FibrilGen: A Python Package for Atomistic Modeling of Peptide β-Sheet Nanostructures.

Area of Science:

• Biomaterials Science
• Computational Chemistry
• Nanotechnology

Background:

• Rational design of peptide-based nanomaterials requires accurate modeling of self-assembly.
• Predicting diverse nanostructures from peptide sequences is computationally challenging.

Purpose of the Study:

• To introduce FibrilGen, a Python package for atomistic modeling of cross-β peptide nanostructures.
• To provide a tool for generating, analyzing, and simulating peptide fibril morphologies.

Main Methods:

• FibrilGen initializes peptide packing and fibril morphology using geometric parameters.
• A refinement step ensures compact assembly of peptide structures.
• The package facilitates geometric analysis and simulation trajectory assessment.

Main Results:

• FibrilGen successfully generated diverse cross-β nanostructures with varying morphologies.
• Modeled structures showed good agreement with experimental data (cryo-EM, ssNMR).
• Simulated structures demonstrated conformational stability in molecular dynamics.

Conclusions:

• FibrilGen enables the construction of atomistic supramolecular peptide structures.
• The package aids in visualizing, simulating, and assessing peptide nanostructures.
• FibrilGen supports the rational design of peptide-based nanomaterials.