RajarshiMondal commited on
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9cb37e8
1 Parent(s): 096a065

Upload main.py

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  1. main.py +94 -2
main.py CHANGED
@@ -1,4 +1,3 @@
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-
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  import gradio as gr
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  import py3Dmol
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  from Bio.PDB import *
@@ -14,6 +13,7 @@ from transformMD import GNNTransformMD
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  import sys
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  import pytraj as pt
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  import pickle
 
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  # JavaScript functions
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  resid_hover = """function(atom,viewer) {{
@@ -180,6 +180,97 @@ def predict(pdb_code, pdb_file):
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  data = []
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  for i in range(adaptability.shape[0]):
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  data.append([i, atom_mapping[atoms_protein.iloc[i, atoms_protein.columns.get_loc("element")] - 1], atoms_protein.iloc[i, atoms_protein.columns.get_loc("x")],atoms_protein.iloc[i, atoms_protein.columns.get_loc("y")],atoms_protein.iloc[i, atoms_protein.columns.get_loc("z")],adaptability[i]])
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@@ -209,6 +300,7 @@ def predict(pdb_code, pdb_file):
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  callback = gr.CSVLogger()
 
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  def run():
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  with gr.Blocks() as demo:
@@ -236,4 +328,4 @@ def run():
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  if __name__ == "__main__":
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- run()
 
 
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  import gradio as gr
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  import py3Dmol
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  from Bio.PDB import *
 
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  import sys
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  import pytraj as pt
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  import pickle
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+ import nglview as nv
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  # JavaScript functions
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  resid_hover = """function(atom,viewer) {{
 
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  data = []
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+ for i in range(10):
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+ data.append([i, atom_mapping[atoms_protein.iloc[i, atoms_protein.columns.get_loc("element")] - 1], atoms_protein.iloc[topN_ind[i], atoms_protein.columns.get_loc("x")],
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+ atoms_protein.iloc[topN_ind[i], atoms_protein.columns.get_loc("y")],
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+ atoms_protein.iloc[topN_ind[i], atoms_protein.columns.get_loc("z")],
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+ adaptability[topN_ind[i]]
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+ ])
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+
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+ pdb = open(pdb_file.name, "r").read()
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+
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+ """ NGL
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+ view = nv.NGLWidget()
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+ view._remote_call("setSize", target="Widget", args=["800px", "600px"])
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+ view.add_pdbstr(pdb, defaultRepresentation=True)
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+ """
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+
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+ view = py3Dmol.view(width=600, height=400)
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+ view.setBackgroundColor('white')
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+ view.addModel(pdb, "pdb")
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+ view.setStyle({'stick': {'colorscheme': {'prop': 'resi', 'C': 'turquoise'}}})
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+
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+ for i in range(10):
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+ view.addSphere({'center':{'x':atoms_protein.iloc[topN_ind[i], atoms_protein.columns.get_loc("x")], 'y':atoms_protein.iloc[topN_ind[i], atoms_protein.columns.get_loc("y")],'z':atoms_protein.iloc[topN_ind[i], atoms_protein.columns.get_loc("z")]},'radius':adaptability[topN_ind[i]]/1.5,'color':'orange','alpha':0.75})
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+
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+ # Add lighting and shading options to the view object:
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+ view.setStyle({'stick': {'colorscheme': {'prop': 'resi', 'C': 'turquoise'}}})
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+ view.setStyle({'sphere': {}})
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+ view.addLight([0, 0, 10], [1, 1, 1], 1) # Add directional light from the z-axis
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+ view.setSpecular(0.5) # Adjust the specular lighting effect
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+ view.setAmbient(0.5) # Adjust the ambient lighting effect
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+
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+ view.zoomTo()
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+ view.rotate(180, "y") # Rotate the structure by 180 degrees along the y-axis
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+ # Add animation options to the view object:
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+ view.animate({'loop': 'forward', 'reps': 2}) # Animate the visualization to loop forward 2 times
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+ output = view._make_html().replace("'", '"')
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+
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+ """ NGLviewer
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+ output = view.render_notebook()
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+ """
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+
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+ x = f"""<!DOCTYPE html><html> {output} </html>""" # do not use ' in this input
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+ return f"""<iframe style="width: 100%; height:420px" name="result" allow="midi; geolocation; microphone; camera;
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+ display-capture; encrypted-media;" sandbox="allow-modals allow-forms
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+ allow-scripts allow-same-origin allow-popups
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+ allow-top-navigation-by-user-activation allow-downloads" allowfullscreen=""
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+ allowpaymentrequest="" frameborder="0" srcdoc='{x}'></iframe>""", pd.DataFrame(data, columns=['index','element','x','y','z','Adaptability'])
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+
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+ """ NGLviewer
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+ return output, pd.DataFrame(data, columns=['index','element','x','y','z','Adaptability'])
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+ """
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+
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+ callback = gr.CSVLogger()
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+
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+ """
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+ def predict(pdb_code, pdb_file):
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+ #path_to_pdb = get_pdb(pdb_code=pdb_code, filepath=pdb_file)
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+
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+ #pdb = open(path_to_pdb, "r").read()
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+ # switch to misato env if not running from container
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+
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+ pdbid = get_pdbid_from_filename(pdb_file.name)
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+ mdh5_file = "inference_for_md.hdf5"
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+ mappath = "/maps"
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+ mask = "!@H="
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+ preprocess(pdbid=pdbid, ouputfile=mdh5_file, mask=mask, mappath=mappath)
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+
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+ md_H5File = h5py.File(mdh5_file)
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+
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+ column_names = ["x", "y", "z", "element"]
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+ atoms_protein = pd.DataFrame(columns = column_names)
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+ cutoff = md_H5File[pdbid]["molecules_begin_atom_index"][:][-1] # cutoff defines protein atoms
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+
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+ atoms_protein["x"] = md_H5File[pdbid]["atoms_coordinates_ref"][:][:cutoff, 0]
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+ atoms_protein["y"] = md_H5File[pdbid]["atoms_coordinates_ref"][:][:cutoff, 1]
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+ atoms_protein["z"] = md_H5File[pdbid]["atoms_coordinates_ref"][:][:cutoff, 2]
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+
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+ atoms_protein["element"] = md_H5File[pdbid]["atoms_element"][:][:cutoff]
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+
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+ item = {}
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+ item["scores"] = 0
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+ item["id"] = pdbid
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+ item["atoms_protein"] = atoms_protein
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+
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+ transform = GNNTransformMD()
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+ data_item = transform(item)
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+ adaptability = model(data_item)
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+ adaptability = adaptability.detach().numpy()
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+
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+ data = []
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+
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+
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  for i in range(adaptability.shape[0]):
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  data.append([i, atom_mapping[atoms_protein.iloc[i, atoms_protein.columns.get_loc("element")] - 1], atoms_protein.iloc[i, atoms_protein.columns.get_loc("x")],atoms_protein.iloc[i, atoms_protein.columns.get_loc("y")],atoms_protein.iloc[i, atoms_protein.columns.get_loc("z")],adaptability[i]])
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  callback = gr.CSVLogger()
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+ """
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  def run():
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  with gr.Blocks() as demo:
 
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  if __name__ == "__main__":
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+ run()