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. 

Vibrational sum frequency generation (SFG) spectroscopy has been extensively used for obtaining structural information of molecular functional groups at two-dimensional (2D) interfaces buried in the gas or liquid medium. Although the SFG experiment can be done elegantly, interpreting the measured intensity in terms of molecular orientation with respect to the lab coordinate is quite complicated. One of the main reasons is the difficulty of determining the hyperpolarizability tensors of even simple molecules that govern their SFG responses. The single-bond polarizability derivative (SBPD) model has been proposed to estimate the relative magnitude of SFG-active hyperpolarizability by assuming that the perturbation associated to each vibration is negligible. In this study, density functional theory (DFT) was used to calculate the polarizability and dipole derivative tensors of the CH3 stretch mode of CH3I, CH3¬CH2I, CH3OH, CH3¬CH2OH. Then, the hyperpolarizability tensors of symmetric and asymmetric vibration modes were calculated considering the Boltzmann distribution of representative conformers, which allowed theoretical calculation of their SFG intensities at all polarization combinations as a function of the tilt angle of the CH3 group with respect to the surface normal direction. Then the ratios of the calculated SFG intensities for the CH3 peaks used in experimental studies for the CH3 tilt angle determination were compared. This comparison clearly showed the effect of vibrational coupling among neighboring functional groups. This study presents new parameters that can be used in determining the average tilt angle of the CH3 group at the 2D interface with SFG measurements as well as limitations of the method. 

Abstract Single‐stranded DNA (ssDNA) plays a pivotal role in both nanotechnology and various biological processes. Many processes and applications can be better understood with enhanced structural characterization of ssDNA; however, the dynamic nature of the molecule makes accurate characterization with atomistic resolution extremely difficult. This study uses a method that integrates experimental small‐angle X‐ray scatter (SAXS) data and molecular modeling data using a genetic algorithm (GA) to predict an all‐atom conformational ensemble of ssDNA. The results of this study also validate the performance of various AMBER force fields and implicit solvent models for ssDNA. Overall, the results are able to determine the most accurate atomistic representation of poly‐Thymine (polyT) in solution to date that closely matches the experimental SAXS observations enabling a better understanding of the behavior of ssDNA in solution. 

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.