Search for: All records

Diblock oligomeric peptide–polymer amphiphiles (PPAs) are biohybrid materials that offer versatile functionality by integrating the sequence-dependent properties of peptides with the synthetic versatility of polymers. Despite their potential as biocompatible materials, the rational design of PPAs for assembly into multichain nanoparticles remains challenging due to the complex intra- and intermolecular interactions emanating from the polymer and peptide segments. To systematically explore the impact of monomer composition on nanoparticle assembly, PPAs were synthesized with a random coil peptide (XTEN2) and oligomeric alkyl acrylates with different side chains: ethyl, tert-butyl, n-butyl, and cyclohexyl. Experimental characterization using electron and atomic force microscopies demonstrated that the tail hydrophobicity impacted accessible morphologies. Moreover, the characterization of different assembly protocols (i.e., bath sonication and thermal annealing) revealed that certain tail compositions provide access to kinetically trapped assemblies. All-atom molecular dynamics simulations of micelle formation unveiled key interactions and differences in core hydration, dictating the PPA assembly behavior. These findings highlight the complexity of PPA assembly dynamics and serve as valuable benchmarks to guide the design of PPAs for a variety of applications, including catalysis, mineralization, targeted sequestration, antimicrobial activity, and cargo transportation. 

Adsorbents featuring high-affinity phosphate-binding proteins (PBPs) have demonstrated highly selective and rapid phosphorus removal and recovery. 

Knowledge graphs (KGs), with their flexible encoding of heterogeneous data, have been increasingly used in a variety of applications. At the same time, domain data are routinely stored in formats such as spreadsheets, text, or figures. Storing such data in KGs can open the door to more complex types of analytics, which might not be supported by the data sources taken in isolation. Giving domain experts the option to use a predefined automated workflow for integrating heterogeneous data from multiple sources into a single unified KG could significantly alleviate their data-integration time and resource burden, while potentially resulting in higher-quality KG data capable of enabling meaningful rule mining and machine learning.In this paper we introduce a domain-agnostic workflow called BUILD-KG for integrating heterogeneous scientific and experimental data from multiple sources into a single unified KG potentially enabling richer analytics. BUILD-KG is broadly applicable, accepting input data in popular structured and unstructured formats. BUILD-KG is also designed to be carried out with end users as humans-in-the-loop, which makes it domain aware. We present the workflow, report on our experiences with applying it to scientific and experimental data in the materials science domain, and provide suggestions for involving domain scientists in BUILD-KG as humans-in-the-loop. 

RNA-based therapeutics hold a great promise in treating a variety of diseases. However, double-stranded RNAs (dsRNAs) are inherently unstable, highly charged, and stiff macromolecules that require a delivery vehicle. Cationic ligand functionalized gold nanoparticles (AuNPs) are able to compact nucleic acids and assist in RNA delivery. Here, we use large-scale all-atom molecular dynamics simulations to show that correlations between ligand length, metal core size, and ligand excess free volume control the ability of nanoparticles to bend dsRNA far below its persistence length. The analysis of ammonium binding sites showed that longer ligands that bind deep within the major groove did not cause bending. By limiting ligand length and, thus, excess free volume, we have designed nanoparticles with controlled internal binding to RNA's major groove. NPs that are able to induce RNA bending cause a periodic variation in RNA's major groove width. Density functional theory studies on smaller models support large-scale simulations. Our results are expected to have significant implications in packaging of nucleic acids for their applications in nanotechnology and gene delivery.