Introduction
PathDiffusion is a software that automatically predicts protein folding pathways using evolution-guided diffusion models. It comprises two main modules: the first module focuses on preparing position-specific noise schedules (PSNS), and the second module employs PSNS-guided diffusion models to generate the folding pathway.
Model
sequence-conditional model
unconditional model
Training datasets
We train PathDiffusion using protein structures from the Protein Data Bank (for conditional generation) and the IDRome database (for unconditional generation). Details on dataset preparation can be found in https://github.com/YangLab-SDU/PathDiffusion
Benchmark datasets
FP52 dataset
IDP50 dataset
Reference
Zhao et al, PathDiffusion: modeling protein folding pathway using evolution-guided diffusion, bioRxiv 2026.