inference_eval

Dockerfile

@@ -1,20 +1,39 @@
-FROM continuumio/miniconda3
+ARG BASE_IMAGE=mambaorg/micromamba
+ARG BASE_TAG=1.5-jammy
+ARG MAMBA_PYTHON_VERSION=3.10
+
+FROM --platform=linux/amd64 ${BASE_IMAGE}:${BASE_TAG}
+
+ARG MAMBA_PYTHON_VERSION
+ENV DEBIAN_FRONTEND=noninteractive
 
-RUN useradd -m -u 1000 user
 WORKDIR /usr/src/app
-COPY --link --chown=1000 ./ /usr/src/app
 
-COPY . .
+# Install conda env
+RUN micromamba install -y -n base -c conda-forge \
+    pyopenssl=23.2.0 \
+    python=${MAMBA_PYTHON_VERSION} \
+    requests=2.25.1 \
+    aivant::openstructure \
+    vina \
+    && micromamba clean --all --yes
 
-# install dependcies
-RUN conda install -y pandas numpy scikit-learn
-RUN pip install --no-cache-dir -r requirements.txt
+ARG MAMBA_DOCKERFILE_ACTIVATE=1  # (otherwise python will not be found)
+ENV BASH_ENV=/usr/local/bin/_activate_current_env.sh
+ENV LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/opt/conda/lib
 
-#if you need to download executable and run them switch to the default non-root user
-USER user
+# install dependencies
+ADD requirements.txt .
+RUN pip install --no-cache-dir -r requirements.txt
 
-#do not modify below
 EXPOSE 7860
 ENV GRADIO_SERVER_NAME="0.0.0.0"
 
+ADD . .
+
+# Prepare user
+USER $MAMBA_USER
+
+ENTRYPOINT ["/usr/local/bin/_entrypoint.sh"]
+
 CMD ["python", "inference_app.py"]

inference_app.py

@@ -1,38 +1,152 @@
-
+from __future__ import annotations
+from pathlib import Path
 import time
+from biotite.application.autodock import VinaApp
 
 import gradio as gr
 
 from gradio_molecule3d import Molecule3D
+from gradio_molecule2d import molecule2d
+import numpy as np
+from rdkit import Chem
+from rdkit.Chem import AllChem
+import pandas as pd
+from biotite.structure import centroid, from_template
+from biotite.structure.io import load_structure
+from biotite.structure.io.mol import MOLFile, SDFile
+
+from plinder.eval.docking.write_scores import evaluate
+
+
+EVAL_METRICS = ["system_id", "LDDT-PLI", "LDDT-LP", "BISY-RMSD"]
+
+
+def vina(
+    ligand, receptor, pocket_center, output_folder: Path, size=10, max_num_poses=5
+):
+    app = VinaApp(
+        ligand,
+        receptor,
+        center=pocket_center,
+        size=[size, size, size],
+    )
+    app.set_max_number_of_models(max_num_poses)
+    app.start()
+    app.join()
+    docked_ligand = from_template(ligand, app.get_ligand_coord())
+    docked_ligand = docked_ligand[..., ~np.isnan(docked_ligand.coord[0]).any(axis=-1)]
+    output_files = []
+    for i in range(max_num_poses):
+        sdf_file = MOLFile()
+        sdf_file.set_structure(docked_ligand[i])
+        sdf_file.write(output_folder / f"docked_ligand_{i}.sdf")
+        output_files.append(sdf_file)
+    return output_files
 
 
+def predict(
+    input_sequence: str,
+    input_ligand: str,
+    input_msa: gr.File | None = None,
+    input_protein: gr.File | None = None,
+    max_num_poses: int = 1,
+):
+    """
+    Main prediction function that calls ligsite and smina
 
+    Parameters
+    ----------
+    input_sequence: str
+        monomer sequence
+    input_ligand: str
+        ligand as SMILES string
+    input_msa: gradio.File | None
+        Gradio file object to MSA a3m file
+    input_protein: gradio.File | None
+        Gradio file object to monomer protein structure as CIF file
+    max_num_poses: int
+        Number of poses to generate
 
-def predict (input_sequence, input_ligand,input_msa, input_protein):
+    Returns
+    -------
+    output_structures: tuple
+        (output_protein, output_ligand_sdf)
+    run_time: float
+        run time of the program
+    """
     start_time = time.time()
-    # Do inference here
-    # return an output pdb file with the protein and ligand with resname LIG or UNK. 
+
+    if input_protein is None:
+        raise gr.Error("need input_protein")
+    ligand_file = "ligand.sdf"
+    conformer = Chem.AddHs(Chem.MolFromSmiles(input_ligand))
+    AllChem.EmbedMolecule(conformer)
+    AllChem.MMFFOptimizeMolecule(conformer)
+    Chem.SDWriter(ligand_file).write(conformer)
+    ligand = SDFile.read(ligand_file).record.get_structure()
+    receptor = load_structure(input_protein, include_bonds=True)
+    docking_poses = vina(
+        ligand,
+        receptor,
+        centroid(receptor),
+        Path(input_protein).parent,
+        max_num_poses=max_num_poses,
+    )
     end_time = time.time()
     run_time = end_time - start_time
-    return ["test_out.pdb", "test_docking_pose.sdf"], run_time
+    return [input_protein.name, docking_poses[0]], run_time
 
-with gr.Blocks() as app:
 
-    gr.Markdown("# Template for inference")
+def get_metrics(
+    system_id: str,
+    receptor_file: Path,
+    ligand_file: Path,
+) -> tuple[pd.DataFrame, float]:
+    start_time = time.time()
+    metrics = pd.DataFrame(
+        [
+            evaluate(
+                model_system_id=system_id,
+                reference_system_id=system_id,
+                receptor_file=receptor_file,
+                ligand_files=[ligand_file],
+                flexible=False,
+                posebusters=False,
+                posebusters_full=False,
+            )
+        ]
+    )
+    metrics = metrics[
+        ["system_id", "lddt_pli_ave", "lddt_lp_ave", "bisy_rmsd_ave"]
+    ].copy()
+    metrics.rename(
+        columns={
+            "lddt_pli_ave": "LDDT-PLI",
+            "lddt_lp_ave": "LDDT-LP",
+            "bisy_rmsd_ave": "BISY-RMSD",
+        },
+        inplace=True,
+    )
+    end_time = time.time()
+    run_time = end_time - start_time
+    return metrics, run_time
+
 
-    gr.Markdown("Title, description, and other information about the model")   
+with gr.Blocks() as app:
+    gr.Markdown("# Vina")
+
+    gr.Markdown(
+        "Example model using Vina to dock the ligand with the pocket center defined by the centroid of the input protein."
+    )
     with gr.Row():
         input_sequence = gr.Textbox(lines=3, label="Input Protein sequence (FASTA)")
         input_ligand = gr.Textbox(lines=3, label="Input ligand SMILES")
-    with gr.Row():
-        input_msa = gr.File(label="Input Protein MSA (A3M)")
-        input_protein = gr.File(label="Input protein monomer")
-        
-    
-    # define any options here
+        input_msa = gr.File(label="Input MSA (a3m)")
+        input_protein = gr.File(label="Input protein monomer (CIF)")
 
+    # define any options here
     # for automated inference the default options are used
-    # slider_option = gr.Slider(0,10, label="Slider Option")
+    max_num_poses = gr.Slider(1, 10, value=1, label="Max number of poses to generate")
     # checkbox_option = gr.Checkbox(label="Checkbox Option")
     # dropdown_option = gr.Dropdown(["Option 1", "Option 2", "Option 3"], label="Radio Option")
 
@@ -41,30 +155,167 @@ with gr.Blocks() as app:
     gr.Examples(
         [
             [
-                "SVKSEYAEAAAVGQEAVAVFNTMKAAFQNGDKEAVAQYLARLASLYTRHEELLNRILEKARREGNKEAVTLMNEFTATFQTGKSIFNAMVAAFKNGDDDSFESYLQALEKVTAKGETLADQIAKAL:SVKSEYAEAAAVGQEAVAVFNTMKAAFQNGDKEAVAQYLARLASLYTRHEELLNRILEKARREGNKEAVTLMNEFTATFQTGKSIFNAMVAAFKNGDDDSFESYLQALEKVTAKGETLADQIAKAL",
-                "COc1ccc(cc1)n2c3c(c(n2)C(=O)N)CCN(C3=O)c4ccc(cc4)N5CCCCC5=O",
-                "test_out.pdb"
+                "QECTKFKVSSCRECIESGPGCTWCQKLNFTGPGDPDSIRCDTRPQLLMRGCAADDIMDPTSLAETQEDHNGGQKQLSPQKVTLYLRPGQAAAFNVTFRRAKGYPIDLYYLMDLSYSMLDDLRNVKKLGGDLLRALNEITESGRIGFGSFVDKTVLPFVNTHPDKLRNPCPNKEKECQPPFAFRHVLKLTDNSNQFQTEVGKQLISGNLDAPEGGLDAMMQVAACPEEIGWRKVTRLLVFATDDGFHFAGDGKLGAILTPNDGRCHLEDNLYKRSNEFDYPSVGQLAHKLAENNIQPIFAVTSRMVKTYEKLTEIIPKSAVGELSEDSSNVVQLIKNAYNKLSSRVFLDHNALPDTLKVTYDSFCSNGVTHRNQPRGDCDGVQINVPITFQVKVTATECIQEQSFVIRALGFTDIVTVQVLPQCECRCRDQSRDRSLCHGKGFLECGICRCDTGYIGKNCECQTQGRSSQELEGSCRKDNNSIICSGLGDCVCGQCLCHTSDVPGKLIYGQYCECDTINCERYNGQVCGGPGRGLCFCGKCRCHPGFEGSACQCERTTEGCLNPRRVECSGRGRCRCNVCECHSGYQLPLCQECPGCPSPCGKYISCAECLKFEKGPFGKNCSAACPGLQLSNNPVKGRTCKERDSEGCWVAYTLEQQDGMDRYLIYVDESRECCGGPAALQTLFQG",
+                "CC(=O)N[C@H]1[C@H](O[C@H]2[C@H](O)[C@@H](NC(C)=O)CO[C@@H]2CO)O[C@H](CO)[C@@H](O)[C@@H]1O",
+                None,
+                "input_test.cif",
             ],
         ],
-        [input_sequence, input_ligand, input_protein],
+        [input_sequence, input_ligand, input_msa, input_protein],
     )
-    reps =    [
-    {
-      "model": 0,
-      "style": "cartoon",
-      "color": "whiteCarbon",
-    },
+    reps = [
+        {
+            "model": 0,
+            "style": "cartoon",
+            "color": "whiteCarbon",
+        },
+        {
+            "model": 0,
+            "resname": "UNK",
+            "style": "stick",
+            "color": "greenCarbon",
+        },
         {
-      "model": 1,
-      "style": "stick",
-      "color": "greenCarbon",
-    }
-        
-  ]
-    
+            "model": 0,
+            "resname": "LIG",
+            "style": "stick",
+            "color": "greenCarbon",
+        },
+        {
+            "model": 1,
+            "style": "stick",
+            "color": "greenCarbon",
+        },
+    ]
+    smiles = molecule2d(input_ligand)
     out = Molecule3D(reps=reps)
     run_time = gr.Textbox(label="Runtime")
 
-    btn.click(predict, inputs=[input_sequence, input_ligand, input_msa, input_protein], outputs=[out, run_time])
+    btn.click(
+        predict,
+        inputs=[input_sequence, input_ligand, input_msa, input_protein, max_num_poses],
+        outputs=[out, run_time],
+    )
+
+app.launch()
+
+with gr.Blocks() as app:
+    with gr.Tab("🧬 Vina"):
+        gr.Markdown(
+            "Example model using Vina to dock the ligand with the pocket center defined by the centroid of the input protein."
+        )
+        with gr.Row():
+            input_sequence = gr.Textbox(lines=3, label="Input Protein sequence (FASTA)")
+            input_ligand = gr.Textbox(lines=3, label="Input ligand SMILES")
+            input_msa = gr.File(label="Input MSA (a3m)")
+            input_protein = gr.File(label="Input protein monomer (CIF)")
+        max_num_poses = gr.Slider(
+            1, 10, value=1, label="Max number of poses to generate"
+        )
+        btn = gr.Button("Run Inference")
+        gr.Examples(
+            [
+                [
+                    "QECTKFKVSSCRECIESGPGCTWCQKLNFTGPGDPDSIRCDTRPQLLMRGCAADDIMDPTSLAETQEDHNGGQKQLSPQKVTLYLRPGQAAAFNVTFRRAKGYPIDLYYLMDLSYSMLDDLRNVKKLGGDLLRALNEITESGRIGFGSFVDKTVLPFVNTHPDKLRNPCPNKEKECQPPFAFRHVLKLTDNSNQFQTEVGKQLISGNLDAPEGGLDAMMQVAACPEEIGWRKVTRLLVFATDDGFHFAGDGKLGAILTPNDGRCHLEDNLYKRSNEFDYPSVGQLAHKLAENNIQPIFAVTSRMVKTYEKLTEIIPKSAVGELSEDSSNVVQLIKNAYNKLSSRVFLDHNALPDTLKVTYDSFCSNGVTHRNQPRGDCDGVQINVPITFQVKVTATECIQEQSFVIRALGFTDIVTVQVLPQCECRCRDQSRDRSLCHGKGFLECGICRCDTGYIGKNCECQTQGRSSQELEGSCRKDNNSIICSGLGDCVCGQCLCHTSDVPGKLIYGQYCECDTINCERYNGQVCGGPGRGLCFCGKCRCHPGFEGSACQCERTTEGCLNPRRVECSGRGRCRCNVCECHSGYQLPLCQECPGCPSPCGKYISCAECLKFEKGPFGKNCSAACPGLQLSNNPVKGRTCKERDSEGCWVAYTLEQQDGMDRYLIYVDESRECCGGPAALQTLFQG",
+                    "CC(=O)N[C@H]1[C@H](O[C@H]2[C@H](O)[C@@H](NC(C)=O)CO[C@@H]2CO)O[C@H](CO)[C@@H](O)[C@@H]1O",
+                    None,
+                    "input_test.cif",
+                ],
+            ],
+            [input_sequence, input_ligand, input_msa, input_protein],
+        )
+        reps = [
+            {
+                "model": 0,
+                "style": "cartoon",
+                "color": "whiteCarbon",
+            },
+            {
+                "model": 0,
+                "resname": "UNK",
+                "style": "stick",
+                "color": "greenCarbon",
+            },
+            {
+                "model": 0,
+                "resname": "LIG",
+                "style": "stick",
+                "color": "greenCarbon",
+            },
+            {
+                "model": 1,
+                "style": "stick",
+                "color": "greenCarbon",
+            },
+        ]
+        smiles = molecule2d(input_ligand)
+        out = Molecule3D(reps=reps)
+        run_time = gr.Textbox(label="Runtime")
+
+        btn.click(
+            predict,
+            inputs=[
+                input_sequence,
+                input_ligand,
+                input_msa,
+                input_protein,
+                max_num_poses,
+            ],
+            outputs=[out, run_time],
+        )
+    with gr.Tab("⚖️ PLINDER evaluation template"):
+        with gr.Row():
+            with gr.Column():
+                input_system_id = gr.Textbox(label="PLINDER system ID")
+                input_receptor_file = gr.File(label="Receptor file (CIF)")
+                input_ligand_file = gr.File(label="Ligand file (SDF)")
+
+        eval_btn = gr.Button("Run Evaluation")
+        gr.Examples(
+            [
+                [
+                    "4neh__1__1.B__1.H",
+                    "input_protein_test.cif",
+                    "input_ligand_test.sdf",
+                ],
+            ],
+            [input_system_id, input_receptor_file, input_ligand_file],
+        )
+        reps = [
+            {
+                "model": 0,
+                "style": "cartoon",
+                "color": "whiteCarbon",
+            },
+            {
+                "model": 0,
+                "resname": "UNK",
+                "style": "stick",
+                "color": "greenCarbon",
+            },
+            {
+                "model": 0,
+                "resname": "LIG",
+                "style": "stick",
+                "color": "greenCarbon",
+            },
+            {
+                "model": 1,
+                "style": "stick",
+                "color": "greenCarbon",
+            },
+        ]
+
+        # pred_native = Molecule3D(reps=reps, config={"backgroundColor": "black"})
+        eval_run_time = gr.Textbox(label="Evaluation runtime")
+        metric_table = gr.DataFrame(
+            pd.DataFrame([], columns=EVAL_METRICS), label="Evaluation metrics"
+        )
+
+        eval_btn.click(
+            evaluate,
+            inputs=[input_system_id, input_receptor_file, input_ligand_file],
+            outputs=[metric_table, eval_run_time],
+        )
 
 app.launch()

input_ligand_test.sdf

@@ -0,0 +1,76 @@
+
+
+
+ 35 36  0     0  0  0  0  0  0  1 V2000
+  -90.5920   50.9670   16.1800 C   0  0  0  0  0  0  0  0  0  0  0  0
+  -89.6380   50.4350   17.2150 C   0  0  0  0  0  0  0  0  0  0  0  0
+  -88.4570   50.2310   16.9640 O   0  0  0  0  0  0  0  0  0  0  0  0
+  -90.2160   50.2100   18.4400 N   0  0  0  0  0  0  0  0  0  0  0  0
+  -89.4740   50.1610   19.7290 C   0  0  0  0  0  0  0  0  0  0  0  0
+  -90.3860   50.7570   20.8330 C   0  0  0  0  0  0  0  0  0  0  0  0
+  -90.7120   52.0920   20.4450 O   0  0  0  0  0  0  0  0  0  0  0  0
+  -91.8650   52.6560   21.0970 C   0  0  0  0  0  0  0  0  0  0  0  0
+  -91.5010   53.8240   22.0290 C   0  0  0  0  0  0  0  0  0  0  0  0
+  -90.8100   53.3420   23.1970 O   0  0  0  0  0  0  0  0  0  0  0  0
+  -92.7380   54.6080   22.5210 C   0  0  0  0  0  0  0  0  0  0  0  0
+  -92.4070   56.0380   22.6160 N   0  0  0  0  0  0  0  0  0  0  0  0
+  -93.2740   56.9190   23.2260 C   0  0  0  0  0  0  0  0  0  0  0  0
+  -93.4830   56.6660   24.6950 C   0  0  0  0  0  0  0  0  0  0  0  0
+  -93.8230   57.8400   22.6340 O   0  0  0  0  0  0  0  0  0  0  0  0
+  -93.9600   54.3810   21.6250 C   0  0  0  0  0  0  0  0  0  0  0  0
+  -93.5500   54.3160   20.2620 O   0  0  0  0  0  0  0  0  0  0  0  0
+  -92.8010   53.1300   19.9560 C   0  0  0  0  0  0  0  0  0  0  0  0
+  -93.7640   52.0180   19.4950 C   0  0  0  0  0  0  0  0  0  0  0  0
+  -93.1180   51.0190   18.7110 O   0  0  0  0  0  0  0  0  0  0  0  0
+  -89.7000   50.7930   22.0760 O   0  0  0  0  0  0  0  0  0  0  0  0
+  -89.5010   49.4740   22.5760 C   0  0  0  0  0  0  0  0  0  0  0  0
+  -88.9070   49.5870   23.9880 C   0  0  0  0  0  0  0  0  0  0  0  0
+  -87.5240   49.2420   24.0130 O   0  0  0  0  0  0  0  0  0  0  0  0
+  -88.5810   48.6720   21.6460 C   0  0  0  0  0  0  0  0  0  0  0  0
+  -88.5650   47.2950   22.0610 O   0  0  0  0  0  0  0  0  0  0  0  0
+  -89.0090   48.7460   20.1620 C   0  0  0  0  0  0  0  0  0  0  0  0
+  -87.8630   48.3210   19.4000 O   0  0  0  0  0  0  0  0  0  0  0  0
+  -91.1580   50.5990   18.5310 H   0  0  0  0  0  0  0  0  0  0  0  0
+  -91.1430   53.8690   23.9480 H   0  0  0  0  0  0  0  0  0  0  0  0
+  -91.8120   56.4160   21.8870 H   0  0  0  0  0  0  0  0  0  0  0  0
+  -93.4990   51.0950   17.8170 H   0  0  0  0  0  0  0  0  0  0  0  0
+  -87.4660   48.2780   23.8900 H   0  0  0  0  0  0  0  0  0  0  0  0
+  -87.7020   47.1520   22.5000 H   0  0  0  0  0  0  0  0  0  0  0  0
+  -87.1460   48.9740   19.5550 H   0  0  0  0  0  0  0  0  0  0  0  0
+  1  2  1  0  0  0  0
+  2  3  2  0  0  0  0
+  2  4  1  0  0  0  0
+  4  5  1  0  0  0  0
+  5  6  1  0  0  0  0
+  6  7  1  0  0  0  0
+  7  8  1  0  0  0  0
+  8  9  1  0  0  0  0
+  9 10  1  0  0  0  0
+  9 11  1  0  0  0  0
+ 11 12  1  0  0  0  0
+ 12 13  1  0  0  0  0
+ 13 14  1  0  0  0  0
+ 13 15  2  0  0  0  0
+ 11 16  1  0  0  0  0
+ 16 17  1  0  0  0  0
+ 17 18  1  0  0  0  0
+ 18 19  1  0  0  0  0
+ 19 20  1  0  0  0  0
+  6 21  1  0  0  0  0
+ 21 22  1  0  0  0  0
+ 22 23  1  0  0  0  0
+ 23 24  1  0  0  0  0
+ 22 25  1  0  0  0  0
+ 25 26  1  0  0  0  0
+ 25 27  1  0  0  0  0
+ 27 28  1  0  0  0  0
+  5 27  1  0  0  0  0
+  8 18  1  0  0  0  0
+  4 29  1  0  0  0  0
+ 10 30  1  0  0  0  0
+ 12 31  1  0  0  0  0
+ 20 32  1  0  0  0  0
+ 24 33  1  0  0  0  0
+ 26 34  1  0  0  0  0
+ 28 35  1  0  0  0  0
+M  END

requirements.txt

@@ -1,2 +1,4 @@
 gradio
 gradio_molecule3d
+gradio_molecule2d
+plinder @ git+https://github.com/plinder-org/plinder.git@eval_refactor_cherrypick

test_docking_pose.sdf

@@ -1,85 +0,0 @@
-
- OpenBabel09192409083D
-
- 36 40  0  0  0  0  0  0  0  0999 V2000
-  108.2560  -14.3390   -8.2420 N   0  0  0  0  0  0  0  0  0  0  0  0
-  108.0640  -15.5020   -7.5120 C   0  0  0  0  0  0  0  0  0  0  0  0
-  106.8180  -15.9740   -7.8870 C   0  0  0  0  0  0  0  0  0  0  0  0
-  106.2330  -14.9610   -8.6810 C   0  0  0  0  0  0  0  0  0  0  0  0
-  107.0800  -13.9290   -8.7970 N   0  0  0  0  0  0  0  0  0  0  0  0
-  106.3370  -17.3000   -7.4520 C   0  0  0  0  0  2  0  0  0  0  0  0
-  106.9630  -17.6470   -6.0950 C   0  0  0  0  0  2  0  0  0  0  0  0
-  108.4110  -17.3630   -6.0010 N   0  0  0  0  0  0  0  0  0  0  0  0
-  108.9200  -16.1410   -6.5320 C   0  0  0  0  0  0  0  0  0  0  0  0
-  109.9720  -15.6370   -6.1530 O   0  0  0  0  0  0  0  0  0  0  0  0
-  111.7640  -12.1520   -9.2230 C   0  0  0  0  0  0  0  0  0  0  0  0
-  111.5380  -12.5620   -7.9090 C   0  0  0  0  0  3  0  0  0  0  0  0
-  110.3870  -13.2820   -7.5640 C   0  0  0  0  0  3  0  0  0  0  0  0
-  109.4320  -13.5860   -8.5360 C   0  0  0  0  0  0  0  0  0  0  0  0
-  109.6780  -13.1990   -9.8650 C   0  0  0  0  0  3  0  0  0  0  0  0
-  110.8310  -12.4790  -10.2040 C   0  0  0  0  0  3  0  0  0  0  0  0
-  114.0540  -11.8750   -8.6550 C   0  0  0  0  0  1  0  0  0  0  0  0
-  112.9260  -11.4570   -9.4150 O   0  0  0  0  0  0  0  0  0  0  0  0
-  109.2010  -18.1590   -5.0960 C   0  0  0  0  0  0  0  0  0  0  0  0
-  110.5900  -18.2460   -5.2280 C   0  0  0  0  0  3  0  0  0  0  0  0
-  111.3670  -19.0330   -4.3580 C   0  0  0  0  0  3  0  0  0  0  0  0
-  110.7870  -19.7750   -3.3220 C   0  0  0  0  0  0  0  0  0  0  0  0
-  109.3970  -19.6900   -3.1960 C   0  0  0  0  0  3  0  0  0  0  0  0
-  108.6200  -18.9030   -4.0650 C   0  0  0  0  0  3  0  0  0  0  0  0
-  111.5850  -20.5710   -2.4330 N   0  0  0  0  0  0  0  0  0  0  0  0
-  112.5740  -21.5070   -2.9690 C   0  0  0  0  0  2  0  0  0  0  0  0
-  113.9390  -21.2760   -2.3370 C   0  0  0  0  0  2  0  0  0  0  0  0
-  113.8510  -21.1820   -0.8130 C   0  0  0  0  0  2  0  0  0  0  0  0
-  112.4390  -21.4180   -0.2930 C   0  0  0  0  0  2  0  0  0  0  0  0
-  111.4390  -20.5420   -1.0320 C   0  0  0  0  0  0  0  0  0  0  0  0
-  110.6190  -19.8910   -0.3890 O   0  0  0  0  0  0  0  0  0  0  0  0
-  104.8990  -14.9150   -9.2940 C   0  0  0  0  0  0  0  0  0  0  0  0
-  104.3150  -15.8830   -9.7700 O   0  0  0  0  0  0  0  0  0  0  0  0
-  104.3240  -13.6710   -9.3560 N   0  0  0  0  0  0  0  0  0  0  0  0
-  104.9260  -12.8600   -9.3540 H   0  0  0  0  0  0  0  0  0  0  0  0
-  103.5080  -13.6300   -9.9540 H   0  0  0  0  0  0  0  0  0  0  0  0
-  1  2  1  0  0  0  0
-  2  9  1  0  0  0  0
-  3  2  2  0  0  0  0
-  3  6  1  0  0  0  0
-  4  3  1  0  0  0  0
-  5  4  2  0  0  0  0
-  5  1  1  0  0  0  0
-  6  7  1  0  0  0  0
-  7  8  1  0  0  0  0
-  8 19  1  0  0  0  0
-  9 10  2  0  0  0  0
-  9  8  1  0  0  0  0
- 11 12  1  0  0  0  0
- 12 13  2  0  0  0  0
- 14  1  1  0  0  0  0
- 14 13  1  0  0  0  0
- 15 14  2  0  0  0  0
- 16 15  1  0  0  0  0
- 16 11  2  0  0  0  0
- 18 11  1  0  0  0  0
- 18 17  1  0  0  0  0
- 19 24  1  0  0  0  0
- 20 19  2  0  0  0  0
- 20 21  1  0  0  0  0
- 21 22  2  0  0  0  0
- 22 23  1  0  0  0  0
- 22 25  1  0  0  0  0
- 24 23  2  0  0  0  0
- 25 30  1  0  0  0  0
- 26 25  1  0  0  0  0
- 26 27  1  0  0  0  0
- 27 28  1  0  0  0  0
- 28 29  1  0  0  0  0
- 30 31  2  0  0  0  0
- 30 29  1  0  0  0  0
- 32  4  1  0  0  0  0
- 33 32  2  0  0  0  0
- 34 35  1  0  0  0  0
- 34 32  1  0  0  0  0
- 36 34  1  0  0  0  0
-M  END
->  <minimizedAffinity>
-41.9578323
-
-$$$$