|
import streamlit as st |
|
import pandas as pd |
|
import rdkit |
|
import streamlit_ketcher |
|
from streamlit_ketcher import st_ketcher |
|
import run |
|
|
|
|
|
st.set_page_config(page_title="DeepDAP", page_icon="🔋", layout="wide") |
|
st.title("🔋DeepDAP") |
|
|
|
|
|
|
|
url1= r"https://docs.google.com/spreadsheets/d/1AKkZS04VF3osFT36aNHIb4iUbV8D1uNfsldcpHXogj0/gviz/tq?tqx=out:csv&sheet=dap" |
|
df1 = pd.read_csv(url1, dtype=str, encoding='utf-8') |
|
|
|
text_search = st.text_input("🔍Search papers or molecules", value="") |
|
m1 = df1["Donor_Name"].str.contains(text_search) |
|
m2 = df1["reference"].str.contains(text_search) |
|
m3 = df1["Acceptor_Name"].str.contains(text_search) |
|
df_search = df1[m1 | m2|m3] |
|
if text_search: |
|
st.write(df_search) |
|
st.download_button( "⬇️Download edited files as .csv", df_search.to_csv(), "df_search.csv", use_container_width=True) |
|
edited_df = st.data_editor(df1, num_rows="dynamic") |
|
|
|
st.download_button( |
|
"⬇️ Download edited files as .csv", edited_df.to_csv(), "edited_df.csv", use_container_width=True |
|
) |
|
|
|
molecule = st.text_input("👨🔬Molecule") |
|
smile_code = st_ketcher(molecule) |
|
st.markdown("🏆New SMILES of edited molecules: {smile_code }") |
|
|
|
acceptor= st.text_input("🎈SMILES of acceptor") |
|
|
|
donor = st.text_input("🎈SMILES of donor") |
|
|
|
try: |
|
pce = run.smiles_aas_test( str(acceptor ), str(donor) ) |
|
st.markdown("⚡PCE: ``{pce}``") |
|
except: |
|
st.markdown("⚡PCE: None ") |
|
|
