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At least 91 records · Page 5

Controlled cyclization of peptoids to form chiral diketopiperazines

The present disclosure provides improved methods for controlled cyclization of peptoid dimers to form N,N′-2,5-diketopiperazines (N,N′-2,5-DKPs) with significant selectivity. In at least some examples, selectivity is based on a serendipitous conglomeration of slow exchange of amide rotamers, steric repulsion from the degree of α-substitution, and the geometric bulk of an amine nucleophile. By varying reaction conditions, the selectivity of the reaction and formation of a particular N,N′-2,5-DKP can be switched. The cyclization works in the presence of a variety of protection groups and diverse functionalities. The teachings herein provide techniques for synthesizing N,N′-2,5-DKPs that can be readily docked with drug candidates for shuttling across the blood brain barrier. This method provides a facile way to produce substituted DKPs containing groups ready for post-modification to include docking drug candidates.

Williams, Robert F.↗

A high-throughput workflow to analyze sequence-conformation relationships and explore hydrophobic patterning in disordered peptoids

Understanding how a macromolecule’s primary sequence governs its conformational landscape is crucial for elucidating its function, yet these design principles are still emerging for macromolecules with intrinsic disorder. Herein, we introduce a high-throughput workflow that implements a practical colorimetric conformational assay, introduces a semi-automated sequencing protocol using matrix-assisted laser desorption/ionization and tandem mass spectrometry (MALDI-MS/MS), and develops a generalizable sequence-structure algorithm. Using a model system of 20mer peptidomimetics containing polar glycine and hydrophobic N-butylglycine residues, we identified nine classifications of conformational disorder and isolated 122 unique sequences across varied compositions and conformations. Conformational distributions of three compositionally identical library sequences were corroborated through atomistic simulations and ion mobility spectrometry coupled with liquid chromatography. A data-driven strategy was developed using existing sequence variables and data-derived “motifs” to inform a machine-learning algorithm toward conformation prediction. Here, this multifaceted approach enhances our understanding of sequence-conformation relationships and offers a powerful tool for accelerating the discovery of materials with conformational control.

data-driven analysis↗

Atomic-scale cryogenic electron microscopy imaging of self-assembled peptoid nanostructures

Amphiphilic polypeptoids with defined sequences, versatile in forming various nanostructures, are ideal for mimicking biomacromolecular structures. The predictive design of nanostructures depends on our understanding of the relationship between molecular structure and the locations of atoms in the nanostructure. Factors of importance include chain conformation, crystal motifs, and the arrangement of the molecules within the nanostructure. Here, this review introduces the cryogenic transmission electron microscopy (cryo-TEM) method, sorting and averaging unit cells in nanosheets for resolution enhancement and identifying structural heterogeneity. The resulting atomic-scale images reveal the presence of two types of crystal motifs. The impact of processing conditions, capping group chemistry, and side chain chemistry on structural heterogeneity and crystal motifs can be quantified. The 3D reconstruction of nanosheets, wherein atomic-scale corrugations were revealed, is introduced in this review. New developments in cryo-TEM, such as phase retrieval reconstruction, hold great promise for atomic-scale imaging of soft nanostructures.

36 MATERIALS SCIENCE↗