I've trained the OpenFold model https://github.com/aqlaboratory/openfold and it geterated checkpoint file (*ckpt) (Pytorch Lighntning).
Explain me please, how can I use *.ckpt files for the prediction by run_pretrained_openfold.py? Or perhaps I need to somehow convert this to another format first?
python3 run_pretrained_openfold.py \ fasta_dir \ data/pdb_mmcif/mmcif_files/ \ --uniref90_database_path data/uniref90/uniref90.fasta \ --mgnify_database_path data/mgnify/mgy_clusters_2018_12.fa \ --pdb70_database_path data/pdb70/pdb70 \ --uniclust30_database_path data/uniclust30/uniclust30_2018_08/uniclust30_2018_08 \ --output_dir ./ \ --bfd_database_path data/bfd/bfd_metaclust_clu_complete_id30_c90_final_seq.sorted_opt \ --model_device "cuda:0" \ --jackhmmer_binary_path lib/conda/envs/openfold_venv/bin/jackhmmer \ --hhblits_binary_path lib/conda/envs/openfold_venv/bin/hhblits \ --hhsearch_binary_path lib/conda/envs/openfold_venv/bin/hhsearch \ --kalign_binary_path lib/conda/envs/openfold_venv/bin/kalign \ --config_preset "model_1_ptm" \ **--openfold_checkpoint_path openfold/resources/openfold_params/finetuning_ptm_2.pt**
If I use this: --openfold_checkpoint_path /checkpoints/14my.ckpt I got this error message:
raise RuntimeError('Error(s) in loading state_dict for {}:\n\t{}'.format( RuntimeError: Error(s) in loading state_dict for AlphaFold: Missing key(s) in state_dict: "aux_heads.tm.linear.weight", "aux_heads.tm.linear.bias".
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I resolved the error by using --config_preset "model_1" instead of model_1_ptm.
However now I have pdb where the coordinates of amino acids are calculated incorrectly. I use "manual optimization mode" because I am testing my own optimizer, the standard Adam generally gives normal results.
Is it a problem with Manual Optimization of Lightning or what?
Peptide after Manual Optimization: enter image description here
Standard Adam and Automatic Optimization: enter image description here
