Docked structures from "Optimizing active learning for free energy calculations"
收藏NIAID Data Ecosystem2026-05-02 收录
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https://zenodo.org/record/13759489
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资源简介：
This archive contains the docked TYK2 structures used in the paper "Optimizing active learning for free energy calculations" (https://doi.org/10.1016/j.ailsci.2022.100050). AM1-BCC charges are stored in the field "AM1Cache" in the SD file. The charges can be extracted using the code sample below.
from rdkit import Chem
import base64
import pickle
suppl = Chem.SDMolSupplier("10k_most_similar_tyk2_charged.sdf", removeHs=False)
for mol in suppl:
am1 = mol.GetProp("AM1Cache")
am1_charges = pickle.loads(base64.b64decode(mol.GetProp("AM1Cache")))
assert len(am1_charges) == mol.GetNumAtoms(), "Charge cache has different number of charges than mol atoms"
创建时间：
2024-09-13
