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from dataclasses import dataclass
@dataclass(frozen=True)
class Config:
# Embeddings information
morgan_radius: int = 15
fingerprint_size: int = 224
protein_embedding_size: int = 1024
cell_embedding_size: int = 768
# Data information
dmax_threshold: float = 0.6
pdc50_threshold: float = 6.0
e3_ligase2uniprot: dict = {
'VHL': 'P40337',
'CRBN': 'Q96SW2',
'DCAF11': 'Q8TEB1',
'DCAF15': 'Q66K64',
'DCAF16': 'Q9NXF7',
'MDM2': 'Q00987',
'Mdm2': 'Q00987',
'XIAP': 'P98170',
'cIAP1': 'Q7Z460',
'IAP': 'P98170', # I couldn't find the Uniprot ID for IAP, so it's XIAP instead
'Iap': 'P98170', # I couldn't find the Uniprot ID for IAP, so it's XIAP instead
'AhR': 'P35869',
'RNF4': 'P78317',
'RNF114': 'Q9Y508',
'FEM1B': 'Q9UK73',
'Ubr1': 'Q8IWV7',
}
def __post_init__(self):
self.active_label: str = f'Active (Dmax {self.dmax_threshold}, pDC50 {self.pdc50_threshold})'
config = Config() |