Comments (3)
It looks like the parsed_pdbs.jsonl
file includes a -
(which I assume is a gap). So I needed to put a X
in the original chain sequence at that gap position.
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From their examples it would look like something like this: {A: -1.1, F: 0.7}. I tried using one and my json file looks like this, and it ran ok: {"A": -1.50487820683775, "C": -1.50336065414758, "D": 0.451363945615286, "E": 0.407588387244967, "F": 1.37065067139209, "G": -1.50487820683775, "H": 0.801568412577877, "I": 0.538915062355937, "K": -0.292820546680218, "L": 0.670241737466907, "M": -0.0301671964582751, "N": -0.227157209124733, "P": -1.50487820683775, "Q": -0.0301671964582751, "R": 0.889119529318528, "S": -0.774351688753783, "T": -0.686800572013134, "V": 0.0136083619120431, "W": 1.63330402161404, "Y": 1.28309955465145}
In one of the examples, they have the usage of one of their scripts to automatically create the json file.
I do not know if it is possible to have different biases for each position. It would be tedious but maybe you can write a script to design one position at a time passing the respective bias. I would also like to know if there is a better approach here!
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Thanks!
Yes. I've been successful doing the per residue bias. Essentially it is a JSON where the first level is the name, the second is the chain, and the third is a N x M matrix of bias values where N is the number of residues and the M is 21 (the 20 amino acids plus a gap character). This works well so long as you account for any gaps that are in the PDB file's sequence.
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Related Issues (20)
- From 2 distinct structure to a single sequence ? HOT 4
- Tying Multiple Chains Independently HOT 4
- Indexing with Missing Residues HOT 4
- Clarify 'design chains' HOT 1
- conditional_probs_only_backbone is ignored when used alone
- Warnings From Example Scripts? HOT 2
- `parse_cif_noX.py` misses some chains in CATH? HOT 2
- Training model
- Retrieve per-position scores or score a chain in the context of another
- whether to redesign low confidence aas
- Design complexes with unknown chains (proposed fix included)
- Amino acid sequence has too many "K/E" HOT 2
- How do I use a PSSM with proteinMPNN?
- Need of assistance and advising
- Model is adding an amino acid to the original sequence HOT 5
- Creates hydrophobic surface patches wit many Ala side chains HOT 2
- Training time HOT 1
- What is the difference between --conditional_probs_only_backbone and --unconditional_probs_only HOT 1
- Empty parsed_pdbs.jsonl file from parse_multiple_chains.py helper script? HOT 1
- RuntimeError: Class values must be smaller than num_classes. | protein_mpnn_utils.py & mask_size issue?
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