import streamlit as st from stmol import showmol import py3Dmol import requests import biotite.structure.io as bsio import random import hashlib import urllib3 from Bio.Blast import NCBIWWW, NCBIXML from Bio.Seq import Seq from Bio.SeqRecord import SeqRecord import time urllib3.disable_warnings(urllib3.exceptions.InsecureRequestWarning) st.set_page_config(layout='wide') st.sidebar.title('🔮 GenPro2 Protein Generator & Structure Predictor') st.sidebar.write('GenPro2 is an end-to-end single sequence protein generator and structure predictor based [*ESMFold*](https://esmatlas.com/about) and the ESM-2 language model.') def generate_sequence_from_words(words, length): seed = ' '.join(words).encode('utf-8') random.seed(hashlib.md5(seed).hexdigest()) amino_acids = "ACDEFGHIKLMNPQRSTVWY" return ''.join(random.choice(amino_acids) for _ in range(length)) def render_mol(pdb): pdbview = py3Dmol.view() pdbview.addModel(pdb,'pdb') pdbview.setStyle({'cartoon':{'color':'spectrum'}}) pdbview.setBackgroundColor('white') pdbview.zoomTo() pdbview.zoom(2, 800) pdbview.spin(True) showmol(pdbview, height = 500,width=800) def perform_blast_analysis(sequence): st.subheader('Protein Analysis') with st.spinner("Analyzing generated protein... This may take a few minutes."): progress_bar = st.progress(0) for i in range(100): progress_bar.progress(i + 1) time.sleep(0.1) # Simulate analysis time try: record = SeqRecord(Seq(sequence), id='random_protein') result_handle = NCBIWWW.qblast("blastp", "swissprot", record.seq) blast_record = NCBIXML.read(result_handle) if blast_record.alignments: alignment = blast_record.alignments[0] # Get the top hit hsp = alignment.hsps[0] # Get the first (best) HSP # Extract protein name and organism title_parts = alignment.title.split('|') protein_name = title_parts[-1].strip() organism = title_parts[-2].split('OS=')[-1].split('OX=')[0].strip() # Calculate identity percentage identity_percentage = (hsp.identities / alignment.length) * 100 st.write(f"**Top Match:** {protein_name}") st.write(f"**Organism:** {organism}") st.write(f"**Sequence Identity:** {identity_percentage:.2f}%") st.write(f"**E-value:** {hsp.expect:.2e}") # Fetch protein function (if available) if hasattr(alignment, 'description') and alignment.description: st.write(f"**Potential Function:** {alignment.description}") # Link to BLAST results blast_link = f"https://blast.ncbi.nlm.nih.gov/Blast.cgi?PROGRAM=blastp&PAGE_TYPE=BlastSearch&LINK_LOC=blasthome" st.markdown(f"[View full BLAST results (may require re-running the search)]({blast_link})") else: st.write("No significant matches found. This might be a unique protein sequence!") except Exception as e: st.error(f"An error occurred during protein analysis: {str(e)}") st.write("Please try again later or contact support if the issue persists.") def update(sequence, word1, word2, word3, sequence_length): headers = { 'Content-Type': 'application/x-www-form-urlencoded', } try: response = requests.post('https://api.esmatlas.com/foldSequence/v1/pdb/', headers=headers, data=sequence, verify=False, timeout=300) response.raise_for_status() pdb_string = response.content.decode('utf-8') with open('predicted.pdb', 'w') as f: f.write(pdb_string) struct = bsio.load_structure('predicted.pdb', extra_fields=["b_factor"]) b_value = round(struct.b_factor.mean(), 2) st.session_state.structure_info = { 'pdb_string': pdb_string, 'b_value': b_value, 'word1': word1, 'word2': word2, 'word3': word3, 'sequence_length': sequence_length } st.session_state.show_analyze_button = True except requests.exceptions.RequestException as e: st.error(f"An error occurred while calling the API: {str(e)}") st.write("Please try again later or contact support if the issue persists.") # Initialize session state variables if 'sequence' not in st.session_state: st.session_state.sequence = None if 'show_analyze_button' not in st.session_state: st.session_state.show_analyze_button = False if 'structure_info' not in st.session_state: st.session_state.structure_info = None st.title("Word-Seeded Protein Sequence Generator and Structure Predictor") st.sidebar.subheader("Generate Sequence from Words") word1 = st.sidebar.text_input("Word 1") word2 = st.sidebar.text_input("Word 2") word3 = st.sidebar.text_input("Word 3") sequence_length = st.sidebar.number_input("Sequence Length", min_value=50, max_value=400, value=100, step=10) if st.sidebar.button('Generate and Predict'): if word1 and word2 and word3: sequence = generate_sequence_from_words([word1, word2, word3], sequence_length) st.session_state.sequence = sequence st.sidebar.text_area("Generated Sequence", sequence, height=100) st.sidebar.info("Note: The same words and sequence length will always produce the same sequence.") with st.spinner("Predicting protein structure... This may take a few minutes."): update(sequence, word1, word2, word3, sequence_length) else: st.sidebar.warning("Please enter all three words to generate a sequence.") # Display structure information if available if st.session_state.structure_info: info = st.session_state.structure_info st.subheader(f'Predicted protein structure using seed: {info["word1"]}, {info["word2"]}, and {info["word3"]} + length {info["sequence_length"]}') render_mol(info['pdb_string']) st.subheader('plDDT Score') st.write('plDDT is a per-residue estimate of the confidence in prediction on a scale from 0-100%.') st.info(f'Average plDDT: {int(info["b_value"] * 100)}%') st.download_button( label="Download PDB", data=info['pdb_string'], file_name='predicted.pdb', mime='text/plain', ) st.markdown(""" ## What to do next: If you find interesting results from the sequence folding, you can explore further: 1. Learn more about protein structures and sequences. 2. Visit the [Protein Data Bank (PDB)](https://www.rcsb.org/) for known protein structures. 3. Compare your folded structure with known functional proteins by downloading your results. 4. Read about similar proteins to gain insights into potential functions. 5. Click the "Analyze Protein" button below to get more information about your generated protein. **Remember, this folding is based on randomly generated sequences. Interpret the results with caution. Enjoy exploring the world of protein sequences! Share your high-confidence protein images with us on X [*@WandsAI*](https://x.com/wandsai)! """) # Show the Analyze Protein button if a sequence has been generated if st.session_state.show_analyze_button: if st.button('Analyze Protein'): perform_blast_analysis(st.session_state.sequence)