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diffdock

Running on T4

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Simon Duerr commited on Oct 10, 2022

Commit

334e3a1

•

1 Parent(s): d40328c

add test set examples

Browse files

Files changed (9) hide show

app.py +135 -49
esm/LICENSE +21 -0
esm/scripts/extract.py +1 -1
examples/6ahs_ligand.sdf +97 -0
examples/6ahs_protein_processed.pdb +0 -0
examples/6o5u_ligand.sdf +154 -0
examples/6o5u_protein_processed.pdb +0 -0
examples/6w70.pdb +0 -0
examples/6w70_ligand.sdf +170 -0

app.py CHANGED Viewed

@@ -15,6 +15,10 @@ from rdkit import RDLogger
 from rdkit.Chem import MolFromSmiles, AddHs
 from torch_geometric.loader import DataLoader
 import yaml
 print(torch.__version__)
 os.makedirs("data/esm2_output", exist_ok=True)
@@ -41,6 +45,8 @@ with open(f"workdir/paper_score_model/model_parameters.yml") as f:
 with open(f"workdir/paper_confidence_model/model_parameters.yml") as f:
     confidence_args = Namespace(**yaml.full_load(f))
 t_to_sigma = partial(t_to_sigma_compl, args=score_model_args)
 model = get_model(score_model_args, device, t_to_sigma=t_to_sigma, no_parallel=True)
@@ -66,30 +72,17 @@ state_dict = torch.load(
 confidence_model.load_state_dict(state_dict, strict=True)
 confidence_model = confidence_model.to(device)
 confidence_model.eval()
-tr_schedule = get_t_schedule(inference_steps=10)
-rot_schedule = tr_schedule
-tor_schedule = tr_schedule
-print("common t schedule", tr_schedule)
-failures, skipped, confidences_list, names_list, run_times, min_self_distances_list = (
-    0,
-    0,
-    [],
-    [],
-    [],
-    [],
-)
-N = 10
 def get_pdb(pdb_code="", filepath=""):
-    if pdb_code is None or pdb_code == "":
-        try:
-            return filepath.name
-        except AttributeError as e:
             return None
-    else:
-        os.system(f"wget -qnc https://files.rcsb.org/view/{pdb_code}.pdb")
-        return f"{pdb_code}.pdb"
 def get_ligand(smiles="", filepath=""):
@@ -111,11 +104,23 @@ def read_mol(molpath):
     return mol
-def molecule(input_pdb, ligand_pdb):
     structure = read_mol(input_pdb)
     mol = read_mol(ligand_pdb)
     x = (
         """<!DOCTYPE html>
         <html>
@@ -134,11 +139,27 @@ def molecule(input_pdb, ligand_pdb):
     .mol-container select{
         background-image:None;
     }
     </style>
     <script src="https://3Dmol.csb.pitt.edu/build/3Dmol-min.js"></script>
     </head>
     <body>
-     <button id="startanimation">Replay diffusion process</button>
     <div id="container" class="mol-container"></div>
             <script>
@@ -147,7 +168,10 @@ def molecule(input_pdb, ligand_pdb):
         + """`
         let structure = `"""
         + structure
-        + """`
              let viewer = null;
@@ -163,6 +187,9 @@ def molecule(input_pdb, ligand_pdb):
                 viewer.animate({loop: "forward",reps: 1});
                 viewer.getModel(1).setStyle({stick:{colorscheme:"magentaCarbon"}});
                 viewer.render();
               })
@@ -189,18 +216,14 @@ def esm(protein_path, out_file):
     esm_embedding_prep(out_file, protein_path)
     # create args object with defaults
     os.environ["HOME"] = "esm/model_weights"
-    print("calling ", sys.executable)
-    print("datadir", os.listdir("data"))
-    print(os.environ)
-    print(torch.__file__)
     subprocess.call(
         f"python esm/scripts/extract.py esm2_t33_650M_UR50D {out_file} data/esm2_output --repr_layers 33 --include per_tok",
         shell=True,
-        env=os.environ
     )
-def update(inp, file, ligand_inp, ligand_file):
     pdb_path = get_pdb(inp, file)
     ligand_path = get_ligand(ligand_inp, ligand_file)
@@ -208,7 +231,26 @@ def update(inp, file, ligand_inp, ligand_file):
         pdb_path,
         f"data/{os.path.basename(pdb_path)}_prepared_for_esm.fasta",
     )
     protein_path_list = [pdb_path]
     ligand_descriptions = [ligand_path]
     no_random = False
@@ -320,7 +362,7 @@ def update(inp, file, ligand_inp, ligand_file):
             data_list, confidence = sampling(
                 data_list=data_list,
                 model=model,
-                inference_steps=10,
                 tr_schedule=tr_schedule,
                 rot_schedule=rot_schedule,
                 tor_schedule=tor_schedule,
@@ -359,6 +401,7 @@ def update(inp, file, ligand_inp, ligand_file):
                 f'{out_dir}/index{idx}_{data_list[0]["name"][0].replace("/","-")}'
             )
             os.makedirs(write_dir, exist_ok=True)
             for rank, pos in enumerate(ligand_pos):
                 mol_pred = copy.deepcopy(lig)
                 if score_model_args.remove_hs:
@@ -367,6 +410,7 @@ def update(inp, file, ligand_inp, ligand_file):
                     write_mol_with_coords(
                         mol_pred, pos, os.path.join(write_dir, f"rank{rank+1}.sdf")
                     )
                 write_mol_with_coords(
                     mol_pred,
                     pos,
@@ -404,19 +448,27 @@ def update(inp, file, ligand_inp, ligand_file):
             print("Failed on", orig_complex_graph["name"], e)
             failures += 1
             return None
-    labels = [f"rank {i+1}" for i in range(len(filenames))]
     return (
-        molecule(pdb_path, filenames[0]),
-        gr.Dropdown.update(choices=labels, value="rank 1"),
         filenames,
         pdb_path,
     )
-def updateView(out, filenames, pdb):
-    i = int(out.replace("rank", ""))
-    return molecule(pdb, filenames[i])
 demo = gr.Blocks()
@@ -426,7 +478,7 @@ with demo:
     gr.Markdown(
         ">**DiffDock: Diffusion Steps, Twists, and Turns for Molecular Docking**, Corso, Gabriele and Stärk, Hannes and Jing, Bowen and Barzilay, Regina and Jaakkola, Tommi, arXiv:2210.01776  [GitHub](https://github.com/gcorso/diffdock)"
     )
-    gr.Markdown("Runs the diffusion model `10` times with `10` inference steps")
     with gr.Box():
         with gr.Row():
             with gr.Column():
@@ -442,6 +494,9 @@ with demo:
                     label="SMILES string",
                 )
                 ligand_file = gr.File(file_count="single", label="Input Ligand")
     btn = gr.Button("Run predictions")
@@ -450,23 +505,54 @@ with demo:
     filenames = gr.Variable()
     out = gr.Dropdown(interactive=True, label="Ranked samples")
     mol = gr.HTML()
     gr.Examples(
         [
             [
-                None,
-                "examples/1a46_protein_processed.pdb",
-                None,
-                "examples/1a46_ligand.sdf",
-            ]
         ],
-        [inp, file, ligand_inp, ligand_file],
-        [mol, out],
         # cache_examples=True,
     )
     btn.click(
         fn=update,
-        inputs=[inp, file, ligand_inp, ligand_file],
-        outputs=[mol, out, filenames, pdb],
     )
-    out.change(fn=updateView, inputs=[out, filenames, pdb], outputs=mol)
 demo.launch()

 from rdkit.Chem import MolFromSmiles, AddHs
 from torch_geometric.loader import DataLoader
 import yaml
+import sys
+import csv
+csv.field_size_limit(sys.maxsize)
 print(torch.__version__)
 os.makedirs("data/esm2_output", exist_ok=True)
 with open(f"workdir/paper_confidence_model/model_parameters.yml") as f:
     confidence_args = Namespace(**yaml.full_load(f))
+import shutil
 t_to_sigma = partial(t_to_sigma_compl, args=score_model_args)
 model = get_model(score_model_args, device, t_to_sigma=t_to_sigma, no_parallel=True)
 confidence_model.load_state_dict(state_dict, strict=True)
 confidence_model = confidence_model.to(device)
 confidence_model.eval()
 def get_pdb(pdb_code="", filepath=""):
+    try:
+        return filepath.name
+    except AttributeError as e:
+        if pdb_code is None or pdb_code == "":
             return None
+        else:
+            os.system(f"wget -qnc https://files.rcsb.org/view/{pdb_code}.pdb")
+            return f"{pdb_code}.pdb"
 def get_ligand(smiles="", filepath=""):
     return mol
+def molecule(input_pdb, ligand_pdb, original_ligand):
     structure = read_mol(input_pdb)
     mol = read_mol(ligand_pdb)
+    try:
+        ligand = read_mol(original_ligand.name)
+        _, ext = os.path.splitext(original_ligand.name)
+        lig_str_1 = """let original_ligand = `""" + ligand + """`"""
+        lig_str_2 = f"""
+        viewer.addModel( original_ligand, "{ext[1:]}" );
+        viewer.getModel(2).setStyle({{stick:{{colorscheme:"greenCarbon"}}}});"""
+    except AttributeError as e:
+        ligand = None
+        lig_str_1 = ""
+        lig_str_2 = ""
     x = (
         """<!DOCTYPE html>
         <html>
     .mol-container select{
         background-image:None;
     }
+    .green{
+        width:20px;
+        height:20px;
+        background-color:#33ff45;
+        display:inline-block;
+    }
+    .magenta{
+        width:20px;
+        height:20px;
+        background-color:magenta;
+        display:inline-block;
+    }
     </style>
     <script src="https://3Dmol.csb.pitt.edu/build/3Dmol-min.js"></script>
     </head>
     <body>
+     <button id="startanimation">Replay diffusion process</button>
+     <div>
+     <span class="green"></span> Uploaded ligand position
+     <span class="magenta"></span> Predicted ligand position
+     </div>
     <div id="container" class="mol-container"></div>
             <script>
         + """`
         let structure = `"""
         + structure
+        + """`
+        """
+        + lig_str_1
+        + """
              let viewer = null;
                 viewer.animate({loop: "forward",reps: 1});
                 viewer.getModel(1).setStyle({stick:{colorscheme:"magentaCarbon"}});
+                """
+        + lig_str_2
+        + """
                 viewer.render();
               })
     esm_embedding_prep(out_file, protein_path)
     # create args object with defaults
     os.environ["HOME"] = "esm/model_weights"
     subprocess.call(
         f"python esm/scripts/extract.py esm2_t33_650M_UR50D {out_file} data/esm2_output --repr_layers 33 --include per_tok",
         shell=True,
+        env=os.environ,
     )
+def update(inp, file, ligand_inp, ligand_file, n_it):
     pdb_path = get_pdb(inp, file)
     ligand_path = get_ligand(ligand_inp, ligand_file)
         pdb_path,
         f"data/{os.path.basename(pdb_path)}_prepared_for_esm.fasta",
     )
+    tr_schedule = get_t_schedule(inference_steps=n_it)
+    rot_schedule = tr_schedule
+    tor_schedule = tr_schedule
+    print("common t schedule", tr_schedule)
+    (
+        failures,
+        skipped,
+        confidences_list,
+        names_list,
+        run_times,
+        min_self_distances_list,
+    ) = (
+        0,
+        0,
+        [],
+        [],
+        [],
+        [],
+    )
+    N = 10  # number of samples to generate
     protein_path_list = [pdb_path]
     ligand_descriptions = [ligand_path]
     no_random = False
             data_list, confidence = sampling(
                 data_list=data_list,
                 model=model,
+                inference_steps=n_it,
                 tr_schedule=tr_schedule,
                 rot_schedule=rot_schedule,
                 tor_schedule=tor_schedule,
                 f'{out_dir}/index{idx}_{data_list[0]["name"][0].replace("/","-")}'
             )
             os.makedirs(write_dir, exist_ok=True)
+            confidences = []
             for rank, pos in enumerate(ligand_pos):
                 mol_pred = copy.deepcopy(lig)
                 if score_model_args.remove_hs:
                     write_mol_with_coords(
                         mol_pred, pos, os.path.join(write_dir, f"rank{rank+1}.sdf")
                     )
+                confidences.append(confidence[rank])
                 write_mol_with_coords(
                     mol_pred,
                     pos,
             print("Failed on", orig_complex_graph["name"], e)
             failures += 1
             return None
+    # zip outputs
+    zippath = shutil.make_archive(pdb_path, "zip", write_dir)
+    print("Zipped outputs to", zippath)
+    labels = [
+        f"rank {i+1}, confidence {confidences[i]:.2f}" for i in range(len(filenames))
+    ]
     return (
+        molecule(pdb_path, filenames[0], ligand_file),
+        gr.Dropdown.update(choices=labels, value=labels[0]),
         filenames,
         pdb_path,
+        zippath,
     )
+def updateView(out, filenames, pdb, ligand_file):
+    print("updating view")
+    i = out  # int(out.replace("rank", ""))
+    print(i)
+    i = int(i.split(",")[0].replace("rank", "")) - 1
+    return molecule(pdb, filenames[i], ligand_file)
 demo = gr.Blocks()
     gr.Markdown(
         ">**DiffDock: Diffusion Steps, Twists, and Turns for Molecular Docking**, Corso, Gabriele and Stärk, Hannes and Jing, Bowen and Barzilay, Regina and Jaakkola, Tommi, arXiv:2210.01776  [GitHub](https://github.com/gcorso/diffdock)"
     )
+    gr.Markdown("")
     with gr.Box():
         with gr.Row():
             with gr.Column():
                     label="SMILES string",
                 )
                 ligand_file = gr.File(file_count="single", label="Input Ligand")
+        n_it = gr.Slider(
+            minimum=10, maximum=40, label="Number of inference steps", step=1
+        )
     btn = gr.Button("Run predictions")
     filenames = gr.Variable()
     out = gr.Dropdown(interactive=True, label="Ranked samples")
     mol = gr.HTML()
+    output_file = gr.File(file_count="single", label="Output files")
     gr.Examples(
         [
             [
+                "6w70",
+                "examples/6w70.pdb",
+                "COc1ccc(cc1)n2c3c(c(n2)C(=O)N)CCN(C3=O)c4ccc(cc4)N5CCCCC5=O",
+                "examples/6w70_ligand.sdf",
+                10,
+            ],
+            [
+                "",
+                "examples/6o5u_protein_processed.pdb",
+                "",
+                "examples/6o5u_ligand.sdf",
+                10,
+            ],
+            [
+                "",
+                "examples/6o5u_protein_processed.pdb",
+                "[NH3+]C[C@H]1O[C@H](O[C@@H]2[C@@H]([NH3+])C[C@H]([C@@H]([C@H]2O)O[C@H]2O[C@H](CO)[C@H]([C@@H]([C@H]2O)[NH3+])O)[NH3+])[C@@H]([C@H]([C@@H]1O)O)O",
+                "examples/6o5u_ligand.sdf",
+                10,
+            ],
+            [
+                "",
+                "examples/6o5u_protein_processed.pdb",
+                "",
+                "examples/6o5u_ligand.sdf",
+                10,
+            ],
+            [
+                "",
+                "examples/6ahs_protein_processed.pdb",
+                "",
+                "examples/6ahs_ligand.sdf",
+                10,
+            ],
         ],
+        [inp, file, ligand_inp, ligand_file, n_it],
+        [mol, out, filenames, pdb, output_file],
+        # fn=update,
         # cache_examples=True,
     )
     btn.click(
         fn=update,
+        inputs=[inp, file, ligand_inp, ligand_file, n_it],
+        outputs=[mol, out, filenames, pdb, output_file],
     )
+    out.change(fn=updateView, inputs=[out, filenames, pdb, ligand_file], outputs=mol)
 demo.launch()

esm/LICENSE ADDED Viewed

	@@ -0,0 +1,21 @@

+MIT License
+Copyright (c) Facebook, Inc. and its affiliates.
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

esm/scripts/extract.py CHANGED Viewed

@@ -12,7 +12,7 @@ print("using", sys.executable)
 sys.path.insert( 0,"/home/user/.local/lib/python3.8/site-packages")
 sys.path.insert( 0,"/home/user/app/esm/")
 import os
-print(os.environ)
 import torch
 from esm import Alphabet, FastaBatchedDataset, ProteinBertModel, pretrained, MSATransformer

 sys.path.insert( 0,"/home/user/.local/lib/python3.8/site-packages")
 sys.path.insert( 0,"/home/user/app/esm/")
 import os
 import torch
 from esm import Alphabet, FastaBatchedDataset, ProteinBertModel, pretrained, MSATransformer

examples/6ahs_ligand.sdf ADDED Viewed

	@@ -0,0 +1,97 @@

+6ahs_ligand
+  -I-interpret-
+ 44 47  0  0  0  0  0  0  0  0999 V2000
+  -12.3770   21.8080   53.5010 C   0  0  0  0  0
+  -13.7990   19.8830   53.8470 C   0  0  0  0  0
+  -12.7140   27.6870   53.9730 C   0  0  0  0  0
+  -14.5790   28.9380   54.4000 C   0  0  0  0  0
+  -15.0000   26.1900   58.7440 C   0  0  0  0  0
+  -10.5140   22.1070   55.1220 O   0  0  0  0  0
+  -11.1780   22.7720   54.0310 S   0  0  0  0  0
+  -10.2040   22.9400   53.0000 O   0  0  0  0  0
+  -12.7440   20.6930   54.2570 C   0  0  0  0  0
+  -13.0670   22.0720   52.3070 C   0  0  0  0  0
+  -12.6220   23.4480   51.2580 Cl  0  0  0  0  0
+  -14.1300   21.2760   51.9160 C   0  0  0  0  0
+  -14.4890   20.1760   52.6790 C   0  0  0  0  0
+  -11.7830   24.2640   54.5210 N   0  0  0  0  0
+  -11.7700   25.3520   53.7050 C   0  0  0  0  0
+  -12.5570   24.4620   55.6400 C   0  0  0  0  0
+  -12.9850   23.6850   56.7070 C   0  0  0  0  0
+  -13.0050   25.7840   55.5680 C   0  0  0  0  0
+  -13.7490   26.3750   56.5810 C   0  0  0  0  0
+  -14.1450   25.5950   57.6610 C   0  0  0  0  0
+  -13.7760   24.2500   57.7130 C   0  0  0  0  0
+  -12.3430   26.3420   54.5030 C   0  0  0  0  0
+  -14.1740   27.8640   53.8610 N   0  0  0  0  0
+  -12.3600   28.8800   54.9120 C   0  0  0  0  0
+  -13.6180   29.6030   54.9940 N   0  0  0  0  0
+  -16.0210   29.3400   54.4520 C   0  0  0  0  0
+  -14.0838   19.0169   54.4444 H   0  0  0  0  0
+  -12.1648   27.7040   53.0316 H   0  0  0  0  0
+  -14.4736   27.0274   59.2019 H   0  0  0  0  0
+  -15.9379   26.5405   58.3133 H   0  0  0  0  0
+  -15.2065   25.4321   59.4997 H   0  0  0  0  0
+  -12.2019   20.4558   55.1724 H   0  0  0  0  0
+  -14.6845   21.5143   51.0083 H   0  0  0  0  0
+  -15.3149   19.5397   52.3611 H   0  0  0  0  0
+  -11.4030   25.4307   52.6817 H   0  0  0  0  0
+  -12.7045   22.6331   56.7614 H   0  0  0  0  0
+  -14.0172   27.4303   56.5300 H   0  0  0  0  0
+  -14.1081   23.6324   58.5475 H   0  0  0  0  0
+  -11.5409   29.4916   54.5336 H   0  0  0  0  0
+  -11.9880   28.5603   55.8854 H   0  0  0  0  0
+  -13.7372   30.5065   55.4522 H   0  0  0  0  0
+  -16.4083   29.4311   53.4372 H   0  0  0  0  0
+  -16.5888   28.5825   54.9924 H   0  0  0  0  0
+  -16.1116   30.2979   54.9641 H   0  0  0  0  0
+  7  1  1  0  0  0
+  1  9  4  0  0  0
+  1 10  4  0  0  0
+  9  2  4  0  0  0
+  2 13  4  0  0  0
+ 22  3  1  0  0  0
+  3 23  1  0  0  0
+  3 24  1  0  0  0
+ 23  4  2  0  0  0
+  4 25  1  0  0  0
+  4 26  1  0  0  0
+ 20  5  1  0  0  0
+  7  6  2  0  0  0
+  7  8  2  0  0  0
+ 14  7  1  0  0  0
+ 10 11  1  0  0  0
+ 10 12  4  0  0  0
+ 12 13  4  0  0  0
+ 15 14  4  0  0  0
+ 16 14  4  0  0  0
+ 22 15  4  0  0  0
+ 16 17  4  0  0  0
+ 18 16  4  0  0  0
+ 17 21  4  0  0  0
+ 19 18  4  0  0  0
+ 18 22  4  0  0  0
+ 19 20  4  0  0  0
+ 20 21  4  0  0  0
+ 24 25  1  0  0  0
+  2 27  1  0  0  0
+  3 28  1  0  0  0
+  5 29  1  0  0  0
+  5 30  1  0  0  0
+  5 31  1  0  0  0
+  9 32  1  0  0  0
+ 12 33  1  0  0  0
+ 13 34  1  0  0  0
+ 15 35  1  0  0  0
+ 17 36  1  0  0  0
+ 19 37  1  0  0  0
+ 21 38  1  0  0  0
+ 24 39  1  0  0  0
+ 24 40  1  0  0  0
+ 25 41  1  0  0  0
+ 26 42  1  0  0  0
+ 26 43  1  0  0  0
+ 26 44  1  0  0  0
+M  END
+$$$$

examples/6ahs_protein_processed.pdb ADDED Viewed

The diff for this file is too large to render. See raw diff

examples/6o5u_ligand.sdf ADDED Viewed

	@@ -0,0 +1,154 @@

+6o5u_ligand
+  -I-interpret-
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+ 32 72  1  0  0  0
+ 33 73  1  0  0  0
+M  END
+$$$$

examples/6o5u_protein_processed.pdb ADDED Viewed

The diff for this file is too large to render. See raw diff

examples/6w70.pdb ADDED Viewed

The diff for this file is too large to render. See raw diff

examples/6w70_ligand.sdf ADDED Viewed

	@@ -0,0 +1,170 @@

+GG2
+  ModelServer 0.9.9
+ 59 63  0  0  0  0  0  0  0  0  0
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+ 34 59  1  0  0  0  0
+M  END
+> <model_server_result.job_id>
+jhYbiAhZngEaKGexZ2WIZQ
+> <model_server_result.datetime_utc>
+2022-10-10 01:28:25
+> <model_server_result.server_version>
+0.9.9
+> <model_server_result.query_name>
+ligand
+> <model_server_result.source_id>
+pdb-bcif
+> <model_server_result.entry_id>
+6w70
+> <model_server_params.name>
+atom_site
+> <model_server_params.value>
+{"label_asym_id":"E","auth_seq_id":303}
+> <model_server_stats.io_time_ms>
+49
+> <model_server_stats.parse_time_ms>
+60
+> <model_server_stats.create_model_time_ms>
+10
+> <model_server_stats.query_time_ms>
+220
+> <model_server_stats.encode_time_ms>
+0
+> <model_server_stats.element_count>
+59
+$$$$