Hi everyone, as part of a series of shared components, I will share a new component that we integrated Molstar (A modern web-based open-source toolkit for visualisation and analysis of large-scale molecular data.) into Streamlit in a real project a year ago. It can basically meet the visualization needs of proteins, molecules, and other scenarios, making it perfect for building some small research tools in the field of biological sciences. The project address:
Install
pip install streamlit-molstar
Basic Usage
Show Molecule
Protein with Traj
import streamlit as st
from streamlit_molstar import st_molstar, st_molstar_rcsb, st_molstar_remote
#st_molstar_rcsb('1LOL', key='xx')
#st_molstar_remote("https://files.rcsb.org/view/1LOL.cif", key='sds')
#st_molstar('examples/complex.pdb',key='3')
st_molstar('examples/complex.pdb', 'examples/complex.xtc', key='4')
Protein & Pocket
Select pocket from local protein (pockets predicted using p2rank)
import streamlit as st
from streamlit_molstar.pocket import select_pocket_from_local_protein
selected = select_pocket_from_local_protein("examples/pocket/protein.pdb", prank_home='/Users/wfluo/Downloads/p2rank_2.4/')
if selected:
protein_file_path, pocket = selected
st.write('Protein Path: ', protein_file_path)
st.write('Selected Pocket: ', pocket)
Select pocket from uploaded protein (pockets predicted using p2rank)
import streamlit as st
from streamlit_molstar import st_molstar, st_molstar_rcsb, st_molstar_remote
selected = select_pocket_from_upload_protein(prank_home='/Users/wfluo/Downloads/p2rank_2.4/')
if selected:
protein_file_path, pocket = selected
st.write('Protein Path: ', protein_file_path)
st.write('Selected Pocket: ', pocket)
Docking
Show docking result with ground truth
import streamlit as st
from streamlit_molstar.docking import st_molstar_docking
st_molstar_docking('examples/docking/2zy1_protein.pdb',
'examples/docking/docking.2zy1.0.sdf',
gt_ligand_file_path='examples/docking/2zy1_ligand.sdf', key="5", height=240)
Auto files
import streamlit as st
from streamlit_molstar.auto import st_molstar_auto
import streamlit as st
st.set_page_config(layout="wide")
st.write("from remote url")
files = ["https://files.rcsb.org/download/3PTB.pdb", "https://files.rcsb.org/download/1LOL.pdb"]
st_molstar_auto(files, key="6", height="320px")
st.write("from local file")
files = ['examples/7bcq.pdb', "examples/7bcq.mrc"]
st_molstar_auto(files, key="7", height="320px")
In addition, stmol is also a very nice solution for addressing molecular rendering issues, but the two projects integrate different visualization engines, with Streamlit-Molstar providing more complex features for real-life scenarios.
