Modeling Self-Assembly Processes Driven by Nonbonded Interactions in Soft Materials

Computation meets experiment: identification of highly efficient fibrillating peptides

Self-assembling peptides are of huge interest for biological, medical and nanotechnological applications. The enormous chemical variety that is available from the 20 amino acids offers potentially unlimited peptide sequences, but it is currently an issue to predict their supramolecular behavior in a reliable and cheap way. Herein we report a computational method to screen and forecast the aqueous self-assembly propensity of amyloidogenic pentapeptides. This method was found also as an interesting tool to predict peptide crystallinity, which may be of interest for the development of peptide based drugs.

Accelerating the prediction and discovery of peptide hydrogels with human-in-the-loop

The amino acid sequences of peptides determine their self-assembling properties. Accurate prediction of peptidic hydrogel formation, however, remains a challenging task. This work describes an interactive approach involving the mutual information exchange between experiment and machine learning for robust prediction and design of (tetra)peptide hydrogels. We chemically synthesize more than 160 natural tetrapeptides and evaluate their hydrogel-forming ability, and then employ machine learning-experiment iterative loops to improve the accuracy of the gelation prediction. We construct a score function coupling the aggregation propensity, hydrophobicity, and gelation corrector Cg, and generate an 8,000-sequence library, within which the success rate of predicting hydrogel formation reaches 87.1%. Notably, the de novo-designed peptide hydrogel selected from this work boosts the immune response of the receptor binding domain of SARS-CoV-2 in the mice model. Our approach taps into the potential of machine learning for predicting peptide hydrogelator and significantly expands the scope of natural peptide hydrogels.

Graph-based Automated Macro-Molecule Assembly

We present a general molecular framework assembly algorithm that takes a largely arbitrary molecular fragment database and a user-supplied target template graph as input. Automatic assembly of molecular fragments from the database, following a prescribed, user-supplied set of connection rules, then turns the template graph into an actual, chemically reasonable molecular framework. Assembly capabilities of our algorithm are tested by producing several abstract, closed-loop shapes. To indicate a few of many possible application areas we demonstrate a host-guest complex and a road toward catalysis. Postassembly substituent exchange can be used to produce electric fields of desired values at desired points inside the framework or at its surface as a stepping stone toward rationally designed, artificial heterogeneous catalysts.

Supramolecular gold(i) vesicles: an in-depth study of their aggregation process

The synthesis and aggregation behaviour of two gold(i) complexes containing a pyridyl ligand with a polyethyleneglycol pendant arm at one position and a chromophore (aniline or coumarin) at the second coordination position is herein reported.

Advances in the Structural Design of Polyelectrolyte Complex Micelles

Polyelectrolyte complex micelles (PCMs) are a unique class of self-assembled nanoparticles that form with a core of associated polycations and polyanions, microphase-separated from neutral, hydrophilic coronas in aqueous solution. The hydrated nature and structural and chemical versatility make PCMs an attractive system for delivery and for fundamental polymer physics research. By leveraging block copolymer design with controlled self-assembly, fundamental structure-property relationships can be established to tune the size, morphology, and stability of PCMs precisely in pursuit of tailored nanocarriers, ultimately offering storage, protection, transport, and delivery of active ingredients. This perspective highlights recent advances in predictive PCM design, focusing on (i) structure-property relationships to target specific nanoscale dimensions and shapes and (ii) characterization of PCM dynamics primarily using time-resolved scattering techniques. We present several vignettes from these two emerging areas of PCM research and discuss key opportunities for PCM design to advance precision medicine.

Implicit Solvation Using the Superposition Approximation (IS-SPA): Extension to Peptides in a Polar Solvent

Efficient, accurate, and adaptable implicit solvent models remain a significant challenge in the field of molecular simulation. A recent implicit solvent model, IS-SPA, based on approximating the mean solvent force using the superposition approximation, provides a platform to achieve these goals. IS-SPA was originally developed to handle nonpolar solutes in a polar solvent and did not accurately capture polar solvation. Here, we demonstrate that IS-SPA can accurately capture polar solvation by incorporating solvent orientation and accounting for the contributions from long ranged electrostatics. Solvent orientation is approximated as that of an ideal dipole aligned in a mean electrostatic field and an analytic form of the long ranged electrostatics is derived. Parameters for the model are calculated from explicit solvent simulations of an isolated atom or molecule and include atom-based solvent densities, mean electric field functions, radially symmetric averaged Lennard-Jones forces, and multipoles of the explicit solvent model. Using these parameters, IS-SPA accounts for asymmetry of charge solvation and reproduces the explicit solvent potential of mean force of dimerization of two oppositely charged Lennard-Jones spheres in chloroform with high fidelity. Additionally, the model more accurately captures the effect of explicit solvent on the monomer and dimer configurations of alanine dipeptide in chloroform than a generalized Born or constant density dielectric model. The current version of the algorithm is expected to outperform explicit solvent simulations for aggregation of small peptides at concentrations below 150 mM, well above the typical experimental concentrations for these materials.

Molecular Modeling and Simulations of Peptide–Polymer Conjugates

Peptide–polymer conjugates are a class of soft materials composed of covalently linked blocks of protein/polypeptides and synthetic/natural polymers. These materials are practically useful in biological applications, such as drug delivery, DNA/gene delivery, and antimicrobial coatings, as well as nonbiological applications, such as electronics, separations, optics, and sensing. Given their broad applicability, there is motivation to understand the molecular and macroscale structure, dynamics, and thermodynamic behavior exhibited by such materials. We focus on the past and ongoing molecular simulation studies aimed at obtaining such fundamental understanding and predicting molecular design rules for the target function. We describe briefly the experimental work in this field that validates or motivates these computational studies. We also describe the various models (e.g., atomistic, coarse-grained, or hybrid) and simulation methods (e.g., stochastic versus deterministic, enhanced sampling) that have been used and the types of questions that have been answered using these computational approaches.

Self-assembling outside equilibrium: emergence of structures mediated by dissipation

Self-assembly under non-equilibrium conditions may give rise to the formation of structures not available at equilibrium.

Low molecular weight supramolecular dehydroepiandrosterone-based gelators: synthesis and molecular modeling study

Three novel isomeric low molecular weight dehydroepiandrosterone-based gelators are synthesized. Their ability to self-assemble is studied in several solvents both experimentally and theoretically by molecular modeling.

Molecular simulations of self-assembling bio-inspired supramolecular systems and their connection to experiments

In bionanotechnology, the field of creating functional materials consisting of bio-inspired molecules, the function and shape of a nanostructure only appear through the assembly of many small molecules together. The large number of building blocks required to define a nanostructure combined with the many degrees of freedom in packing small molecules has long precluded molecular simulations, but recent advances in computational hardware as well as software have made classical simulations available to this strongly expanding field. Here, we review the state of the art in simulations of self-assembling bio-inspired supramolecular systems. We will first discuss progress in force fields, simulation protocols and enhanced sampling techniques using recent examples. Secondly, we will focus on efforts to enable the comparison of experimentally accessible observables and computational results. Experimental quantities that can be measured by microscopy, spectroscopy and scattering can be linked to simulation output either directly or indirectly, via quantum mechanical or semi-empirical techniques. Overall, we aim to provide an overview of the various computational approaches to understand not only the molecular architecture of nanostructures, but also the mechanism of their formation.

Structural and Spectroscopic Properties of Assemblies of Self-Replicating Peptide Macrocycles

Self-replication at the molecular level is often seen as essential to the early origins of life. Recently a mechanism of self-replication has been discovered in which replicator self-assembly drives the process. We have studied one of the examples of such self-assembling self-replicating molecules to a high level of structural detail using a combination of computational and spectroscopic techniques. Molecular Dynamics simulations of self-assembled stacks of peptide-derived replicators provide insights into the structural characteristics of the system and serve as the basis for semiempirical calculations of the UV-vis, circular dichroism (CD) and infrared (IR) absorption spectra that reflect the chiral organization and peptide secondary structure of the stacks. Two proposed structural models are tested by comparing calculated spectra to experimental data from electron microscopy, CD and IR spectroscopy, resulting in a better insight into the specific supramolecular interactions that lead to self-replication. Specifically, we find a cooperative self-assembly process in which β-sheet formation leads to well-organized structures, while also the aromatic core of the macrocycles plays an important role in the stability of the resulting fibers.

High-Resolution Insights into the Stepwise Self-Assembly of Nanofiber from Bioactive Peptides

Peptide self-assembly has a profound biological significance since self-assembled bioactive peptides are gifted with improved bioactivity as well as life-span. In this study, peptide self-assembly was investigated using a therapeutic peptide, PTP-7S (EENFLGALFKALSKLL). Combining experiments of atomic force microscopy (AFM), circular dichroism (CD), and 8-anilino-1-naphthalenesulfonic acid (ANS) fluorescence spectra, PTP-7S showed the α-helical structure and was found self-assembling into nanofibers in solution. Relying on the coarse-grained (CG) dynamic simulations, the self-assembling of PTP-7S was revealed as a stepwise process that peptide monomers first clustered into peptide-assembling units (PUs) with charged surface, and then the PUs integrated together to construct nanofibril aggregates. Different roles of the nonbonded driving forces did play in the two phases: the hydrophobic force and electrostatic interaction acted as the predominant motivations in the formation of PUs and nanofiber, respectively. Moreover, the electrostatic interaction helped to guide the longitudinal growth of peptide nanofibers. A sequence principle is proposed for peptide self-assembling in aqueous solution: a balance of the counter charges and sufficient hydrophobicity degree. The self-assembled PTP-7S displayed good anticancer activity, proteases resistance, and sustained drug-release, showing a great potential for clinical application. This study reveals the molecular mechanism in explaining PTP-7S self-assembly and it is beneficial for future innovation of the self-assembled bioactive peptides.

Simulation of self-assembly of polyzwitterions into vesicles

Using the Langevin dynamics method and a coarse-grained model, we have studied the formation of vesicles by hydrophobic polymers consisting of periodically placed zwitterion side groups in dilute salt-free aqueous solutions. The zwitterions, being permanent charge dipoles, provide long-range electrostatic correlations which are interfered by the conformational entropy of the polymer. Our simulations are geared towards gaining conceptual understanding in these correlated dipolar systems, where theoretical calculations are at present formidable. A competition between hydrophobic interactions and dipole-dipole interactions leads to a series of self-assembled structures. As the spacing d between the successive zwitterion side groups decreases, single chains undergo globule → disk → worm-like structures. We have calculated the Flory-Huggins χ parameter for these systems in terms of d and monitored the radius of gyration, hydrodynamic radius, spatial correlations among hydrophobic and dipole monomers, and dipole-dipole orientational correlation functions. During the subsequent stages of self-assembly, these structures lead to larger globules and vesicles as d is decreased up to a threshold value, below which no large scale morphology forms. The vesicles form via a polynucleation mechanism whereby disk-like structures form first, followed by their subsequent merger.

Lattice model of oligonucleotide hybridization in solution. II. Specificity and cooperativity

Because oligonucleotides are short sequences of nucleic acid bases, their association in solution with complementary strands (hybridization) is often seen to conform to a simple two-state model. However, experimental evidence suggests that, despite their short length, oligonucleotides may hybridize through multiple states involving intermediates. We investigate whether these apparently contradictory scenarios are possible by imposing different levels of sequence specificity on a lattice model of oligonucleotides in solution, which we introduced in Part I [J. C. Araque et al., J. Chem. Phys. 134, 165103 (2011)]. We find that both multiple-intermediate (weakly cooperative) and two-state (strongly cooperative) transitions are possible and that these are directly linked to the level of sequence specificity. Sequences with low specificity hybridize (base-by-base) by way of multiple stable intermediates with increasing number of paired bases. Such intermediate states are weakly cooperative because the energetic gain from adding an additional base pair is outweighed by the conformational entropy loss. Instead, sequences with high specificity hybridize through multiple metastable intermediates which easily bridge the configurational and energetic gaps between single- and double-stranded states. These metastable intermediates interconvert with minimal loss of conformational entropy leading to a strongly cooperative hybridization. The possibility of both scenarios, multiple- and two-states, is therefore encoded in the specificity of the sequence which in turn defines the level of cooperativity.

Micelle response to changes in solvent properties

The dynamics of co-polymer systems play an important role in the preparation and stability of formulations, as well as on their capability to function in drug delivery systems. Micelle inversion can occur as a result of a change in concentration when a solvent is very volatile and evaporates, or as a result of a change in solvent quality upon addition of another solvent to the original solution, or upon changes in pH. In this work, dissipative particle dynamics (DPD) is used to examine the dynamics of micelle inversion in concentrated systems of diblock and triblock amphiphiles, where interactions between neighboring aggregates are observed. Significant differences were observed in the inversion process of different amphiphilic molecules, with a large amount of co-polymer exchange between inverting aggregates made of diblock amphiphiles, and practically no exchange of molecules between aggregates during the inversion of triblock copolymer aggregates. Fundamental mechanisms of inversion are revealed that provide information which can be used to help design micelles for targeted drug release and allow understanding of history dependant formulations.

Water ordering controls the dynamic equilibrium of micelle-fibre formation in self-assembly of peptide amphiphiles

Understanding the role of water in governing the kinetics of the self-assembly processes of amphiphilic peptides remains elusive. Here, we use a multistage atomistic-coarse-grained approach, complemented by circular dichroism/infrared spectroscopy and dynamic light scattering experiments to highlight the dual nature of water in driving the self-assembly of peptide amphiphiles (PAs). We show computationally that water cage formation and breakage near the hydrophobic groups control the fusion dynamics and aggregation of PAs in the micellar stage. Simulations also suggest that enhanced structural ordering of vicinal water near the hydrophilic amino acids shifts the equilibrium towards the fibre phase and stimulates structure and order during the PA assembly into nanofibres. Experiments validate our simulation findings; the measured infrared O–H bond stretching frequency is reminiscent of an ice-like bond which suggests that the solvated water becomes increasingly ordered with time in the assembled peptide network, thus shedding light on the role of water in a self-assembly process.

The role of water in the kinetics of the self-assembly process of amphiphilic peptides still remains unknown. Sankaranarayanan et al. have shown through computational study that water has a dual nature when dictating the mechanism and dynamics of self-assembly of peptide amphiphiles.

Binding Preferences of Amino Acids for Gold Nanoparticles: A Molecular Simulation Study

A better understanding of the binding preference of amino acids for gold nanoparticles of different diameters could aid in the design of peptides that bind specifically to nanoparticles of a given diameter. Here we identify the binding preference of 19 natural amino acids for three gold nanoparticles with diameters of 1.0, 2.0, and 4.0 nm, and investigate the mechanisms that govern these preferences. We calculate potentials of mean force between 36 entities (19 amino acids and 17 side chains) and the three gold nanoparticles in explicit water using well-tempered metadynamics simulations. Comparing these potentials of mean force determines the amino acids' nanoparticle binding preferences and if these preferences are controlled by the backbone, the side chain, or both. Twelve amino acids prefer to bind to the 4.0 nm gold nanoparticle, and seven prefer to bind to the 2.0 nm one. We also use atomistic molecular dynamics simulations to investigate how water molecules near the nanoparticle influence the binding of the amino acids. The solvation shells of the larger nanoparticles have higher water densities than those of the smaller nanoparticles while the orientation distributions of the water molecules in the shells of all three nanoparticles are similar. The nanoparticle preferences of the amino acids depend on whether their binding free energy is determined mainly by their ability to replace or to reorient water molecules in the nanoparticle solvation shell. The amino acids whose binding free energy depends mainly on the replacement of water molecules are likely to prefer to bind to the largest nanoparticle and tend to have relatively simple side chain structures. Those whose binding free energy depends mainly on their ability to reorient water molecules prefer a smaller nanoparticle and tend to have more complex side chain structures.

Tripeptide Emulsifiers

A series of tripeptides is shown to form emulsions with sequence tunable properties. Using a combination of simulations and experiments, it is shown that two types of oil-in-water emulsions may be produced, either forming stable interfacial nanofiber networks with remarkable stability, or more conventional surfactant-like monolayers.

CHARMM force field parameterization protocol for self-assembling peptide amphiphiles: the Fmoc moiety

Aromatic peptide amphiphiles are known to self-assemble into nanostructures but the molecular level structure and the mechanism of formation of these nanostructures is not yet understood in detail.

Tuning the self-assembly of surfactants by the confinement of carbon nanotube arrays: a cornucopia of lamellar phase variants

Tuning the self-assembly of building blocks to obtain a kaleidoscope of nanostructures is very important and challenging for the preparation of advanced nanomaterials. Amphiphiles confined within carbon nanotube (CNT) arrays can self-assemble into complex structures that maintain the "bilayer" characteristic of a lamellar phase, we call them "lamellar phase variants (LPVs)". In this work, we carried out coarse-grained molecular dynamics (MD) studies to uncover novel LPVs. By varying the pattern of a CNT array, we obtained the "bilayer tube (BT) series", which contains circular, hexagonal, octagonal, and elliptical nanotubes. Furthermore, by introducing dislocation to CNT arrays, we obtained the "bilayer scroll (BS) series" that contains polymorphic nano-scrolls. These nanostructures are very novel and intriguing. To gain insights into the formation of LPVs, we studied the morphology evolution, which was demonstrated to be an unfamiliar "successive self-assembly process". These unusual self-assembling nanostructures and the formation process could provide clues for further studies on tuning the self-assembly of building blocks. The strategies developed in this work to obtain novel nanostructures are expected to facilitate the design and fabrication of nano-devices.

What controls the hybridization thermodynamics of spherical nucleic acids?

The hybridization of free oligonucleotides to densely packed, oriented arrays of DNA modifying the surfaces of spherical nucleic acid (SNA)-gold nanoparticle conjugates occurs with negative cooperativity; i.e., each binding event destabilizes subsequent binding events. DNA hybridization is thus an ever-changing function of the number of strands already hybridized to the particle. Thermodynamic quantification of this behavior reveals a 3 orders of magnitude decrease in the binding constant for the capture of a free oligonucleotide by an SNA conjugate as the fraction of pre-hybridized strands increases from 0 to ∼30%. Increasing the number of pre-hybridized strands imparts an increasing enthalpic penalty to hybridization that makes binding more difficult, while simultaneously decreasing the entropic penalty to hybridization, which makes binding more favorable. Hybridization of free DNA to an SNA is thus governed by both an electrostatic barrier as the SNA accumulates charge with additional binding events and an effect consistent with allostery, where hybridization at certain sites on an SNA modify the binding affinity at a distal site through conformational changes to the remaining single strands. Leveraging these insights allows for the design of conjugates that hybridize free strands with significantly higher efficiencies, some of which approach 100%.

Exploring the sequence space for (tri-)peptide self-assembly to design and discover new hydrogels

Peptides that self-assemble into nanostructures are of tremendous interest for biological, medical, photonic and nanotechnological applications. The enormous sequence space that is available from 20 amino acids probably harbours many interesting candidates, but it is currently not possible to predict supramolecular behaviour from sequence alone. Here, we demonstrate computational tools to screen for the aqueous self-assembly propensity in all of the 8,000 possible tripeptides and evaluate these by comparison with known examples. We applied filters to select for candidates that simultaneously optimize the apparently contradicting requirements of aggregation propensity and hydrophilicity, which resulted in a set of design rules for self-assembling sequences. A number of peptides were subsequently synthesized and characterized, including the first reported tripeptides that are able to form a hydrogel at neutral pH. These tools, which enable the peptide sequence space to be searched for supramolecular properties, enable minimalistic peptide nanotechnology to deliver on its promise.

Unusual, photo-induced self-assembly of azobenzene-containing amphiphiles

Stimuli-responsive self-assembly is playing an increasingly important role in emerging applications, ranging from smart materials to biosensors. However, obtaining essential information for further development, such as molecular arrangement and interaction, is still experimentally challenging. A molecular-level understanding of the stimuli-responsive self-assembly is needed. Azobenzene-containing (azo-containing) amphiphiles organize into photo-responsive assemblies because of the cis-trans isomerization triggered by the irradiation of ultraviolet (UV) and visible light. In this study, we applied a coarse grained (CG) molecular dynamics (MD) simulation, with the necessary potential parameters fitted from theoretical calculation data, to study the photo-induced self-assembly of 4,4'-bis(hydroxymethyl)-azobenzene (AzoCO), a simple azo-containing amphiphile. An unusual "chaotic micelle" and "monolayer phase" were obtained with cis- and trans-AzoCO molecules, respectively. The structural information and formation mechanism were studied. The "chaotic micelle" possesses a chaotic but not a pure hydrophobic interior as commonly understood. Through comparative simulations, we found that the azo (-N[double bond, length as m-dash]N-) group of azobenzene plays a crucial role in the formation of the "chaotic micelle". The "monolayer phase" is arranged by abreast rod-like trans-AzoCO molecules; the axial symmetry of the trans-AzoCO molecule drives the formation of this structure. The novel "chaotic micelle" and "monolayer phase" have potential applications in nanotechnology and bioengineering. This work is expected to trigger further studies on stimuli-responsive phenomena and materials.

Force-Field Parameters from the SAFT-γ Equation of State for Use in Coarse-Grained Molecular Simulations

A description of fluid systems with molecular-based algebraic equations of state (EoSs) and by direct molecular simulation is common practice in chemical engineering and the physical sciences, but the two approaches are rarely closely coupled. The key for an integrated representation is through a well-defined force field and Hamiltonian at the molecular level. In developing coarse-grained intermolecular potential functions for the fluid state, one typically starts with a detailed, bottom-up quantum-mechanical or atomic-level description and then integrates out the unwanted degrees of freedom using a variety of techniques; an iterative heuristic simulation procedure is then used to refine the parameters of the model. By contrast, with a top-down technique, one can use an accurate EoS to link the macroscopic properties of the fluid and the force-field parameters. We discuss the latest developments in a top-down representation of fluids, with a particular focus on a group-contribution formulation of the statistical associating fluid theory (SAFT-γ). The accurate SAFT-γ EoS is used to estimate the parameters of the Mie force field, which can then be used with confidence in direct molecular simulations to obtain thermodynamic, structural, interfacial, and dynamical properties that are otherwise inaccessible from the EoS. This is exemplified for several prototypical fluids and mixtures, including carbon dioxide, hydrocarbons, perfluorohydrocarbons, and aqueous surfactants.

Short peptide based self-assembled nanostructures: implications in drug delivery and tissue engineering

Self-assembling peptides with many potential biomedical applications.

Molecular insights into the self-assembly of short amphiphilic peptides FmDn and FmKn

Molecular dynamics simulation is reported for the self-assembly of short amphiphilic peptides F_mD_n and F_mK_n.

Free energy profile and mechanism of self-assembly of peptide amphiphiles based on a collective assembly coordinate

By combining targeted molecular dynamics (TMD) simulations, umbrella sampling, and the weighted histogram analysis method (WHAM), we have calculated the potential of mean force (PMF) for the transition between the bound and free states of 90 peptide amphiphiles (PAs) in aqueous solution, with the bound state corresponding to a cylindrical micelle fiber. We specifically consider a collective reaction coordinate, the radius of gyration of the PAs, to describe assembly in this work. It is found that the free energy, enthalpy, and entropy differences between the free and bound states are -126 kcal/mol, -185 kcal/mol, and -190 cal/(mol K), respectively, for the self-assembly process. This indicates that the driving force to form the micelle structure is enthalpic. The enthalpic driving forces originate from several factors, including the conformational energy of PAs and the electrostatic and van der Waals interaction energy between solvent molecules and between solvent and PAs. Among these interactions, the solvent electrostatic interaction is the dominating one, contributing 54% of the total driving force. The PMF profile can be recognized as involving two stages of assembly: (1) PAs initially approach each other in mostly random configurations and loosely aggregate, resulting in significant desolvation and initiation of head-tail conformational reorganization; (2) PAs undergo a conformational disorder-to-order transition, including forming secondary structures that include more β-sheets and fewer random coils, along with tail-head core-shell alignment and condensation that leads to total exclusion of water from the core. The PMF decreases slowly in the first stage, but rapidly in the second. This study demonstrates a hierarchy of assembly steps in which PA structural changes, solvation, and redistribution of solvent molecules play significant roles in the PA self-assembly process.

Steered molecular dynamics studies of the potential of mean force for peptide amphiphile self-assembly into cylindrical nanofibers

Steered molecular dynamics (SMD) simulations were applied to determine the potential of mean force for the self-assembly of peptide amphiphile (PA) nanofibers, specifically considering a single PA adding to a growing cylindrical nanofiber at 310 K. It is found that the free energy, enthalpy, and entropy differences for this assembly process are -67 kcal/mol, -71.5 kcal/ml, and -14.5 cal/(mol K), respectively, and therefore that enthalpy provides the driving force for self-assembly to form a fiber. A pairwise interaction analysis shows that both electrostatic and van der Waals interactions play important roles in the self-assembly process, with the van der Waals interaction being the larger effect. The mechanistic picture that emerges from this work is that as the PA is pulled from the fiber, the interaction evolves through three stages: (1) initially electrostatic interactions between the charged head of the pulled PA and other PAs, and between the pulled PA and solvent are dominant, (2) after the charged head emerges, the rest of the peptide comes out, with both PA-solvent electrostatic interactions and van der Waals interactions being significant, and (3) in the last step, the alkane tail emerges, dominated by van der Waals interactions with either peptide or solvent.

Dispersion of graphene sheets in aqueous solution by oligodeoxynucleotides

Applications of graphene sheets in the fields of biosensors and biomedical devices are limited by their insolubility in water. Consequently, understanding the dispersion mechanism of graphene in water and exploring an effective way to prepare stable dispersions of graphene sheets in water is of vital importance for their application in biomaterials, biosensors, biomedical devices, and drug delivery. Herein, a method for stable dispersion of graphene sheets in water by single-stranded oligodeoxynucleotides (ssODNs) is studied. Owing to van der Waals interactions between graphene sheets, they undergo layer-to-layer (LtL) aggregation in water. Molecular dynamics simulations show that, by disrupting van der Waals interaction of graphene sheets with ssODNs, LtL aggregation of graphene sheets is prevented, and water molecules can be distributed stably between graphene sheets. Thus, graphene sheets are dispersed stably in water in the presence of ssODNs. The effects of size and molarity of ssODNs and noncovalent modification of graphene sheets are also discussed.

Predicted ordered assembly of ethylene molecules induced by polarized off-resonance laser pulses

We illustrate a new phenomenon in the dynamics of molecular ensembles subjected to moderately intense, far-off-resonance laser fields, namely, field-driven formation of perfectly ordered, defect-free assembly. Interestingly, both the arrangement of the constituting molecules within the individual assembly and the long-range order of the assembly with respect to one another are subject to control through choice of the field polarization. Relying on strong induced dipole-induced dipole interactions that are established in dense molecular media, the effect is expected to be general.

Modeling the self-assembly of peptide amphiphiles into fibers using coarse-grained molecular dynamics

We have studied the self-assembly of peptide amphiphiles (PAs) into a cylindrical micelle fiber starting from a homogeneous mixture of PAs in water using coarse-grained molecular dynamics simulations. Nine independent 16 μs runs all show spontaneous fiber formation in which the PA molecules first form spherical micelles, and then micelles form a three-dimensional network via van der Waals interactions. As the hydrophobic core belonging to the different micelles merge, the three-dimensional network disappears and a fiber having a diameter of ∼80 Å appears. In agreement with atomistic simulation results, water molecules are excluded from the hydrophobic core and penetrate to ∼15 Å away from the axis of fiber. About 66% of the surface of fiber is covered with the IKVAV epitope, and ∼92% of the epitope is exposed to water molecules.

Fabrication of nanostructures through molecular self-assembly of small amphiphilic glyco-dehydropeptides

Self-assembled peptide-based nanostructures have been the focus of research in the past decade because of their potential applications in various biological systems. Normally, small self-assembled peptide nanostructures contain hydrophobic moieties, therefore, their solubility in aqueous systems poses the important challenge in the field of molecular self-assembly in order to make effective use of these in a wide variety of applications. To improve their aqueous solubility, the self-assembled amphiphilic α,β-dehydrophenylalanine containing small glyco-dehydropeptides, Boc-Phe-ΔPhe-εAhx-GA (I) and H-Phe-ΔPhe-εAhx-GA (II) with glucosamine (GA) attached at the C-terminal through a 6-aminocaproic acid linker, were synthesized, demonstrating the formation of nanostructures in aqueous media, which were characterized by DLS, AFM and TEM. Further, nanostructure II reduced auric chloride to gold nanoparticles and formed a peptide-gold conjugate (VII). The feasibility of using the nanostructures I and II as nanovectors for drug delivery was demonstrated by loading hydrophobic molecules, eosin and N-fluoresceinyl-2-aminoethanol (FAE) dyes. Besides, these peptides displayed antimicrobial activity against Micrococcus flavus, Bacillus subtilis and Pseudomonas aeruginosa. All these results advocate the potential of these nanostructures as efficient vectors for drug delivery applications.

Monte Carlo study of the molecular mechanisms of surface-layer protein self-assembly

The molecular mechanisms guiding the self-assembly of proteins into functional or pathogenic large-scale structures can be only understood by studying the correlation between the structural details of the monomer and the eventual mesoscopic morphologies. Among the myriad structural details of protein monomers and their manifestations in the self-assembled morphologies, we seek to identify the most crucial set of structural features necessary for the spontaneous selection of desired morphologies. Using a combination of the structural information and a Monte Carlo method with a coarse-grained model, we have studied the functional protein self-assembly into S(surface)-layers, which constitute the crystallized outer most cell envelope of a great variety of bacterial cells. We discover that only few and mainly hydrophobic amino acids, located on the surface of the monomer, are responsible for the formation of a highly ordered anisotropic protein lattice. The coarse-grained model presented here reproduces accurately many experimentally observed features including the pore formation, chemical description of the pore structure, location of specific amino acid residues at the protein-protein interfaces, and surface accessibility of specific amino acid residues. In addition to elucidating the molecular mechanisms and explaining experimental findings in the S-layer assembly, the present work offers a tool, which is chemical enough to capture details of primary sequences and coarse-grained enough to explore morphological structures with thousands of protein monomers, to promulgate design rules for spontaneous formation of specific protein assemblies.

Heat conductivity of DNA double helix

Thermal conductivity of isolated single molecule DNA fragments is of importance for nanotechnology, but has not yet been measured experimentally. Theoretical estimates based on simplified (1D) models predict anomalously high thermal conductivity. To investigate thermal properties of single molecule DNA we have developed a 3D coarse-grained (CG) model that retains the realism of the full all-atom description, but is significantly more efficient. Within the proposed model each nucleotide is represented by 6 particles or grains; the grains interact via effective potentials inferred from classical molecular dynamics (MD) trajectories based on a well-established all-atom potential function. Comparisons of 10 ns long MD trajectories between the CG and the corresponding all-atom model show similar root-mean-square deviations from the canonical B-form DNA, and similar structural fluctuations. At the same time, the CG model is 10 to 100 times faster depending on the length of the DNA fragment in the simulation. Analysis of dispersion curves derived from the CG model yields longitudinal sound velocity and torsional stiffness in close agreement with existing experiments. The computational efficiency of the CG model makes it possible to calculate thermal conductivity of a single DNA molecule not yet available experimentally. For a uniform (polyG-polyC) DNA, the estimated conductivity coefficient is 0.3 W/mK which is half the value of thermal conductivity for water. This result is in stark contrast with estimates of thermal conductivity for simplified, effectively 1D chains ("beads on a spring") that predict anomalous (infinite) thermal conductivity. Thus, full 3D character of DNA double-helix retained in the proposed model appears to be essential for describing its thermal properties at a single molecule level.