Spaces:
Sleeping
Sleeping
Added an option to select anchor atoms
Browse files- app.py +102 -55
- output.py +91 -3
- src/generation.py +38 -0
app.py
CHANGED
@@ -9,12 +9,30 @@ import output
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from rdkit import Chem
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from src import const
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from src.visualizer import save_xyz_file
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from src.datasets import get_dataloader, collate_with_fragment_edges, parse_molecule
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from src.lightning import DDPM
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from src.linker_size_lightning import SizeClassifier
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N_SAMPLES = 5
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parser = argparse.ArgumentParser()
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parser.add_argument('--ip', type=str, default=None)
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@@ -33,13 +51,22 @@ if not os.path.exists(size_gnn_path):
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size_nn = SizeClassifier.load_from_checkpoint('models/geom_size_gnn.ckpt', map_location=device).eval().to(device)
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print('Loaded SizeGNN model')
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link = '
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print('
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def read_molecule_content(path):
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with open(path, "r") as f:
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@@ -60,7 +87,7 @@ def read_molecule(path):
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def show_input(input_file):
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if input_file is None:
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return ['', gr.Radio.update(visible=False, value='Sample 1')]
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if isinstance(input_file, str):
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path = input_file
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else:
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@@ -70,7 +97,8 @@ def show_input(input_file):
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msg = output.INVALID_FORMAT_MSG.format(extension=extension)
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return [
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output.IFRAME_TEMPLATE.format(html=msg),
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gr.Radio.update(visible=False)
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]
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try:
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@@ -78,17 +106,22 @@ def show_input(input_file):
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except Exception as e:
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return [
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f'Could not read the molecule: {e}',
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gr.Radio.update(visible=False)
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]
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html = output.INITIAL_RENDERING_TEMPLATE.format(molecule=molecule, fmt=extension)
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return [
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output.IFRAME_TEMPLATE.format(html=html),
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gr.Radio.update(visible=False)
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]
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def draw_sample(idx, out_files):
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in_file = out_files[0]
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in_sdf = in_file if isinstance(in_file, str) else in_file.name
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@@ -97,24 +130,43 @@ def draw_sample(idx, out_files):
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input_fragments_content = read_molecule_content(in_sdf)
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generated_molecule_content = read_molecule_content(out_sdf)
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html = output.SAMPLES_RENDERING_TEMPLATE.format(
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fragments=input_fragments_content,
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fragments_fmt=
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molecule=generated_molecule_content,
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molecule_fmt=
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)
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return output.IFRAME_TEMPLATE.format(html=html)
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def generate(input_file, n_steps, n_atoms):
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if input_file is None:
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return
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path = input_file.name
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extension = path.split('.')[-1]
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if extension not in ['sdf', 'pdb', 'mol', 'mol2']:
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msg = output.INVALID_FORMAT_MSG.format(extension=extension)
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return output.IFRAME_TEMPLATE.format(html=msg)
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try:
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molecule = read_molecule(path)
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@@ -122,16 +174,22 @@ def generate(input_file, n_steps, n_atoms):
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name = '.'.join(path.split('/')[-1].split('.')[:-1])
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inp_sdf = f'results/input_{name}.sdf'
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except Exception as e:
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if molecule.GetNumAtoms() > 50:
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with Chem.SDWriter(inp_sdf) as w:
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w.write(molecule)
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positions, one_hot, charges = parse_molecule(molecule, is_geom=True)
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anchors = np.zeros_like(charges)
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fragment_mask = np.ones_like(charges)
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linker_mask = np.zeros_like(charges)
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print('Read and parsed molecule')
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@@ -151,7 +209,6 @@ def generate(input_file, n_steps, n_atoms):
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print('Created dataloader')
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ddpm.edm.T = n_steps
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assert ddpm.center_of_mass == 'fragments'
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if n_atoms == 0:
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def sample_fn(_data):
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@@ -169,34 +226,21 @@ def generate(input_file, n_steps, n_atoms):
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return torch.ones(_data['positions'].shape[0], device=device, dtype=torch.long) * n_atoms
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for data in dataloader:
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x = x + mean * node_mask
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names = [f'output_{i+1}_{name}' for i in range(N_SAMPLES)]
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save_xyz_file('results', h, x, node_mask, names=names, is_geom=True, suffix='')
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print('Saved XYZ files')
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break
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out_files = []
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for i in range(N_SAMPLES):
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out_xyz = f'results/output_{i+1}_{name}_.xyz'
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out_sdf = f'results/output_{i+1}_{name}_.sdf'
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subprocess.run(f'obabel {out_xyz} -O {out_sdf}', shell=True)
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out_files.append(out_sdf)
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print('Converted to SDF')
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return [
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draw_sample(
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gr.Radio.update(visible=True,
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]
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@@ -215,6 +259,7 @@ with demo:
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)
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with gr.Box():
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with gr.Row():
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with gr.Column():
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gr.Markdown('## Input Fragments')
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gr.Markdown('Upload the file with 3D-coordinates of the input fragments in .pdb, .mol2 or .sdf format:')
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@@ -238,11 +283,11 @@ with demo:
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output_files = gr.File(file_count='multiple', label='Output Files', interactive=False)
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with gr.Column():
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gr.Markdown('## Visualization')
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samples = gr.Radio(
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choices=['Sample 1', 'Sample 2', 'Sample 3', 'Sample 4', 'Sample 5'],
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value='Sample 1',
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type='
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show_label=False,
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visible=False,
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interactive=True,
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@@ -252,27 +297,29 @@ with demo:
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input_file.change(
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fn=show_input,
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inputs=[input_file],
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outputs=[visualization, samples],
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)
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input_file.clear(
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fn=lambda: [None, '', gr.Radio.update(visible=False)],
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inputs=[],
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outputs=[input_file, visualization, samples],
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)
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examples.click(
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fn=lambda idx: [f'examples/example_{idx+1}.sdf', 10, 0] + show_input(f'examples/example_{idx+1}.sdf'),
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inputs=[examples],
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outputs=[input_file, n_steps, n_atoms, visualization, samples]
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)
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button.click(
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fn=generate,
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inputs=[input_file, n_steps, n_atoms],
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outputs=[visualization, output_files, samples],
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)
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samples.change(
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fn=draw_sample,
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inputs=[samples, output_files],
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outputs=[visualization],
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)
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demo.launch(server_name=args.ip)
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from rdkit import Chem
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from src import const
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from src.datasets import get_dataloader, collate_with_fragment_edges, parse_molecule
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from src.lightning import DDPM
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from src.linker_size_lightning import SizeClassifier
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from src.generation import N_SAMPLES, generate_linkers, try_to_convert_to_sdf
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MODELS_METADATA = {
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'geom_difflinker': {
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'link': 'https://zenodo.org/record/7121300/files/geom_difflinker.ckpt?download=1',
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'path': 'models/geom_difflinker.ckpt',
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},
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'geom_difflinker_given_anchors': {
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'link': 'https://zenodo.org/record/7775568/files/geom_difflinker_given_anchors.ckpt?download=1',
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'path': 'models/geom_difflinker_given_anchors.ckpt',
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},
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'pockets_difflinker': {
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'link': 'https://zenodo.org/record/7775568/files/pockets_difflinker_full_no_anchors.ckpt?download=1',
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'path': 'models/pockets_difflinker.ckpt',
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},
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'pockets_difflinker_given_anchors': {
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'link': 'https://zenodo.org/record/7775568/files/pockets_difflinker_full.ckpt?download=1',
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'path': 'models/pockets_difflinker_given_anchors.ckpt',
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},
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}
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parser = argparse.ArgumentParser()
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parser.add_argument('--ip', type=str, default=None)
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size_nn = SizeClassifier.load_from_checkpoint('models/geom_size_gnn.ckpt', map_location=device).eval().to(device)
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print('Loaded SizeGNN model')
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diffusion_models = {}
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for model_name, metadata in MODELS_METADATA.items():
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link = metadata['link']
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diffusion_path = metadata['path']
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if not os.path.exists(diffusion_path):
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print(f'Downloading {model_name}...')
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subprocess.run(f'wget {link} -O {diffusion_path}', shell=True)
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diffusion_models[model_name] = DDPM.load_from_checkpoint(diffusion_path, map_location=device).eval().to(device)
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print(f'Loaded model {model_name}')
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print(os.curdir)
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print(os.path.abspath(os.curdir))
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print(os.listdir(os.curdir))
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def read_molecule_content(path):
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with open(path, "r") as f:
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def show_input(input_file):
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if input_file is None:
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return ['', gr.Radio.update(visible=False, value='Sample 1'), None]
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if isinstance(input_file, str):
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path = input_file
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else:
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msg = output.INVALID_FORMAT_MSG.format(extension=extension)
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return [
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output.IFRAME_TEMPLATE.format(html=msg),
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gr.Radio.update(visible=False),
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None,
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]
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try:
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except Exception as e:
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return [
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f'Could not read the molecule: {e}',
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gr.Radio.update(visible=False),
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None,
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]
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html = output.INITIAL_RENDERING_TEMPLATE.format(molecule=molecule, fmt=extension)
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return [
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output.IFRAME_TEMPLATE.format(html=html),
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gr.Radio.update(visible=False),
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None,
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]
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def draw_sample(idx, out_files):
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if isinstance(idx, str):
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idx = int(idx.strip().split(' ')[-1]) - 1
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in_file = out_files[0]
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in_sdf = in_file if isinstance(in_file, str) else in_file.name
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input_fragments_content = read_molecule_content(in_sdf)
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generated_molecule_content = read_molecule_content(out_sdf)
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fragments_fmt = in_sdf.split('.')[-1]
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molecule_fmt = out_sdf.split('.')[-1]
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html = output.SAMPLES_RENDERING_TEMPLATE.format(
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fragments=input_fragments_content,
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fragments_fmt=fragments_fmt,
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molecule=generated_molecule_content,
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molecule_fmt=molecule_fmt,
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)
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return output.IFRAME_TEMPLATE.format(html=html)
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def generate(input_file, n_steps, n_atoms, radio_samples, selected_atoms):
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# Parsing selected atoms (javascript output)
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selected_atoms = selected_atoms.strip()
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if selected_atoms == '':
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selected_atoms = []
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else:
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selected_atoms = list(map(int, selected_atoms.split(',')))
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# Selecting model
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if len(selected_atoms) == 0:
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selected_model_name = 'geom_difflinker'
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else:
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selected_model_name = 'geom_difflinker_given_anchors'
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if input_file is None:
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return [None, None, None, None]
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print(f'Start generating with model {selected_model_name}, selected_atoms:', selected_atoms)
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ddpm = diffusion_models[selected_model_name]
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path = input_file.name
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extension = path.split('.')[-1]
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if extension not in ['sdf', 'pdb', 'mol', 'mol2']:
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msg = output.INVALID_FORMAT_MSG.format(extension=extension)
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return [output.IFRAME_TEMPLATE.format(html=msg), None, None, None]
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try:
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molecule = read_molecule(path)
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name = '.'.join(path.split('/')[-1].split('.')[:-1])
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inp_sdf = f'results/input_{name}.sdf'
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except Exception as e:
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error = f'Could not read the molecule: {e}'
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msg = output.ERROR_FORMAT_MSG.format(message=error)
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return [output.IFRAME_TEMPLATE.format(html=msg), None, None, None]
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if molecule.GetNumAtoms() > 50:
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error = f'Too large molecule: upper limit is 50 heavy atoms'
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msg = output.ERROR_FORMAT_MSG.format(message=error)
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return [output.IFRAME_TEMPLATE.format(html=msg), None, None, None]
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with Chem.SDWriter(inp_sdf) as w:
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w.write(molecule)
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positions, one_hot, charges = parse_molecule(molecule, is_geom=True)
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anchors = np.zeros_like(charges)
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anchors[selected_atoms] = 1
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fragment_mask = np.ones_like(charges)
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linker_mask = np.zeros_like(charges)
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print('Read and parsed molecule')
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print('Created dataloader')
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ddpm.edm.T = n_steps
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if n_atoms == 0:
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def sample_fn(_data):
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return torch.ones(_data['positions'].shape[0], device=device, dtype=torch.long) * n_atoms
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for data in dataloader:
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try:
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generate_linkers(ddpm=ddpm, data=data, sample_fn=sample_fn, name=name)
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except Exception as e:
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error = f'Caught exception while generating linkers: {e}'
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msg = output.ERROR_FORMAT_MSG.format(message=error)
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return [output.IFRAME_TEMPLATE.format(html=msg), None, None, None]
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out_files = try_to_convert_to_sdf(name)
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out_files = [inp_sdf] + out_files
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return [
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draw_sample(radio_samples, out_files),
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out_files,
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gr.Radio.update(visible=True),
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None
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]
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)
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with gr.Box():
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with gr.Row():
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hidden = gr.Textbox(visible=False)
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with gr.Column():
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gr.Markdown('## Input Fragments')
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gr.Markdown('Upload the file with 3D-coordinates of the input fragments in .pdb, .mol2 or .sdf format:')
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output_files = gr.File(file_count='multiple', label='Output Files', interactive=False)
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with gr.Column():
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gr.Markdown('## Visualization')
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gr.Markdown('**Hint:** click on atoms to select anchor points (optionally)')
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samples = gr.Radio(
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choices=['Sample 1', 'Sample 2', 'Sample 3', 'Sample 4', 'Sample 5'],
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value='Sample 1',
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type='value',
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show_label=False,
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visible=False,
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interactive=True,
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input_file.change(
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fn=show_input,
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inputs=[input_file],
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outputs=[visualization, samples, hidden],
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)
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input_file.clear(
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fn=lambda: [None, '', gr.Radio.update(visible=False), None],
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inputs=[],
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305 |
+
outputs=[input_file, visualization, samples, hidden],
|
306 |
)
|
307 |
examples.click(
|
308 |
fn=lambda idx: [f'examples/example_{idx+1}.sdf', 10, 0] + show_input(f'examples/example_{idx+1}.sdf'),
|
309 |
inputs=[examples],
|
310 |
+
outputs=[input_file, n_steps, n_atoms, visualization, samples, hidden]
|
311 |
)
|
312 |
button.click(
|
313 |
fn=generate,
|
314 |
+
inputs=[input_file, n_steps, n_atoms, samples, hidden],
|
315 |
+
outputs=[visualization, output_files, samples, hidden],
|
316 |
+
_js=output.RETURN_SELECTION_JS,
|
317 |
)
|
318 |
samples.change(
|
319 |
fn=draw_sample,
|
320 |
inputs=[samples, output_files],
|
321 |
outputs=[visualization],
|
322 |
)
|
323 |
+
demo.load(_js=output.STARTUP_JS)
|
324 |
|
325 |
demo.launch(server_name=args.ip)
|
output.py
CHANGED
@@ -22,9 +22,42 @@ INITIAL_RENDERING_TEMPLATE = """<!DOCTYPE html>
|
|
22 |
$(document).ready(function() {{
|
23 |
let element = $("#container");
|
24 |
let config = {{ backgroundColor: "white" }};
|
25 |
-
let viewer = $3Dmol.createViewer(
|
26 |
-
|
27 |
-
viewer.
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
28 |
viewer.zoomTo();
|
29 |
viewer.zoom(0.7);
|
30 |
viewer.render();
|
@@ -113,8 +146,63 @@ INVALID_FORMAT_MSG = """
|
|
113 |
</html>
|
114 |
"""
|
115 |
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
|
|
116 |
|
117 |
IFRAME_TEMPLATE = """<iframe style="width: 100%; height: 700px" name="result" allow="midi; geolocation; microphone; camera;
|
118 |
display-capture; encrypted-media;" sandbox="allow-modals allow-forms allow-scripts allow-same-origin allow-popups
|
119 |
allow-top-navigation-by-user-activation allow-downloads" allowfullscreen=""
|
120 |
allowpaymentrequest="" frameborder="0" srcdoc='{html}'></iframe>"""
|
|
|
|
|
|
|
|
|
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|
|
|
|
|
|
|
|
|
|
|
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|
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|
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|
|
|
|
|
|
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|
|
|
|
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|
|
|
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|
|
|
|
|
|
|
|
|
22 |
$(document).ready(function() {{
|
23 |
let element = $("#container");
|
24 |
let config = {{ backgroundColor: "white" }};
|
25 |
+
let viewer = $3Dmol.createViewer(element, config);
|
26 |
+
let defaultStyle = {{ stick: {{ colorscheme: "greenCarbon" }} }};
|
27 |
+
viewer.addModel(`{molecule}`, "{fmt}");
|
28 |
+
viewer.getModel(0).setStyle(defaultStyle);
|
29 |
+
// document.cookie = document.cookie + "|selected_atoms:";
|
30 |
+
|
31 |
+
viewer.getModel(0).setClickable(
|
32 |
+
{{}},
|
33 |
+
true,
|
34 |
+
function (_atom, _viewer, _event, _container) {{
|
35 |
+
if (!_atom.isClicked) {{
|
36 |
+
_atom.isClicked = true;
|
37 |
+
_viewer.addStyle(
|
38 |
+
{{"serial": _atom.serial, "model": 0}},
|
39 |
+
{{"sphere": {{"color": "magenta", "radius": 0.4}} }}
|
40 |
+
);
|
41 |
+
// document.cookie = document.cookie + "atom_" + String(_atom.serial) + "-";
|
42 |
+
window.parent.postMessage({{
|
43 |
+
name: "atom_selection",
|
44 |
+
data: {{"atom": _atom.serial, "add": true}}
|
45 |
+
// data: JSON.stringify({{"add": _atom.serial}})
|
46 |
+
}}, "*");
|
47 |
+
}} else {{
|
48 |
+
delete _atom.isClicked;
|
49 |
+
_viewer.setStyle({{"serial": _atom.serial, "model": 0}}, defaultStyle);
|
50 |
+
// document.cookie = document.cookie.replace("atom_" + String(_atom.serial) + "-", "");
|
51 |
+
window.parent.postMessage({{
|
52 |
+
name: "atom_selection",
|
53 |
+
data: {{"atom": _atom.serial, "add": false}}
|
54 |
+
// data: JSON.stringify({{"remove": _atom.serial}})
|
55 |
+
}}, "*");
|
56 |
+
}}
|
57 |
+
_viewer.render();
|
58 |
+
}}
|
59 |
+
);
|
60 |
+
|
61 |
viewer.zoomTo();
|
62 |
viewer.zoom(0.7);
|
63 |
viewer.render();
|
|
|
146 |
</html>
|
147 |
"""
|
148 |
|
149 |
+
ERROR_FORMAT_MSG = """
|
150 |
+
<!DOCTYPE html>
|
151 |
+
<html>
|
152 |
+
<head>
|
153 |
+
<meta http-equiv="content-type" content="text/html; charset=UTF-8" />
|
154 |
+
<style>
|
155 |
+
body{{
|
156 |
+
font-family:sans-serif
|
157 |
+
}}
|
158 |
+
</style>
|
159 |
+
</head>
|
160 |
+
|
161 |
+
<body>
|
162 |
+
<h3>Error:</h3>
|
163 |
+
{message}
|
164 |
+
</body>
|
165 |
+
</html>
|
166 |
+
"""
|
167 |
+
|
168 |
|
169 |
IFRAME_TEMPLATE = """<iframe style="width: 100%; height: 700px" name="result" allow="midi; geolocation; microphone; camera;
|
170 |
display-capture; encrypted-media;" sandbox="allow-modals allow-forms allow-scripts allow-same-origin allow-popups
|
171 |
allow-top-navigation-by-user-activation allow-downloads" allowfullscreen=""
|
172 |
allowpaymentrequest="" frameborder="0" srcdoc='{html}'></iframe>"""
|
173 |
+
|
174 |
+
|
175 |
+
STARTUP_JS = """
|
176 |
+
() => {
|
177 |
+
window.selected_elements = {}
|
178 |
+
|
179 |
+
function handleMessage(event) {
|
180 |
+
// console.log("New message: ", event.data)
|
181 |
+
let atom = event.data.data["atom"];
|
182 |
+
let add = event.data.data["add"];
|
183 |
+
console.log("add: ", add, " atom: ", atom);
|
184 |
+
window.selected_elements[atom] = add;
|
185 |
+
}
|
186 |
+
|
187 |
+
window.addEventListener("message", handleMessage);
|
188 |
+
console.log("Listener Added");
|
189 |
+
}
|
190 |
+
"""
|
191 |
+
|
192 |
+
RETURN_SELECTION_JS = """
|
193 |
+
(input_file, n_steps, n_atoms, samples, hidden) => {
|
194 |
+
let selected = []
|
195 |
+
for (const [atom, add] of Object.entries(window.selected_elements)) {
|
196 |
+
if (add) {
|
197 |
+
console.log("Adding atom ", atom);
|
198 |
+
selected.push(String(atom));
|
199 |
+
window.parent.postMessage({
|
200 |
+
name: "atom_selection",
|
201 |
+
data: {"atom": parseInt(atom), "add": false}
|
202 |
+
}, "*");
|
203 |
+
}
|
204 |
+
}
|
205 |
+
console.log("Finished parsing");
|
206 |
+
return [input_file, n_steps, n_atoms, samples, selected.join(",")];
|
207 |
+
}
|
208 |
+
"""
|
src/generation.py
ADDED
@@ -0,0 +1,38 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
import os.path
|
2 |
+
import subprocess
|
3 |
+
import torch
|
4 |
+
|
5 |
+
from src.visualizer import save_xyz_file
|
6 |
+
|
7 |
+
N_SAMPLES = 5
|
8 |
+
|
9 |
+
|
10 |
+
def generate_linkers(ddpm, data, sample_fn, name):
|
11 |
+
chain, node_mask = ddpm.sample_chain(data, sample_fn=sample_fn, keep_frames=1)
|
12 |
+
print('Generated linker')
|
13 |
+
x = chain[0][:, :, :ddpm.n_dims]
|
14 |
+
h = chain[0][:, :, ddpm.n_dims:]
|
15 |
+
|
16 |
+
# Put the molecule back to the initial orientation
|
17 |
+
pos_masked = data['positions'] * data['fragment_mask']
|
18 |
+
N = data['fragment_mask'].sum(1, keepdims=True)
|
19 |
+
mean = torch.sum(pos_masked, dim=1, keepdim=True) / N
|
20 |
+
x = x + mean * node_mask
|
21 |
+
|
22 |
+
names = [f'output_{i + 1}_{name}' for i in range(N_SAMPLES)]
|
23 |
+
save_xyz_file('results', h, x, node_mask, names=names, is_geom=True, suffix='')
|
24 |
+
print('Saved XYZ files')
|
25 |
+
|
26 |
+
|
27 |
+
def try_to_convert_to_sdf(name):
|
28 |
+
out_files = []
|
29 |
+
for i in range(N_SAMPLES):
|
30 |
+
out_xyz = f'results/output_{i + 1}_{name}_.xyz'
|
31 |
+
out_sdf = f'results/output_{i + 1}_{name}_.sdf'
|
32 |
+
subprocess.run(f'obabel {out_xyz} -O {out_sdf}', shell=True)
|
33 |
+
if os.path.exists(out_sdf):
|
34 |
+
out_files.append(out_sdf)
|
35 |
+
else:
|
36 |
+
out_files.append(out_xyz)
|
37 |
+
|
38 |
+
return out_files
|