HighFold-Lasso: Topology-Guided Prediction of Lasso Peptide Structures Using AlphaFold3
- 1Macao Polytechnic University
Abstract
Lasso peptides are a class of ribosomally synthesized and post-translationally modified peptides (RiPPs) characterized by a mechanically interlocked topology, in which the C-terminal tail is threaded through an N-terminal macrolactam ring formed by an isopeptide bond. This unique topology often confers high thermal stability and resistance to proteolytic degradation. However, the isopeptide linkage, threaded topology, and class-specific disulfide connectivity make lasso peptide structures difficult to reconstruct reliably using general-purpose structure prediction models. Here, we developed HighFold-Lasso, which combines custom covalent connectivity with lasso scaffold-guided adaptive low-noise initialization to enable conditional structure generation guided by lasso conformational priors. On a test set of 52 experimentally determined structures, HighFold-Lasso achieved a 100% lasso topology success rate, with a mean RMSD C-alpha of 1.942 Angstrom for the ring-loop region and 2.375 Angstrom for the full peptide. The framework supports modeling of the four classical lasso peptide classes (I-IV) and can represent noncanonical amino acids, providing computational support for structure-function studies and molecular engineering of lasso peptides.
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BibTeX
@misc{sen2026highfoldlasso,
title = {{HighFold-Lasso: Topology-Guided Prediction of Lasso Peptide Structures Using AlphaFold3}},
author = {C. Sen and C. Zhang and H. Yang and Y. Ge and H. Hou and N. Zhu and C. Li and J. Mo and Y. Wu and J. Guo and J. GUO and H. Duan},
howpublished = {bioRxiv},
year = {2026},
month = oct,
doi = {10.64898/2026.10.14.759041},
url = {https://www.biorxiv.org/content/10.64898/2026.10.14.759041v1},
note = {CC BY},
}
RIS
TY - UNPB
TI - HighFold-Lasso: Topology-Guided Prediction of Lasso Peptide Structures Using AlphaFold3
AU - C. Sen
AU - C. Zhang
AU - H. Yang
AU - Y. Ge
AU - H. Hou
AU - N. Zhu
AU - C. Li
AU - J. Mo
AU - Y. Wu
AU - J. Guo
AU - J. GUO
AU - H. Duan
PY - 2026
DA - 2026/10/14
PB - bioRxiv
DO - 10.64898/2026.10.14.759041
UR - https://www.biorxiv.org/content/10.64898/2026.10.14.759041v1
AB - Lasso peptides are a class of ribosomally synthesized and post-translationally modified peptides (RiPPs) characterized by a mechanically interlocked topology, in which the C-terminal tail is threaded through an N-terminal macrolactam ring formed by an isopeptide bond. This unique topology often confers high thermal stability and resistance to proteolytic degradation. However, the isopeptide linkage, threaded topology, and class-specific disulfide connectivity make lasso peptide structures difficult to reconstruct reliably using general-purpose structure prediction models. Here, we developed HighFold-Lasso, which combines custom covalent connectivity with lasso scaffold-guided adaptive low-noise initialization to enable conditional structure generation guided by lasso conformational priors. On a test set of 52 experimentally determined structures, HighFold-Lasso achieved a 100% lasso topology success rate, with a mean RMSD C-alpha of 1.942 Angstrom for the ring-loop region and 2.375 Angstrom for the full peptide. The framework supports modeling of the four classical lasso peptide classes (I-IV) and can represent noncanonical amino acids, providing computational support for structure-function studies and molecular engineering of lasso peptides.
ER -