Update app.py

app.py

@@ -15,8 +15,8 @@ import urllib.parse
 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.')
+st.sidebar.title('🔮 GenPro2 Protein Generator, Structure Predictor, and Analysis Tool')
+st.sidebar.write('GenPro2 is an end-to-end sequence protein generator, structure predictor, analysis tool based [*ESMFold*](https://esmatlas.com/about), the ESM-2 language model, and known proteins.')
 
 def generate_sequence_from_words(words, length):
     seed = ' '.join(words).encode('utf-8')
@@ -36,7 +36,7 @@ def render_mol(pdb):
 
 def perform_blast_analysis(sequence):
     st.subheader('Protein Analysis')
-    with st.spinner("Analyzing generated protein... This may take a few minutes."):
+    with st.spinner("Analyzing generated protein... This may take a several minutes. Stay tuned!"):
         progress_bar = st.progress(0)
         for i in range(100):
             progress_bar.progress(i + 1)
@@ -61,18 +61,14 @@ def perform_blast_analysis(sequence):
                 identity_percentage = (hsp.identities / alignment.length) * 100
                 
                 st.write(f"**Top Match:** {protein_name}")
-                st.write(f"**Organism:** {organism}")
+                st.write(f"**Organism Code:** {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)}")
@@ -113,7 +109,7 @@ def update(sequence, word1, word2, word3, sequence_length):
         st.write("Please try again later or contact support if the issue persists.")
 
 def share_on_twitter(word1, word2, word3, length, plddt):
-    tweet_text = f"I generated a new protein using GenPro2 by @WandsAI from the words '{word1}', '{word2}', and '{word3}' + sequence length {length}! It's Predictive Protein Score is: {plddt}%"
+    tweet_text = f"I just generated a new protein using #GenPro2 from the seed-words '{word1}', '{word2}', and '{word3}' + sequence length {length}! It's Predictive Protein Score is: {plddt}%.  -- made by @WandAI"
     tweet_url = f"https://twitter.com/intent/tweet?text={urllib.parse.quote(tweet_text)}"
     return tweet_url
 
@@ -151,8 +147,8 @@ if 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.subheader('plDDT Confidence Score')
+    st.write('plDDT is bench mark for scoring the confidence in prediction on a scale from 0-100%. 70% or more is really good!')
     plddt_score = int(info["b_value"] * 100)
     st.info(f'Average plDDT: {plddt_score}%')
  
@@ -162,32 +158,27 @@ if st.session_state.structure_info:
     <div style='background-color: #e6f2ff; padding: 10px; border-radius: 5px; font-size: 0.8em;'>
     <ol>
         <li>Take a screenshot of the protein structure above.</li>
-        <li>Click the 'Share on X' button below to open a pre-filled tweet.</li>
-        <li>Attach your screenshot to the tweet before posting.</li>
+        <li>Click the 'Share on X' button below to open a pre-filled protein seed-words and score.</li>
+        <li>Attach your screenshot to your post before posting.</li>
     </ol>
     </div>
     """, unsafe_allow_html=True)
     
-    st.write("1. Take a screenshot of the protein structure above.")
-    st.write("2. Click the 'Share Results' button below to open a pre-filled tweet.")
-    st.write("3. Attach your protein screenshot to the post.")
-    
     tweet_url = share_on_twitter(info["word1"], info["word2"], info["word3"], info["sequence_length"], plddt_score)
     st.markdown(f"[Share Results]({tweet_url})")
 
     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 to get more information about your generated protein.
+    ## Think might have discovered a useful and unique protein?  Here is what to do next:
+    1. Analyze your protein using (BLAST)](https://blast.ncbi.nlm.nih.gov/Blast.cgi?PROGRAM=blastp&PAGE_TYPE=BlastSearch&LINK_LOC=blasthome).
+    2. Download protein data and visit the [Protein Data Bank (PDB)](https://www.rcsb.org/) for known protein structures.
+    3. Compare your folded protein structure and data with known functional proteins.
+
+  
     **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)!
+    Enjoy exploring the world of protein sequences! 
     """)
 
-    # Moved Analyze and Download buttons to the bottom
+   
     col1, col2 = st.columns(2)
     with col1:
         if st.button('Analyze Protein'):
@@ -200,14 +191,4 @@ if st.session_state.structure_info:
             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 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)!
-    """)
+