Update app.py

app.py

@@ -1,4 +1,4 @@
-import streamlit as st
+ import streamlit as st
 from stmol import showmol
 import py3Dmol
 import requests
@@ -14,9 +14,39 @@ import urllib.parse
 
 urllib3.disable_warnings(urllib3.exceptions.InsecureRequestWarning)
 
+# Set page config and apply dark theme
 st.set_page_config(layout='wide')
-st.sidebar.title('🔮 GenPro2 Protein Generator, Structure Predictor, and Analysis Tool')
-st.sidebar.write('GenPro2 is an end-to-end protein sequence generator, structure predictor, and analysis tool based [*ESMFold*](https://esmatlas.com/about) and the ESM-2 language model.')
+st.markdown("""
+    <style>
+    body {
+        color: #fff;
+        background-color: #0e1117;
+    }
+    .stApp {
+        background-color: #0e1117;
+    }
+    .stTextInput > div > div > input {
+        color: #fff;
+        background-color: #262730;
+    }
+    .stNumberInput > div > div > input {
+        color: #fff;
+        background-color: #262730;
+    }
+    .stTextArea > div > div > textarea {
+        color: #fff;
+        background-color: #262730;
+    }
+    .stButton > button {
+        color: #fff;
+        background-color: #0e1117;
+        border: 1px solid #fff;
+    }
+    </style>
+    """, unsafe_allow_html=True)
+
+st.title('🔮 GenPro2 Protein Generator, Structure Predictor, and Analysis Tool')
+st.write('GenPro2 is an end-to-end protein sequence generator, structure predictor, and analysis tool 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')
@@ -64,11 +94,10 @@ def perform_blast_analysis(sequence):
                 st.write(f"**Organism Code:** {organism}")
                 st.write(f"**Sequence Identity:** {identity_percentage:.2f}%")
                
-                
                 # Fetch protein function (if available)
                 if hasattr(alignment, 'description') and alignment.description:
                     st.write(f"**Potential Function:** {alignment.description}")
-                
+            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)}")
@@ -109,7 +138,7 @@ 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 just generated a new protein using #GenPro2 from the seed-words '{word1}', '{word2}', and '{word3}' + sequence length {length}! It has a predicted protein score of: {plddt}%."
+    tweet_text = f"I just generated a new protein using #GenPro2 from the seed-words '{word1}', '{word2}', and '{word3}' + sequence length of {length}! It's plDDT Score: {plddt}%."
     tweet_url = f"https://twitter.com/intent/tweet?text={urllib.parse.quote(tweet_text)}"
     return tweet_url
 
@@ -121,25 +150,29 @@ if 'show_analyze_button' not in st.session_state:
 if 'structure_info' not in st.session_state:
     st.session_state.structure_info = None
 
-st.title("Word-Seeded Protein Sequence Generator, Structure Predictor, and Analysis Tool")
+# Main layout
+st.subheader("Generate Sequence from Words")
+col1, col2, col3 = st.columns(3)
+with col1:
+    word1 = st.text_input("Word 1")
+with col2:
+    word2 = st.text_input("Word 2")
+with col3:
+    word3 = st.text_input("Word 3")
 
-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)
+sequence_length = st.number_input("Sequence Length", min_value=50, max_value=400, value=100, step=10)
 
-if st.sidebar.button('Generate and Predict'):
+if st.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.")
+        st.text_area("Generated Sequence", sequence, height=100)
+        st.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.")
+        st.warning("Please enter all three words to generate a sequence.")
 
 # Display structure information if available
 if st.session_state.structure_info:
@@ -148,14 +181,14 @@ if st.session_state.structure_info:
     render_mol(info['pdb_string'])
     
     st.subheader('plDDT Confidence Score')
-    st.write('plDDT is a bench mark for scoring the confidence level in protein folding prediction based on a scale from 0-100%. 70% or more is really good!')
+    st.write('plDDT is a benchmark for scoring the confidence level in protein folding predictions based on a scale from 0-100%. 70% or more is good!')
     plddt_score = int(info["b_value"] * 100)
-    st.info(f'Average plDDT: {plddt_score}%')
+    st.info(f'Your plDDT score is: {plddt_score}%')
  
     st.subheader("Share your unique protein on X(Twitter)")
     
     st.markdown("""
-    <div style='background-color: #e6f2ff; padding: 10px; border-radius: 5px; font-size: 0.8em;'>
+    <div style='background-color: #262730; 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 post with your protein seed-words and score.</li>
@@ -180,18 +213,3 @@ if st.session_state.structure_info:
     **Remember, this folding is based on randomly generated sequences. Interpret the results with caution.
     Enjoy exploring the world of protein sequences!
     """)
-
-   
-    col1, col2 = st.columns(2)
-    with col1:
-        if st.button('Analyze Protein'):
-            perform_blast_analysis(st.session_state.sequence)
-    
-    with col2:
-        st.download_button(
-            label="Download PDB",
-            data=info['pdb_string'],
-            file_name='predicted.pdb',
-            mime='text/plain',
-        )
-