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{
"cells": [
{
"cell_type": "markdown",
"id": "834aeced-c3c5-42a0-bad1-41e009dd86ee",
"metadata": {},
"source": [
"### Preprocessing"
]
},
{
"cell_type": "code",
"execution_count": 27,
"id": "86476f6e-802a-463b-a1b0-2ae228bb92af",
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd"
]
},
{
"cell_type": "code",
"execution_count": 45,
"id": "9b2be11c-f4bb-4107-af49-abd78052afcf",
"metadata": {},
"outputs": [],
"source": [
"df = pd.read_table('pdbbind/data/index/INDEX_general_PL_data.2020',skiprows=4,sep=r'\\s+',usecols=[0,4]).drop(0)\n",
"df = df.rename(columns={'#': 'name','release': 'affinity'})\n",
"df_refined = pd.read_table('pdbbind/data/index/INDEX_refined_data.2020',skiprows=4,sep=r'\\s+',usecols=[0,4]).drop(0)\n",
"df_refined = df_refined.rename(columns={'#': 'name','release': 'affinity'})\n",
"df = pd.concat([df,df_refined])"
]
},
{
"cell_type": "code",
"execution_count": 46,
"id": "68983ab8-bf11-4ed6-ba06-f962dbdc077e",
"metadata": {},
"outputs": [],
"source": [
"quantities = ['ki','kd','ka','k1/2','kb','ic50','ec50']"
]
},
{
"cell_type": "code",
"execution_count": 47,
"id": "3acbca3c-9c0b-43a1-a45e-331bf153bcfa",
"metadata": {},
"outputs": [],
"source": [
"from pint import UnitRegistry\n",
"ureg = UnitRegistry()\n",
"\n",
"def to_uM(affinity):\n",
" val = ureg(affinity)\n",
" try:\n",
" return val.m_as(ureg.uM)\n",
" except Exception:\n",
" pass\n",
" \n",
" try:\n",
" return 1/val.m_as(1/ureg.uM)\n",
" except Exception:\n",
" pass"
]
},
{
"cell_type": "code",
"execution_count": 48,
"id": "58e5748b-2cea-43ff-ab51-85a5021bd50b",
"metadata": {},
"outputs": [],
"source": [
"df['affinity_uM'] = df['affinity'].str.split('[=\\~><]').str[1].apply(to_uM)\n",
"df['affinity_quantity'] = df['affinity'].str.split('[=\\~><]').str[0]"
]
},
{
"cell_type": "code",
"execution_count": 49,
"id": "d92f0004-68c1-4487-94b9-56b4fd598de4",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"<AxesSubplot:>"
]
},
"execution_count": 49,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"df['affinity_quantity'].hist()"
]
},
{
"cell_type": "code",
"execution_count": 50,
"id": "aa358835-55f3-4551-9217-e76a15de4fe8",
"metadata": {},
"outputs": [],
"source": [
"df_filter = df[df['affinity_quantity'].str.lower().isin(quantities)]"
]
},
{
"cell_type": "code",
"execution_count": 51,
"id": "d6dda488-f709-4fe7-b372-080042cf7c66",
"metadata": {},
"outputs": [],
"source": [
"df_complex = pd.read_parquet('data/pdbbind_complex.parquet')"
]
},
{
"cell_type": "code",
"execution_count": 52,
"id": "df7929e3-c7fd-4e1b-a165-92f8d53b9011",
"metadata": {},
"outputs": [],
"source": [
"df_all = df_complex.merge(df_filter,on='name').drop('affinity',axis=1)"
]
},
{
"cell_type": "code",
"execution_count": 53,
"id": "4d105c42-0d11-49db-9012-52fafc9cd299",
"metadata": {},
"outputs": [],
"source": [
"df_all.to_parquet('data/pdbbind.parquet')"
]
},
{
"cell_type": "code",
"execution_count": 54,
"id": "2955b056-26dd-45fa-8d74-f17661253a9a",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"24759"
]
},
"execution_count": 54,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"len(df_all)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "ed3fe035-6035-4d39-b072-d12dc0a95857",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.4"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
|