in stacks of Azo stars but remain necessary stabilizers. Both types of interactions, π-π stacking and H-bonds, are required to maintain the columnar arrangement of the aggregates.

Toward Chemotactic Supramolecular Nanoparticles: From Autonomous Surface Motion Following Specific Chemical Gradients to Multivalency-Controlled Disassembly

Nature designs chemotactic supramolecular structures that can selectively bind specific groups present on surfaces, autonomously scan them moving along density gradients, and react once a critical concentration is encountered. Since such properties are key in many biological functions, these also offer inspirations for designing artificial systems capable of similar bioinspired autonomous behaviors. One approach is to use soft molecular units that self-assemble in an aqueous solution generating nanoparticles (NPs) that display specific chemical groups on their surface, enabling multivalent interactions with complementarily functionalized surfaces. However, a first challenge is to explore the behavior of these assemblies at sufficiently high-resolution to gain insights on the molecular factors controlling their behaviors. Here, by coupling coarse-grained molecular models and advanced simulation approaches, we show that it is possible to study the (autonomous or driven) motion of self-assembled NPs on a receptor-grafted surface at submolecular resolution. As an example, we focus on self-assembled NPs composed of facially amphiphilic oligomers. We observe how tuning the multivalent interactions between the NP and the surface allows to control of the NP binding, its diffusion along chemical surface gradients, and ultimately, the NP reactivity at determined surface group densities. In silico experiments provide physical-chemical insights on key molecular features in the self-assembling units which determine the dynamic behavior and fate of the NPs on the surface: from adhesion, to diffusion, and disassembly. This offers a privileged point of view into the chemotactic properties of supramolecular assemblies, improving our knowledge on how to design new types of materials with bioinspired autonomous behaviors.

Controlling Exchange Pathways in Dynamic Supramolecular Polymers by Controlling Defects

Supramolecular fibers composed of monomers that self-assemble directionally via noncovalent interactions are ubiquitous in nature, and of great interest in chemistry. In these structures, the constitutive monomers continuously exchange in-and-out the assembly according to a well-defined supramolecular equilibrium. However, unraveling the exchange pathways and their molecular determinants constitutes a nontrivial challenge. Here, we combine coarse-grained modeling, enhanced sampling, and machine learning to investigate the key factors controlling the monomer exchange pathways in synthetic supramolecular polymers having an intrinsic dynamic behavior. We demonstrate how the competition of directional vs. nondirectional interactions between the monomers controls the creation/annihilation of defects in the supramolecular polymers, from where monomers exchange proceeds. This competition determines the exchange pathway, dictating whether a fiber statistically swaps monomers from the tips or from all along its length. Finally, thanks to their generality, our models allow the investigation of molecular approaches to control the exchange pathways in these dynamic assemblies.

The Martini Model in Materials Science

The Martini model, a coarse-grained force field initially developed with biomolecular simulations in mind, has found an increasing number of applications in the field of soft materials science. The model's underlying building block principle does not pose restrictions on its application beyond biomolecular systems. Here, the main applications to date of the Martini model in materials science are highlighted, and a perspective for the future developments in this field is given, particularly in light of recent developments such as the new version of the model, Martini 3.

Surface science of cosmetic substrates, cleansing actives and formulations

The development of shampoo and cleansing formulations in cosmetics is at a crossroads due to consumer demands for better performing, more natural products and also the strong commitment of cosmetic companies to improve the sustainability of cosmetic products. In order to go beyond traditional formulations, it is of great importance to clearly establish the science behind cleansing technologies and appreciate the specificity of cleansing biological surfaces such as hair and skin. In this review, we present recent advances in our knowledge of the physicochemical properties of the hair surface from both an experimental and a theoretical point of view. We discuss the opportunities and challenges that newer, sustainable formulations bring compared to petroleum-based ingredients. The inevitable evolution towards more bio-based, eco-friendly ingredients and sustainable formulations requires a complete rethink of many well-known physicochemical principles. The pivotal role of digital sciences and modelling in the understanding and conception of new ingredients and formulations is discussed. We describe recent numerical approaches that take into account the specificities of the hair surface in terms of structuration, different methods that study the adsorption of formulation ingredients and finally the success of new data-driven approaches. We conclude with practical examples on current formulation efforts incorporating bio-surfactants, controlling foaming and searching for new rheological properties.

Discordant Supramolecular Fibres Reversibly Depolymerised by Temperature and Light

Synthetic stimuli responsive supramolecular polymers attract increasing interest for their ability to mimic the unique properties of natural assemblies. Here we focus on the well-studied benzene-1,3,5-tricarboxamide (BTA) motif, and substitute it with two (S)-3,7-dimethyloctyl groups and an azobenzene photoswitch. We demonstrate the UV (λ=365 nm) induced depolymerisation of the helical hydrogen-bonded polymers in methylcyclohexane (MCH) through circular dichroism and UV-vis spectroscopy in dilute solution (15 μm), and NMR and iPAINT super-resolution microscopy in concentrated solution (300 μm). The superstructure can be regenerated after thermal depolymerization, whilst repeated depolymerisation can be reversed without degradation by irradiating at λ=455 nm. Molecular dynamics simulations show that the most energetically favourable configuration for these polymers in MCH is a left-handed helical network of hydrogen-bonds between the BTA cores surrounded by two right-handed helices of azobenzenes. The responsiveness to two orthogonal triggers across a broad concentration range holds promise for use in, for example, photo-responsive gelation.

Swarm-CG: Automatic Parametrization of Bonded Terms in MARTINI-Based Coarse-Grained Models of Simple to Complex Molecules via Fuzzy Self-Tuning Particle Swarm Optimization

We present Swarm-CG, a versatile software for the automatic iterative parametrization of bonded parameters in coarse-grained (CG) models, ideal in combination with popular CG force fields such as MARTINI. By coupling fuzzy self-tuning particle swarm optimization to Boltzmann inversion, Swarm-CG performs accurate bottom-up parametrization of bonded terms in CG models composed of up to 200 pseudo atoms within 4-24 h on standard desktop machines, using default settings. The software benefits from a user-friendly interface and two different usage modes (default and advanced). We particularly expect Swarm-CG to support and facilitate the development of new CG models for the study of complex molecular systems interesting for bio- and nanotechnology. Excellent performances are demonstrated using a benchmark of 9 molecules of diverse nature, structural complexity, and size. Swarm-CG is available with all its dependencies via the Python Package Index (PIP package: swarm-cg). Demonstration data are available at: www.github.com/GMPavanLab/SwarmCG.

Temperature dependent aggregation mechanism and pathway of lysozyme: By all atom and coarse grained molecular dynamics simulation

Aggregation of protein causes various diseases including Alzheimer's disease, Parkinson's disease, and type II diabetes. It was found that aggregation of protein depends on many factors like temperature, pH, salt type, salt concentration, ionic strength, protein concentration, co solutes. Here we have tried to capture the aggregation mechanism and pathway of hen egg white lysozyme using molecular dynamics simulations at two different temperatures; 300 K and 340 K. Along with the all atom simulations to get the atomistic details of aggregation mechanism, we have used coarse grained simulation with MARTINI force field to monitor the aggregation for longer duration. Our results suggest that due to the aggregation, changes in the conformation of lysozyme are more at 340 K than at 300 K. The change in the conformation of the lysozyme at 300 K is mainly due to aggregation where at 340 K change in conformation of lysozyme is due to both aggregation and temperature. Also, a more compact aggregated system is formed at 340 K.

On the Structure and Chiral Aggregation of Liquid Crystalline Star-Shaped Triazines H-Bonded to Benzoic Acids

The ability of a star-shaped tris(triazolyl)triazine derivative to hierarchically build supramolecular chiral columnar organizations through the formation of H-bonded complexes with benzoic acids was studied from a theoretical and experimental point of view. The combined study has been done at three different levels including the study of the structure of the triazine core, the association with benzoic acids in stoichiometry 1:3, and the assembly of 1:3 complexes in helical aggregates. Although the star-shaped triazine core crystallizes in a non-C₃ conformation, the C₃ -symmetric conformation is theoretically predicted to be more stable and gives rise to a favorable C₃ supramolecular 1:3 complex upon the interaction with three benzoic acids in their voids. In addition, calculations at different levels (DFT, PM7, and MM3) for the 1:3 host-guest complex predict the formation of large stable columnar helical aggregates stabilized by the compact packing of the interstitial acids by π-π and CH⋅⋅⋅π interactions. The acids restrict the movement of the the star-shaped triazine cores along the stacking axis causing a template effect in the self-assembly of the complex. Theoretical predictions correlate with experimental results, since the interaction with achiral or chiral 3,4,5-(4-alkoxybenzyloxy)benzoic acids gives rise to supramolecular complexes that organize in bulk hexagonal columnar mesophases stable at room temperature with intracolumnar order. The existence of supramolecular chirality in the mesophase was determined for complexes formed by acids derived from (S)-2-octanol. Chiral aggregation was also evidenced for complexes formed in dodecane.

Solvent-driven chirality for luminescent self-assembled structures: experiments and theory

We describe, for a single platinum complex bearing a dipeptide moiety, a solvent-driven interconversion from twisted to straight micrometric assembled structures with different chirality. The photophysical and morphological properties of the aggregates have been investigated as well as the role of the media and concentration. A real-time visualization of the solvent-driven interconversion processes has been achieved by confocal microscopy. Finally, atomistic and coarse-grained simulations, providing results consistent with the experimental observations, allow to obtain a molecular-level insight into the interesting solvent-responsive behavior of this system.

Exploring the Potential of Benzene-1,3,5-tricarboxamide Supramolecular Polymers as Biomaterials

The fast dynamics occurring in natural processes increases the difficulty of creating biomaterials capable of mimicking Nature. Within synthetic biomaterials, water-soluble supramolecular polymers show great potential in mimicking the dynamic behavior of these natural processes. In particular, benzene-1,3,5-tricaboxamide (BTA)-based supramolecular polymers have shown to be highly dynamic through the exchange of monomers within and between fibers, but their suitability as biomaterials has not been yet explored. Herein we systematically study the interactions of BTA supramolecular polymers bearing either tetraethylene glycol or mannose units at the periphery with different biological entities. When BTA fibers were incubated with bovine serum albumin (BSA), the protein conformation was only affected by the fibers containing tetraethylene glycol at the periphery (BTA-OEG₄). Coarse-grained molecular simulations showed that BSA interacted with BTA-OEG₄ fibers rather than with BTA-OEG₄ monomers that are present in solution or that may exchange out of the fibers. Microscopy studies revealed that, in the presence of BSA, BTA-OEG₄ retained their fiber conformation although their length was slightly shortened. When further incubated with fetal bovine serum (FBS), both long and short fibers were visualized in solution. Nevertheless, in the hydrogel state, the rheological properties were remarkably preserved. Further studies on the cellular compatibility of all the BTA assemblies and mixtures thereof were performed in four different cell lines. A low cytotoxic effect at most concentrations was observed, confirming the suitability of utilizing functional BTA supramolecular polymers as dynamic biomaterials.

Cooperative Supramolecular Block Copolymerization for the Synthesis of Functional Axial Organic Heterostructures

Supramolecular block copolymerzation with optically or electronically complementary monomers provides an attractive bottom-up approach for the non-covalent synthesis of nascent axial organic heterostructures, which promises to deliver useful applications in energy conversion, optoelectronics, and catalysis. However, the synthesis of supramolecular block copolymers (BCPs) constitutes a significant challenge due to the exchange dynamics of non-covalently bound monomers and hence requires fine microstructure control. Furthermore, temporal stability of the segmented microstructure is a prerequisite to explore the applications of functional supramolecular BCPs. Herein, we report the cooperative supramolecular block copolymerization of fluorescent monomers in solution under thermodynamic control for the synthesis of axial organic heterostructures with light-harvesting properties. The fluorescent nature of the core-substituted naphthalene diimide (cNDI) monomers enables a detailed spectroscopic probing during the supramolecular block copolymerization process to unravel a nucleation-growth mechanism, similar to that of chain copolymerization for covalent block copolymers. Structured illumination microscopy (SIM) imaging of BCP chains characterizes the segmented microstructure and also allows size distribution analysis to reveal the narrow polydispersity (polydispersity index (PDI) ≈ 1.1) for the individual block segments. Spectrally resolved fluorescence microscopy on single block copolymerized organic heterostructures shows energy migration and light-harvesting across the interfaces of linearly connected segments. Molecular dynamics and metadynamics simulations provide useful mechanistic insights into the free energy of interaction between the monomers as well as into monomer exchange mechanisms and dynamics, which have a crucial impact on determining the copolymer microstructure. Our comprehensive spectroscopic, microscopic, and computational analyses provide an unambiguous structural, dynamic, and functional characterization of the supramolecular BCPs. The strategy presented here is expected to pave the way for the synthesis of multi-component organic heterostructures for various functions.

Divergent Self-Assembly Pathways to Hierarchically Organized Networks of Isopeptide-Modified Discotics under Kinetic Control

Natural proteins traverse complex free energy landscapes to assemble into hierarchically organized structures, often through stimuli-directed kinetic pathways in response to relevant biological cues. Bioinspired strategies have sought to emulate the complexity, dynamicity, and modularity exhibited in these natural processes with synthetic analogues. However, these efforts are limited by many factors that complicate the rational design and predictable assembly of synthetic constructs, especially in aqueous environments. Herein, a model discotic amphiphile gelator is described that undergoes pathway-dependent structural maturation when exposed to varying application rates of a pH stimulus, investigated by electron microscopy, spectroscopy, and X-ray scattering techniques. Under the direction of a slowly changing pH stimulus, complex hierarchical assemblies result, characterized by mesoscale elongated "superstructure" bundles embedded in a percolated mesh of narrow nanofibers. In contrast, the assembly under a rapidly applied pH stimulus is characterized by homogeneous structures that are reminiscent of the superstructures arising from the more deliberate path, except with significantly reduced scale and concomitantly large increases in bulk rheological properties. This synthetic system bears resemblance to the pathway complexity and hierarchical ordering observed for native structures, such as collagen, and points to fundamental design principles that might be applied toward enhanced control of the properties of supramolecular self-assembly across length scales.

Supramolecular polymer bottlebrushes

The field of supramolecular chemistry has long been known to generate complex materials of different sizes and shapes via the self-assembly of single or multiple low molar mass building blocks. Matching the complexity found in natural assemblies, however, remains a long-term challenge considering its precision in organizing large macromolecules into well-defined nanostructures. Nevertheless, the increasing understanding of supramolecular chemistry has paved the way to several attempts in arranging synthetic macromolecules into larger ordered structures based on non-covalent forces. This review is a first attempt to summarize the developments in this field, which focus mainly on the formation of one-dimensional, linear, cylindrical aggregates in solution with pendant polymer chains - therefore coined supramolecular polymer bottlebrushes in accordance with their covalent equivalents. Distinguishing by the different supramolecular driving forces, we first describe systems based on π-π interactions, which comprise, among others, the well-known perylene motif, but also the early attempts using cyclophanes. However, the majority of reported supramolecular polymer bottlebrushes are formed by hydrogen bonds as they can for example be found in linear and cyclic peptides, as well as so called sticker molecules containing multiple urea groups. Besides this overview on the reported motifs and their impact on the resulting morphology of the polymer nanostructures, we finally highlight the potential benefits of such non-covalent interactions and refer to promising future directions of this still mostly unrecognized field of supramolecular research.

Identifying and Tracking Defects in Dynamic Supramolecular Polymers

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 recent years, great efforts have been directed toward perfecting 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, 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 5 Å resolution coarse-grained molecular simulations of a family of supramolecular polymers. We show 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.

Pitfalls of the Martini Model

The computational and conceptual simplifications realized by coarse-grain (CG) models make them a ubiquitous tool in the current computational modeling landscape. Building block based CG models, such as the Martini model, possess the key advantage of allowing for a broad range of applications without the need to reparametrize the force field each time. However, there are certain inherent limitations to this approach, which we investigate in detail in this work. We first study the consequences of the absence of specific cross Lennard-Jones parameters between different particle sizes. We show that this lack may lead to artificially high free energy barriers in dimerization profiles. We then look at the effect of deviating too far from the standard bonded parameters, both in terms of solute partitioning behavior and solvent properties. Moreover, we show that too weak bonded force constants entail the risk of artificially inducing clustering, which has to be taken into account when designing elastic network models for proteins. These results have implications for the current use of the Martini CG model and provide clear directions for the reparametrization of the Martini model. Moreover, our findings are generally relevant for the parametrization of any other building block based force field.

The influence of substituents on gelation and stacking order of oligoaramid - based supramolecular networks

Self-assembly has proven to be a powerful tool for functional, smart materials such as hydrogels derived from low molecular weight compounds. However, the targeted design of functional gelators remains difficult. Here, we present a set of four Y-shaped aromatic amide tetramers with varying functionalities able to undergo different non-covalent interactions. These compounds were explored towards their self-assembly behavior and hydrogel formation by experimental methods such as UV-vis spectroscopy, rheology, small angle X-ray scattering (SAXS), scanning/transmission electron, and atomic force microscopy. Additionally, we investigated the main mechanisms behind oligomer aggregation and the structure of the resulting supramolecular chains through full atomistic molecular dynamics simulations.

How Defects Control the Out-of-Equilibrium Dissipative Evolution of a Supramolecular Tubule

Supramolecular architectures that work out-of-equilibrium or that can change in specific ways when absorbing external energy are ubiquitous in nature. Gaining the ability to create via self-assembly artificial materials possessing such fascinating behaviors would have a major impact in many fields. However, the rational design of similar dynamic structures requires to understand and, even more challenging, to learn how to master the molecular mechanisms governing how the assembled systems evolve far from the equilibrium. Typically, this represents a daunting challenge due to the limited molecular insight that can be obtained by the experiments or by classical modeling approaches. Here we combine coarse-grained molecular models and advanced simulation approaches to study at submolecular (<5 Å) resolution a supramolecular tubule, which breaks and disassembles upon absorption of light energy triggering isomerization of its azobenzene-containing monomers. Our approach allows us to investigate the molecular mechanism of monomer transition in the assembly and to elucidate the kinetic process for the accumulation of the transitions in the system. Despite the stochastic nature of the excitation process, we demonstrate how these tubules preferentially dissipate the absorbed energy locally via the amplification of defects in their supramolecular structure. We find that this constitutes the best kinetic pathway for accumulating monomer transitions in the system, which determines the dynamic evolution out-of-equilibrium and the brittle behavior of the assembly under perturbed conditions. Thanks to the flexibility of our models, we finally come out with a general principle, where defects explain and control the brittle/soft behavior of such light-responsive assemblies.

Insights into the Kinetics of Supramolecular Comonomer Incorporation in Water

Multicomponent supramolecular polymers are a versatile platform to prepare functional architectures, but a few studies have been devoted to investigate their noncovalent synthesis. Here, we study supramolecular copolymerizations by examining the mechanism and time scales associated with the incorporation of new monomers in benzene-1,3,5-tricarboxamide (BTA)-based supramolecular polymers. The BTA molecules in this study all contain three tetra(ethylene glycol) chains at the periphery for water solubility but differ in their alkyl chains that feature either 10, 12 or 13 methylene units. C₁₀BTA does not form ordered supramolecular assemblies, whereas C₁₂BTA and C₁₃BTA both form high aspect ratio supramolecular polymers. First, we illustrate that C₁₀BTA can mix into the supramolecular polymers based on either C₁₂BTA or C₁₃BTA by comparing the temperature response of the equilibrated mixtures to the temperature response of the individual components in water. Subsequently, we mix C₁₀BTA with the polymers and follow the copolymerization over time with UV spectroscopy and hydrogen/deuterium exchange mass spectrometry experiments. Interestingly, the time scales obtained in both experiments reveal significant differences in the rates of copolymerization. Coarse-grained simulations are used to study the incorporation pathway and kinetics of the C₁₀BTA monomers into the different polymers. The results demonstrate that the kinetic stability of the host supramolecular polymer controls the rate at which new monomers can enter the existing supramolecular polymers.

Composite Nanotube Ring Structures Formed by Two-Step Self-Assembly for Drug Loading/Release

Nanotube rings are barely reported novel structures formed by the self-assembly of soft matter, as compared with nanotube structures and ring structures. The two-step self-assembly of amphiphilic copolymer AB and solvophobic copolymer CDC was studied. We found that nanotube rings can be formed from a certain mass ratio of copolymer CDC to copolymer AB and block D of certain rigidity. More interestingly, we discovered a new strategy for drug loading and release, which is different from the usual strategies reported in the literature. The present study provides a new rationale for the self-assembly of copolymers.

Sequence-Regulated Supracolloidal Copolymers via Copolymerization-Like Coassembly of Binary Mixtures of Patchy Nanoparticles

Synthetic copolymers of molecular systems serve as an inspiration for creation of one-dimensional copolymer-like superstructures via coassembly of anisometric nanoparticles. In contrast to the covalent and molecular copolymers, the details of formation mechanisms of copolymer-like superstructures, as well as the factors determining their length and the sequences of arranged nanoparticles, are still poorly understood. Herein, we propose a joint theoretical-computational framework to probe into the coassembly mechanism and kinetics of binary mixtures of patchy nanoparticles. By applying the coarse-grained molecular dynamics simulations, it is demonstrated that the coassembly of patchy nanoparticles markedly resembles many aspects of molecular step-growth copolymerization, and the sequences of nanoparticles inside the copolymer-like superstructures can be finely regulated by the relative activity and the initial ingredient of patchy nanoparticles as well as the coassembly strategy. A quantitatively copolymerization-like model is developed to account for the coassembly kinetics of patchy nanoparticles and the sequence distribution of arranged nanoparticles, all governed by the elaborate design of lower-level building units. The jointly theoretical and simulated studies offer mechanistic insights into the copolymerization-like kinetics and the sequence prediction for the coassembly of binary mixtures of patchy nanoparticles, paving the way toward the rational design of copolymer-like superstructures with various sequences and functionalities.

DNA-inspired oligomers: from oligophosphates to functional materials

Replacement of the natural nucleotides in DNA by non-nucleosidic building blocks leads to phosphodiester-linked oligomers with a high functional diversity.

Differentiating the mechanism of self-assembly in supramolecular polymers through computation

The mechanism by which monomers in solution, beyond a certain concentration or below a certain temperature, self-assemble to form one dimensional supramolecular polymers determines much of the bulk properties of the polymer.

Consequences of a cosolvent on the structure and molecular dynamics of supramolecular polymers in water

Polar cosolvents are commonly used to guide the self-assembly of amphiphiles in water. Here we investigate the influence of the cosolvent acetonitrile (ACN) on the structure and dynamics of a supramolecular polymer in water, which is based on the well-known benzene-1,3,5-tricarboxamide motif. Hydrogen/deuterium exchange mass spectroscopy measurements show that a gradual increase in the amount of ACN results in a gradual increase in the exchange dynamics of the monomers. In contrast, the morphology of the supramolecular polymers remains unchanged up to 15% of ACN, but then an abrupt change occurs and spherical aggregates are formed. Remarkably, this abrupt change coincides with the formation of micro-heterogeneity in the water-ACN mixtures. The results illustrate that in order to completely characterize supramolecular polymers it is important to add time-resolved measurements that probe their dynamic behavior, to the conventional techniques that are used to assess the morphology of the polymers. Subsequently we have used time-resolved measurements to investigate the influence of the concentration of ACN on the polymerization and depolymerization rates of the supramolecular polymers. Polymerization occurs within minutes when molecularly dissolved monomers are injected from ACN into water and is independent of the fraction of ACN up to 15%. In the depolymerization experiments-initiated by mixing equilibrated supramolecular polymers with dissolved monomers-the equilibration of the system takes multiple hours and does depend on the fraction of ACN. Interestingly, the longest equilibration time of the polymers is observed at a critical solvent composition of around 15% ACN. The differences in the timescales detected in the polymerization and depolymerization experiments are likely correlated to the non-covalent interactions involved, namely the hydrophobic effect and hydrogen-bonding interactions. We attribute the observed fast kinetics in the polymerization reactions to the hydrophobic effect, whereas the formation of intermolecular hydrogen bonds is the retarding factor in the equilibration of the polymers in the depolymerization experiments. Molecular dynamics simulations show that the latter is a likely explanation because ACN interferes with the hydrogen bonds and loosens the internal structure of the polymers. Our results highlight the importance of the solution conditions during the non-covalent synthesis of supramolecular polymers, as well as after equilibration of the polymers.