No abstract

Peptoids (poly-N-substituted glycines) are a class of synthetic polymers that are regioisomers of peptides (poly-C-substituted glycines), in which the point of side-chain connectivity is shifted from the backbone C to the N atom. Peptoids have found diverse applications as peptidomimetic drugs, protein mimetic polymers, surfactants, and catalysts. Computational modeling is valuable in the understanding and design of peptoid-based nanomaterials. In this work, we report the bottom-up parameterization of coarse-grained peptoid force fields based on the MARTINI peptide force field against all-atom peptoid simulation data. Our parameterization pipeline iteratively refits coarse-grained bonded interactions using iterative Boltzmann inversion and nonbonded interactions by matching the potential of mean force for chain extension. We assure good sampling of the amide bond cis/trans isomerizations in the all-atom simulation data using parallel bias metadynamics. We develop coarse-grained models for two representative peptoidspolysarcosine (poly­(N-methyl glycine)) and poly­(N-((4-bromophenyl)­ethyl)­glycine)and show their structural and thermodynamic properties to be in excellent accord with all-atom calculations but up to 25-fold more efficient and compatible with MARTINI force fields. This work establishes a new rigorously parameterized coarse-grained peptoid force field for the understanding and design of peptoid nanomaterials at length and time scales inaccessible to all-atom calculations.

Molecular recognition between peptides and metal oxide surfaces is a fundamental process in biomineralization, self-assembly, and biocompatibility. Yet, the underlying driving forces and dominant mechanisms remain unclear, bringing obstacles to understand and control this process. To elucidate the mechanism of peptide/surface recognition, specifically the role of serine phosphorylation, we employed molecular dynamics simulation and metadynamics-enhanced sampling to study five artificial peptides, DDD, DSS, DpSpS, DpSpSGKK, and DpSKGpSK, interacting with two surfaces: rutile TiO 2 and quartz SiO 2 . On both surfaces, we observe that phosphorylation increases the binding energy. However, the interfacial peptide conformation reveals a distinct binding mechanism on each surface. We also study the impact of peptide sequence to binding free energy and interfacial conformation on both surfaces, specifically the impact on the behavior of phosphorylated serine. Finally, the results are discussed in context of prior studies investigating the role of serine phosphorylation in peptide binding to silica.

Peptoids (N-substituted glycines) are a class of tailorable synthetic peptidomic polymers. Amphiphilic diblock peptoids have been engineered to assemble 2D crystalline lattices with applications in catalysis and molecular separations. Assembly is induced in an organic solvent/water mixture by evaporating the organic phase, but the assembly pathways remain uncharacterized. We conduct all-atom molecular dynamics simulations of Nbrpe6Nc6 as a prototypical amphiphilic diblock peptoid comprising an NH2-capped block of six hydrophobic N-((4-bromophenyl)­ethyl)­glycine residues conjugated to a polar NH3(CH2)5CO tail. We identify a thermodynamically controlled assembly mechanism by which monomers assemble into disordered aggregates that self-order into 1D chiral helical rods then 2D achiral crystalline sheets. We support our computational predictions with experimental observations of 1D rods using small-angle X-ray scattering, circular dichroism, and atomic force microscopy and 2D crystalline sheets using X-ray diffraction and atomic force microscopy. This work establishes a new understanding of hierarchical peptoid assembly and principles for the design of peptoid-based nanomaterials.

Using coarse-grained molecular dynamics simulations, we study ionomers in equilibrium and under uniaxial tensile deformation. The spacing of ions along the chain is varied, allowing us to consider how different ionic aggregate morphologies, from percolated to discrete aggregates, impact the mechanical properties. From the equilibrium simulations, we calculate the stress-stress auto correlation function, showing a distinct deviation from the Rouse relaxation due to ionic associations that depends on ion content. We then quantify the morphology during strain, particularly the degree to which both chains and ionic aggregates tend to align. We also track the location of the ionomer peak in the anisotropic structure factor during strain. The length scale of aggregate order increases in the axial direction and decreases in the transverse direction, in qualitative agreement with prior experimental results.