Session F49: Biomaterials 4: Structure, Function, Design

Bioinspired Nanomaterials: from Clay and Graphene Composites to Chiral Nanostructures.

Nanometer scale particle of inorganic materials enable scalable manufacturing of materials and devices using self-assembly. This technological property originates from (a) Brownian mobility; (b) intrinsic anisotropy; and (c) charge transport functionalities characteristic of nanoscale building blocks from metals and semiconductors. Formation of nanocomposites with ordered layered architectures from graphene, its oxides, ceramics, and other materials forming nanoplatelets using layer-by-layer assembly (LBL) provide vivid examples of self-organization that led to marked technological advancements. Self-assembly of anisotropic platelet-like nanoparticles of clay and graphene afford large scale manufacturing of high performance composites for different applications.
Recent findings show that engineering of the interparticle forces between nanoparticles make possible self-organization into complex superstructures without templates of pattern-guiding biological ligands of high molecular weight. Remarkably, their geometrical and functional complexity can rival those found in biology which reflects the biomimetic behavior of nanoscale inorganic matter. The new opportunities in nano-manufacturing based on the complex self-assembled nanostructures will be demonstrated using chiral nanomaterials that can lead to new optoelectronic devices.
  

Nanostructured substrates for multi-cue Investigations of Single Cells

Cellular adhesion and migration are crucial aspects of many physiological functions which depend on the integration of numerous signaling inputs generated by chemical and physical properties of the substrate. Typically, these chemical/physical parameters are investigated individually, making it difficult to predict how their interdependencies modify the adhesion and migratory process. Furthermore, these cues rarely exist in orderd isotropic patterns that fabrication techniques produce, but rather are present in stochastic gradients in vivo. To address this, we have employed a combination of nano/micro-lithography in conjunction with etching techniques to fabricate substrates which expose individual cells to tightly controlled topographical and chemical cues. Nanolithography is employed to pattern gold nanodots atop a quartz substrate, while selective etching creates nanopillars. Ligand density is tuned by varying the nanodot/pillar pitch and using thiol chemistry techniques for biofunctionalization. Furthermore this experimental platform design enables incorporating nanostructure density gradients to better mimic in vivo multi-cue environments. The approach was validated by imaging individual A549 cells as they simultaneously adhered to distinct biofunctionalized topographies.   

Primary structure, thermodynamics, and function of self-assembled π-conjugated oligopeptides

Engineered self-assembling peptides offer a promising approach for the fabrication of novel macromolecular materials with applications as far reaching as drug delivery, antimicrobials, and regenerative medicine. Synthetic oligopeptides containing embedded π-conjugated subunits have been demonstrated to assemble β-sheet-like 1D ribbons with electronic and photophysical functionality, making them promising candidates as biocompatible organic electronics. An in-depth understanding of the relationship between peptide chemistry, molecular thermodynamics, and photophysical function of peptide aggregates can enable rational design of peptides tailored to specific applications. In this work, we conduct atomistic molecular simulations of assembly for an ensemble of peptide chemistries and use these data to train and validate a quantitative structure-property relationship (QSPR) relating peptide sequence to structural alignment and photophysical function. We use the QSPR model to perform high-throughput traversal of peptide sequence space to identify and test promising candidates for experimental fabrication.   

The impact of additives on crystallization of amorphous CaCO3

Amorphous calcium carbonate (ACC) serves as a precursor to crystalline biominerals. Both inorganic and organic additives dramatically impact its formation and transformation, but these processes have largely been the subject of bulk assays while direct observations are lacking. Here we report in situ TEM experiments on the effects of Mg, citrate and poly-acrylate (PAA) on the ACC-to-crystal transformation. For citrate, PAA and ≤ 2.5 mM Mg, we find dissolution/re-precipitation dominates, with each additive extending the ACC lifetime and/or timescale for dissolution, but the final crystals exhibit expected morphologies. In contrast, for Mg ≥ 5 mM, transformation occurs in the absence of a morphological change to give spheroidal Mg-calcite and is accompanied by loss of structural water seen both via an increase in electron density and changes in Raman spectra. TGA shows Mg brings excess water into ACC and molecular dynamics simulations predict this promotes atomic rearrangement. We hypothesize that slow dehydration coupled with ease of reorganization enables the isomorphic conversion and may explain why Mg is a common impurity in biominerals, as its presence would allow ACC to be moulded into complex shapes and maintain those shapes while transforming into a crystalline polymorph.   

Calculating the Structure of Isoxanthopterin Crystals, Efficient Reflectors in the Crustacean Eyes

Shrimp, crayfish and lobsters possess a reflection superposition compound eye, which operates by reflective optics and is suited to vision in dim-light conditions.
The reflector units in the eye are made of millions of crystals of isoxanthopterin, a previously unknown biocrystal. We report here the determination of the crystal structure of isoxanthopterin using first principles calculations based on dispersion-inclusive density functional theory. In a manner akin to the generation of the H-bonded layer and 3D arrangement of the biogenic photonic crystals of guanine, we constructed an H-bonded planar layer of isoxanthopterin molecules, followed by generation of various interlayer motifs, via monoclinic and orthorhombic symmetries. Geometry optimization yielded an isoxanthopterin crystal structure with orthorhombic Cmce symmetry, which gave an excellent fit to the experimental X-ray measurements. The resulting refractive index, calculated from the structure, is very high (n=2.0), explaining why this material functions as an efficient reflector.   

A Coarse-grained Minimal Model for the Hierarchical Self-assembly of Biocompatible Optoelectronic Nanostructures

Self-assembling peptides containing aromatic groups are attractive targets for bioelectronic materials design due to their ease of manufacture, biocompatibility, aqueous solubility, and controllability of side chain chemistry. Microscopic understanding of the properties that control assembly is a prerequisite for rational design. In this work, we employ a patchy particle model to efficiently traverse the parameter space of interactions. We study the effects of side chain and aromatic group interaction strength and side chain steric constraints on peptide assembly kinetics and thermodynamics. We characterize the growth rate of different cluster types and the fractal dimension of the final aggregates to identify parameters that lead to rapid growth of linear aggregates with interacting aromatic cores. Using these parameters, we identify sequence-defined candidate peptides for high-resolution computational and experimental testing. Our work leads to greater understanding of the parameters controlling aggregation and demonstrates a method for identification of candidate chemistries to assemble hierarchical nanostructures with desirable optoelectronic properties.   

Toward de novo design of bioadhesives with classical DFT and genetic algorithm

Sea animals like mussel and the sandcastle worm can adhere to wet surfaces by using a collection of flexible proteins. A good understanding of these adhesives may result in novel concepts (viz. biomimicry) to solve the need for improved adhesives that can function well in water. Current research into bioadhesive materials is mostly focused on identifying the amino acid sequence of polypeptides and understanding their contribution towards the overall adhesion strength. A sequence specific coarse-grained model can capture important parameters include electrostatic charge, chain length, ordering, and various modifications of the natural amino acids (e.g., from tyrosine to Dopa). By integrating the classical density functional theory (DFT) and machine-learning strategies and generic algorithms, we investigate the bioadhesive behavior of polypeptides under various environmental conditions and validate the theoretical results with known experimental data. The combination of molecular modeling with machine-learning strategies allows us to sample the polypeptide sequence and identify conditions leading to the maximum adhesive strengths.   

Hidden Complexity of Synergistic Roles of Dopa and Lysine for Strong Wet Adhesion

Dopa and lysine are widely found in mussel foot proteins and are suggested to provide synergistic roles for wet adhesion; yet, the detailed molecular mechanism remains unclear. Here, combining single molecule force spectroscopy and ensemble measurements, we found that the neighboring lysine can significantly enhance surface binding of Dopa through three distinct mechanisms: 1) Displacing surface water and ion to increase the effective binding sites; 2) Being directly involved in cooperative surface binding in a sequence dependent manner; 3) Enhancing cohesion by Michael addition to oxidized species or forming cation-p interactions. This study may be helpful for rational design of biomimetic strong adhesives for biomedical applications.   

Modeling Adsorption Based Filters and the Bio-remediation of Heavy Metal Contaminated Water

I will discuss kinetic models of adsorption, as well as our mathematical models of such filters. These mathematical models have been developed in support of our interdisciplinary lab group. Our group conducts research into bio-remediation of heavy metal contaminated water via filtration. The filters are constructed out of biomass, such as spent tea leaves. The spent tea leaves are available in large quantities as a result of the industrial production of tea beverages. The heavy metals bond with the surfaces of the tea leaves (adsorption). I will compare the models' predictions to data obtained from computer simulations and experimentally by our lab group.