Multiscale, Multiresolution Coarse-Grained Model via a Hybrid Approach: Solvation, Structure, and Self-Assembly of Aromatic Tripeptides

Abstract

Short aromatic peptides have been observed to assemble into diverse nanostructures, including fibers, tubes, and vesicles, using computational techniques. However, the computational studies have employed top-down coarse-grained (CG) models, which are unable to capture the assembly along with the conformation, packing, and organization of the peptides within the aggregates in a manner that is consistent with the all atom (AA) representation of the molecules. In this study, a hybrid structureand force-based approach is adapted to develop a bottom-up CG force field of triphenylalanine using reference data from AA trajectories. This approach follows a flexible methodology to approximate the chemical complexity of the underlying AA representation with the chosen CG representation. Two CG models are developed with distinct representations of the aromatic side chains. The first uses a simple single-bead representation, while the second uses a three-bead representation to more accurately represent the planarity of the ring. The one-bead model yields nanorods, while the three-bead model results in nanospheres. The role of different chemical groups in the assembly of nanostructures is identified, along with the importance of steric effects on the packing of the peptides within assemblies.

Tips and Tricks in the Modeling of Supramolecular Peptide Assemblies

“…Olvera de la Cruz et al employed such model to study the self-assembly of PAs as a balance between hydrophobic interactions and hydrogen bonding, predicting its effect on morphology (Figure ). A more recent study on FFF tripeptide supported that a higher resolution of the F side chains leads to better agreement with the experimental formation of solid-core nanospheres …”

A perspective on coarse-graining methodologies for biomolecules: resolving self-assembly over extended spatiotemporal scales

“…These models were able to resolve the assembly of the molecules while capturing their packing and organization within the aggregates (Figure 2). Using suitable backmapping protocols yielded the AA representation of individual molecules within assemblies (Banerjee et al, 2022;Hooten et al, 2023). In addition, these models (Banerjee et al, 2022;Banerjee and Dutt, 2023a;Hooten et al, 2023) enabled the study of large-scale self-assembly of biomolecules which resulted in the formation of aggregates in accordance with experimental observations.…”

“…The spacing between the peptoids in the monolayer were observed to be in agreement with x-ray scattering measurements. A coarse-graining approach which captured multibody PMFs and the structure of the AA reference was used to develop CG models of aliphatic peptides, aromatic peptides and helical peptoids (Banerjee et al, 2022;Banerjee and Dutt, 2023a;Hooten et al, 2023). These models were able to resolve the assembly of the molecules while capturing their packing and organization within the aggregates (Figure 2).…”

“…(B) All atom representation of selfassembled hemispherical micelle encompassing helical peptoids, reproduced from (Banerjee and Dutt, 2023a). (C) Packing of aromatic tripeptides within an aggregate obtained using a CG model, adapted with permission from (Hooten et al, 2023). Copyright 2023 American Chemical Society.…”

“…This approach provides a framework for systematically tuning structure-based CG representation. This is of particular interest since choice of molecular representation has been shown to influence the aggregation behavior of models with identical parameterization routines (Hooten et al, 2023).…”