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trRosetta for protein design
Hi!
I downloaded everything written in the README, than tried to run trDesign on a protein. However, I get the following
No such file or directory: '../../tools/trDesign/models/model_xaa.npy'
None of the downloaded files or the github repo contained a model_xaa.npy. How can I obtain it?
Thank you!
Hi, I tried to run by python design.py -p 1QYS.pdb -o tmp.txt
but it appeared:
< ERROR: Output file not defined --out=None >
Is the license included in 01-hallucinate
intended to apply to the whole of the trDesign
repository, or is it intended for only 01-hallucinate
?
I am trying to create a structure from the amino acid sequence using the tool.
Running this code gives me a somewhat linear feature space with little off diagonal elements. The predicted protein shape isn’t close to the one in the protein data bank.
seq = "MRYRLAWLLHSALPSTFRSVLGARLPPSERLCGFQKKTYSKMNNPAIKRIGHHIIKSHEDKREYRGLELANGIKVLLVSDPTTDKSSAALDVHIGSLSDPPNIAGLSHFCEHMLFLGTKKYPKENEYSQFLSEHAGSSNAFTSGEHTNYYFDVSHEHLEGALDRFAQFFLCPLFDESCKDREVNAVDSEHEKNVMNDAWRLFQLEKATGNPKHPFSKFGTGNKYTLETRPNQEGIDVRQELLKFHSTYYSSNLMAICVLGRESLDDLTNLVVKLFSEVENKNVPLPEFPEHPFQEEHLKQLYKIVPIKDIRNLYVTFPIPDLQKYYKSNPGHYLGHLIGHEGPGSLLSELKSKGWVNTLVGGQKEGARGFMFFIINVDLTEEGLLHVEDIILHMFQYIQKLRAEGPQEWVFQECKDLNAVAFRFKDKERPRGYTSKIAGILHYYPLEEVLTAEYLLEEFRPDLIEMVLDKLRPENVRVAIVSKSFEGKTDRTEEWYGTQYKQEAIPDEVIKKWQNADLNGKFKLPMKNEFIPTNFEILSLEKEATPYPSLIKDTAMSKLWFKQDDKFFLPKACLNFEFFSPFAYVDPLHCNMAYLYLELLKDSLNEYAYAAELAGLSYDLQNTIYGMYLSVKGYNDKQPILLKKIIEKMATFEIDEKRFEIIKEAYMRSLNNFRAEQPHQHAMYYLRLLMTEVAWTKDELKEALDDVTLPRLKAFIPQLLSRLHIEALLHGNITKQAALGIMQMVEDTLIEHAHTKPLLPSQLVRYREVQLPDRGWFVYQQRNEVHNNCGIEIYYQTDMQSTSENMFLELFCQIISEPCFNTLRTKEQLGYIVFSGPRRANGIQGLRFIIQSEKPPHYLESRVEAFLITMEKSIEDMTEEAFQKHIQALAIRRLDKPKKLSAECAKYWGEIISQQYNFDRDNIEVAYLKTLTKEDIIKFYKEMLAVDAPRRHKVSVHVLA" _seq = np.eye(20)[AA_to_N(seq)] preds = model.predict({"I":_seq[None,None]}) plot_feat(preds["feat"]) get_pdb(preds,"random.pdb")
Actual shape
https://www.uniprot.org/uniprotkb/Q24K02/feature-viewer
Hello,
I am running TrDesign_GD_demo.ipynb on Linux (not in Colab) and in Part 2 Step 2 I get many warnings:
model = mk_design_model(add_pdb=True, n_models=1)
mode: single sequence design
WARNING: Entity <bound method PSSM.call of <models.PSSM object at 0x2b5fa15e9b90>> could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, export AUTOGRAPH_VERBOSITY=10
) and attach the full output. Cause: converting <bound method PSSM.call of <models.PSSM object at 0x2b5fa15e9b90>>: AttributeError: module 'gast' has no attribute 'Num'
loading model: xaa
WARNING: Entity <bound method instance_norm.call of <models.instance_norm object at 0x2b5fa1648250>> could not be transformed and will be executed as-is. Please report this to the AutgoGraph team. When filing the bug, set the verbosity to 10 (on Linux, export AUTOGRAPH_VERBOSITY=10
) and attach the full output. Cause: converting <bound method instance_norm.call of <models.instance_norm object at 0x2b5fa1648250>>: AssertionError: Bad argument number for Name: 3, expecting 4
...
The warnings do not appear if I run the notebook in Colab. Also, after the warnings the does still run and would appear to generate correct results. Just thought you might want to know.
Thanks!
Scott
Hello,
I was wondering if it is possible to do a partial sequence design? What I'm thinking is that I would like to start with a known backbone (from a PDB file) and then mask out some of the residues and allow the model to predict only those.
I can see there is some functionality to 'spike' the seq_start but I think I'm thinking of something a bit different. Also, it would probably be necessary to backprop and update only the residues covered by the mask.
Like to hear your thoughts or ideas as I start thinking about this.
Thanks!
Scott
Does this code have a visual effect?
The process of reproducing the code has the following questions:
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