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Simon Duerr
commited on
Commit
•
de38e57
1
Parent(s):
fceeb17
add sasa and plddt selection
Browse files- README.md +1 -1
- app.py +63 -28
- requirements.txt +2 -2
README.md
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@@ -4,7 +4,7 @@ emoji: ⚡
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colorFrom: red
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colorTo: pink
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sdk: gradio
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sdk_version: 3.
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app_file: app.py
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pinned: false
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license: mit
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colorFrom: red
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colorTo: pink
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sdk: gradio
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sdk_version: 3.1
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app_file: app.py
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pinned: false
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license: mit
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app.py
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import json, time, os, sys, glob
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import gradio as gr
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sys.path.append("/home/user/app/ProteinMPNN/vanilla_proteinmpnn")
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sys.path.append("/home/duerr/phd/08_Code/ProteinMPNN/ProteinMPNN/vanilla_proteinmpnn")
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import matplotlib.pyplot as plt
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import shutil
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import warnings
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import numpy as np
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import torch
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from torch import optim
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from torch.utils.data import DataLoader
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from torch.utils.data.dataset import random_split, Subset
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import copy
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import torch.nn as nn
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import torch.nn.functional as F
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import random
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import
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import os.path
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import plotly.express as px
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import urllib
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import jax.numpy as jnp
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import tensorflow as tf
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from moleculekit.molecule import Molecule
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if "/home/user/app/af_backprop" not in sys.path:
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sys.path.append("/home/user/app/af_backprop")
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if "/home/duerr/phd/08_Code/ProteinMPNN/af_backprop" not in sys.path:
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sys.path.append("/home/duerr/phd/08_Code/ProteinMPNN/af_backprop")
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from utils import *
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from alphafold.common import protein
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from alphafold.data import pipeline
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from alphafold.model import data, config
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from alphafold.model import model as afmodel
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from alphafold.common import residue_constants
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import re
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import numpy as np
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import jax
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tf.config.set_visible_devices([], "GPU")
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@@ -322,10 +317,43 @@ def preprocess_mol(pdb_code="", filepath=""):
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mol.write("cleaned.pdb")
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return "cleaned.pdb", df
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def make_fixed_positions_dict(atomsel, residue_index_df):
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# we use the uploaded file for the selection
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mol = Molecule('original.pdb')
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# use index for selection as resids will change
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selected_residues = mol.get("index",atomsel)
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# clean up
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- <code>resid 94 96 119</code> Residues 94, 94 and 119
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- <code>within 5 of resname ZN</code> All residues with any atom <5 Å of zinc ion
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- <code>chain A and within 5 of chain B </code> All residues of chain A that are part of the interface with chain B
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- <code>protein and within 5 of nucleic </code> All residues that bind to DNA (if present in structure)
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atomsel = gr.Textbox(placeholder="Specify atom selection ", label="Fixed positions")
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btn = gr.Button("Run")
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["Redesign of Homomer to Heteromer", "3HTN", "A,B", "C", False, 2, 0.1, ""],
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["Redesign of MID1 scaffold keeping binding site fixed", "3V1C", "A,B", "", False, 2, 0.1, "within 5 of resname ZN"],
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["Redesign of DNA binding protein", "3JRD", "A,B", "", False, 2, 0.1, "within 8 of nucleic"],
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],
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)
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import json, time, os, sys, glob
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import urllib
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import shutil
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import warnings
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import copy
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import random
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import re
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import os.path
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import torch
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import ray
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import jax
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import gradio as gr
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import pandas as pd
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import numpy as np
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import plotly.express as px
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import jax.numpy as jnp
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import tensorflow as tf
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import matplotlib.pyplot as plt
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import colabfold as cf
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import plotly.graph_objects as go
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import torch.nn as nn
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import torch.nn.functional as F
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if "/home/user/app/af_backprop" not in sys.path:
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sys.path.append("/home/user/app/af_backprop")
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if "/home/duerr/phd/08_Code/ProteinMPNN/af_backprop" not in sys.path:
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sys.path.append("/home/duerr/phd/08_Code/ProteinMPNN/af_backprop")
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from torch import optim
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from torch.utils.data import DataLoader
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from torch.utils.data.dataset import random_split, Subset
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from moleculekit.molecule import Molecule
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from alphafold.common import protein
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from alphafold.data import pipeline
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from alphafold.model import data, config
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from alphafold.model import model as afmodel
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from alphafold.common import residue_constants
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from utils import *
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sys.path.append("/home/user/app/ProteinMPNN/vanilla_proteinmpnn")
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sys.path.append("/home/duerr/phd/08_Code/ProteinMPNN/ProteinMPNN/vanilla_proteinmpnn")
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tf.config.set_visible_devices([], "GPU")
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mol.write("cleaned.pdb")
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return "cleaned.pdb", df
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def assign_sasa(mol):
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from moleculekit.projections.metricsasa import MetricSasa
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metr = MetricSasa(
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mode="residue", filtersel="protein"
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)
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sasaR = metr.project(mol)[0]
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is_prot = mol.atomselect("protein")
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resids=pd.DataFrame.from_dict({"resid":mol.resid, "is_prot":is_prot})
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new_masses=[]
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i_without_non_prot = 0
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for i, g in resids.groupby((resids['resid'].shift() != resids['resid']).cumsum()):
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if g["is_prot"].unique()[0]==True:
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g["sasa"]=sasaR[i_without_non_prot]
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i_without_non_prot+=1
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else:
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g["sasa"]=0
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new_masses.extend(list(g.sasa))
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return np.array(new_masses)
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def process_atomsel(atomsel):
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"""everything lowercase and replace some keywords not relevant for protein design"""
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atomsel=re.sub('sasa', 'mass',atomsel, flags=re.I)
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atomsel=re.sub('plddt', 'beta',atomsel, flags=re.I)
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return atomsel
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def make_fixed_positions_dict(atomsel, residue_index_df):
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# we use the uploaded file for the selection
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mol = Molecule('original.pdb')
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# use index for selection as resids will change
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# set sasa to 0 for all non protein atoms (all non protein atoms are deleted later)
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mol.masses = assign_sasa(mol)
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print(mol.masses.shape)
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print(assign_sasa(mol).shape)
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atomsel = process_atomsel("chain B or (chain A and Sasa < 30)")
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selected_residues = mol.get("index",atomsel)
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# clean up
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- <code>resid 94 96 119</code> Residues 94, 94 and 119
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- <code>within 5 of resname ZN</code> All residues with any atom <5 Å of zinc ion
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- <code>chain A and within 5 of chain B </code> All residues of chain A that are part of the interface with chain B
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- <code>protein and within 5 of nucleic </code> All residues that bind to DNA (if present in structure)
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- <code>not (chain A and within 5 of chain B) </code> only modify residues that are in the interface with the fixed chain, not further away
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- <code>chain A or (chain B and sasa < 20) </code> Keep chain A and all core residues fixeds
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- <code>pLDDT >70 </code> Redesign all residues with low pLDDT
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Note that <code>sasa</code> and <code>pLDDT</code> selectors modify default VMD behavior. SASA is calculated using moleculekit and written to the mass attribute. Selections based on mass do not work.
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pLDDT is an alias for beta, it only works correctly with structures that contain the appropriate values in the beta column of the PDB file. """)
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atomsel = gr.Textbox(placeholder="Specify atom selection ", label="Fixed positions")
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btn = gr.Button("Run")
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["Redesign of Homomer to Heteromer", "3HTN", "A,B", "C", False, 2, 0.1, ""],
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["Redesign of MID1 scaffold keeping binding site fixed", "3V1C", "A,B", "", False, 2, 0.1, "within 5 of resname ZN"],
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["Redesign of DNA binding protein", "3JRD", "A,B", "", False, 2, 0.1, "within 8 of nucleic"],
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["Surface Redesign of miniprotein", "7JZM", "A,B", "", False, 2, 0.1, "chain B or (chain A and sasa < 20)"],
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],
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)
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requirements.txt
CHANGED
@@ -18,6 +18,6 @@ plotly
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GPUtil
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ray
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tqdm
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gradio==3.
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protobuf<4
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-f https://storage.googleapis.com/jax-releases/jax_releases.html
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GPUtil
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ray
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tqdm
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gradio==3.1
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protobuf<4
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-f https://storage.googleapis.com/jax-releases/jax_releases.html
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