Closed kehan777 closed 1 year ago
kxz18
commented
1 year ago Hi, thx for your interest in our work. To obtain the epitope for e, F, and f, you need to replace the value of the argument '--ligand' to e, F, and f, respectively. The output path should also be changed correspondingly, otherwise each running will overwrite the same file "E_epitope.json".
kehan777
commented
1 year ago 谢谢您，孔老师，很赞！
kehan777
commented
1 year ago annother error occur when using api.optimize, it seems like the force field is not defined or force file missing, could u tell me how to fix it?
python -m api.optimize
Traceback (most recent call last):
File "/home/ad/miniconda3/envs/abc/lib/python3.10/runpy.py", line 196, in _run_module_as_main
return _run_code(code, main_globals, None,
File "/home/ad/miniconda3/envs/abc/lib/python3.10/runpy.py", line 86, in _run_code
exec(code, run_globals)
File "/home/ad/dyMEAN/api/optimize.py", line 223, in
kxz18
commented
1 year ago It looks like the same issue as #2. You can pull the latest updates to avoid this problem.
Excellent work, and very thx for open source. This is my question. When testing api.design, error: api/design.py", line 43, in get_epitope with open(epitope_def, 'r') as fin: FileNotFoundError: [Errno 2] No such file or directory: './demos/data/e_epitope.json'
I have './demos/data/E_epitope.json; but don't have other 3 " e,F,f "
from api.design import design ckpt = './checkpoints/cdrh3_design.ckpt' root_dir = './demos/data' pdbs = [os.path.join(rootdir, '7l2m.pdb') for in range(4)] toxin_chains = ['E', 'e', 'F', 'f'] remove_chains = [toxinchains for in range(4)] epitope_defs = [os.path.join(root_dir, c + '_epitope.json') for c in toxin_chains] identifiers = [f'{c}_antibody' for c in toxin_chains]
frameworks = [ ( ('H', 'QVQLKESGPGLLQPSQTLSLTCTVSGISLSDYGVHWVRQAPGKGLEWMGIIGHAGGTDYNSNLKSRVSISRDTSKSQVFLKLNSLQQEDTAMYFC----------WGQGIQVTVSSA'), ('L', 'YTLTQPPLVSVALGQKATITCSGDKLSDVYVHWYQQKAGQAPVLVIYEDNRRPSGIPDHFSGSNSGNMATLTISKAQAGDEADYYCQSWDGTNSAWVFGSGTKVTVLGQ') ) \ for _ in pdbs ] # the first item of each tuple is heavy chain, the second is light chain
design(ckpt=ckpt, # path to the checkpoint of the trained model gpu=0, # the ID of the GPU to use pdbs=pdbs, # paths to the PDB file of each antigen (here antigen is all TRPV1) epitope_defs=epitope_defs, # paths to the epitope definitions frameworks=frameworks, # the given sequences of the framework regions out_dir=root_dir, # output directory identifiers=identifiers, # name of each output antibody remove_chains=remove_chains,# remove the original ligand enable_openmm_relax=True, # use openmm to relax the generated structure auto_detect_cdrs=False) # manually use '-' to represent CDR residues