<jupyter_start><jupyter_text>Step 1: Prepare Data In this part, we load the raw molecule data for experiment.The [117 ligand](http://www.rcsb.org/ligand/117) was put in the repository. We assign the relative path to **raw_path**.The **s3_bucket** and **prefix** are used to store the optimization results. We can use the one created with the cloudformation for convenience.<jupyter_code>from utility.MoleculeParser import MoleculeData
from utility.QMUQUBO import QMUQUBO
from utility.AnnealerOptimizer import Annealer
from utility.ResultProcess import ResultParser
import time

timestamp = time.strftime("%Y%m%d-%H")
# initial parameters for experiment data
s3_bucket = f"xxxx" # the name of the bucket
prefix = "xxxx" # the name of the folder in the bucket

raw_path = './molecule-data/117_ideal.mol2' # the mol2 file for this experiment
mol_data = MoleculeData(raw_path, 'qmu')

data_path = mol_data.save("latest")

num_rotation_bond = mol_data.bond_graph.rb_num
print(f"You have loaded the raw molecule data and saved as {data_path}. \n\
This molecule has {num_rotation_bond} rotable bond")<jupyter_output>INFO:root:parse mol2 file!
INFO:root:finish save qmu_117_ideal_data_latest.pickle
{'fraction_non_alphanumeric': 0.0865546218487395, 'fraction_numerical': 0.015126050420168067, 'mean_word_length': 5.884393063583815, 'pattern_counts': {'":': 0, '<': 4, '<?xml version=': 0, '>': 4, 'https://': 0, 'lorem ipsum': 0, 'www.': 1, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '1', 'dir': 'jupyter-structured-clean-dedup', 'id': '171157', 'license': 'Apache-2.0', 'n_tokens_mistral': 394, 'n_tokens_neox': 363, 'n_words': 129, 'path': 'docs/en/workshop/a-molecular-unfolding/prepare-data.ipynb', 'repo_name': 'hy714335634/quantum-ready-solution-for-drug-discovery', 'size': '1190'}