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clean up output
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‎cookbook/openfold3_to_openfe.ipynb‎

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"\n",
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"<div class=\"alert alert-block alert-warning\"> \n",
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"⚠️ <b>Important Note:</b>\n",
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" Here we use the first model for each complex predicted by OpenFold3. In practice you would filter through all predicted models, possibly using pose busters (https://github.com/maabuu/posebusters) and some other scoring metrics to identify the most plausible inputs.\n",
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" Here we use the first model for each complex predicted by OpenFold3. In practice you would filter through all predicted models, possibly using pose busters (github.com/maabuu/posebusters) and some other scoring metrics to identify the most plausible inputs.\n",
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"</div>"
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"cell_type": "code",
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"execution_count": 4,
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"id": "25ef33bf-fb1a-45da-96e4-004f77ef7d34",
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"metadata": {
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"scrolled": true
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},
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"text": [
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"/Users/atravitz/micromamba/envs/openfe-notebooks/lib/python3.13/site-packages/MDAnalysis/coordinates/PDB.py:885: UserWarning: Unit cell dimensions not found. CRYST1 record set to unitary values.\n",
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" warnings.warn(\n",
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"[11:04:36] WARNING: More than one matching pattern found - picking one\n",
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"[11:04:36] WARNING: More than one matching pattern found - picking one\n",
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@@ -430,7 +428,7 @@
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" ligand = pdb.name.split('_seed')[0]\n",
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" mob = mda.Universe(pdb)\n",
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"\n",
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" # 2) Align mobile → reference using protein backbone\n",
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" # Align mobile → reference using protein backbone\n",
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" ref_prot = ref.select_atoms(\"protein and backbone\")\n",
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" mob_prot = mob.select_atoms(\"protein and backbone\")\n",
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" \n",
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"id": "fe3ca792-4615-4be3-8a41-feb0819e968d",
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"metadata": {},
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"source": [
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"<div class=\"alert alert-block alert-danger\"> \n",
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"<div class=\"alert alert-block alert-warning\"> \n",
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"⚠️ <b>Important Note:</b>\n",
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" <br><br>\n",
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" Here simply we assign ligand protonation states to those we defined at the start of this exercise. Additionally, below we will assign protein protonation states using PDBFixer at pH 7 without accounting for the ligand.<br><br>\n",
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"text": [
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"Generating charges: 100%|███████████████████████| 10/10 [00:05<00:00, 1.73it/s]\n"
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"Generating charges: 100%|███████████████████████| 10/10 [00:05<00:00, 1.75it/s]\n"
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"name": "stderr",
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"text": [
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"/Users/atravitz/micromamba/envs/openfe-notebooks/lib/python3.13/site-packages/gufe/components/explicitmoleculecomponent.py:59: UserWarning: Molecule (name='') doesn't have any hydrogen atoms present. If this is unexpected, consider loading the molecule with `removeHs=False`\n",
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"/Users/atravitz/micromamba/envs/openfe-notebooks/lib/python3.13/site-packages/gufe/components/explicitmoleculecomponent.py:59: UserWarning: Molecule (name='tyk2') doesn't have any hydrogen atoms present. If this is unexpected, consider loading the molecule with `removeHs=False`\n",
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" warnings.warn(\n"
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]
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}
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],
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"source": [
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"protein = openfe.ProteinComponent.from_pdb_file(\"openfold_to_openfe/p_aligned/protein.pdb\")"
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"protein = openfe.ProteinComponent.from_pdb_file(\"openfold_to_openfe/p_aligned/protein.pdb\", name=\"tyk2\")"
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]
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{
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"## 4. Creating a Binding Free Energy Transformation\n",
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"\n",
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"### 4a) Absolute Binding Free Energy\n",
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"Using these inputs, we can create ABFE Transformations. For the sake of simplicity, we will only create a Transformation for `lig_jmc_27`.\n",
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"Using these inputs, we can create ABFE Transformations. For the sake of simplicity, we will only create a Transformation for `lig_jmc_27`, but this process is generalizable to the rest of the ligands in the series.\n",
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"\n",
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"First we create the `ChemicalSystems` defining the end states of the simulation:"
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]
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"execution_count": 10,
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"id": "c405e50c-1df3-4bef-8278-393550e1fc6a",
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"metadata": {},
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"outputs": [],
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"outputs": [
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{
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"data": {
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"text/plain": [
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"SmallMoleculeComponent(name=lig_jmc_27)"
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]
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},
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"execution_count": 10,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"ligand = [l for l in charged_ligands if l.name == 'lig_jmc_27'][0]"
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"# choose the first ligand\n",
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"ligand = [l for l in charged_ligands if l.name == 'lig_jmc_27'][0]\n",
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"ligand"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 11,
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"id": "987a1657-82d0-4310-9fe7-4eecd289632a",
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"metadata": {},
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"outputs": [],
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"outputs": [
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{
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"data": {
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"text/plain": [
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"(ChemicalSystem(name=state_A, components={'ligand': SmallMoleculeComponent(name=lig_jmc_27), 'protein': ProteinComponent(name=tyk2), 'solvent': SolventComponent(name=O, Na+, Cl-)}),\n",
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" ChemicalSystem(name=state_B, components={'protein': ProteinComponent(name=tyk2), 'solvent': SolventComponent(name=O, Na+, Cl-)}))"
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]
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},
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"execution_count": 11,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"# Create the two end states\n",
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"\n",
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" 'ligand': ligand,\n",
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" 'protein': protein,\n",
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" 'solvent': solvent,\n",
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"})\n",
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"}, name=\"state_A\")\n",
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"# state B is the system without the ligand\n",
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"stateB = openfe.ChemicalSystem({\n",
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" 'protein': protein,\n",
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" 'solvent': solvent,\n",
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"})"
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"}, name=\"state_B\")\n",
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"\n",
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"stateA, stateB"
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")"
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},
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{
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"cell_type": "markdown",
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"id": "f89a9800-9d25-470c-845f-87479095806e",
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"metadata": {},
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"source": [
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"This transformation can now be run using `openfe quickrun`."
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]
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},
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"cell_type": "markdown",
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"id": "f9e4f4a1-ed28-4d33-b73b-865dc5023b93",
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"metadata": {},
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"source": [
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"### 4b) Separated Topologies Relative Binding Free Energy Transformation\n",
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"\n",
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"Next we create a SepTop RBFE Transformation. Here we will do the transformation between `lig_jmc_27` and `lig_ejm_46`."
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"We can instead build a SepTop RBFE Transformation. Here we will do the transformation between `lig_jmc_27` and `lig_ejm_46`."
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"}, name=\"state_A\",)\n",
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"# state B is the system with lig_ejm_46\n",
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"stateB = openfe.ChemicalSystem({\n",
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"}, name=\"state_B\",)"
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")"
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"id": "d59f5d1b-f078-49c2-9965-9cb8abc64a71",
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"metadata": {},
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"source": [
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"This transformation can now be run using `openfe quickrun`."
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},
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"source": [
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"}, name=\"state_A_complex\",)\n",
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"stateB_complex = openfe.ChemicalSystem({\n",
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"}, name=\"state_B_complex\")"
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"}, name=\"state_A_solvent\",)\n",
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"},name=\"state_B_solvent\",)"
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{
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"cell_type": "markdown",
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"id": "f08aaff4-97d0-4f53-bb32-1c7e247432aa",
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"metadata": {},
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"source": [
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"This transformation can now be run using `openfe quickrun`."
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]
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},
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"In practice, one would create entire network of Transformations, and then run all the simulations.\n",
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"This notebook will not cover these aspects. To find out more about this, please see the [OpenFE Tutorials](https://docs.openfree.energy/en/latest/tutorials/index.html)."
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"execution_count": null,
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"id": "ac79eed4-0030-4a9a-b86e-39c53681446b",
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"metadata": {},
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"outputs": [],
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"source": []
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