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# ✅ dependencies: gradio, rdkit-pypi, pandas, matplotlib, openpyxl
import gradio as gr
import pandas as pd
from rdkit import Chem
from rdkit.Chem import Descriptors
import matplotlib.pyplot as plt
import io
import base64
def get_admet(smiles):
mol = Chem.MolFromSmiles(smiles)
if not mol:
return pd.Series([None]*7, index=["MW", "LogP", "TPSA", "HBA", "HBD", "RotB", "Lipinski"])
mw = Descriptors.MolWt(mol)
logp = Descriptors.MolLogP(mol)
tpsa = Descriptors.TPSA(mol)
hba = Descriptors.NumHAcceptors(mol)
hbd = Descriptors.NumHDonors(mol)
rotb = Descriptors.NumRotatableBonds(mol)
lipinski = "✅" if (mw <= 500 and logp <= 5 and hba <= 10 and hbd <= 5) else "❌"
return pd.Series([mw, logp, tpsa, hba, hbd, rotb, lipinski],
index=["MW", "LogP", "TPSA", "HBA", "HBD", "RotB", "Lipinski"])
def analyze_admet(file):
smiles_list = [line.strip() for line in file.read().decode().splitlines() if line.strip()]
df = pd.DataFrame({"SMILES": smiles_list})
admet_df = df["SMILES"].apply(get_admet)
final_df = pd.concat([df, admet_df], axis=1)
# Save Excel to buffer
excel_buffer = io.BytesIO()
final_df.to_excel(excel_buffer, index=False)
excel_buffer.seek(0)
excel_data = base64.b64encode(excel_buffer.read()).decode()
# Create and save plot to buffer
plt.figure(figsize=(12, 6))
plot_df = final_df.dropna(subset=["LogP"])
plt.barh(plot_df["SMILES"], plot_df["LogP"], color='skyblue')
plt.xlabel("LogP")
plt.title("LogP Values per SMILES")
plt.gca().invert_yaxis()
plt.tight_layout()
img_buffer = io.BytesIO()
plt.savefig(img_buffer, format='png')
img_buffer.seek(0)
return (
final_df.to_markdown(index=False),
f"data:application/vnd.openxmlformats-officedocument.spreadsheetml.sheet;base64,{excel_data}",
img_buffer
)
# Gradio interface
with gr.Blocks() as demo:
gr.Markdown("## 🧪 ADMET Analysis from SMILES File")
with gr.Row():
smiles_file = gr.File(label="📄 Upload SMILES .txt File")
run_btn = gr.Button("🚀 Analyze")
result = gr.Textbox(label="📊 Results Table (Markdown)", lines=20)
download_excel = gr.File(label="⬇️ Download Excel")
image_output = gr.Image(label="📈 LogP Plot")
run_btn.click(fn=analyze_admet, inputs=smiles_file, outputs=[result, download_excel, image_output])
demo.launch()
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