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CENTER FOR THE SCIENCE OF
SYNTHESIS ACROSS SCALES

RESEARCH HIGHLIGHTS

The MoSiC-CGenFF-NTOID simulation package enables high-throughput simulations of peptoids. It is accurate in describing states and transitions at the individual residue level, but can also explain self-assembly and aggregation phenomena.

General-Purpose Peptoid High-Throughput Simulation Package

Semi-supervised learning of imaging data

April 23, 2024
Schematic of the rotationally-invariant semi-supervised variational autoencoder (ss-rVAE, left) and disentanglement of representations for SEM images of gold nanoparticles create a nanoparticle library (right).

Semi-supervised learning of imaging data

Concept and design of protein template (top), that nucleates nano-calcite, which then assembles to form a calcite mesocyrstal (bottom)

Directing Polymorph Specific Calcium Carbonate Formation with De Novo Protein Templates

(A-C) Schematic of angular states (top-panel of A-C) and HS-AFM snapshots (bottom panel of A-C) of protein nanorods in their energetically preferred orientations, corresponding to specific directions of the mineral lattice. (D) Orientational free energy landscape and heat map of relative populations at each angle determined from deep learning analysis of HS-AFM data.

Anomalous Rotational Dynamics of Proteins on Surfaces

(A) When the far-field polarization response of water obtained from molecular simulations of mica and the synthetic protein DHR10-mica6 each in isolation are adjoined, the induced pressure between them can be predicted. Exchanging KCl for NaCl results in a sign change in the interaction. (B,C) Assembly of the engineered protein C98RhuA on mica differs dramatically when KCl (left) and NaCl (right) are used.

Protein Assembly on Surfaces Reflects Intrinsic Ion-Specific Solvent Response to the Surface

Ziatdinov et al Highlight Graphic_Deep M

Deep Machine Learning for Quantifying Protein Dynamics from High-Speed Atomic Force Microscopy Data

Hellner et al Highlight Graphic_Peptide

Uncovering Relationships Between Peptide Sequence, Structure, and Inorganic Adhesion Behavior

The structures of RhuA nanotubes (left) and the embedded b-cyclodextrin and azobenzene host-guest interactions were determined by cryo-electron microscopy and solution X-ray scattering.

Synthetic chemical motifs to build dynamic protein materials

Molecular packing model of peptoid nanohelices (top) with controlled supramolecular chirality (bottom)

Assembling nanohelices with control over chirality

Water's distinct response to substantially similar micas. Images show simulated water density at two different heights above the mica surface.

The Response of Water to Surface Structure is Key to Understanding Protein Self-Assembly on Mica

Top. The assembly of 10 nm silica nanoparticles by a homo-bifunctional silica-binding protein is reversibly controlled by switching the solution pH between 7.5 and 8.5, as demonstrated by DLS (left) and FRET experiments (right).

Bottom. Schematic illustration of the theoretical framework. Silica nanoparticles assembled by proteins in a pH 7.5 solution (left) are depicted by interacting colloidal spheres at the collective scale (middle) with protein-nanoparticle interactions derived from the atomic scale (right).

Predictive Framework for Dynamic Control of Protein-Nanoparticle Assembly

Ma et al Highlight Graphic_Layered Heter

Layered Heterostructures from Nanoparticle-Mediated Assembly of Protein-Modified Peptoid Nanosheets

Zhao et al Highlight Graphic_Mesoscale M

Mesoscale Model for Engineered Peptoid Materials

Pyles et al Highlight Graphic_Designer P

Designer Proteins Self-Assemble into Wires and Lattices on Crystal Surfaces

(Top) Fusing the silica-binding Car9 dodecamer to an elastin-ike peptide leads to micelle formation above 45ºC. These micelles template the mineralization of highly monodisperse SiO2 nanoparticles bearing a positive surface charge. (Bottom) These particles allows for facile electrostatic assembly of a variety of superstructures.

Enabling electrostatic fabrication with biomimetic mineralization templates

A polypeptoid molecule (black) that binds more strongly to a silica surface by adopting an extended conformation produces monodisperse silica nanoparticles at much lower concentrations than the peptide it was based upon (red).

Rational Design of Polypeptoids for Silica Mineralization

Conceptual illustration (top) and outcomes (bottom) of the biomimetic mineralization process.

Controlled Mineralization with Protein-Functionalized Peptoid Nanotubes

$Molecular dynamics simulations predict a hierarchical self-assembly pathway of peptoid sheets in evaporation-induced assembly: monomers first assemble disordered aggregates, then 1D helical rods, and finally 2D crystalline sheets. Predictions are supported by experimental observations using x-ray diffraction and atomic force microscopy.$

Hierarchical Self-Assembly Pathways of Peptoid Helices and Sheets

Monahan et al Highlight Graphic_Peptoid

Peptoid-Directed Assembly of CdSe Nanoparticles

Zhang et al Highlight Graphic_Multiple 2

Multiple 2D Materials From a Single, Patchy Protein

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