Computational Design of Oligopeptide Containing Poly(ethylene glycol) Brushes for Stimuli-Responsive Drug Delivery

Stimuli-responsive biomaterials are used to facilitate drug and gene delivery by shielding the drug/gene during circulation times and selectively releasing the cargo at the desired target. Within stimuli-responsive materials, pH-responsive materials are exploited for delivery to specific organs, intracellular compartments, cancer cells, site of inflammation or infection as those sites are characterized by pH that is different from the blood pH. In this paper we use molecular dynamics (MD) simulations to design such pH-responsive biomaterials where the balance between the various intermolecular interactions (e.g., electrostatics, van der Waals) within the biomaterials allow biofunctional molecules to be reversibly shielded and exposed to the environment with change in pH. In our model the shielding aspect is imparted by a polyethylene glycol (PEG) brush and the pH-responsive component is a PEG-tethered oligopeptide that undergoes changes in conformations via protonation of residues upon changes in pH. Starting with a PEG-tethered peptide in a monodisperse short PEG brush, we first vary the composition and sequence of histidine (H), lysine (K), and glutamate (E) along the oligopeptide sequence to find the design parameters that maximize the shielding and exposure of the oligopeptide at pH ∼ 7.0 and pH < 7.0, respectively. Then, we probe the effect of the PEG brush on the conformations of the oligopeptides by simulating PEG-tethered peptide in a bimodal PEG brush containing short PEG and long PEG chains. We characterize the intermolecular interactions involving the PEG, peptide, and solvent that influence the shielded and exposed conformations of the oligopeptides at the two different pHs. In a short monodisperse PEG brush, with a longer PEG-tethered peptide containing large blocks of histidines that undergo change in protonation state as a response to pH change, placed between a protonated lysine and deprotonated glutamate, the PEG brush exhibits maximum shielding and exposure with pH change. This change from shielded to exposed state is driven by electrostatic repulsion upon H protonation. The presence of long PEG chains in a bimodal PEG brush leads to dominating PEG–peptide attractive interactions that reduces the contrast in shielded and exposed conformations of the PEG-tethered peptide upon protonation of histidines

Hybrid Atomistic and Coarse-Grained Molecular Dynamics Simulations of Polyethylene Glycol (PEG) in Explicit Water

<i>In-silico</i> design of polymeric biomaterials requires molecular dynamics (MD) simulations that retain essential atomistic/molecular details (e.g., explicit water around the biofunctional macromolecule) while simultaneously achieving large length and time scales pertinent to macroscale function. Such large-scale atomistically detailed macromolecular MD simulations with explicit solvent representation are computationally expensive. One way to overcome this limitation is to use an adaptive resolution scheme (AdResS) in which the explicit solvent molecules dynamically adopt either atomistic or coarse-grained resolution depending on their location (e.g., near or far from the macromolecule) in the system. In this study we present the feasibility and the limitations of AdResS methodology for studying polyethylene glycol (PEG) in adaptive resolution water, for varying PEG length and architecture. We first validate the AdResS methodology for such systems, by comparing PEG and solvent structure with that from all-atom simulations. We elucidate the role of the atomistic zone size and the need for calculating thermodynamic force correction within this AdResS approach to correctly reproduce the structure of PEG and water. Lastly, by varying the PEG length and architecture, we study the hydration of PEG, and the effect of PEG architectures on the structural properties of water. Changing the architecture of PEG from linear to multiarm star, we observe reduction in the solvent accessible surface area of the PEG, and an increase in the order of water molecules in the hydration shells

Effects of Polymer Conjugation on Hybridization Thermodynamics of Oligonucleic Acids

In this work, we perform coarse-grained (CG) and atomistic simulations to study the effects of polymer conjugation on hybridization/melting thermodynamics of oligonucleic acids (ONAs). We present coarse-grained Langevin molecular dynamics simulations (CG-NVT) to assess the effects of the polymer flexibility, length, and architecture on hybridization/melting of ONAs with different ONA duplex sequences, backbone chemistry, and duplex concentration. In these CG-NVT simulations, we use our recently developed CG model of ONAs in implicit solvent, and treat the conjugated polymer as a CG chain with purely repulsive Weeks–Chandler–Andersen interactions with all other species in the system. We find that 8–100-mer linear polymer conjugation destabilizes 8-mer ONA duplexes with weaker Watson–Crick hydrogen bonding (WC H-bonding) interactions at low duplex concentrations, while the same polymer conjugation has an insignificant impact on 8-mer ONA duplexes with stronger WC H-bonding. To ensure the configurational space is sampled properly in the CG-NVT simulations, we also perform CG well-tempered metadynamics simulations (CG-NVT-MetaD) and analyze the free energy landscape of ONA hybridization for a select few systems. We demonstrate that CG-NVT-MetaD simulation results are consistent with the CG-NVT simulations for the studied systems. To examine the limitations of coarse-graining in capturing ONA–polymer interactions, we perform atomistic parallel tempering metadynamics simulations at well-tempered ensemble (AA-MetaD) for a 4-mer DNA in explicit water with and without conjugation to 8-mer poly­(ethylene glycol) (PEG). AA-MetaD simulations also show that, for a short DNA duplex at <i>T</i> = 300 K, a condition where the DNA duplex is unstable, conjugation with PEG further destabilizes DNA duplex. We conclude with a comparison of results from these three different types of simulations and discuss their limitations and strengths

Development of a Coarse-Grained Model of Collagen-Like Peptide (CLP) for Studies of CLP Triple Helix Melting

In this paper, we present the development of a phenomenological coarse-grained model that represents single strands of collagen-like peptides (CLPs) as well as CLP triple helices. The goal of this model development is to enable coarse-grained molecular simulations of solutions of CLPs and conjugates of CLPs with other macromolecules and to predict trends in the CLP melting temperature with varying CLP design, namely CLP length and composition. Since the CLP triple helix is stabilized primarily by hydrogen bonds between amino acids in adjacent strands, for modeling CLP melting we get inspiration from a recent coarse-grained (CG) model that was used to capture specific and directional hydrogen-bonding interactions in base-pair hybridization within oligonucleotides and reproduced known DNA melting trends with DNA sequence and composition in implicit water. In this paper, we systematically describe the changes we make to this original CG model and then show that these improvements reproduce the known melting trends of CLPs seen in past experiments. Specifically, the CG simulations of CLP solutions at experimentally relevant concentrations show increasing melting temperature with increasing CLP length and decreasing melting temperature with incorporation of charged residues in place of uncharged residues in the CLP, in agreement with past experimental observations. Finally, results from simulations of CLP triple helices conjugated with elastin like peptides (ELPs), using this new CG model of CLP, reproduce the same trends in ELP aggregation as seen in past experiments

Using Theory and Simulations To Calculate Effective Interactions in Polymer Nanocomposites with Polymer-Grafted Nanoparticles

Using theory and large-scale simulations, we demonstrate how one can program structure and thermodynamics into polymer-grafted particles filled polymer nanocomposites (PNCs). We simulate varying graft (G) and matrix (M) polymer compositions for varying model graft–matrix bead pairwise interactions, χ_GM, and calculate structural features and the effective graft–matrix interaction parameter, χ_GM^eff, in the PNC. Varying the graft (G) and matrix (M) polymer compositions provides tunability of morphology (particle dispersion/aggregation) and graft–matrix interpenetration at each χ_GM. Thermodynamically, for all composites the χ_GM^eff exhibits negative values (effective attraction) at low values of χ_GM, with a sharp transition to positive values (effective repulsion) at large values of χ_GM. The sharp transition in χ_GM^eff coincides with the structurally characterized particle dispersion–aggregation transition marked by the onset of upturn in the matrix–matrix structure factor at zero wavenumber. Strikingly, regardless of the composition of the graft and matrix chains or the dispersion–aggregation transition point, universally, the effective interactions in the PNC at the dispersion–aggregation transition is identical to the analogous athermal PNC

Coarse-Grained Simulation Studies of Effects of Polycation Architecture on Structure of the Polycation and Polycation–Polyanion Complexes

Polycations are a promising class of nonviral DNA delivery agents that bind to negatively charged DNA and transfect the DNA into target cells. The architecture and chemistry of the polycation strongly affect polycation–DNA complexation and in turn the ability of polycations to transfect DNA into cells. Here we develop coarse-grained models and conduct Langevin dynamics simulations to understand how the architecture of lysine-based polycations affects their complexation with DNA-like polyanions. We first characterize the structure of linear polylysine and oligolysines grafted to a polyolefin backbone and then the structure of complexes (termed polyplexes) formed by these polycations with polyanions of varying flexibility. We find that increasing oligolysine graft length and decreasing graft spacing both increase the size and rigidity of the grafted oligolysines, although they remain less rigid than semiflexible linear polylysine. Increasing ionic strength or counterion valency reduces polycation size and most architecture-dependent effects. The effects of polycation architecture on polyplex size and flexibility are dependent on the charge ratio in the system. Polyplex surface charge increases with increasing graft length or decreasing graft spacing

Assembly of Amphiphilic Block Copolymers and Nanoparticles in Solution: Coarse-Grained Molecular Simulation Study

Controlled assembly of amphiphilic block copolymers (BCPs) and inorganic nanoparticles (NPs) into hybrid materials is desirable for a broad range of applications such as biological or nonbiological cargo delivery, imaging contrast agents, pollutant capture, chemical sensing, and separation/purification applications. There has been growing interest in changing solvent quality for BCPs by mixing solvents and utilizing the effective solvophobicity of the BCP block(s) to tailor the assembled structure, namely the size and shape, composition, and spatial arrangement of the components in the NP–BCP hybrid assemblies. In this work, we present a comprehensive coarse-grained molecular dynamics (MD) simulations study exploring the impact of varying solvophobicity on assembly of amphiphilic BCP and NP as a function of BCP composition and sequence and NP affinity to either or both block(s) of BCP. We quantify the solvophobicity marking the transition from disassembled solution to assembled state (e.g., micelles). We also quantify and visualize, as a function of varying solvophobicity, the shape and size of assembled structures with and without NPs, the amount of NP uptake, and the spatial arrangement of the NPs in the assembled NP–BCP structure

Understanding Self-Assembly and Molecular Packing in Methylcellulose Aqueous Solutions Using Multiscale Modeling and Simulations

We present a multiscale molecular dynamics (MD) simulation study on self-assembly in methylcellulose (MC) aqueous solutions. First, using MD simulations with a new coarse-grained (CG) model of MC chains in implicit water, we establish how the MC chains self-assemble to form fibrils and fibrillar networks and elucidate the MC chains’ packing within the assembled fibrils. The CG model for MC is extended from a previously developed model for unsubstituted cellulose and captures the directionality of H-bonding interactions between the –OH groups. The choice and placement of the CG beads within each monomer facilitates explicit modeling of the exact degree and position of methoxy substitutions in the monomers along the MC chain. CG MD simulations show that with increasing hydrophobic effect and/or increasing H-bonding strength, the commercial MC chains (with degree of methoxy substitution, DS, ∼1.8) assemble from a random dispersed configuration into fibrils. The assembled fibrils exhibit consistent fibril diameters regardless of the molecular weight and concentration of MC chains, in agreement with past experiments. Most MC chains’ axes are aligned with the fibril axis, and some MC chains exhibit twisted conformations in the fibril. To understand the molecular driving force for the twist, we conduct atomistic simulations of MC chains preassembled in fibrils (without any chain twists) in explicit water at 300 and 348 K. These atomistic simulations also show that at DS = 1.8, MC chains adopt twisted conformations, with these twists being more prominent at higher temperatures, likely as a result of shielding of hydrophobic methyl groups from water. For MC chains with varying DS, at 348 K, atomistic simulations show a nonmonotonic effect of DS on water-monomer contacts. For 0.0 < DS < 0.6, the MC monomers have more water contacts than at DS = 0.0 or DS > 0.6, suggesting that with few methoxy substitutions, the MC chains are effectively hydrophilic, letting the water molecules diffuse into the fibril to participate in H-bonds with the MC chains’ remaining –OH groups. At DS > 0.6, the MC monomers become increasingly hydrophobic, as seen by decreasing water contacts around each monomer. We conclude based on the atomistic observations that MC chains with lower degrees of substitutions (DS ≤ 0.6) should exhibit solubility in water over broader temperature ranges than DS ∼ 1.8 chains

Molecular simulation study of assembly of DNA-grafted nanoparticles: effect of bidispersity in DNA strand length

<div><p>In this paper, we use molecular dynamics simulations to study the assembly of DNA-grafted nanoparticles to demonstrate specifically the effect of bidispersity in grafted DNA strand length on the thermodynamics and structure of nanoparticle assembly at varying number of grafted single-stranded DNA (ssDNA) strands and number of guanine/cytosine (G/C) bases per strand. At constant number of grafted ssDNA strands and G/C nucleotides per strand, as bidispersity in strand lengths increases, the number of nanoparticles that assemble as well as the number of neighbours per particle in the assembled cluster increases. When the number of G/C nucleotides per strand in short and long strands is equal, the long strands hybridise with the other long strands with higher frequency than the short strands hybridise with short/long strands. This dominance of the long strands leads to bidisperse systems having similar thermodynamics to that in corresponding systems with monodisperse long strands. Structurally, however, as a result of long–long, long–short and short–short strand hybridisation, bidispersity in DNA strand length leads to a broader inter-particle distance distribution within the assembled cluster than seen in systems with monodisperse short or monodisperse long strands. The effect of increasing the number of G/C bases per strand or increasing the number of grafted DNA strands on the thermodynamics of assembly is similar for bidisperse and monodisperse systems. The effect of increasing the number of grafted ssDNA strands on the structure of the assembled cluster is dependent on the extent of strand bidispersity because the presence of significantly shorter ssDNA strands among long ssDNA strands reduces the crowding among the strands at high grafting density. This relief in crowding leads to larger number of strands hybridised and as a result larger coordination number in the assembled cluster in systems with high bidispersity in strands than in corresponding monodisperse or low bidispersity systems.</p></div

Controlling the Morphology of Model Conjugated Thiophene Oligomers through Alkyl Side Chain Length, Placement, and Interactions

We have performed coarse-grained molecular dynamics simulations of thiophene-based conjugated oligomers to elucidate how the oligomer architecture, specifically the orientation and density of alkyl side chains extending from the thiophene backbones, impacts the order–disorder temperatures and the various ordered morphologies that the oligomers form. We find that the orientation of side chains along the oligomer backbone plays a more significant role than side chain density, side chain–side chain interactions, or side chain length in determining the thermodynamically stable morphologies and the phase transition temperatures. Oligomers with side chains oriented on both sides of the backbone (“<i>anti</i>”) form lamellae, while oligomers with side chains oriented on one side of the backbone (“<i>syn</i>”) assemble into hexagonally packed cylinders that can undergo a second, lower temperature transition to lamellae or ribbons depending on side chain–side chain interaction strength. The strength of side chain–side chain interactions affects the order–disorder temperature, with oligomers having moderately attractive side chains exhibiting higher transition temperatures than those with weakly attractive side chains. Side chain length modulates the spacing between morphological features, such as cylinders and lamellae, and affects the order–disorder temperature differently depending on oligomer architecture