Diphenylalanine Peptide Nanowires as a Substrate for Neural Cultures

A modular and extensible CHARMM-compatible model for all-atom simulation of polypeptoids

Peptoids (N-substituted glycines) are a class of sequence-defined synthetic peptidomimetic polymers with applications including drug delivery, catalysis, and biomimicry. Classical molecular simulations have been used to predict and understand the conformational dynamics of single chains and their self-assembly into morphologies including sheets, tubes, spheres, and fibrils. The CGenFF-NTOID model based on the CHARMM General Force Field has demonstrated success in accurate all-atom molecular modeling of peptoid structure and thermodynamics. Extension of this force field to new peptoid side chains has historically required reparameterization of side chain bonded interactions against ab initio data. This fitting protocol improves the accuracy of the force field but is also burdensome and precludes modular extensibility of the model to arbitrary peptoid sequences. In this work, we develop and demonstrate a Modular Side Chain CGenFF-NTOID (MoSiC-CGenFF-NTOID) as an extension of CGenFF-NTOID employing a modular decomposition of the peptoid backbone and side chain parameterizations, wherein arbitrary side chains within the large family of substituted methyl groups (i.e., -CH3, -CH2R, -CHRR', and -CRR'R″) are directly ported from CGenFF. We validate this approach against ab initio calculations and experimental data to develop a MoSiC-CGenFF-NTOID model for all 20 natural amino acid side chains along with 13 commonly used synthetic side chains and present an extensible paradigm to efficiently determine whether a novel side chain can be directly incorporated into the model or whether refitting of the CGenFF parameters is warranted. We make the model freely available to the community along with a tool to perform automated initial structure generation.

Vertically Grown Bioinspired Diphenylalanine Nanowire-Coated Fabric for Oil-Water Separation

Due to the pervasive use of oil for energy and other industrial applications, solutions to oil-water separation have received a great deal of attention lately to address the environmental damage of oil spills and groundwater contamination. However, many of these separation methods are materially expensive and environmentally hazardous, require elaborate fabrication, or rely on large amounts of energy to function. Herein, we provide an effective low-cost method for oil-water separation based on the hydrophobicity induced by self-assembled bioinspired diphenylalanine peptide nanowires grown on polyester fabric. This modified polyester fabric mesh exhibits parahydrophobicity and oleophilicity due to the hierarchical nano-to-microscale surface roughness. This mesh also achieves consistent high water separation efficiencies of over 99% and an ultrahigh oil flux of up to 26.7 ± 5 kLm-2·h-1. The growth of bioinspired peptide-based nanostructures on fabrics using facile technique and their application in oil-water separation presents the potential for using bioinspired materials for environmental remediation while minimizing environmental footprint.

Self-Assembling Hydrogel Structures for Neural Tissue Repair

Hydrogel materials have been employed as biological scaffolds for tissue regeneration across a wide range of applications. Their versatility and biomimetic properties make them an optimal choice for treating the complex and delicate milieu of neural tissue damage. Aside from finely tailored hydrogel properties, which aim to mimic healthy physiological tissue, a minimally invasive delivery method is essential to prevent off-target and surgery-related complications. The specific class of injectable hydrogels termed self-assembling peptides (SAPs), provide an ideal combination of in situ polymerization combined with versatility for biofunctionlization, tunable physicochemical properties, and high cytocompatibility. This review identifies design criteria for neural scaffolds based upon key cellular interactions with the neural extracellular matrix (ECM), with emphasis on aspects that are reproducible in a biomaterial environment. Examples of the most recent SAPs and modification methods are presented, with a focus on biological, mechanical, and topographical cues. Furthermore, SAP electrical properties and methods to provide appropriate electrical and electrochemical cues are widely discussed, in light of the endogenous electrical activity of neural tissue as well as the clinical effectiveness of stimulation treatments. Recent applications of SAP materials in neural repair and electrical stimulation therapies are highlighted, identifying research gaps in the field of hydrogels for neural regeneration.

Necessity of regulatory guidelines for the development of amyloid based biomaterials

Amyloid diseases are caused due to protein homeostasis failure where incorrectly folded proteins/peptides form cross-β-sheet rich amyloid fibrillar structures. Besides proteins/peptides, small metabolite assemblies also exhibit amyloid-like features. These structures are linked to several human and animal diseases. In addition, non-toxic amyloids with diverse physiological roles are characterized as a new functional class. This finding, along with the unique properties of amyloid like stability and mechanical strength, led to a surge in the development of amyloid-based biomaterials. However, the usage of these materials by humans and animals may pose a health risk such as the development of amyloid diseases and toxicity. This is possible because amyloid-based biomaterials and their fragments may assist seeding and cross-seeding mechanisms of amyloid formation in the body. This review summarizes the potential uses of amyloids as biomaterials, the concerns regarding their usage, and a prescribed workflow to initiate a regulatory approach.