You can first install the Conda version of AlphaFold3 by following the tutorial (https://github.com/pyDock/AlphaFold3-Conda-Install). Then, copy the source code of HighFold3 into the already installed AlphaFold3 project, with the core position matrix code located in the /model directory.
unnatural amino acids using HighFold3 HighFold3 is an enhanced model developed on the basis of AlphaFold 3, designed to accurately predict the three-dimensional structures of peptides containing unnatural amino acids (unAAs), including both monomers and their protein complexes. It is capable of handling special topological features such as head-to-tail cyclization and disulfide bond constraints. The overall architecture of HighFold3 is illustrated in Figure . HighFold3 introduces the Cyclic Position Offset Encoding Matrix (CycPOEM) and employs an innovatively designed “Cyclization Switch” module to dynamically select either a linear or cyclic positional encoding matrix within the model. When predicting cyclic peptide–protein complexes, the model explicitly divides the input distance matrix into two components: a linear positional encoding matrix for the target protein and a CycPOEM for the cyclic peptide ligand. This design enables the model to flexibly accommodate diverse conformational requirements and accurately model the binding of cyclic peptide ligands to protein receptors.
python run_alphafold_HF3.py
db_dir=af3_db_path
--model_dir=models_path
--json_path=json_path
--output_dir=output_path
--head_to_tail
python run_alphafold_HF3.py
db_dir=af3_db_path
--model_dir=models_path
--json_path=json_path
--output_dir=output_path
--head_to_tail=0 # Non-head to tail
--disulfide_chain_res [[1,3,11]]
The parameter head_to_tail indicates whether the head and tail form a ring, a boolean type. The parameter disulfide_chain_res specifies the chain and positions where disulfide bonds are located.