Programmable Assembly of Iron Oxide Nanoparticles Using DNA Origami.

Magnetic iron oxide nanoparticles (IONPs) have received significant interest for the use in biomedical applications. The assembly of IONPs into larger superstructures has been used to modify the properties and functionality of these particles. For example, the clustering of IONPs can lead to improvements in MRI contrast generation, changes in heat generation during magnetic fluid hyperthermia, and alterations to pharmacokinetics and biodistribution. Nevertheless, the IONP clustering leads to significant heterogeneity in the assembly. Here, we demonstrate a method for using DNA origami to precisely control the number and positions of IONPs. We also showed how this technique can be used to module the functionality of IONP clusters by showing how MRI contrast generation efficiency can be tuned by altering the number and spacing of IONPs. Finally, we show that these property changes can be dynamically regulated, demonstrating the possibility for this technology to be used in biosensing applications.

Tunable DNA Origami Motors Translocate Ballistically Over µm Distances at nm/s Speeds.

Inspired by biological motor proteins, that efficiently convert chemical fuel to unidirectional motion, there has been considerable interest in developing synthetic analogues. Among the synthetic motors created thus far, DNA motors that undertake discrete steps on RNA tracks have shown the greatest promise. Nonetheless, DNA nanomotors lack intrinsic directionality, are low speed and take a limited number of steps prior to stalling or dissociation. Herein, we report the first example of a highly tunable DNA origami motor that moves linearly over micron distances at an average speed of 40 nm/min. Importantly, nanomotors move unidirectionally without intervention through an external force field or a patterned track. Because DNA origami enables precise testing of nanoscale structure-function relationships, we were able to experimentally study the role of motor shape, chassis flexibility, leg distribution, and total number of legs in tuning performance. An anisotropic rigid chassis coupled with a high density of legs maximizes nanomotor speed and endurance.

Structurally Ordered Nanowire Formation from Co-Assembly of DNA Origami and Collagen-Mimetic Peptides.

We describe the co-assembly of two different building units: collagen-mimetic peptides and DNA origami. Two peptides CP++ and sCP++ are designed with a sequence comprising a central block (Pro-Hyp-Gly) and two positively charged domains (Pro-Arg-Gly) at both N- and C-termini. Co-assembly of peptides and DNA origami two-layer (TL) nanosheets affords the formation of one-dimensional nanowires with repeating periodicity of ∼10 nm. Structural analyses suggest a face-to-face stacking of DNA nanosheets with peptides aligned perpendicularly to the sheet surfaces. We demonstrate the potential of selective peptide-DNA association between face-to-face and edge-to-edge packing by tailoring the size of DNA nanostructures. This study presents an attractive strategy to create hybrid biomolecular assemblies from peptide- and DNA-based building blocks that takes advantage of the intrinsic chemical and physical properties of the respective components to encode structural and, potentially, functional complexity within readily accessible biomimetic materials.

Site-Specific Surface Functionalization of Gold Nanorods Using DNA Origami Clamps.

Precise control over surface functionalities of nanomaterials offers great opportunities for fabricating complex functional nanoarchitectures but still remains challenging. In this work, we successfully developed a novel strategy to modify a gold nanorod (AuNR) with specific surface recognition sites using a DNA origami clamp. AuNRs were encapsulated by the DNA origami through hybridization of single-stranded DNA on the AuNRs and complementary capture strands inside the clamp. Another set of capture strands on the outside of the clamp create the specific recognition sites on the AuNR surface. By means of this strategy, AuNRs were site-specifically modified with gold nanoparticles at the top, middle, and bottom of the surface, respectively, to construct a series of well-defined heterostructures with controlled "chemical valence". Our study greatly expands the utility of DNA origami as a tool for building complex nanoarchitectures and represents a new approach for precise tailoring of nanomaterial surfaces.

A User's Guide to Machine Learning for Polymeric Biomaterials.

The development of novel biomaterials is a challenging process, complicated by a design space with high dimensionality. Requirements for performance in the complex biological environment lead to difficult a priori rational design choices and time-consuming empirical trial-and-error experimentation. Modern data science practices, especially artificial intelligence (AI)/machine learning (ML), offer the promise to help accelerate the identification and testing of next-generation biomaterials. However, it can be a daunting task for biomaterial scientists unfamiliar with modern ML techniques to begin incorporating these useful tools into their development pipeline. This Perspective lays the foundation for a basic understanding of ML while providing a step-by-step guide to new users on how to begin implementing these techniques. A tutorial Python script has been developed walking users through the application of an ML pipeline using data from a real biomaterial design challenge based on group's research. This tutorial provides an opportunity for readers to see and experiment with ML and its syntax in Python. The Google Colab notebook can be easily accessed and copied from the following URL: www.gormleylab.com/MLcolab.

Martini 3 Coarse-Grained Force Field for Carbohydrates.

The Martini 3 force field is a full reparametrization of the Martini coarse-grained model for biomolecular simulations. Due to the improved interaction balance, it allows for a more accurate description of condensed phase systems. In the present work, we develop a consistent strategy to parametrize carbohydrate molecules accurately within the framework of Martini 3. In particular, we develop a canonical mapping scheme which decomposes arbitrarily large carbohydrates into a limited number of fragments. Bead types for these fragments have been assigned by matching physicochemical properties of mono- and disaccharides. In addition, guidelines for assigning bonds, angles, and dihedrals were developed. These guidelines enable a more accurate description of carbohydrate conformations than in the Martini 2 force field. We show that models obtained with this approach are able to accurately reproduce osmotic pressures of carbohydrate water solutions. Furthermore, we provide evidence that the model differentiates correctly the solubility of the polyglucoses dextran (water-soluble) and cellulose (water insoluble but soluble in ionic liquids). Finally, we demonstrate that the new building blocks can be applied to glycolipids. We show they are able to reproduce membrane properties and induce binding of peripheral membrane proteins. These test cases demonstrate the validity and transferability of our approach.

Automation and data-driven design of polymer therapeutics.

Polymers are uniquely suited for drug delivery and biomaterial applications due to tunable structural parameters such as length, composition, architecture, and valency. To facilitate designs, researchers may explore combinatorial libraries in a high throughput fashion to correlate structure to function. However, traditional polymerization reactions including controlled living radical polymerization (CLRP) and ring-opening polymerization (ROP) require inert reaction conditions and extensive expertise to implement. With the advent of air-tolerance and automation, several polymerization techniques are now compatible with well plates and can be carried out at the benchtop, making high throughput synthesis and high throughput screening (HTS) possible. To avoid HTS pitfalls often described as "fishing expeditions," it is crucial to employ intelligent and big data approaches to maximize experimental efficiency. This is where the disruptive technologies of machine learning (ML) and artificial intelligence (AI) will likely play a role. In fact, ML and AI are already impacting small molecule drug discovery and showing signs of emerging in drug delivery. In this review, we present state-of-the-art research in drug delivery, gene delivery, antimicrobial polymers, and bioactive polymers alongside data-driven developments in drug design and organic synthesis. From this insight, important lessons are revealed for the polymer therapeutics community including the value of a closed loop design-build-test-learn workflow. This is an exciting time as researchers will gain the ability to fully explore the polymer structural landscape and establish quantitative structure-property relationships (QSPRs) with biological significance.

Purification Techniques for Three-Dimensional DNA Nanostructures.

Separation of self-assembled three-dimensional nanostructures from excess staple strands, misfolded structures, or unattached functional elements is critical for downstream applications. Numerous purification techniques exist, with varying yields, purities, and hetero-element compatibilities. In this chapter, we focus on three such techniques-agarose gel electrophoresis, ultrafiltration, and polymeric bead pull-down-which together satisfy requirements for a range of applications.

Controlling Iron Oxide Nanoparticle Clustering Using Dual Solvent Exchange Coating Method.

Superparamagnetic iron oxide nanoparticles (SPIOs) have considerable promise for magnetic resonance imaging, drug/gene delivery, and hyperthermia applications. It has been shown recently that self-assembly of SPIOs into large superstructures can have a significant impact on their magnetic properties and functionality. In this work, we developed a novel method for controlling the clustering of SPIOs with two different core sizes (8 nm and 15 nm) by varying the amount of amphiphilic coating molecules used during the dual solvent exchange coating process. We show that hydrodynamic size and T2 relaxivity can be increased using this approach, while the specific absorption rate is decreased. These results demonstrate a new, simple method for triggering the self-assembly of SPIO clusters using commercially available and biocompatible phospholipid-poly(ethylene glycol) conjugates.

Poly(PS-b-DMA) micelles for reactive oxygen species triggered drug release.

A new micelle drug carrier that consists of a diblock polymer of propylene sulfide (PS) and N,N-dimethylacrylamide (poly(PS74-b-DMA310)) has been synthesized and characterized for site-specific release of hydrophobic drugs to sites of inflammation. Propylene sulfide was first polymerized using a thioacyl group transfer (TAGT) method with the RAFT chain transfer agent (CTA) 4-cyano-4-(ethylsulfanylthiocarbonylsulfanyl) pentanoic acid (CEP), and the resultant poly(PS74-CEP) macro-CTA was used to polymerize a second polymer block of DMA using reversible addition-fragmentation chain transfer (RAFT). The formation of the poly(PS74-b-DMA310) diblock polymer was confirmed by ¹H NMR spectra and gel permeation chromatography (GPC). Poly(PS74-b-DMA310) formed 100 nm micelles in aqueous media as confirmed by dynamic light scattering (DLS) and transmission electron microscopy (TEM). Micelles loaded with the model drugs Nile red and DiO were used to demonstrate the ROS-dependent drug release mechanism of these micelles following treatment with hydrogen peroxide (H2O2), 3-morpholinosydnonimine (SIN-1), and peroxynitrite. These oxidants were found to oxidize the micelle PPS core, making it more hydrophilic and triggering micelle disassembly and cargo release. Delivery of poly(PS74-b-DMA310) micelles dual-loaded with the Förster Resonance Energy Transfer (FRET) fluorophore pair DiI and DiO was used to prove that endogenous oxidants generated by lipopolysaccharide (LPS)-treated RAW 264.7 macrophages significantly increased release of nanocarrier contents relative to macrophages that were not activated. In vitro studies also demonstrated that the poly(PS74-b-DMA310) micelles were cytocompatible across a broad range of concentrations. These combined data suggest that the poly(PS74-b-DMA310) micelles synthesized using a combination of TAGT and RAFT have significant potential for site-specific drug delivery to tissues with high levels of oxidative stress.