Dumbbells, chains, and ribbons: anisotropic self-assembly of isotropic nanoparticles.

Functionalizing the surface of metal nanoparticles can assure their stability in solution or mediate their self-assembly into aggregates with controlled shapes. Here we present a computational study of the colloidal aggregation of gold nanoparticles (Au NPs) isotropically functionalized by a mixture of charged and hydrophobic ligands. We show that, by varying the relative proportion of the two ligands, the NPs form anisotropic aggregates with markedly different topologies: dumbbells, chains, or ribbons. In all cases, two kinds of connections keep the aggregates together: hydrophobic bonds and ion bridges. We show that the anisotropy of the aggregates derives from the NP shell reshaping due to the formation of the hydrophobic links, while ion bridges are accountable for the "secondary structure" of the aggregates. Our findings provide a general physical principle that can also be exploited in different self-assembled systems: anisotropic/directional aggregation can be achieved starting from isotropic objects with a soft, deformable surface.

Nanoparticle-induced biomembrane fusion: unraveling the effect of core size on stalk formation.

Membrane fusion in vitro is a strategy to load model or cell-derived vesicles with proteins, drugs, and genetic materials for theranostic applications. It is thus crucial to develop strategies to control the fusion process, also through synthetic fusogenic agents. Ligand-protected, membrane-penetrating gold nanoparticles (Au NPs) can facilitate membrane fusion, but the molecular mechanisms remain unresolved. Here, we tackle NP-induced stalk formation using a coarse-grained molecular dynamics approach and enhanced sampling techniques. We show that smaller (2 nm in diameter) NPs lead to a lower free energy barrier and higher stalk stability than larger NPs (4 nm). We demonstrate that this difference is due to a different ligand conformational freedom, which in turn depends on the Au core curvature. Our study provides precious insights into the mechanisms underlying NP-mediated membrane fusion, while our computational approach is general and applicable to studying stalk formation caused by other fusogenic agents.

Cholesterol-Containing Liposomes Decorated With Au Nanoparticles as Minimal Tunable Fusion Machinery.

Membrane fusion is essential for the basal functionality of eukaryotic cells. In physiological conditions, fusion events are regulated by a wide range of specialized proteins, operating with finely tuned local lipid composition and ionic environment. Fusogenic proteins, assisted by membrane cholesterol and calcium ions, provide the mechanical energy necessary to achieve vesicle fusion in neuromediator release. Similar cooperative effects must be explored when considering synthetic approaches for controlled membrane fusion. We show that liposomes decorated with amphiphilic Au nanoparticles (AuLips) can act as minimal tunable fusion machinery. AuLips fusion is triggered by divalent ions, while the number of fusion events dramatically changes with, and can be finely tuned by, the liposome cholesterol content. We combine quartz-crystal-microbalance with dissipation monitoring (QCM-D), fluorescence assays, and small-angle X-ray scattering (SAXS) with molecular dynamics (MD) at coarse-grained (CG) resolution, revealing new mechanistic details on the fusogenic activity of amphiphilic Au nanoparticles (AuNPs) and demonstrating the ability of these synthetic nanomaterials to induce fusion regardless of the divalent ion used (Ca2+ or Mg2+ ). The results provide a novel contribution to developing new artificial fusogenic agents for next-generation biomedical applications that require tight control of the rate of fusion events (e.g., targeted drug delivery).

Protein Content in the Diet Influences Growth and Diarrhea in Weaning Piglets.

The aim of this research has been to assess the effect of the dietary protein level on piglet growth and post-weaning diarrhea (PWD) incidence. Piglet fecal microbiota and feces composition were also assessed. The experiment was carried out on 144 weaned piglets (Duroc × Large White; 72 piglets per treatment) and lasted from weaning (at 25 days of age) until the end of the post-weaning phase (at 95 days). Two dietary protein levels were compared: high (HP; 17.5% crude protein on average, during the experiment) and low (LP; 15.5% on average). Lower (p < 0.01) average daily gain and feed conversion ratio were observed in LP piglets in the first growth phase. However, at the end of the post-weaning period, the growth parameters were not significantly different in the two diets. Diarrhea scores were lower in piglets fed LP diets than in piglets fed HP diets (28.6% of the total vs. 71.4% in the HP piglets). Fibrobacteres, Proteobacteria, and Spirochaetes were more abundant in the feces of the piglets fed LP diets. Feces nitrogen content was lower in piglets fed LP diets. In conclusion, low protein levels in the diet can reduce the incidence of PWD while only marginally affecting growth parameters.

Correction: Development of a transferable coarse-grained model of polydimethylsiloxane.

Correction for 'Development of a transferable coarse-grained model of polydimethylsiloxane' by Sonia Cambiaso et al., Soft Matter, 2022, https://doi.org/10.1039/d2sm00939k.

Development of a transferable coarse-grained model of polydimethylsiloxane.

Polydimethylsiloxane (PDMS) is a popular silicon-based polymer with advanced applications in microfluidics and nanocomposites. The slow dynamics of polymer chains in such complex systems hinders molecular dynamics investigations based on all atom force fields. This limitation can be overcome by exploiting finely tuned coarse-grained (CG) models. This paper develops a transferable CG model of PDMS, compatible with the recent Martini 3 force field, using structural and thermodynamic properties as targets in the parametrization, including a vast set of experimental free energies of transfer. We validate the model transferability by reproducing the correct scaling laws for the PDMS gyration radius in the melt and good and bad solvents. We successfully test the model by reproducing the wetting behavior of water and acetonitrile on PDMS and the phase behavior of a PDMS-peptide triblock copolymer system. This work sets the stage for computational studies involving the interaction between PDMS and many synthetic and biological molecules modeled within the Martini framework.

Amphiphilic Gold Nanoparticles: A Biomimetic Tool to Gain Mechanistic Insights into Peptide-Lipid Interactions.

Functional peptides are now widely used in a myriad of biomedical and clinical contexts, from cancer therapy and tumor targeting to the treatment of bacterial and viral infections. Underlying this diverse range of applications are the non-specific interactions that can occur between peptides and cell membranes, which, in many contexts, result in spontaneous internalization of the peptide within cells by avoiding energy-driven endocytosis. For this to occur, the amphipathicity and surface structural flexibility of the peptides play a crucial role and can be regulated by the presence of specific molecular residues that give rise to precise molecular events. Nevertheless, most of the mechanistic details regulating the encounter between peptides and the membranes of bacterial or animal cells are still poorly understood, thus greatly limiting the biomimetic potential of these therapeutic molecules. In this arena, finely engineered nanomaterials-such as small amphiphilic gold nanoparticles (AuNPs) protected by a mixed thiol monolayer-can provide a powerful tool for mimicking and investigating the physicochemical processes underlying peptide-lipid interactions. Within this perspective, we present here a critical review of membrane effects induced by both amphiphilic AuNPs and well-known amphiphilic peptide families, such as cell-penetrating peptides and antimicrobial peptides. Our discussion is focused particularly on the effects provoked on widely studied model cell membranes, such as supported lipid bilayers and lipid vesicles. Remarkable similarities in the peptide or nanoparticle membrane behavior are critically analyzed. Overall, our work provides an overview of the use of amphiphilic AuNPs as a highly promising tailor-made model to decipher the molecular events behind non-specific peptide-lipid interactions and highlights the main affinities observed both theoretically and experimentally. The knowledge resulting from this biomimetic approach could pave the way for the design of synthetic peptides with tailored functionalities for next-generation biomedical applications, such as highly efficient intracellular delivery systems.

Ion-bridges and lipids drive aggregation of same-charge nanoparticles on lipid membranes.

The control of the aggregation of biomedical nanoparticles (NP) in physiological conditions is crucial as clustering may change completely the way they interact with the biological environment. Here we show that Au nanoparticles, functionalized by an anionic, amphiphilic shell, spontaneously aggregate in fluid zwitterionic lipid bilayers. We use molecular dynamics and enhanced sampling techniques to disentangle the short-range and long-range driving forces of aggregation. At short inter-particle distances, ion-mediated, charge-charge interactions (ion bridging) stabilize the formation of large NP aggregates, as confirmed by cryo-electron microscopy. Lipid depletion and membrane curvature are the main membrane deformations driving long-range NP-NP attraction. Ion bridging, lipid depletion, and membrane curvature stem from the configurational flexibility of the nanoparticle shell. Our simulations show, more in general, that the aggregation of same-charge membrane inclusions can be expected as a result of intrinsically nanoscale effects taking place at the NP-NP and NP-bilayer soft interfaces.

Polystyrene perturbs the structure, dynamics, and mechanical properties of DPPC membranes: An experimental and computational study.

Synthetic plastic oligomers can interact with the cells of living organisms by different ways. They can be intentionally administered to the human body as part of nanosized biomedical devices. They can be inhaled by exposed workers, during the production of multicomponent, polymer-based nanocomposites. They can leak out of food packaging. Most importantly, they can result from the degradation of plastic waste, and enter the food chain. A physicochemical characterization of the effects of synthetic polymers on the structure and dynamics of cell components is still lacking. Here, we combine a wide spectrum of experimental techniques (calorimetry, x-ray, and neutron scattering) with atomistic Molecular Dynamics simulations to study the interactions between short chains of polystyrene (25 monomers) and model lipid membranes (DPPC, in both gel and fluid phase). We find that doping doses of polystyrene oligomers alter the thermal properties of DPPC, stabilizing the fluid lipid phase. They perturb the membrane structure and dynamics, in a concentration-dependent fashion. Eventually, they modify the mechanical properties of DPPC, reducing its bending modulus in the fluid phase. Our results call for a systematic, interdisciplinary assessment of the mechanisms of interaction of synthetic, everyday use polymers with cell membranes.

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.

Cholesterol Hinders the Passive Uptake of Amphiphilic Nanoparticles into Fluid Lipid Membranes.

Plasma membranes represent pharmacokinetic barriers for the passive transport of site-specific drugs within cells. When engineered nanoparticles (NPs) are considered as transmembrane drug carriers, the plasma membrane composition can affect passive NP internalization in many ways. Among these, cholesterol-regulated membrane fluidity is probably one of the most biologically relevant. Herein, we consider small (2-5 nm in core diameter) amphiphilic gold NPs capable of spontaneously and nondisruptively entering the lipid bilayer of plasma membranes. We study their incorporation into model 1,2-dioleoyl-sn-glycero-3-phosphocholine membranes with increasing cholesterol content. We combine dissipative quartz crystal microbalance experiments, atomic force microscopy, and molecular dynamics simulations to show that membrane cholesterol, at biologically relevant concentrations, hinders the molecular mechanism for passive NP penetration within fluid bilayers, resulting in a dramatic reduction in the amount of NP incorporated.

Living supramolecular polymerization of fluorinated cyclohexanes.

The development of powerful methods for living covalent polymerization has been a key driver of progress in organic materials science. While there have been remarkable reports on living supramolecular polymerization recently, the scope of monomers is still narrow and a simple solution to the problem is elusive. Here we report a minimalistic molecular platform for living supramolecular polymerization that is based on the unique structure of all-cis 1,2,3,4,5,6-hexafluorocyclohexane, the most polar aliphatic compound reported to date. We use this large dipole moment (6.2 Debye) not only to thermodynamically drive the self-assembly of supramolecular polymers, but also to generate kinetically trapped monomeric states. Upon addition of well-defined seeds, we observed that the dormant monomers engage in a kinetically controlled supramolecular polymerization. The obtained nanofibers have an unusual double helical structure and their length can be controlled by the ratio between seeds and monomers. The successful preparation of supramolecular block copolymers demonstrates the versatility of the approach.

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.

Amphiphilic gold nanoparticles perturb phase separation in multidomain lipid membranes.

Amphiphilic gold nanoparticles with diameters in the 2-4 nm range are promising as theranostic agents thanks to their spontaneous translocation through cell membranes. This study addresses the effects that these nanoparticles may have on a distinct feature of plasma membranes: lipid lateral phase separation. Atomic force microscopy, quartz crystal microbalance, and molecular dynamics are combined to study the interaction between model neuronal membranes, which spontaneously form ordered and disordered lipid domains, and amphiphilic gold nanoparticles having negatively charged surface functionalization. Nanoparticles are found to interact with the bilayer and form bilayer-embedded ordered aggregates. Nanoparticles also suppress lipid phase separation, in a concentration-dependent fashion. A general, yet simple thermodynamic model is developed to show that the change of lipid-lipid enthalpy is the dominant driving force towards the nanoparticle-induced destabilization of phase separation.

Self-Sorted, Random, and Block Supramolecular Copolymers via Sequence Controlled, Multicomponent Self-Assembly.

Multicomponent supramolecular copolymerization promises to construct complex nanostructures with emergent properties. However, even with two monomeric components, various possible outcomes such as self-sorted supramolecular homopolymers, a random (statistical) supramolecular copolymer, an alternate supramolecular copolymer, or a complex supramolecular block copolymer can occur, determined by their intermolecular interactions and monomer exchange dynamics and hence structural prediction is extremely challenging. Herein, we target this challenge and demonstrate unprecedented two-component sequence controlled supramolecular copolymerization by manipulating thermodynamic and kinetic routes in the pathway complexity of self-assembly of the constitutive monomers. Extensive molecular dynamics simulations provided useful mechanistic insights into the monomer exchange rates and free energy of interactions between the monomers that dictate the self-assembly pathway and sequence. The fluorescent nature of core-substituted naphthalene diimide monomers has been further utilized to characterize the three sequences via Structured Illumination Microscopy (SIM).

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.

Biomimetic Synthesis of Sub-20 nm Covalent Organic Frameworks in Water.

Covalent organic frameworks (COFs) are commonly synthesized under harsh conditions yielding unprocessable powders. Control in their crystallization process and growth has been limited to studies conducted in hazardous organic solvents. Herein, we report a one-pot synthetic method that yields stable aqueous colloidal solutions of sub-20 nm crystalline imine-based COF particles at room temperature and ambient pressure. Additionally, through the combination of experimental and computational studies, we investigated the mechanisms and forces underlying the formation of such imine-based COF colloids in water. Further, we show that our method can be used to process the colloidal solution into 2D and 3D COF shapes as well as to generate a COF ink that can be directly printed onto surfaces. These findings should open new vistas in COF chemistry, enabling new application areas.

Symbiotic Self-Assembly Strategy toward Lipid-Encased Cross-Linked Polymer Nanoparticles for Efficient Gene Silencing.

A novel "symbiotic self-assembly" strategy that integrates the advantages of biocompatible lipids with a structurally robust polymer to efficiently encapsulate and deliver siRNAs is reported. The assembly process is considered to be symbiotic because none of the assembling components are capable of self-assembly but can form well-defined nanostructures in the presence of others. The conditions of the self-assembly process are simple but have been chosen such that it offers the ability to arrive at a system that is noncationic for mitigating carrier-based cytotoxicity, efficiently encapsulate siRNA to minimize cargo loss, be effectively camouflaged to protect the siRNA from nuclease degradation, and efficiently escape the endosome to cause gene knockdown. The lipid-siRNA-polymer (L-siP) nanoassembly formation and its disassembly in the presence of an intracellular trigger have been extensively characterized experimentally and through computational modeling. The complexes have been evaluated for the delivery of four different siRNA molecules in six different cell lines, where an efficient gene knockdown is demonstrated. The reported generalized strategy has the potential to make an impact on the development of a safe and effective delivery agent for RNAi-mediated gene therapy that holds the promise of targeting several hard-to-cure diseases.