Peptide Assembly Design Algorithm: A User-Friendly Computational Tool for Discovering Amyloid-forming Peptides

Abstract

Abstract Rational design of self-assembling peptides that form amyloid-like structures is challenging due to the vast combinatorial sequence space for amino acids. To address this challenge, we have developed the Peptide Assembly Design (PepAD) algorithm, a Monte Carlo-based method for designing self-assembling peptides based on pre-defined amyloid backbones. In this work, we introduce the user-friendly package, PepAD, to the research community (GitHub link: https://github.com/CarolHall-NCSU-CBE/PepAD-User-Friendly-Package). This package allows users to flexibly design and customize peptides by specifying initial structure, amino acid composition, and constraints. Detailed instructions for code compilation, execution, and interpretation of outputs are provided. Guidance on selecting several important design parameters is provided. As an example to illustrate the use of PepAD, we describe the design of peptides that assemble into antiparallel fibrils with and without single-site constraints. We expect that this release will streamline the design process and speed up the discovery of programmable self-assembling peptides for biofunctional materials.