Update app.py

app.py

@@ -404,7 +404,7 @@ else:
                 expander.markdown(
                 """<span style="word-wrap:break-word;">Contact prediction is based on a logistic regression over the model's attention maps. This methodology is based on ICLR 2021 paper, Transformer protein language models are unsupervised structure learners. (Rao et al. 2020)The MSA Transformer (ESM-MSA-1) takes a multiple sequence alignment (MSA) as input, and uses the tied row self-attention maps in the same way.</span>
                 """, unsafe_allow_html=True)
-        elif option == 'search the database':
+        elif option == 'search the database for similar proteins':
             sequence = st.text_input('protein sequence', '')
             st.write('Try an example:')
             if st.button('Cas9 Enzyme'):
@@ -436,7 +436,7 @@ else:
                     show_protein_structure(result_temp_seq[4])
                 
 
-        elif option == 'activity prediction':
+        elif option == 'activity prediction with similar proteins':
             st.markdown('we predict the biological activity of mutations of a protein, using fixed embeddings from ESM.')
             # st.text('we predict the biological activity of mutations of a protein, using fixed embeddings from ESM.')
             sequence = st.text_input('protein sequence', '')