Comments (2)
I'm not one of the developers.
Have you looked at https://github.com/nrbennet/dl_binder_design The binder design protocol might be what you're looking for. It couples proteinmpnn with AF2 and predicts solubility and binding affinity using AF2 scores.
If running proteinmpnn by itself, I'll run a few jobs using different models and different values for T to generate several sequences. I'll then filter out sequences with high counts of alanine. I'll also calculate pI values as the models have a tendency to generate a lot of charged residues (e.g. glutamic acid).
The issue of repeats isn't something unique to ProteinMPNN, I notice it when running ESM.
It's also not unique to this domain. If I use OpenAI's whisper to transcribe audio it's common for it to generate repeats there as well.
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Thank you for your comment! Yes, I am using the binder design protocol. I guess I should have posted the question there but I thought this is related to proteinmpnn.
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Related Issues (20)
- Questions about model weights
- .Fa Output reorganization question
- Sampling temperature for flexible chains
- what pdbx package does parse_cif_noX.py expect? HOT 1
- Global_score
- No use of GPU?
- `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
- 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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