Martinoid: the peptoid martini force field.

Many exciting innovations have been made in the development of assembling peptoid materials. Typically, these have utilised large oligomeric sequences, though elsewhere the study of peptide self-assembly has yielded numerous examples of assemblers below 6-8 residues in length, evidencing that minimal peptoid assemblers are not only feasible but expected. A productive means of discovering such materials is through the application of in silico screening methods, which often benefit from the use of coarse-grained molecular dynamics (CG-MD) simulations. At the current level of development, CG models for peptoids are insufficient and we have been motivated to develop a Martini forcefield compatible peptoid model. A dual bottom-up and top-down parameterisation approach has been adopted, in keeping with the Martini parameterisation methodology, targeting the reproduction of atomistic MD dynamics and trends in experimentally obtained log D7.4 partition coefficients, respectively. This work has yielded valuable insights into the practicalities of parameterising peptoid monomers. Additionally, we demonstrate that our model can reproduce the experimental observations of two very different peptoid assembly systems, namely peptoid nanosheets and minimal tripeptoid assembly. Further we can simulate the peptoid helix secondary structure relevant for antimicrobial sequences. To be of maximum usefulness to the peptoid research community, we have developed freely available code to generate all requisite simulation files for the application of this model with Gromacs MD software.

Minimal Peptoid Dynamics Inform Self-Assembly Propensity.

Peptoids are structural isomers of natural peptides, with side chain attachment at the amide nitrogen, conferring this class of compounds with the ability to access both cis and trans ω torsions as well as an increased diversity of ψ/φ states with respect to peptides. Sampling within these dimensions is controlled through side chain selection, and an expansive set of viable peptoid residues exists. It has been shown recently that "minimal" di- and tripeptoids with aromatic side chains can self-assemble into highly ordered structures, with size and morphological definition varying as a function of sequence pattern (e.g., XFF and FXF, where X = a nonaromatic peptoid monomer). Aromatic groups, such as phenylalanine, are regularly used in the design of minimal peptide assemblers. In recognition of this, and to draw parallels between these compounds classes, we have developed a series of descriptors for intramolecular dynamics of aromatic side chains to discern whether these dynamics, in a preassembly condition, can be related to experimentally observed nanoscale assemblies. To do this, we have built on the atomistic peptoid force field reported by Weiser and Santiso (CGenFF-WS) through the rigorous fitting of partial charges and the collation of Charmm General Force Field (CGenFF) parameters relevant to these systems. Our study finds that the intramolecular dynamics of side chains, for a given sequence, is dependent on the specific combination of backbone ω torsions and that homogeneity of sampling across these states correlates well with the experimentally observed ability to assemble into nanomorphologies with long-range order. Sequence patterning is also shown to affect sampling, in a manner consistent for both tripeptoids and tripeptides. Additionally, sampling similarities between the nanofiber forming tripeptoid, Nf-Nke-Nf in the cc state, and the nanotube forming dipeptide FF, highlight a structural motif which may be relevant to the emergence of extended linear assemblies. To assess these properties, a variety of computational approaches have been employed.

Solvent-controlled self-assembly of Fmoc protected aliphatic amino acids.

Self-assembly of modified amino acids facilitate the formation of various structures that have unique properties and therefore serve as excellent bio-organic scaffolds for diverse applications. Self-assembly of Fmoc protected single amino acids has attracted great interest owing to their ease of synthesis and applications as functional materials. Smaller assembly units enable synthetic convenience and potentially broader adoption. Herein, we demonstrate the ability to control the morphologies resulting from self-assembly of Fmoc modified aliphatic single amino acids (Fmoc-SAAs) namely, Alanine, Valine, Leucine, Isoleucine, and Proline. Controlled morphological transitions were observed through solvent variation and the mechanism that allows this control was investigated using coarse-grained molecular dynamics simulations. These show that FmocA can form well defined crystalline structures through uniform parallel Fmoc stacking and the optimization of ion concentrations, which is not observed for the other Fmoc-SAAs. We demonstrate that Fmoc protected aliphatic single amino acids are novel scaffolds for the design of distinct micro/nanostructures through a bottom-up approach that can be tuned by control of the environmental parameters.

Constant pH Coarse-Grained Molecular Dynamics with Stochastic Charge Neutralization.

pH dependence abounds in biochemical systems; however, many simulation methods used to investigate these systems do not consider this property. Using a modified version of the hybrid non-equilibrium molecular dynamics (MD)/Monte Carlo algorithm, we include a stochastic charge neutralization method, which is particularly suited to the MARTINI force field and enables artifact-free Ewald summation methods in electrostatic calculations. We demonstrate the efficacy of this method by reproducing pH-dependent self-assembly and self-organization behavior previously reported in experimental literature. In addition, we have carried out experimental oleic acid titrations where we report the results in a more relevant way for the comparison with computational methods than has previously been done.