Mesoscale Simulation of Asphaltene Aggregation

Asphaltenes constitute a heavy aromatic crude oil fraction with a propensity to aggregate and precipitate out of solution during petroleum processing. Aggregation is thought to proceed according to the Yen-Mullins hierarchy, but the molecular mechanisms underlying mesoscopic assembly remain poorly understood. By combining coarse-grained molecular models parametrized using all-atom data with high-performance GPU hardware, we have performed molecular dynamics simulations of the aggregation of hundreds of asphaltenes over microsecond time scales. Our simulations reveal a hierarchical self-assembly mechanism consistent with the Yen-Mullins model, but the details are sensitive and depend on asphaltene chemistry and environment. At low concentrations asphaltenes exist predominantly as dispersed monomers. Upon increasing concentration, we first observe parallel stacking into 1D rod-like nanoaggregates, followed by the formation of clusters of nanoaggregates associated by offset, T-shaped, and edge–edge stacking. Asphaltenes possessing long aliphatic side chains cannot form nanoaggregate clusters due to steric repulsions between their aliphatic coronae. At very high concentrations, we observe a porous percolating network of rod-like nanoaggregates suspended in a sea of interpenetrating aliphatic side chains with a fractal dimension of ∼2. The lifetime of the rod-like aggregates is described by an exponential distribution reflecting a dynamic equilibrium between coagulation and fragmentation

A Study of the Morphology, Dynamics, and Folding Pathways of Ring Polymers with Supramolecular Topological Constraints Using Molecular Simulation and Nonlinear Manifold Learning

Ring polymers are prevalent in natural and engineered systems, including circular bacterial DNA, crown ethers for cation chelation, and mechanical nanoswitches. The morphology and dynamics of ring polymers are governed by the chemistry and degree of polymerization of the ring and intramolecular and supramolecular topological constraints such as knots or mechanically interlocked rings. In this study, we perform molecular dynamics simulations of polyethylene ring polymers at two different degrees of polymerization and in different topological states, including a trefoil knot, catenane state (two interlocked rings), and Borromean state (three interlocked rings). We employ nonlinear manifold learning to extract the low-dimensional free energy surface to which the structure and dynamics of the polymer chain are effectively restrained. The free energy surfaces reveal how the degree of polymerization and topological constraints affect the thermally accessible conformations, chiral symmetry breaking, and folding and collapse pathways of the rings and present a means to rationally engineer ring size and topology to stabilize particular conformational states and folding pathways. We compute the rotational diffusion of the ring in these various states as a crucial property required for the design of engineered devices containing ring polymer components

Coarse-Grained Molecular Simulation of the Hierarchical Self-Assembly of π‑Conjugated Optoelectronic Peptides

Self-assembled aggregates of peptides containing aromatic groups possess optoelectronic properties that make them attractive targets for the fabrication of biocompatible electronics. Molecular-level understanding of the influence of microscopic peptide chemistry on the properties of the aggregates is vital for rational peptide design. In this study, we construct a coarse-grained model of Asp-Phe-Ala-Gly-OPV3-Gly-Ala-Phe-Asp (DFAG-OPV3-GAFD) peptides containing OPV3 (distyrylbenzene) π-conjugated cores explicitly parameterized against all-atom calculations and perform molecular dynamics simulations of the self-assembly of hundreds of molecules over hundreds of nanoseconds. We observe a hierarchical assembly mechanism, wherein approximately two to eight peptides assemble into stacks with aligned aromatic cores that subsequently form elliptical aggregates and ultimately a branched network with a fractal dimensionality of ∼1.5. The assembly dynamics are well described by a Smoluchowski coagulation process, for which we extract rate constants from the molecular simulations to both furnish insight into the microscopic assembly kinetics and extrapolate our aggregation predictions to time and length scales beyond the reach of molecular simulation. This study presents new molecular-level understanding of the morphology and dynamics of the spontaneous self-assembly of DFAG-OPV3-GAFD peptides and establishes a systematic protocol to develop coarse-grained models of optoelectronic peptides for the exploration and design of π-conjugated peptides with tunable optoelectronic properties

Coarse-Grained Molecular Simulation and Nonlinear Manifold Learning of Archipelago Asphaltene Aggregation and Folding

Asphaltenes constitute the heaviest aromatic component of crude oil. The myriad of asphaltene molecules falls largely into two conceptual classes: continentalpossessing a single polyaromatic coreand archipelagopossessing multiple polyaromatic cores linked by alkyl chains. In this work, we study the influence of molecular architecture upon aggregation behavior and molecular folding of prototypical archipelago asphaltenes using coarse-grained molecular dynamics simulation and nonlinear manifold learning. The mechanistic details of aggregation depend sensitively on the molecular structure. Molecules possessing three polyaromatic cores show a higher aggregation propensity than those with two, and linear archipelago architectures more readily form a fractal network than ring topologies, although the resulting aggregates are more susceptible to disruption by chemical dispersants. The Yen–Mullins hierarchy of self-assembled aggregates is attenuated at high asphaltene mass fractions because of the dominance of promiscuous parallel stacking interactions within a percolating network rather than the formation of rodlike nanoaggregates and nanoaggregate clusters. The resulting spanning porous network possesses a fractal dimension of 1.0 on short length scales and 2.0 on long length scales regardless of the archipelago architecture. The incompatibility of the observed assembly behavior with the Yen–Mullins hierarchy lends support that high-molecular weight archipelago architectures do not occur at significant levels in natural crude oils. Low-dimensional free energy surfaces discovered by nonlinear dimensionality reduction reveal a rich diversity of metastable configurations and folding behavior reminiscent of protein folding and inform how intramolecular structures can be modulated by controlling asphaltene mass fraction and dispersant concentration

Thermodynamics, morphology, and kinetics of early-stage self-assembly of π-conjugated oligopeptides

<p>Synthetic oligopeptides containing -conjugated cores self-assemble novel materials with attractive electronic and photophysical properties. All-atom, explicit solvent molecular dynamics simulations of Asp-Phe-Ala-Gly-OPV3-Gly-Ala-Phe-Asp peptides were used to parameterise an implicit solvent model to simulate early-stage self-assembly. Under low-pH conditions, peptides assemble into -sheet-like stacks with strongly favorable monomer association free energies of . Aggregation at high-pH produces disordered aggregates destabilised by Coulombic repulsion between negatively charged Asp termini (). In simulations of hundreds of monomers over 70 ns we observe the spontaneous formation of up to undecameric aggregates under low-pH conditions. Modeling assembly as a continuous-time Markov process, we infer transition rates between different aggregate sizes and microsecond relaxation times for early-stage assembly. Our data suggests a hierarchical model of assembly in which peptides coalesce into small clusters over tens of nanoseconds followed by structural ripening and diffusion limited aggregation on longer time scales. This work provides new molecular-level understanding of early-stage assembly, and a means to study the impact of peptide sequence and aromatic core chemistry upon the thermodynamics, assembly kinetics, and morphology of the supramolecular aggregates.</p

Evidence for Prenucleated Fibrilogenesis of Acid-Mediated Self-Assembling Oligopeptides via Molecular Simulation and Fluorescence Correlation Spectroscopy

An important step in controlling biomimetic amyloid systems is understanding the self-assembly reaction kinetics. We are interested in a family of such materials characterized by symmetric sequences of amino acids flanking a π-conjugated functional core. Many of these materials rapidly self-assemble into long fibers upon protonation in an acidic environment. Despite extensive investigation of these materials’ properties, little is yet understood regarding their reaction kinetics. Based on previous studies, we have chosen DFAG-4T-GAFD as a representative system and conducted molecular dynamics simulations to show that although large-scale assembly is induced by lowering pH, some degree of assembly is thermodynamically favorable in high-pH nonprotonating environments. These results are consistent with findings for other systems such as DFAG-OPV-GAFD. The nonprotonated aggregation also appears to be concentration dependent, occurring at concentrations of 100 nM and above. Single molecule measurements using fluorescence correlation spectroscopy provide experimental support for these computational predictions. We find evidence of spontaneous aggregation in aqueous solutions of peptides with concentrations as low as 100 nM; however, 10 nM solutions appear to be largely homogeneous solutions of unassembled monomer. These results indicate that the simplest explanations for kinetics of acid-mediated assemblyprotonation-induced nucleation by monomeric addition followed by subsequent stages of aggregation and elongationare inappropriate in this system. In fact, the system only exists as pure monomer in very low concentrations, nucleation actually occurs in the absence of protonating elements at concentrations typically used for experiments, and pH triggered assembly proceeds from these preassembled aggregates. Accordingly, triggered assembly must be considered to operate outside the domain of nucleation-dependent models

Compressed sensing (CS), mutual information (MI), and ensemble classifier predictions of HIV-1 Env positions constituting bnMAb epitopes for PGT 135, 143, and 145.

<p>The experimentally identified positions are defined as those at which alanine point mutations were observed to increase the measured IC₅₀ of the mutant by more than 30-fold relative to that of the wild type JR-CSF. Alanine scans were performed as part of the present work for PGT 143 and 145; data for PGT 121–135 were taken from Ref. <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0080562#pone.0080562-Walker2" target="_blank">[51]</a>.</p><p><i>Footnote</i>: See footnote to <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0080562#pone-0080562-t001" target="_blank">Table 1</a>.</p

Supramolecular Polymorphism: Tunable Electronic Interactions within π‑Conjugated Peptide Nanostructures Dictated by Primary Amino Acid Sequence

We present a systematic study of the photophysical properties of one-dimensional electronically delocalized nanostructures assembled from π-conjugated subunits embedded within oligopeptide backbones. The nature of the excited states within these nanostructures is studied as a function of primary amino acid sequence utilizing steady-state and time-resolved spectroscopies, and their atomistic structure is probed by molecular simulation. Variations introduced into the amino acid side chains at specific residue locations along the molecular peptide backbone lead to pronounced changes in the observed photophysical behavior of the fibrillar structures (spanning H-like excitonic coupling and disordered excimeric coupling) that arise from subtle changes in the π-stacking within them. These results indicate that residue modificationin terms of relative size, solvation properties, and with respect to the distance from the central π-electron coreenables the ability to tune chromophore packing and the resulting photophysics of supramolecular assemblies of π-conjugated bioelectronic materials in a rational and systematic manner

Compressed sensing (CS), mutual information (MI), and ensemble classifier predictions of HIV-1 Env positions constituting bnMAb epitopes for PGT 123, 123, 125, and 126.

<p>The experimentally identified positions are defined as those at which alanine point mutations were observed to increase the measured IC₅₀ of the mutant by more than 30-fold relative to that of the wild type JR-CSF. Alanine scans were performed as part of the present work for PGT 143 and 145; data for PGT 121–135 were taken from Ref. <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0080562#pone.0080562-Walker2" target="_blank">[51]</a>.</p><p><i>Footnote</i>: For each of the ten HIV-1 broadly neutralizing monoclonal antibodies (bnMAb) considered in this study, we report the residues identified by the compressed sensing (CS) classifier, positions identified by the mutual information (MI) classifier, and positions identified by the ensemble classifier (formed by combining the CS and MI predictions) predicted to lie within the bnMAb epitope. The number of residues identified by the CS classifier, <i>n_CS</i>, number of positions identified by the MI classifier, <i>n_MI</i>, number of positions predicted by the ensemble classifier, <i>n_ENS</i>, and number of positions identified by alanine scans, <i>n_EXPT</i>, may differ between bnMAbs.</p