# Secondary Structure Bead-Encoded Amphiphilicity Biases Peptide Self-Assembly Prediction in MARTINI Coarse-Grained Simulations

## TL;DR

This study shows that how peptides are modeled in simulations affects predictions of how they self-assemble, with implications for nanotechnology design.

## Contribution

The study reveals that secondary structure encoding biases peptide self-assembly predictions in MARTINI simulations, depending on sequence and length.

## Key findings

- Changes in secondary structure encoding significantly alter predicted self-assembly behavior of peptides.
- Amphiphilicity shifts due to backbone polarity changes impact aggregation propensities.
- Bias in predictions is sequence- and length-dependent, making systematic correction difficult.

## Abstract

Sequence-dependent
self-assembly of peptides yields ordered supramolecular
structures with diverse nanotechnological applications. In the absence
of simple design rules linking sequence to supramolecular morphology,
coarse-grained molecular dynamics (CG-MD) simulations have become
valuable tools for guiding the design of self-assembling peptides.
The MARTINI model, despite the lack of explicit hydrogen bonding,
can predict self-assembling sequences and structural features by introducing
secondary structure-specific beads that adjust backbone polarity.
Extended β-sheet encoding is typically used as input for short
peptides, based on experimental observations. However, this assumption
becomes increasingly unreliable beyond six to ten residues, where
folded conformations begin to emerge. In this study, we investigated
the effect of different secondary structure encodings on self-assembly
simulations of hexapeptides and decapeptides using MARTINI 2.2p. The
results confirmed that changes in the secondary structure encoding
significantly impact the predicted self-assembly behavior, with AP
scores for the same peptide varying by up to one unitshifting
from fully dissolved (AP ≈ 1) to well-aggregated states (AP
> 2) in specific cases. This effect arises from alterations in
overall
peptide amphiphilicity caused by shifts in backbone polarity. However,
the magnitude and direction of this influence depend on side-chain
polarity and peptide length, making the resulting bias highly sequence-specific
and difficult to anticipate or correct systematically. These findings
emphasize the need to reevaluate the conventional use of extended
β-sheet encoding (E-flag) and advocate for more native-like
backbone representations in peptide self-assembly simulations.