diff --git a/cookbook/generate_ligand_network.ipynb b/cookbook/generate_ligand_network.ipynb index b46ec89..2b801fa 100644 --- a/cookbook/generate_ligand_network.ipynb +++ b/cookbook/generate_ligand_network.ipynb @@ -13,32 +13,15 @@ "id": "5da95fa6-c9a7-48a2-9d8e-e35b3b6818f6", "metadata": {}, "source": [ - "A [Ligand Network] is a graph of transformations between small molecules, typically such that every small molecule can reach every other small molecule via a series of transformations. This eventually forms the graph of the free energy campaign. A `LigandNetwork` can be generated from a collection of `SmallMoleculeComponent` instances by optimising over possible networks according to some criteria; in OpenFE, this involves combining a network generating strategy with a scoring function for individual mappings.\n", - "\n", - "[Ligand Network]: https://docs.openfree.energy/en/stable/reference/api/generated/openfe.setup.LigandNetwork.html" + "For an introduction to ``LigandNetwork``s, see [User Guide: Defining the Ligand Network](https://docs.openfree.energy/en/latest/guide/setup/creating_ligand_networks.html). " ] }, { "cell_type": "markdown", - "id": "27106bff-dbcf-49ee-b119-2c0f15305618", + "id": "d486ab37-e2fe-4925-b43d-787bf719cf37", "metadata": {}, "source": [ - "## Setup" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "id": "f8f4ce1e-98e9-4c9b-98d3-aea1d21e0c12", - "metadata": {}, - "outputs": [], - "source": [ - "%matplotlib inline\n", - "\n", - "from rdkit import Chem\n", - "from openmm import unit\n", - "\n", - "import openfe" + "## Load the Ligands" ] }, { @@ -46,25 +29,43 @@ "id": "7f1a272a-ffe7-4397-a8a6-c590d3a210bc", "metadata": {}, "source": [ - "This cookbook assumes you've already loaded a collection of `SmallMoleculeComponent` objects into an iterable called `ligands`. For more information, see [Loading Small Molecules]:\n", + "This cookbook assumes you have already loaded a collection of `SmallMoleculeComponent` objects into an iterable called `ligands`.\n", "\n", - "[Loading Small Molecules]: https://docs.openfree.energy/en/stable/cookbook/loading_molecules.html#loading-small-molecules" + "For more information, see the [Loading Small Molecules Cookbook](https://docs.openfree.energy/en/stable/cookbook/loading_molecules.html#loading-small-molecules)." ] }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 6, "id": "80072b52-ded4-4b38-a5c2-72b87d483f53", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "[SmallMoleculeComponent(name=benzene),\n", + " SmallMoleculeComponent(name=toluene),\n", + " SmallMoleculeComponent(name=phenol),\n", + " SmallMoleculeComponent(name=benzonitrile),\n", + " SmallMoleculeComponent(name=anisole),\n", + " SmallMoleculeComponent(name=benzaldehyde),\n", + " SmallMoleculeComponent(name=styrene)]" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "ligands = [\n", - " openfe.SmallMoleculeComponent(mol) \n", - " for mol in Chem.SDMolSupplier(\n", - " \"assets/somebenzenes.sdf\", \n", - " removeHs=False,\n", - " )\n", - "]" + "%matplotlib inline\n", + "from rdkit import Chem\n", + "import openfe\n", + "\n", + "supplier = Chem.SDMolSupplier(\"assets/somebenzenes.sdf\", removeHs=False)\n", + "ligands = [openfe.SmallMoleculeComponent(mol) for mol in supplier]\n", + "\n", + "ligands" ] }, { @@ -80,34 +81,36 @@ "id": "020cf05c-7bcc-4b10-9ba5-f4ded80d2d66", "metadata": {}, "source": [ - "An atom mapper produces mappings between two given ligands. Atom mapper classes inherit from [LigandAtomMapper]. Each atom mapper suggests one or more mappings, which can be scored seperately. As a result, multiple atom mappers can be used to generate additional mappings for network planning.\n", + "The `AtomMapper` will generate the `AtomMappings` that relate two small molecules and serve as the edges of our LigandNetwork.\n", + "Atom mapper classes inherit from [LigandAtomMapper].\n", + "\n", + "Each atom mapper suggests one or more mappings, which can be scored seperately.\n", + "As a result, multiple atom mappers can be used to generate additional mappings for network planning.\n", "\n", "[LigandAtomMapper]: https://docs.openfree.energy/en/stable/reference/api/generated/openfe.setup.atom_mapping.LigandAtomMapper.html" ] }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 2, "id": "5019c471-a173-4097-b6c8-b42bfb701e03", "metadata": {}, "outputs": [], "source": [ - "mappers = [\n", - " openfe.setup.LomapAtomMapper(\n", + "from openmm import unit\n", + "\n", + "lomap_mapper = openfe.setup.LomapAtomMapper(\n", " time=20, # Time out if MCS algorithm takes 20 seconds\n", " threed=True, # Use atom positions to prune symmetric mappings\n", " max3d=1.0, # Forbid mapping between atoms more than 1.0 Å apart\n", " element_change=True, # Allow mappings that change an atoms element\n", " seed='', # Empty SMARTS string causes MCS search to start from scratch\n", " shift=False, # Keep pre-aligned atom positions for 3D position checks\n", - " ),\n", - " # openfe.setup.PersesAtomMapper(\n", - " # allow_ring_breaking=True, # Propose mappings that break cyclic systems\n", - " # preserve_chirality=True, # Forbid mappings that change stereochemistry\n", - " # use_positions=True, # Use atom positions rather than MCS to choose mappings\n", - " # coordinate_tolerance=0.25 * unit.angstrom, # Forbid mappings between distant atoms\n", - " # ),\n", - "]" + ")\n", + "kartograf_mapper = openfe.setup.KartografAtomMapper()\n", + "\n", + "# to demonstrate passing multiple atom mappers to the planner\n", + "mappers = [lomap_mapper, kartograf_mapper]" ] }, { @@ -123,27 +126,24 @@ "id": "5998c002-4d39-42c0-b37f-bd0357f27fe6", "metadata": {}, "source": [ - "Many ligand network planners require some way to score each possible network so that the optimal network can be identified. OpenFE scores networks by the quality of the mappings between ligands - transformations that are expected to converge quickly without introducing artifacts are scored highly, and more drastic or risky alchemy is penalised. A scoring function is a function that takes an atom mapping and returns a float between 0.0 and 1.0, with higher numbers representing better maps." + "Many ligand network planners require a Mapping Scorer to assign scores (i.e. edge weights) to each of the transformations (i.e. network edges) to be used as an estimation of the quality of the mapping.\n", + "\n", + "A Mapping Scorer is a function that takes an atom mapping and returns a score between 0.0, very hard to compute, and 1.0 for easy to compute.\n", + "\n", + "In other words, transformations that are expected to converge quickly without introducing artifacts are scored highly, while more drastic or risky transformations are scored lower.\n", + "\n", + "Keep in mind that edge scorers are fallible and a score is only the *anticipated* difficulty of a transformation to be used for network creation." ] }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 3, "id": "3bbf3f5b-9e29-467f-aff8-07e8dad7fd4c", "metadata": {}, "outputs": [], "source": [ - "# The product of other LOMAP scorers\n", - "scorer = openfe.lomap_scorers.default_lomap_score \n", - "\n", - "# # The default PERSES scoring function\n", - "# scorer = openfe.perses_scorers.default_perses_score \n", - "\n", - "# # Or define your own scoring function\n", - "# scorer = lambda m: (\n", - "# openfe.lomap_scorers.default_lomap_score(m) \n", - "# * openfe.perses_scorers.default_perses_scorer(m)\n", - "# )" + "# use LOMAP scorer with defaults\n", + "scorer = openfe.lomap_scorers.default_lomap_score " ] }, { @@ -164,32 +164,818 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 7, "id": "9492e2e7-33df-449e-9bd1-847ff52d2029", - "metadata": {}, - "outputs": [], + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "INFO:\t#################################\n", + "INFO:\tMap Heavy Atoms \n", + "INFO:\t#################################\n", + 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+ "INFO:\t#################################\n", + "INFO:\tMasking Atoms\n", + "INFO:\tBuild Distance Matrix\n", + "INFO:\tCalculate Mapping\n", + "INFO:\tFind Maximal overlapping connected sets of mapped atoms\n", + "INFO:\tFiltering bond breaks\n", + "INFO:\t#################################\n", + "INFO:\tMap Heavy Atoms \n", + "INFO:\t#################################\n", + "INFO:\tMasking Atoms\n", + "INFO:\tBuild Distance Matrix\n", + "INFO:\tCalculate Mapping\n", + "INFO:\tFind Maximal overlapping connected sets of mapped atoms\n", + "INFO:\t#################################\n", + "INFO:\tMap Hydrogen Atoms: \n", + "INFO:\t#################################\n", + "INFO:\tMasking Atoms\n", + "INFO:\tBuild Distance Matrix\n", + "INFO:\tCalculate Mapping\n", + "INFO:\tFind Maximal overlapping connected sets of mapped atoms\n", + "INFO:\tFiltering bond breaks\n", + "INFO:\t#################################\n", + "INFO:\tMap Heavy Atoms \n", + "INFO:\t#################################\n", + "INFO:\tMasking Atoms\n", + "INFO:\tBuild Distance Matrix\n", + "INFO:\tCalculate Mapping\n", + "INFO:\tFind Maximal overlapping connected sets of mapped atoms\n", + "INFO:\t#################################\n", + "INFO:\tMap Hydrogen Atoms: \n", + "INFO:\t#################################\n", + "INFO:\tMasking Atoms\n", + "INFO:\tBuild Distance Matrix\n", + "INFO:\tCalculate Mapping\n", + "INFO:\tFind Maximal overlapping connected sets of mapped atoms\n", + "INFO:\tFiltering bond breaks\n", + "INFO:\t#################################\n", + "INFO:\tMap Heavy Atoms \n", + "INFO:\t#################################\n", + "INFO:\tMasking Atoms\n", + "INFO:\tBuild Distance Matrix\n", + "INFO:\tCalculate Mapping\n", + "INFO:\tFind Maximal overlapping connected sets of mapped atoms\n", + "INFO:\t#################################\n", + "INFO:\tMap Hydrogen Atoms: \n", + "INFO:\t#################################\n", + "INFO:\tMasking Atoms\n", + "INFO:\tBuild Distance Matrix\n", + "INFO:\tCalculate Mapping\n", + "INFO:\tFind Maximal overlapping connected sets of mapped atoms\n", + "INFO:\tFiltering bond breaks\n", + "INFO:\t#################################\n", + "INFO:\tMap Heavy Atoms \n", + "INFO:\t#################################\n", + "INFO:\tMasking Atoms\n", + "INFO:\tBuild Distance Matrix\n", + "INFO:\tCalculate Mapping\n", + "INFO:\tFind Maximal overlapping connected sets of mapped atoms\n", + "INFO:\t#################################\n", + "INFO:\tMap Hydrogen Atoms: \n", + "INFO:\t#################################\n", + "INFO:\tMasking Atoms\n", + "INFO:\tBuild Distance Matrix\n", + "INFO:\tCalculate Mapping\n", + "INFO:\tFind Maximal overlapping connected sets of mapped atoms\n", + "INFO:\tFiltering bond breaks\n", + "INFO:\t#################################\n", + "INFO:\tMap Heavy Atoms \n", + "INFO:\t#################################\n", + "INFO:\tMasking Atoms\n", + "INFO:\tBuild Distance Matrix\n", + "INFO:\tCalculate Mapping\n", + "INFO:\tFind Maximal overlapping connected sets of mapped atoms\n", + "INFO:\t#################################\n", + "INFO:\tMap Hydrogen Atoms: \n", + "INFO:\t#################################\n", + "INFO:\tMasking Atoms\n", + "INFO:\tBuild Distance Matrix\n", + "INFO:\tCalculate Mapping\n", + "INFO:\tFind Maximal overlapping connected sets of mapped atoms\n", + "INFO:\tFiltering bond breaks\n", + "INFO:\t#################################\n", + "INFO:\tMap Heavy Atoms \n", + "INFO:\t#################################\n", + "INFO:\tMasking Atoms\n", + "INFO:\tBuild Distance Matrix\n", + "INFO:\tCalculate Mapping\n", + "INFO:\tFind Maximal overlapping connected sets of mapped atoms\n", + "INFO:\t#################################\n", + "INFO:\tMap Hydrogen Atoms: \n", + "INFO:\t#################################\n", + "INFO:\tMasking Atoms\n", + "INFO:\tBuild Distance Matrix\n", + "INFO:\tCalculate Mapping\n", + "INFO:\tFind Maximal overlapping connected sets of mapped atoms\n", + "INFO:\tFiltering bond breaks\n", + "INFO:\t#################################\n", + "INFO:\tMap Heavy Atoms \n", + "INFO:\t#################################\n", + "INFO:\tMasking Atoms\n", + "INFO:\tBuild Distance Matrix\n", + "INFO:\tCalculate Mapping\n", + "INFO:\tFind Maximal overlapping connected sets of mapped atoms\n", + "INFO:\t#################################\n", + "INFO:\tMap Hydrogen Atoms: \n", + "INFO:\t#################################\n", + "INFO:\tMasking Atoms\n", + "INFO:\tBuild Distance Matrix\n", + "INFO:\tCalculate Mapping\n", + "INFO:\tFind Maximal overlapping connected sets of mapped atoms\n", + "INFO:\tFiltering bond breaks\n", + "INFO:\t#################################\n", + "INFO:\tMap Heavy Atoms \n", + "INFO:\t#################################\n", + "INFO:\tMasking Atoms\n", + "INFO:\tBuild Distance Matrix\n", + "INFO:\tCalculate Mapping\n", + "INFO:\tFind Maximal overlapping connected sets of mapped atoms\n", + "INFO:\t#################################\n", + "INFO:\tMap Hydrogen Atoms: \n", + "INFO:\t#################################\n", + "INFO:\tMasking Atoms\n", + "INFO:\tBuild Distance Matrix\n", + "INFO:\tCalculate Mapping\n", + "INFO:\tFind Maximal overlapping connected sets of mapped atoms\n", + "INFO:\tFiltering bond breaks\n", + "INFO:\t#################################\n", + "INFO:\tMap Heavy Atoms \n", + "INFO:\t#################################\n", + "INFO:\tMasking Atoms\n", + "INFO:\tBuild Distance Matrix\n", + "INFO:\tCalculate Mapping\n", + "INFO:\tFind Maximal overlapping connected sets of mapped atoms\n", + "INFO:\t#################################\n", + "INFO:\tMap Hydrogen Atoms: \n", + "INFO:\t#################################\n", + "INFO:\tMasking Atoms\n", + "INFO:\tBuild Distance Matrix\n", + "INFO:\tCalculate Mapping\n", + "INFO:\tFind Maximal overlapping connected sets of mapped atoms\n", + "INFO:\tFiltering bond breaks\n", + "INFO:\t#################################\n", + "INFO:\tMap Heavy Atoms \n", + "INFO:\t#################################\n", + "INFO:\tMasking Atoms\n", + "INFO:\tBuild Distance Matrix\n", + "INFO:\tCalculate Mapping\n", + "INFO:\tFind Maximal overlapping connected sets of mapped atoms\n", + "INFO:\t#################################\n", + "INFO:\tMap Hydrogen Atoms: \n", + "INFO:\t#################################\n", + "INFO:\tMasking Atoms\n", + "INFO:\tBuild Distance Matrix\n", + "INFO:\tCalculate Mapping\n", + "INFO:\tFind Maximal overlapping connected sets of mapped atoms\n", + "INFO:\tFiltering bond breaks\n", + "INFO:\t#################################\n", + "INFO:\tMap Heavy Atoms \n", + "INFO:\t#################################\n", + "INFO:\tMasking Atoms\n", + "INFO:\tBuild Distance Matrix\n", + "INFO:\tCalculate Mapping\n", + "INFO:\tFind Maximal overlapping connected sets of mapped atoms\n", + "INFO:\t#################################\n", + "INFO:\tMap Hydrogen Atoms: \n", + "INFO:\t#################################\n", + "INFO:\tMasking Atoms\n", + "INFO:\tBuild Distance Matrix\n", + "INFO:\tCalculate Mapping\n", + "INFO:\tFind Maximal overlapping connected sets of mapped atoms\n", + "INFO:\tFiltering bond breaks\n", + "INFO:\t#################################\n", + "INFO:\tMap Heavy Atoms \n", + "INFO:\t#################################\n", + "INFO:\tMasking Atoms\n", + "INFO:\tBuild Distance Matrix\n", + "INFO:\tCalculate Mapping\n", + "INFO:\tFind Maximal overlapping connected sets of mapped atoms\n", + "INFO:\t#################################\n", + "INFO:\tMap Hydrogen Atoms: \n", + "INFO:\t#################################\n", + "INFO:\tMasking Atoms\n", + "INFO:\tBuild Distance Matrix\n", + "INFO:\tCalculate Mapping\n", + "INFO:\tFind Maximal overlapping connected sets of mapped atoms\n", + "INFO:\tFiltering bond breaks\n", + "INFO:\t#################################\n", + "INFO:\tMap Heavy Atoms \n", + "INFO:\t#################################\n", + "INFO:\tMasking Atoms\n", + "INFO:\tBuild Distance Matrix\n", + "INFO:\tCalculate Mapping\n", + "INFO:\tFind Maximal overlapping connected sets of mapped atoms\n", + "INFO:\t#################################\n", + "INFO:\tMap Hydrogen Atoms: \n", + "INFO:\t#################################\n", + "INFO:\tMasking Atoms\n", + "INFO:\tBuild Distance Matrix\n", + "INFO:\tCalculate Mapping\n", + "INFO:\tFind Maximal overlapping connected sets of mapped atoms\n", + "INFO:\tFiltering bond breaks\n", + "INFO:\t#################################\n", + "INFO:\tMap Heavy Atoms \n", + "INFO:\t#################################\n", + "INFO:\tMasking Atoms\n", + "INFO:\tBuild Distance Matrix\n", + "INFO:\tCalculate Mapping\n", + "INFO:\tFind Maximal overlapping connected sets of mapped atoms\n", + "INFO:\t#################################\n", + "INFO:\tMap Hydrogen Atoms: \n", + "INFO:\t#################################\n", + "INFO:\tMasking Atoms\n", + "INFO:\tBuild Distance Matrix\n", + "INFO:\tCalculate Mapping\n", + "INFO:\tFind Maximal overlapping connected sets of mapped atoms\n", + "INFO:\tFiltering bond breaks\n", + "INFO:\t#################################\n", + "INFO:\tMap Heavy Atoms \n", + "INFO:\t#################################\n", + "INFO:\tMasking Atoms\n", + "INFO:\tBuild Distance Matrix\n", + "INFO:\tCalculate Mapping\n", + "INFO:\tFind Maximal overlapping connected sets of mapped atoms\n", + "INFO:\t#################################\n", + "INFO:\tMap Hydrogen Atoms: \n", + "INFO:\t#################################\n", + "INFO:\tMasking Atoms\n", + "INFO:\tBuild Distance Matrix\n", + "INFO:\tCalculate Mapping\n", + "INFO:\tFind Maximal overlapping connected sets of mapped atoms\n", + "INFO:\tFiltering bond breaks\n", + "INFO:\tTrying to remove edge 4-5 with similarity 0.670320\n", + "INFO:\tChecking edge deletion on distance-to-actives 0 vs 0\n", + "INFO:\tRemoved edge 4-5\n", + "INFO:\tTrying to remove edge 3-4 with similarity 0.670320\n", + "INFO:\tChecking edge deletion on distance-to-actives 0 vs 0\n", + "INFO:\tRemoved edge 3-4\n", + "INFO:\tTrying to remove edge 3-5 with similarity 0.704688\n", + "INFO:\tChecking edge deletion on distance-to-actives 0 vs 0\n", + "INFO:\tRemoved edge 3-5\n", + "INFO:\tTrying to remove edge 3-6 with similarity 0.704688\n", + "INFO:\tChecking edge deletion on distance-to-actives 0 vs 0\n", + "INFO:\tRemoved edge 3-6\n", + "INFO:\tTrying to remove edge 4-6 with similarity 0.704688\n", + "INFO:\tChecking edge deletion on distance-to-actives 0 vs 0\n", + "INFO:\tRemoved edge 4-6\n", + "INFO:\tTrying to remove edge 2-3 with similarity 0.740818\n", + "INFO:\tChecking edge deletion on distance-to-actives 0 vs 0\n", + "INFO:\tRemoved edge 2-3\n", + "INFO:\tTrying to remove edge 2-5 with similarity 0.740818\n", + "INFO:\tChecking edge deletion on distance-to-actives 0 vs 0\n", + "INFO:\tRemoved edge 2-5\n", + "INFO:\tTrying to remove edge 2-6 with similarity 0.740818\n", + "INFO:\tChecking edge deletion on distance-to-actives 0 vs 0\n", + "INFO:\tRemoved edge 2-6\n", + "INFO:\tTrying to remove edge 1-3 with similarity 0.778801\n", + "INFO:\tRejecting edge deletion on cycle covering\n", + "INFO:\tTrying to remove edge 1-5 with similarity 0.778801\n", + "INFO:\tChecking edge deletion on distance-to-actives 0 vs 0\n", + "INFO:\tRemoved edge 1-5\n", + "INFO:\tTrying to remove edge 1-6 with similarity 0.778801\n", + "INFO:\tChecking edge deletion on distance-to-actives 0 vs 0\n", + "INFO:\tRemoved edge 1-6\n", + "INFO:\tTrying to remove edge 0-3 with similarity 0.818731\n", + "INFO:\tRejecting edge deletion on cycle covering\n", + "INFO:\tTrying to remove edge 0-4 with similarity 0.818731\n", + "INFO:\tChecking edge deletion on distance-to-actives 0 vs 0\n", + "INFO:\tRemoved edge 0-4\n", + "INFO:\tTrying to remove edge 0-5 with similarity 0.818731\n", + "INFO:\tRejecting edge deletion on cycle covering\n", + "INFO:\tTrying to remove edge 0-6 with similarity 0.818731\n", + "INFO:\tRejecting edge deletion on cycle covering\n", + "INFO:\tTrying to remove edge 1-4 with similarity 0.860708\n", + "INFO:\tRejecting edge deletion on cycle covering\n", + "INFO:\tTrying to remove edge 0-1 with similarity 0.904837\n", + "INFO:\tChecking edge deletion on distance-to-actives 0 vs 0\n", + "INFO:\tRemoved edge 0-1\n", + "INFO:\tTrying to remove edge 0-2 with similarity 0.904837\n", + "INFO:\tRejecting edge deletion on cycle covering\n", + "INFO:\tTrying to remove edge 2-4 with similarity 0.904837\n", + "INFO:\tRejecting edge deletion on cycle covering\n", + "INFO:\tTrying to remove edge 1-2 with similarity 0.951229\n", + "INFO:\tChecking edge deletion on distance-to-actives 0 vs 0\n", + "INFO:\tRemoved edge 1-2\n", + "INFO:\tTrying to remove edge 5-6 with similarity 0.951229\n", + "INFO:\tRejecting edge deletion on cycle covering\n", + "INFO:\t#################################\n", + "INFO:\tMap Heavy Atoms \n", + "INFO:\t#################################\n", + "INFO:\tMasking Atoms\n", + "INFO:\tBuild Distance Matrix\n", + "INFO:\tCalculate Mapping\n", + "INFO:\tFind Maximal overlapping connected sets of mapped atoms\n", + "INFO:\t#################################\n", + "INFO:\tMap Hydrogen Atoms: \n", + "INFO:\t#################################\n", + "INFO:\tMasking Atoms\n", + "INFO:\tBuild Distance Matrix\n", + "INFO:\tCalculate Mapping\n", + "INFO:\tFind Maximal overlapping connected sets of mapped atoms\n", + "INFO:\tFiltering bond breaks\n", + "INFO:\t#################################\n", + "INFO:\tMap Heavy Atoms \n", + "INFO:\t#################################\n", + "INFO:\tMasking Atoms\n", + "INFO:\tBuild Distance Matrix\n", + "INFO:\tCalculate Mapping\n", + "INFO:\tFind Maximal overlapping connected sets of mapped atoms\n", + "INFO:\t#################################\n", + "INFO:\tMap Hydrogen Atoms: \n", + "INFO:\t#################################\n", + "INFO:\tMasking Atoms\n", + "INFO:\tBuild Distance Matrix\n", + "INFO:\tCalculate Mapping\n", + "INFO:\tFind Maximal overlapping connected sets of mapped atoms\n", + "INFO:\tFiltering bond breaks\n", + "INFO:\t#################################\n", + "INFO:\tMap Heavy Atoms \n", + "INFO:\t#################################\n", + "INFO:\tMasking Atoms\n", + "INFO:\tBuild Distance Matrix\n", + "INFO:\tCalculate Mapping\n", + "INFO:\tFind Maximal overlapping connected sets of mapped atoms\n", + "INFO:\t#################################\n", + "INFO:\tMap Hydrogen Atoms: \n", + "INFO:\t#################################\n", + "INFO:\tMasking Atoms\n", + "INFO:\tBuild Distance Matrix\n", + "INFO:\tCalculate Mapping\n", + "INFO:\tFind Maximal overlapping connected sets of mapped atoms\n", + "INFO:\tFiltering bond breaks\n", + "INFO:\t#################################\n", + "INFO:\tMap Heavy Atoms \n", + "INFO:\t#################################\n", + "INFO:\tMasking Atoms\n", + "INFO:\tBuild Distance Matrix\n", + "INFO:\tCalculate Mapping\n", + "INFO:\tFind Maximal overlapping connected sets of mapped atoms\n", + "INFO:\t#################################\n", + "INFO:\tMap Hydrogen Atoms: \n", + "INFO:\t#################################\n", + "INFO:\tMasking Atoms\n", + "INFO:\tBuild Distance Matrix\n", + "INFO:\tCalculate Mapping\n", + "INFO:\tFind Maximal overlapping connected sets of mapped atoms\n", + "INFO:\tFiltering bond breaks\n", + "INFO:\t#################################\n", + "INFO:\tMap Heavy Atoms \n", + "INFO:\t#################################\n", + "INFO:\tMasking Atoms\n", + "INFO:\tBuild Distance Matrix\n", + "INFO:\tCalculate Mapping\n", + "INFO:\tFind Maximal overlapping connected sets of mapped atoms\n", + "INFO:\t#################################\n", + "INFO:\tMap Hydrogen Atoms: \n", + "INFO:\t#################################\n", + "INFO:\tMasking Atoms\n", + "INFO:\tBuild Distance Matrix\n", + "INFO:\tCalculate Mapping\n", + "INFO:\tFind Maximal overlapping connected sets of mapped atoms\n", + "INFO:\tFiltering bond breaks\n", + "INFO:\t#################################\n", + "INFO:\tMap Heavy Atoms \n", + "INFO:\t#################################\n", + "INFO:\tMasking Atoms\n", + "INFO:\tBuild Distance Matrix\n", + "INFO:\tCalculate Mapping\n", + "INFO:\tFind Maximal overlapping connected sets of mapped atoms\n", + "INFO:\t#################################\n", + "INFO:\tMap Hydrogen Atoms: \n", + "INFO:\t#################################\n", + "INFO:\tMasking Atoms\n", + "INFO:\tBuild Distance Matrix\n", + "INFO:\tCalculate Mapping\n", + "INFO:\tFind Maximal overlapping connected sets of mapped atoms\n", + "INFO:\tFiltering bond breaks\n" + ] + } + ], "source": [ "# Choose the network that minimises the sum of scores\n", - "ligand_network = openfe.ligand_network_planning.generate_minimal_spanning_network(\n", + "mst_network = openfe.ligand_network_planning.generate_minimal_spanning_network(\n", " ligands=ligands,\n", " mappers=mappers,\n", " scorer=scorer,\n", - ")\n", + ");\n", "\n", - "# # Choose the lomap network that adds some closed ligand cycles\n", - "# ligand_network = openfe.ligand_network_planning.generate_lomap_network(\n", - "# molecules=ligands,\n", - "# mappers=mappers,\n", - "# scorer=scorer,\n", - "# )\n", + "# Choose the lomap network that adds some closed ligand cycles\n", + "lomap_network = openfe.ligand_network_planning.generate_lomap_network(\n", + " molecules=ligands,\n", + " mappers=mappers,\n", + " scorer=scorer,\n", + ");\n", "\n", "# # Connect each ligand to a central ligand\n", - "# ligand_network = openfe.ligand_network_planning.generate_radial_network(\n", - "# ligands=ligands[1:],\n", - "# central_ligand=ligands[0],\n", - "# mappers=mappers,\n", - "# scorer=scorer,\n", - "# )" + "radial_network = openfe.ligand_network_planning.generate_radial_network(\n", + " ligands=ligands[1:],\n", + " central_ligand=ligands[0],\n", + " mappers=mappers,\n", + " scorer=scorer,\n", + ");" ] }, { @@ -197,7 +983,7 @@ "id": "6c2f585e-d609-440a-9498-2affc2badc5c", "metadata": {}, "source": [ - "## Visualize" + "## Visualize the Network" ] }, { @@ -212,18 +998,18 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 5, "id": "92e0b934-8494-41f4-a0ad-0d0b01b3a8f9", "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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", 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" ] }, - "execution_count": 6, + "execution_count": 5, "metadata": {}, "output_type": "execute_result" } @@ -231,7 +1017,7 @@ "source": [ "from openfe.utils.atommapping_network_plotting import plot_atommapping_network\n", "\n", - "plot_atommapping_network(ligand_network)" + "plot_atommapping_network(lomap_network)" ] } ], @@ -251,7 +1037,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.6" + "version": "3.13.11" }, "widgets": { "application/vnd.jupyter.widget-state+json": { diff --git a/cookbook/hand_write_ligand_network.ipynb b/cookbook/hand_write_ligand_network.ipynb index 2f467bd..c950c96 100644 --- a/cookbook/hand_write_ligand_network.ipynb +++ b/cookbook/hand_write_ligand_network.ipynb @@ -5,7 +5,7 @@ "id": "bf739d70-3249-42b3-a352-8a41f8f8c667", "metadata": {}, "source": [ - "# Ligand Networks by Hand" + "# Explicitly Defining Ligand Networks" ] }, { @@ -13,7 +13,16 @@ "id": "f9ad85a0-a3b2-4e95-9784-0a88ba790683", "metadata": {}, "source": [ - "OpenFE provides utilities for ingesting networks from ordinary Python datastructures like `list[tuple[str, str]]` and `list[tuple[int, int]]`. Each string or integer respectively names or indexes a ligand, and tuples represent edges in the network. This allows specific networks to be written by hand, supports use cases where the desired edges are known, and may be helpful for loading networks from other tools." + "OpenFE provides utilities for ingesting networks from ordinary Python datastructures like `list[tuple[str, str]]` and `list[tuple[int, int]]`.\n", + "\n", + "Each string or integer respectively names or indexes a ligand, and tuples represent edges in the network.\n", + "\n", + "This explicit definition of networks supports use-cases where the desired edges are known and may be helpful for loading networks from other tools.\n", + "\n", + "Although this is the most flexible way to define a ``LigandNetwork``, we encourage you to use **openfe** helper functionality when possible for performance, reproducibility, and ease of use:\n", + "\n", + " - [Loading Ligand Networks Exported by Orion or FEP+](https://docs.openfree.energy/en/stable/cookbook/network_from_orion_fepp.html)\n", + " - [Planning a Ligand Network](https://docs.openfree.energy/en/stable/cookbook/generate_ligand_network.html)\n" ] }, { @@ -21,22 +30,7 @@ "id": "de32be93-e8d7-40dd-a043-4920a6e9c3ef", "metadata": {}, "source": [ - "## Setup" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "id": "91423c48-1649-4fae-9f0c-bd6224d83009", - "metadata": {}, - "outputs": [], - "source": [ - "%matplotlib inline\n", - "\n", - "from rdkit import Chem\n", - "\n", - "import openfe\n", - "from openfe.setup import ligand_network_planning" + "## Load the ligands" ] }, { @@ -44,25 +38,43 @@ "id": "39e64f74-337e-4a88-b253-ab051820d5e3", "metadata": {}, "source": [ - "This cookbook assumes you've already loaded a collection of `SmallMoleculeComponent` objects into an iterable called `ligands`. For more information, see [Loading Small Molecules]:\n", + "This cookbook assumes you've already loaded a collection of `SmallMoleculeComponent` objects into an iterable called `ligands`.\n", "\n", - "[Loading Small Molecules]: https://docs.openfree.energy/en/stable/cookbook/loading_molecules.html#loading-small-molecules" + "For more information, see [Loading Small Molecules](https://docs.openfree.energy/en/stable/cookbook/loading_molecules.html#loading-small-molecules)." ] }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 1, "id": "2ef27845-2a17-45fc-ac54-20e75055a7a2", "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "text/plain": [ + "[SmallMoleculeComponent(name=benzene),\n", + " SmallMoleculeComponent(name=toluene),\n", + " SmallMoleculeComponent(name=phenol),\n", + " SmallMoleculeComponent(name=benzonitrile),\n", + " SmallMoleculeComponent(name=anisole),\n", + " SmallMoleculeComponent(name=benzaldehyde),\n", + " SmallMoleculeComponent(name=styrene)]" + ] + }, + "execution_count": 1, + "metadata": {}, + "output_type": "execute_result" + } + ], "source": [ - "ligands = [\n", - " openfe.SmallMoleculeComponent(mol) \n", - " for mol in Chem.SDMolSupplier(\n", - " \"assets/somebenzenes.sdf\", \n", - " removeHs=False,\n", - " )\n", - "]" + "%matplotlib inline\n", + "from rdkit import Chem\n", + "import openfe\n", + "\n", + "supplier = Chem.SDMolSupplier(\"assets/somebenzenes.sdf\", removeHs=False)\n", + "ligands = [openfe.SmallMoleculeComponent(mol) for mol in supplier]\n", + "\n", + "ligands" ] }, { @@ -85,7 +97,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 2, "id": "d2de6fcb-9a9b-44c4-8ad3-f98ec3de5638", "metadata": {}, "outputs": [], @@ -115,7 +127,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 3, "id": "b9372340-327f-4451-9399-21fd01afc967", "metadata": {}, "outputs": [ @@ -147,7 +159,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 4, "id": "aedd67c5-db74-48c1-afe4-bacfec0b2ca3", "metadata": {}, "outputs": [], @@ -161,14 +173,14 @@ " (\"phenol\", \"benzaldehyde\"),\n", "]\n", "\n", - "# topology_by_indices = [\n", - "# (6, 1),\n", - "# (3, 1),\n", - "# (1, 0),\n", - "# (0, 2),\n", - "# (2, 4),\n", - "# (2, 5),\n", - "# ]" + "topology_by_indices = [\n", + " (6, 1),\n", + " (3, 1),\n", + " (1, 0),\n", + " (0, 2),\n", + " (2, 4),\n", + " (2, 5),\n", + "]" ] }, { @@ -179,6 +191,16 @@ "## Create the network" ] }, + { + "cell_type": "code", + "execution_count": 5, + "id": "ca2db32b-48e9-4abc-8dd3-f77cce78397e", + "metadata": {}, + "outputs": [], + "source": [ + "from openfe.setup import ligand_network_planning" + ] + }, { "cell_type": "markdown", "id": "9049e97f-0fdb-4196-808a-8c2fdd8e3576", @@ -192,19 +214,52 @@ "execution_count": 6, "id": "9c3e1d23-3333-4b2c-b687-561f63b3267e", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "parallel map scoring\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/atravitz/micromamba/envs/openfe-notebooks/lib/python3.13/site-packages/gufe/components/explicitmoleculecomponent.py:74: UserWarning: RDKit does not preserve Mol properties when pickled by default, which may drop e.g. atom charges; consider setting `Chem.SetDefaultPickleProperties(Chem.PropertyPickleOptions.AllProps)`\n", + " warnings.warn(\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "parallel map scoring\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/Users/atravitz/micromamba/envs/openfe-notebooks/lib/python3.13/site-packages/gufe/components/explicitmoleculecomponent.py:74: UserWarning: RDKit does not preserve Mol properties when pickled by default, which may drop e.g. atom charges; consider setting `Chem.SetDefaultPickleProperties(Chem.PropertyPickleOptions.AllProps)`\n", + " warnings.warn(\n", + "/Users/atravitz/micromamba/envs/openfe-notebooks/lib/python3.13/site-packages/gufe/components/explicitmoleculecomponent.py:74: UserWarning: RDKit does not preserve Mol properties when pickled by default, which may drop e.g. atom charges; consider setting `Chem.SetDefaultPickleProperties(Chem.PropertyPickleOptions.AllProps)`\n", + " warnings.warn(\n" + ] + } + ], "source": [ - "ligand_network = ligand_network_planning.generate_network_from_names(\n", + "ligand_network_from_names = ligand_network_planning.generate_network_from_names(\n", " ligands=ligands,\n", " mapper=mapper,\n", " names=topology_by_names,\n", ")\n", "\n", - "# ligand_network = ligand_network_planning.generate_network_from_indices(\n", - "# ligands=ligands,\n", - "# mapper=mapper,\n", - "# indices=topology_by_indices,\n", - "# )" + "ligand_network_from_indices = ligand_network_planning.generate_network_from_indices(\n", + " ligands=ligands,\n", + " mapper=mapper,\n", + " indices=topology_by_indices,\n", + ")" ] }, { @@ -233,7 +288,7 @@ "outputs": [ { "data": { - "image/png": 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", + "image/png": 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", "text/plain": [ "
" ] @@ -246,7 +301,7 @@ "source": [ "from openfe.utils.atommapping_network_plotting import plot_atommapping_network\n", "\n", - "plot_atommapping_network(ligand_network)" + "plot_atommapping_network(ligand_network_from_names)" ] } ], @@ -266,7 +321,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.6" + "version": "3.13.11" }, "widgets": { "application/vnd.jupyter.widget-state+json": { diff --git a/cookbook/ligandnetwork_vis.ipynb b/cookbook/ligandnetwork_vis.ipynb index a085528..1fcc79c 100644 --- a/cookbook/ligandnetwork_vis.ipynb +++ b/cookbook/ligandnetwork_vis.ipynb @@ -31,35 +31,7 @@ "tags": [] }, "source": [ - "## Ligand Network Setup" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "id": "aa30a8bc-bdf0-4382-98bd-2f33e703eb2d", - "metadata": { - "slideshow": { - "slide_type": "" - }, - "tags": [] - }, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/Users/atravitz/micromamba/envs/openfe_env/lib/python3.13/site-packages/openmoltools/utils.py:9: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.\n", - " from pkg_resources import resource_filename\n" - ] - } - ], - "source": [ - "%matplotlib inline\n", - "\n", - "import rdkit.Chem\n", - "\n", - "import openfe" + "## Generate or load a Ligand Network" ] }, { @@ -81,7 +53,7 @@ { "cell_type": "code", "execution_count": 2, - "id": "594364f7-00ab-4497-bf5e-74cb497802e7", + "id": "aa30a8bc-bdf0-4382-98bd-2f33e703eb2d", "metadata": { "slideshow": { "slide_type": "" @@ -90,15 +62,18 @@ }, "outputs": [], "source": [ + "%matplotlib inline\n", + "from rdkit import Chem\n", + "import openfe\n", + "\n", + "# load the ligands\n", + "supplier = Chem.SDMolSupplier(\"assets/somebenzenes.sdf\", removeHs=False)\n", + "ligands = [openfe.SmallMoleculeComponent(mol) for mol in supplier]\n", + "\n", + "# generate the network\n", "ligand_network = openfe.ligand_network_planning.generate_minimal_spanning_network(\n", - " ligands=[\n", - " openfe.SmallMoleculeComponent(mol) \n", - " for mol in rdkit.Chem.SDMolSupplier(\n", - " \"assets/somebenzenes.sdf\", \n", - " removeHs=False,\n", - " )\n", - " ],\n", - " mappers=[openfe.setup.LomapAtomMapper()],\n", + " ligands=ligands,\n", + " mappers=[openfe.setup.KartografAtomMapper(map_hydrogens_on_hydrogens_only=True)],\n", " scorer=openfe.lomap_scorers.default_lomap_score,\n", ")" ] @@ -113,19 +88,10 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 4, "id": "7615197d-8b60-47de-8275-e67a1a454d91", "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/Users/atravitz/software/gufe/gufe/components/smallmoleculecomponent.py:286: UserWarning: The atom hybridization data was not found and has been set to unspecified. This can be fixed by recreating the SmallMoleculeComponent from the rdkit molecule after running sanitization.\n", - " warnings.warn(\n" - ] - } - ], + "outputs": [], "source": [ "with open(\"assets/benzenes/ligand_network.graphml\") as f:\n", " graphml = f.read()\n", @@ -151,18 +117,18 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 5, "id": "96de1e7a-baad-4c28-9668-72670d1d6882", "metadata": {}, "outputs": [ { "data": { - "image/png": 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", + "image/png": 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0blz6z9iyRerQQSpe3H1/u3bSjz+mnu/cWWrfXnrmGalsWfc1fftKSUmpr9m1S+rUyf2MQoWk1q2lDRtyoAOiECEKAIAcMmWKlCePtHSpNHKk9Nxz0oQJqedHjJAuuURatUrq00fq3Vtavz41YF1+uVSkiLRwofTZZ+5xq1bSoUOpn/Hxx9KmTe69fZ/VONktbdBasUJ65x1pyRI3xF17bfqghYwhRAEAkEMqVnSD0wUXSB07Snfc4T4OsjBj4em886ShQ6Uzz5Q++cQ9N326lCuXG7ouukiqXl2aNEn6+efU1xgbYXrxRalaNalNG+m666QFC9xzNuJk4ck+o1kzyXaXmTrVHeGaPZv/DDKLEAUAQA5p1EiKiUl93LixG2yOHHEf16qVes5eV6aMtH27+3jlSmnjRneqz0ag7FaihHTggDvyFFSjhpQ7d+pjm9YLfsa6de5IWMOGqedtys9CnZ1D5rB3HgAAYSJv3vSPLUglJ7vHdl+vnjtydLSzzsrYZ6Stv0rLnk8b7pAxhCgAAHLI558f+/j889OPHJ1I3brSjBlSqVJSsWKhff+FF0qHD7s1WZde6j63c6f03Xfu9CAyh+k8AAByyObN0l13Sd9+K02bJo0aJQ0YkLH3Wg2V1UjZFXkJCdIPP0iffuq+/5dfMvYZFtjs/T16uIXpq1dL//ynVL68+zwyhxAFAEAOsaUF9u+XGjRwlx6wwvL4+Iy915YjsKvybOmDG290R45sOQT7vMyMTFkxuk0LWtG51WTZVN7cucdOA+LUYgKBE82Qptq9e7diY2OVmJioYqGOIQIA4PN1ourUCY+tXZA1mYeRKAAAgBAQogAAAELA1XkAAOSAtAtiIjowEgUAABACQhQAAEAICFEAAAAhIEQBAACEgBAFAAAQAkIUAABZ5NChQ/SljxCiAADIAlu3blX16tVVt25drVmzhj71AUIUAABZ4IUXXtD333+vwoULq1atWvSpDxCiAAA4TbbP2pgxY5zjIUOG0J8+QYgCAOA0jRs3ztm49sILL9R1111Hf/oEIQoAgNNw8OBBPf/8887x4MGDlSsXf7X6Bb9pAABOwxtvvOEUlZcrV0633norfekjhCgAAEKUnJys4cOHO8d33nmn8uXLR1/6CCEKAIAQvfvuu1q3bp2KFSum+Ph4+tFnCFEAAIRo2LBhzn3v3r2dIAV/IUQBABCCRYsWOTebwuvfvz996EOEKAAAQhCshbrtttuconL4DyEKAIBMWr9+vebMmeMcDxo0iP7zKUIUAACZ9Mwzzzj37dq1U7Vq1eg/nyJEAQCQCbYm1GuvveYcDx06lL7zMUIUAACZMHLkSB06dEhNmzZV48aN6TsfI0QBAJBBtj/eyy+/7Byz0TAIUQAAZHKj4erVq7PRMAhRAABkhE3hPffcc84xGw3DMBIFAEAGsNEwjkaIAgAgAxsNP/30087xwIEDlT9/fvoMhCgAAE6FjYZxPIxEAQBwCsFRqF69eik2Npb+goMQBQDASSxevFifffaZs9HwgAED6CukIEQBAHASbDSMEyFEAQBwAmw0jJMhRAEAcAIjRoxQIBBgo2EcFyEKAIDj+PXXX/Xqq686x2zxguMhRAEAcJKNhps0aaJLL72UPsIxCFEAAByFjYaREYQoAACOs9FwYmKiqlWrpjZt2tA/OC5CFAAAabDRMDKKEAUAwHE2Gi5btqw6duxI3+CECFEAAKTZaDi4uCYbDeNUCFEAAPxt7ty5+uabb1SsWDH17NmTfsFJEaIAAPgbGw0jMwhRAABIWrJkiRISEpQ3b142GkaGEKIAAGCjYYSAEAUA8L1vv/1Ws2fPdvph0KBBvu8PZAwhCgDge8GNhtu2bavq1av7vj+QMYQoAID8vtHwlClTnGM2GkZmEKIAAL4W3GjYNhm2zYaBjCJEAQB8i42GcToIUQAA3xo/fryz0fAFF1yg66+/3uvmIMIQogAAvsRGwzhdhCgAgC9NmzZNW7ZscTYa/uc//+l1cxCBCFEAAN9ho2FkBUIUAMB33nvvPa1du1ZFixZlo2GEjBAFAPAdNhpGViBEAQB85fPPP9fChQvZaBinjRAFAPCV4cOHO/dWTF6+fHmvm4MIRogCAPhqo+G3337bOWajYZwuQhQAwHcbDdvCmhdeeKHXzUGEI0QBAHxh27ZtbDSMLEWIAgD4aqPhxo0bs9EwsgQhCgAQ9fbs2aPRo0c7x0OHDlVMTIzXTUIUIEQBAKIeGw0jOxCiAABRjY2GkV0IUQCAqDZ9+nT98ssvKlOmDBsNI0sRogAAUcuWMwhu8TJw4EDlz5/f6yYhihCiAABRi42GkZ0IUQCAqDVs2DDnvmfPnjrjjDO8bg6iDCEKABCV2GgY2Y0QBQCI6o2GO3bsqAoVKnjdHEQhQhQAIOp89913KRsNDx482OvmIEoRogAAUYeNhpETCFEAgKjCRsPIKYQoAEBUGTVqlA4ePMhGw8h2hCgAQFRuNDxkyBA2Gka2IkQBAKLGhAkT9Oeff6pq1apq27at181BlCNEAQCiQlJSkp599tmUK/Jy5eKvOGQv/gsDAESFadOmsdEwchQhCgAQVRsNDxgwQAUKFPC6SfABQhQAIGo2Gi5SpIh69erldXPgE4QoAEDEC45CsdEwchIhCgAQ0ZYuXapPP/1UefPm1cCBA71uDnyEEAUAiGhsNAyvEKIAABFrw4YNmjVrlnM8aNAgr5sDnyFEAQAifqPhNm3aqEaNGl43Bz5DiAIARKTffvtNkydPTtniBchphCgAQERvNNyoUSM1bdrU6+bAhwhRAICIs3fvXr300kvOMRsNwyuEKABAxBk/fjwbDcNzhCgAQMRuNGxX5OXOndvrJsGnCFEAgIgyffp0Z6Ph0qVL67bbbvO6OfAxQhQAIGKw0TDCCSEKABAx5s2bp6+//trZaLh3795eNwc+R4gCAEQMNhpGOCFEAQAiwrJly/TJJ58oT548bDSMsECIAgBEBDYaRrghRAEAwt7GjRv11ltvOcdsNIxwQYgCAETMRsPXXXedatas6XVzAAchCgAQ9hsNT5o0yTlmo2GEE0IUACAiNhpu2LChmjVr5nVzgBSEKABA2GKjYYQzQhQAIGxNmDDB2Wj4/PPPV7t27bxuDpAOIQoAEPYbDQ8ePJiNhhF2CFEAgLA0Y8YMbd68mY2GEbYIUQCAsMNGw4gEhCgAQNh5//339dVXXzkbDffq1cvr5gDHRYgCAITtRsPx8fEqXry4180BjosQBQAIK8uXL9fHH3/MRsMIe4QoAEBYjkLdeuutqlixotfNAU6IEAUACBtsNIxIQogCAITdRsPXXnutLrroIq+bA5wUIQoAEBbYaBiRhhAFAAgLL774orPRcIMGDdS8eXOvmwOcEiEKABBWGw0PHTpUMTExXjcJOCVCFADAcxMnTtSuXbvYaBgRhRAFAAibjYYHDRrERsOIGIQoAICn3nzzTf38888qVaqUOnXqxG8DEYMQBQDwDBsNI5IRogAAnvnggw+0Zs0aFS5cWL179+Y3gYhCiAIAeGbYsGHOPRsNIxIRogAAnmCjYUQ6QhQAwBPDhw937m+55RZVqlSJ3wIiDiEKAODpRsODBw/mN4CIlMfrBgAA/Oc///mPateuraZNm7LRMCJWTMCuLz2F3bt3KzY2VomJiSpWrFjOtAwAACCHZSbzMJ0HAAAQAkIUAABACAhRAAAAISBEAQAAhIAQBQAIOy1aSAMHet0K4OQIUQCAbEUgQrQiRAEAAISAEAUAyDadO0uffiq98IIUE+PefvzRfa5BAyl/fqlsWemee6TDh0/8Ofa+2bPTP3fGGdLkyamPt2yROnSQiheXSpaU2rVzvyttW9q3l555xv1Oe03fvlJSUuprDh2ShgyRypeXCheWGjaUPvkkK3sE0YQQBQDINhaeGjeWevSQfv3VveXNK117rVS/vrR6tfTyy9LEidJjj4X+Pfv2SZdfLhUpIi1cKH32mXvcqpUbjII+/ljatMm9nzLFDWFpg1iXLtKiRdL06dKaNdJNN7mfsWHD6fUDohPbvgAAsk1srJQvn1SokFSmjPvc/fdLFStKL77ojjBVqyZt3SoNHSo99JCUK4R/3lvosfdNmOB+ppk0yR2tspGkq692n7NRKvve3Lnd773uOmnBAjfkWbiaNk365RepXDn39YMGSfPmuZ/1xBNZ1SuIFoQoAECOWrfOHZ0Khh3TpIm0d68bYCpVyvxnrlxpmxpLRYumf/7AATccBdWo4QaoIJvW++or9/iLLyTbCK1q1fSfcfCgO/UHHI0QBQDIURZU0gao4HPm6OeD7Pmjd3pNW8uUnCzVqydNnXrse886K/XYphKP/lx7b/AzLGBZIEsbtIxNDQJHI0QBALKVTecdOZL6+MILpbfeSh+mFi92R5GsoPt4LAhZPVWQ1ShZHVRQ3brSjBlSqVLSKfaMPaGLL3bbuX271KxZaJ8Bf6GwHACQrSpXlpYuda+U+/13qU8fafNm6Y47pPXrpTlzpH/9S7rrrhPXQ11xhVvLZFNuK1ZIvXqlH1Xq2FE680z3iryEBOmHH9wrAAcMcKcIM8Km8exzOnWSZs1yP2P5cmnYMGnu3KzpC0QXQhQAIFtZcbZNj9kIlI0o2TSchZJly6Tatd1A1K2b9MADJ/6MESPcYvTmzaVbb3U/04rVg+zYrsqzeqobb5SqV5e6dpX278/cyJQVkFuIuvtu6YILpLZt3QBo3w0cLSYQOHqW+Vi7d+9WbGysEhMTVSzUcVIAAIAwl5nMw0gUAABACAhRAAAAISBEAQAAhIAQBQAAEAJCFAAAQAgIUQAAACEgRAEAAISAEAUAABACQhQA4LRlYN1mIOoQogAAp23SpEmqW7euOnToQKCCbxCiAACnPQo1fPhwrVq1Si1atFBMTAw9Cl8gRAEATsvChQu1fv16FS5cWB07dqQ34RuEKADAaRk7dqxzbwGKTerhJ4QoAEDItm/frpkzZzrHvXr1oifhK4QoAEDIJk+erKSkJNWvX18XX3wxPQlfIUQBAEKSnJycMpXHKBT8iBAFAAjJ/Pnz9f333ys2NtZZ2gDwG0IUACAkwVGoTp06OVfmAX5DiAIAZNrWrVs1Z84c57hnz570IHyJEAUAyLSJEyfqyJEjatq0qWrUqEEPwpcIUQCATLHwNH78eOeYgnL4GSEKAJAp7733njZv3qySJUsqLi6O3oNvEaIAAJkyZswY575Lly4qUKAAvQffIkQBADLsp59+0ty5c53j+Ph4eg6+RogCAGSY1UIFAgFdeeWVOv/88+k5+BohCgCQIba9i12VZygoBwhRAIAMeuedd7Rt2zaVKVNG7dq1o9/ge4xEAQAyVVDetWtX5c2bl16D7xGiAACntGHDBmevvJiYGPXo0YMeA5jOAwBkxLhx45z71q1bq3LlynQaQIgCAJzKwYMHNWnSJOeYgnIgFdN5AICTeuutt7Rz505VrFhR1157Lb0F/I0QBQDIUEF59+7dlTt3bnoL+BshCgBwQmvXrlVCQoITnrp160ZPAWkQogAAJzR27Fjnvm3btipfvjw9BaRBiAIAHNe+ffv06quvOscUlAPHIkQBAI5rxowZSkxM1DnnnKOWLVvSS8BRCFEAgJMWlMfHxytXLv66AI7G/xUAgGOsWrVKy5Ytc7Z36dKlCz0EHAchCgBwwoLyuLg4lSpVih4CjoMQBQBIZ8+ePZo6dapzTEE5cGKEKABAOhag9u7dq2rVqql58+b0DnAChCgAQIpAIJBSUN6zZ0/FxMTQO8AJEKIAACmWLl2q1atXq0CBAurUqRM9A5wEIQoAcExBeYcOHVSiRAl6BjgJQhQAwLFr1y5Nnz7dOaagHDg1QhQAwGFbvBw4cEC1atVSw4YN6RXgFAhRAIB0BeU2CkVBOXBqhCgAgBISErR+/XoVLlxYHTt2pEeADCBEAQBSRqEsQBUrVoweATKAEAUAPrd9+3bNnDkzZW0oABlDiAIAn5s8ebKSkpJUv3591a1b1+vmABGDEAUAPpacnJyyNhTLGgCZQ4gCAB9bsGCBvv/+e8XGxjoLbALIOEIUAPhYsKDctnixK/MAZBwhCgB8auvWrZozZ45zTEE5kHmEKADwqYkTJ+rIkSNq2rSpatSo4XVzgIhDiAIAH7LwNH78eOeYgnIgNIQoAPCh9957T5s3b1bJkiUVFxfndXOAiESIAgAfF5R37txZBQoU8Lo5QEQiRAGAz/z000+aO3eucxwfH+91c4CIRYgCAJ+xWqhAIKArr7xSVatW9bo5QMQiRAGAj9j2LnZVnqGgHDg9hCgA8JF33nlH27ZtU5kyZdSuXTuvmwNENEIUAPiwoLxr167Kmzev180BIhohCgB8YuPGjZo/f75iYmLUo0cPr5sDRDxCFAD4xLhx45z71q1bq3Llyl43B4h4hCgA8IGDBw/qlVdecY4pKAeyBiEKAHzgrbfe0s6dO1WhQgVnJArA6SNEAYCPCsqtFipPnjxeNweICoQoAIhya9euVUJCgnLnzq1u3bp53RwgahCiAMAnBeVt27ZV+fLlvW4OEDUIUQAQxfbt26cpU6Y4xxSUA1mLEAUAUWzGjBlKTEzUOeeco5YtW3rdHCCqEKIAwAcF5fHx8cqViz/ygazE/1EAEKVWrVqlZcuWOdu7dOnSxevmAFGHEAUAUWrs2LHOfVxcnEqVKuV1c4CoQ4gCgCi0Z88eTZ061TmmoBzIHoQoAIhCFqD27t2ratWqqXnz5l43B4hKhCgAiDKBQCCloLxnz56KiYnxuklAVCJEAUCUsWLy1atXq0CBAurUqZPXzQGiFiEKAKJMcBSqQ4cOKlGihNfNAaIWIQoAosiuXbs0ffr0lKk8ANmHEAUAUeTVV1/VgQMHVKtWLTVq1Mjr5gBRjRAFAFFUUB5cG8qWNaCgHMhehCgAiBIJCQlat26dChcurI4dO3rdHCDqEaIAIMoKyi1AFStWzOvmAFGPEAUAUWD79u2aOXOmc0xBOZAzCFEAEAUmT56spKQk1a9fX3Xr1vW6OYAvEKIAIMIlJydr3LhxzjH75AE5hxAFABFuwYIF2rRpk2JjY50FNgHkDEIUAERJQfltt93mXJkHIGcQogAggm3dulVz5sxxjikoB3IWIQoAItgrr7yiI0eOqGnTpqpZs6bXzQF8hRAFABHKwhMF5YB3CFEAEKHee+89bd68WSVLllRcXJzXzQF8hxAFABFeUN65c2cVKFDA6+YAvkOIAoAI9NNPP2nu3LnOcXx8vNfNAXyJEAUAEWjChAkKBAK68sorVbVqVa+bA/gSIQoAIoxt72IhyrBCOeAdQhQARJh33nlH27ZtU+nSpdWuXTuvmwP4FiEKACK0oLxbt27Kmzev180BfIsQBQARZOPGjZo/f75iYmLUo0cPr5sD+BohCgAiSHBxzdatW6ty5cpeNwfwNUIUAESIgwcPOtu8GArKAe8RogAgQrz11lvauXOnKlSo4IxEAfAWIQoAIqyg3Gqh8uTJ43VzAN8jRAFABPjmm2+UkJCg3LlzO1flAfAeIQoAIsDYsWOd+7Zt26p8+fJeNwcAIQoAwt++ffs0ZcoU57hnz55eNwfA3xiJAoAwN2PGDCUmJqpKlSq66qqrvG4OgL8RogAgQqbybBQqVy7+2AbCBf83AkAYW7VqlZYuXeps79KlSxevmwMgDUIUAETAKFRcXJxKlSrldXMApEGIAoAwtWfPHk2dOtU5pqAcCD+EKAAIUxag9u7dqwsuuECXXXaZ180BcBRCFACEoUAgkLJCue2TFxMT43WTAByFEAUAYWjZsmVavXq1ChQooE6dOnndHADHQYgCgDAUHIXq0KGDSpQo4XVzABwHIQoAwsyuXbs0ffp055iCciB8EaIAIMy89tprOnDggGrVqqVGjRp53RwAJ0CIAoAwQkE5EDkIUQAQRhISErRu3ToVLlxYHTt29Lo5AE6CEAUAYVhQfuutt6pYsWJeNwfASRCiACBM7NixQzNnznSOKSgHwh8hCgDCxOTJk5WUlKT69eurXr16XjcHwCkQogAgDCQnJ6dsNmwrlAMIf4QoAAgDCxYs0KZNmxQbG+sssAkg/BGiACCMCspvu+0258o8AOGPEAUAHtu6davmzJnjHFNQDkQOQhQAeOyVV17RkSNH1LRpU9WsWdPr5gDIIEIUAHjIwtO4ceOcYwrKgchCiAIAD7333nvavHmzSpYsqbi4OH4XQAQhRAFAGBSUd+7cWQUKFOB3AUQQQhQAeOSnn37S3LlzneP4+Hh+D0CEyeN1AwDAr959913VqVNHDRo0UNWqVb1uDoBMigkEAoFTvWj37t3OAnCJiYlsiAkAAKJWZjIP03kAAAAhIEQBAACEgBAFAAAQAkIUAABACAhRAAAAISBEAUAOadFCGjiQ7gaiBSEKAAAgBIQoAACAEBCiACAHHT4s9esnnXGGVLKk9MADUnDJ40OHpCFDpPLlpcKFpYYNpU8+SX3v5Mnu+95/X6peXSpSRGrVSvr119TXxMQce6tcOfX8N99I117rvrd0aem226Tff08/5di/v9uOEiWkMmWkhx9O/zMkJto2NVKpUpKtRXjFFdLq1dnWZUDYIkQBQA6aMkXKk0daulQaOVJ67jlpwgT3XJcu0qJF0vTp0po10k03uSFpw4bU9+/bJz3zjPTaa9LChdLPP0uDBqWet0AVvG3cKJ13ntS8eeq5yy6T6tSRVqyQ5s2TfvtNuvnmY9toIc7a+PTT0qOPSh9+6J6zwHfdddK2bZJt+7dypVS3rnTlldIff2R79wFhhW1fACCH2CjP9u3S2rXuCJG55x7pnXek//5XOv986ZdfpHLlUt/TsqXUoIH0xBPuSJQFLQtH557rnh892g05FmrSsrATF+eGrIQEqWBB6aGH3GBkI1lB9n0VK0rffivZ9n3WxiNH3PcE2ffbaNNTT0kffSTdcIP7c+TPn/oaC2s2esU+yvDTti9sQAwAOahRo9QAZRo3lkaMcEeGLPgcvQ/xwYPutF9QoUKpAcqULesGmqPdd5+0ZIm0fLkboIyNGn38sTuVd7RNm1K/u1at9OfSfod9xt696dtk9u93PwPwE0IUAISJ3LndkGL3aaUNPXnzpj9ngezobeRff92dJrR6qgoVUp9PTpauv14aNuzY77agdLLvsPcGP8Nem7ZWK8jqtQA/IUQBQA76/PNjH9s03sUXu9NoNuLTrFnon2+jT927S2PHuqNeaVnt0ltvuYXmVpcVCvsMmzq096ctWAf8iMJyAMhBmzdLd93l1iBNmyaNGiUNGOBOpXXsKHXqJM2aJf3wgzsVZ6NGVsCdERZurF7pH/+QrrnGfWy3HTvc8337usXft9wiLVsmff+99MEHUteuboDLCKvRsinI9u3d2qoff5QWL3avMrQpScBPGIkCgCwSCAQUk7bg6TgsJFn9kBVr27TdHXekFmNPmiQ99ph0993Sli1u3ZEFFluSICPWr3evtrOr6+wWdPbZbtixgnW7+m/oUDdkWb2VnbMrAHNl8J/U9uNZqLv/fjd8WUCzZRDsCkBbMgHwE67OA4DTCE0bN27Up59+6tx27typuRkdNgIQlrg6DwCyKTStX78+JTTZ7dc0K11ebIVNAHyD6TwAOIHk5GR988036ULT9qPWE8iXL58aNmyoyy67TG3atKEvAR8hRAFAmtC0Zs2alMC0cOFCZ4ourQIFCqhRo0ZOaLKbHRcMLsQEwFcIUQB86/Dhw/ryyy9TQlNCQoL+/PPPdK8pVKiQLr300pTQ1KBBA+VPu1Q3AN8iRAHwjaSkJH3xxRdOYPrkk0/02Wefac+ePeleU6RIETVt2jQlNNWrV8+ZsgOAoxGiAEStQ4cOafny5SkjTYsWLdJff/2V7jW2N1azZs2cwNSiRQunODxPqCtRAvAV/qQAEDUOHDigpUuXpoSmJUuWaL8typRG8eLF1bx585SRptq1ayv30fusAEAGEKIARKx9+/Y5QSkYmixAHbQVJNM488wzUwKT3WrWrKlcGV1ZEgBOghAFIGLs3btXixcvTglNy5Ytc+qc0ipdurQzLRcMTdWrVz/lKuJejpx169ZN69at0wUXXKBXXnmFK/2ACEKIAhDWKwdb8XcwNK1cudK5oi6t8uXLpxtpqlq1atiGpqPZcglPPfWUU7y+atUqZ4Ts9ddfj5j2A35HiAIQNnbt2uUsMxAMTRYsbO2mtM4+++x0oemcc86J6NBRsWJF/ec//9GVV16pN954wwlUd9kOxQDCHnvnAfCMLWRpC1oGQ9Pq1audrVXSOvfcc9OFJgtR0WjkyJEaMGCAMxr1wQcfOKEKQHjvnUeIApBjfvvtt3Sh6euvvz7mNTYdlzY0VahQwRe/IQuPnTt31quvvqqSJUtqxYoVqly5stfNAnxndyZCFNN5ALLN1q1b0+07Z5v3Hu3CCy9MCUy29EDZsmV9+RuxKckxY8Zo7dq1Tu3XDTfc4KxrZSumAwhPhCgAWWbz5s3pQtOGDRuOeU2tWrXShaazzjqL38DfbA++t99+26mLsu1ounfvrqlTp0Z0zRcQzQhRAEKefvrxxx/ThaYffvgh3WvsL/86deqkhCZbGdymqnDqQvOWLVtq2rRpuuSSSyg0B8IUNVEAMhyaNm3a5Ow5FwxNNvKUlq38Xbdu3ZTQZHvQnXHGGfRwCEaNGqX+/ftTaA7kMArLAWRJaPr222/TjTRZjVNatsdc/fr1U0JTkyZNVLRoUXo/i/q/S5cumjJlCoXmQA6isBxAptl6TN98801KYLKr6OxqurTy5cunBg0apGzW27hxYxUuXJjezuZCc7tSj0JzIPxQEwX4ODStWbMmXWiydZuOXlG7UaNGKSNNdmzFz8gZ1v+zZs2i0BwIU4QowCeOHDniXPEVDE22MritEJ6WXU5/6aWXpoQmG3XKnz+/Z23GsYXmduXe3XffTdcAYYDCciBK2ca8ti7TF1984aw7ZAHKNvA9OjTZ1XNWDG5XgdlmvXnz5vWszchYofn777/vhCoAWY/CcgCI4kLzEiVKOHVSVapU8bpZgK9DVK4caxUA4LQLzW3E8I8//nAKzfft20ePAh4iRAFAhBWalypVytmsuVu3bsds2Awg5xCiACACC81tja7p06fr2Wef9bpJgG8RogAgwtieg88995xzPGTIEM2fP9/rJgG+RIgCgAjUt29fde7c2Vnvq0OHDsfsWwgg+xGi4AstWkgDByqsde4stW+ftT/H5MlSdmxdl12fi8wVmr/88ssUmgMeIkQBQISi0BzwFiEKAKKo0HzEiBFeNwnwDUIUfOPwYalfP3caqmRJ6YEHbAFD99yhQ1agK5UvL9l+ug0bSp98cuz01fvvS9WrS0WKSK1aSb/+mvqamJhjb5Uru+eOHJG6dZNsbUTbeu6CC6QXXjh5e//6S+rUyf2usmWl4/3deKp2B52o3QsXSrZA+bZt6V9vu4o0b57+569UyVY4l264QTpqiz3Hf/8r1atnoyPSOedIjzzi9jlyttB86NCh+vDDD+l2IAcQouAbU6ZIefJIS5dKI0dK9nfOhAnuuS5dpEWLpOnTpTVrpJtucsPGhg2p77d1DZ95RnrtNTd8/PyzNGhQ6nkLJsHbxo3SeeelBpHkZKlCBenNN6VvvpEeeki67z738YkMHix9/LH09tvSBx+44WjlyvSvOd12W/ss8Ni5IAs+r7/ufrax/uraVerTR/ryS+nyy6XHHjs2pP3zn1L//u7PN3asG7wefzxzvyNkTaH5P/7xDwrNgZwQyIDExET797pzD0Siyy4LBKpXDwSSk1OfGzrUfW7jxkAgJiYQ2LIl/XuuvDIQuPde93jSJBuzcl8b9NJLgUDp0sd+l33HDTcEAvXqBQL79p24TX36BAJxcamPb789EGjXzj3esycQyJcvEJg+PfX8zp2BQMGCgcCAAe7jrGr3sGFuPwTNnh0IFCkSCOzd6z6+5ZZAoFWr9N/RoUMgEBub+rhZs0DgiSfSv+a11wKBsmVP/PMj6+3fvz9Qv35958/rWrVqBfYGf4kAMiwzmYeRKPhGo0buFFtQ48buiM2KFe60XtWq7nRX8Pbpp9KmTamvt6msc89NfWxTbNu3H/s9NsK0ZIk0e7Y7dRc0Zox0ySXSWWe5nz9+vDsqdDz2vTZVZ20MKlHCnQYM+uKLrGm3XRVoI2eff+4+fuUV6eab3elBs25d+nYE+y4tGyF79NH07ejRwx2VY2cSbwrN16xZw4rmQDbLk91fAESC3LndIGD3aVkYCLLaobQskB2944ZNg9k0oU292fRdkE3b3XmnW9dkAaRoUWn4cHeq7HgyspOHTRFmRbtLlZKuv16aNMmd2ps7N31dVUbbYjVQN9547DmrkULOqVChgmbOnKkrrrhCM2bMcJZAGJR23hlAliFEwTeCIy1pH59/vnTxxW7ht43ONGsW+ufb6FP37m49kI16pZWQIF16qVtXFJR2tOhoVk9l4cfaaAXdZtcu6bvvpMsucx9nVbuNtfsf/3CDn41aNWmSeu7CC4/fd2nVrSt9+63bbnivWbNmev7559WvXz+n0Lx27dq66qqrvG4WEHWYzoNvbN4s3XWX+5f9tGnSqFHSgAHudFjHju6VcLNmSbbw8/Ll0rBh7qhMRtjVbXbVmgWRa65xH9ttxw73vIULmza0AmwLQg8+6H7HidhIkl3NZ8XlCxZIX3/tTrvlSvN/bFa0O8jaHBvrFowHC8qDrFh83jzp6afdtr/4ovs4LSuUf/VV6eGHpbVr3SnAGTPcKyDhjT59+qhLly4UmgPZiBAF37CwsX+/1KCBXckk3XGHFB/vnrOpLDtvl/Zb3VHbtu5UW8WKGfvs9eul335zrwC0mqPgrX5993yvXu5UV4cO7jIEtkRA2lGp47HpPrt6ztrSsqXUtKm7hEBap9vuIAtnFtJsZMs+Ly0bVbOrGC101qnjXil4dDiyEPa//0l2Zb39zPYe2xf37LMz1w5k7Yrmo0ePVv369fXHH3+offv2+svWzQCQZWKsuvxUL9q9e7diY2OVmJioYsWKZd23A1lg7969SkhIUOvWrenP02CF4BYE33mHbowmv/zyi+rVq6ft27c7e+xNmzbNCVgATj/zMBKFiHTw4EHNmTPHWQ+ndOnSuv/++71uUsRKTJTmz5emTnVH5xCdhea2orkVmj9ji4YByBKEKESMI0eOaMGCBerevbvKlCnjTE/YXwr79u1ztr5AaNq1c6cBe/aUqD2O7kJzc88997CiOZBFmM5DWLPZ5mXLlumNN97Qm2++qW1p9icpX768Mz1xyy23ONMVTFEAJ/9/qVu3bpo0aZKKFy+uFStW6Bxb0wJAyNN5LHGAsPT11187tRu2oer333+f8nyJEiX0f//3f7r11ludf13nSnu5GoBTFpqvXbvW+YeJjeQuWbJEhYOrqgLINEIUwsYPP/zghCYbdbIQFWR/yNsf+DbiZGvd5MuXz9N2ApG8ovlbb73ljNx+9dVXzsgUheZA6AhR8JRNz9k0nf1B/nmaFRwtKNnVdhacrr/+ehWyvUsAZPmK5haoBtuCZAAyjZoo5Lg///zT2d/LgtNHH33kLAZobGru8ssvd6bqbrjhBqduA0D2sKm9vn37Ov/fzZs3jxXNgRBqoghRyBF2Bd1///tfJzi99957OmS76/6tUaNGzojTzTff7Fx1ByD7UWgOHB+F5QgLSUlJ+uCDD5zgNHv27HSrJdesWdMJTrbOE1cIATmPQnPg9FEThSxlU3O2ergFp//85z/OdhNBVapUcYKT3SxEAQivQvOuXbs6F3ewXAiQMYQoZMm0wMqVK53gZIWqW7ZsSTlnq4kH13Jq2LAhfzgDYVxobhd5WKAaMmSI180CIgI1UQjZ+vXrneBktw0bNqQ8bwV5cXFxToF4ixYtlDt3bnoZiKBCc6tbvPrqq71uEuAJCsuRbX7++WdnuN+C05dffpnyfMGCBdW2bVtnxKlVq1bKnz8/vwUgwkaUbUulV155xbkydvny5Tr33HO9bhaQ4ygsR5basWOHU99kwemzzz5Led42NL3mmmuc4NSuXTsVKVKEngcilNVBvfTSS85Ct7aiuS0zwormwMlRE4UTJnG7os5WD58/f76z+W/wD9rLLrvMCU42ZVeyZEl6EIiiQnNbw41CcyBjCFFIceDAAb377rvOiJPd2+OgSy65xAlOViRuG/8CiE72/7cVmtvCtxSaAydHYbnPHT58WAsWLHCCk/0LdM+ePSnnqlWrlrIkwfnnn+9pOwHkLArN4Ve7WbEcp1rLafHixSlrOVnNU1ClSpWcBTAtONWuXZslCQCfotAcfrU7EyGK6Twf/YG4evVqJzjZ1XV2lV3QWWedpZtuuslZkqBx48bOJc4A/I1Cc+DUCFFRztZvCq7lZOs6BRUtWlQ33nijM+J05ZVXOlfaAUBaFJoDJ8ffnFHIVgy3lcMtOK1YsSLleVu7qU2bNk5wuvbaa521nQAgM4XmdevW1dChQ+k0gMLy6LFz505nDyxbkmDhwoXO9J2x1cJbtmzpBKf27ds787wAkFkvv/yy+vTp40zz2YrmtkYcEI0oLPeJvXv3as6cOc6I0/vvv+9caRfUtGlTJzj93//9n0qVKuVpOwFEPvuHWY8ePTRx4kSdccYZzig3K5ojGhGiotjBgwc1b948Jzi988472r9/f8q5OnXqOMHJrq6zq+wAIKv//LHFdpcuXaqaNWs6K5qzUwGiDVfnRRlbLfyTTz5xpupsLac///wz5dx5553nXFVnwal69eqethNAdLO6SisbsBXNbXuYbt26OVf72hQf4EcUlofx0Ln9a89GnKyYc9u2bSnnypUrl7KWk/1hxh9gAHIKheZAKlYsDzP2rzsbcbJ/3f3www8pz5coUcKpb7Lg1KxZM6dgHAC8QqE5ohU1URHGwlJwLScLUUGFCxd2rqiz4HTVVVcpX758nrYTAIIoNEe0IkRFAJues2k6C06ff/55yvMWlFq3bu0Ep+uvv16FChXytJ0AcCIUmiMaUVgepnbt2uUUhltw+vjjj5097Ixts2IL2VmB+A033KDixYt73VQAyHCh+SWXXOKMonfp0sX5xyF1mvALaqKy2b59+/Tf//7XCU62QN2hQ4dSzjVq1MgZcbr55ptVpkyZ7G4KAGSLRYsWOf8QTEpK0pNPPql77rmHnkbEYjrPYxaUPvzwQ6dA3BbD/Ouvv1LO2doqwbWczjnnHE/bCQBZZcyYMerdu7czCjV37ly1atWKzkVEIkR5wKbmbLsVG3Gyfab++OOPlHNVqlRxgpPdLEQBQDQWmsfHx2vChAnOiubLly931rEDIg0hKgf/0Fi3bp2zgrhtu7Jjx46UcyVLltTVV1/t7C910UUXUSMAIOpRaI5oQIgCAHhiy5YtTqG5XYFsa9tRaI5oDlG5cqxVAADfrGieN29e537YsGFeNwnINoQoAECWatKkiUaOHOkc33fffU7JAxCNCFEAgCzXs2dPde/e3akdtYtqNm7cSC8j6hCiAABZzpY6ePHFF5318P78809nC6u9e/fS04gqhCgAQLauaG6LCa9du9ZZ0dxGpoBoEXEhqnNnqX17r1sBAMiIcuXKOUEqWGj+1FNP0XGIGhEXorJKmt1XAADZ6NJLL9WoUaOc4/vvv9/ZAguIBmEbombOlC66SCpY0BaulFq2lAYPlqZMkebMsfl29/bJJ9IVV0j9+qV//86dNpQsffSR+7hyZemxx9yRrNhYqUcP9/nFi6Xmzd3vqVhR6t9fSrNLi/O+J56QunaVihaVKlWSxo1L/11btkgdOki2b7C1tV076ccfs7uHACCyCs179OjhTOfZZusUmiMahGWI+vVX6ZZb3OCybp0blG68UfrXv6Sbb5ZsSyZ7jd0uvVTq3l164w1bLTf1M6ZOtWFk6fLLU58bPtz2rpNWrpQefFD66ivpmmvcz16zRpoxQ/rss2MD2YgR0iWXSKtWSX36SL17S+vXu+f27XO/o0gRaeFC9/12bG1ktAsAUtloFIXmiCYxgQxU+WVm9c6s8MUXUr167mjO2WenP2cjSX/+Kc2enfqchScLTC+/7IYsc/HFbu2UBa/giJI99/bbqe/r1MkdgRo7NvU5C0GXXeaORhUo4L6vWTPptdfc89ZbZcpIjzwi9eolvfKK9PTTbtizkTFj4emMM9w2Xn11NnUSAESgrVu3ql69eqxojrAV8SuW164tXXmlO513003S+PHSrl0nfr1N2/3zn26gMV9+Ka1e7QautGw0KS0bkZo82R05Ct5sZCo5Wfrhh9TX1aqVemxByULU9u2pn2HLn9hUX/AzSpSQDhyQNm06/b4AgGhCoTmiSR6Fody5pQ8/dOuVPvjAhoCtGFFauvTE77EpvTp1pF9+ccOUhbCjR7EKF07/2MJSz55uHdTRrPYpKG/e9OcsSNl7g59ho2Y2fXi0s87KwA8LAD4tNO/Vq5dTaF6nTh21bt3a62YB0RGigkGlSRP39tBDbiCyqbh8+aQjR459vY1a2UiTjVpZfdTfF4KcVN260tq10nnnhd5O+wyrpSpVSsqBmU4AiJpC85UrV2r8+PFOofny5ct13un8YQx4ICyn82zEya6IW7FC+vlnadYsaccOqXp1t0bJisC//Vb6/XcpKSn9aJQtQWIh64YbTv09Q4dKS5ZIffu6U4AbNkjvvCPdcUfG29qxo3Tmme4VeQkJ7jTgp59KAwa4o2IAgOOz0ajGjRunrGi+Z88eugoRJSxDlI3o2JVu114rVa0qPfCAe4Wcjfba0gQXXOCOOtl02aJFqe+zK/ry5JFuvdUtCj8Vq3WywGPhyYrHrfDcrtorWzbjbS1UyG2rTf/ZVX4W9Oyqwv37GZkCgFOtaG4LcLKiOSJVWF6dF6rNm92RquXL3Wk2AED4W7x4sVq0aKGkpCQ9/vjjuu+++7xuEnxsd6RfnZdZNqVn0342PdeoEQEKACKt0Nw2KzYPPPCA5s6d63WTgAyJihBlU3pWeG7LDYwZ43VrAACZFR8fz4rmiDhRNZ0HAIhcBw8e1OWXX64lS5aoRo0azn1RW4QPyEG+m84DAEQ+Cs0RaQhRAICwXNHc7p988kmvmwScECEKABBWKDRHpCBEAQDCstDcbla2ayuab7AF/YAwQ4gCAISlkSNHOiuaW4EvK5ojHBGiAABhW2hudVFly5bVN998o86dOzsjU0C4IEQBAMKWBahgofmsWbP0hG2sCoQJQhQAIKzZlF5wRfMHH3xQ7777rtdNAhyEKABARBWad+zYkUJzhAVCFAAgIlBojnBDiAIARAQKzRFuCFEAgIhBoTnCCSEKABBxheYvvfSSc0yhObxEiAIARJwePXqoZ8+eFJrDU4QoAEDEFprbPnusaA6vEKIAABEpX758mjlzZsqK5rfffruSk5O9bhZ8hBAFAIiKQvO3336bFc2RowhRAICoKTR/6KGHWNEcOYYQBQCIeBSawwuEKABAVKDQHDmNEAUAiKpC83LlylFojhxBiAIARF2huQUqCs2R3QhRAICo0qhRIwrNkSMIUQCAqNO9e3f16tXLWdH81ltv1Xfffed1kxCFCFEAgKj0wgsvOCua7969W+3bt3fugaxEiAIARH2h+bp161jRHFmOEAUA8EWh+ezZs/X444+f8j0tWkgDByrixcRIs2eH9t7KlaXnn8+az4pmhCgAgG8Kzf/1r39p4cKF8oNff5Vat3aPf/zRDUJffpmx9y5fLsXHZ2vzogIhCgDgq0LzBx54QH5QpoyUP3/m3nPokHt/1llSoULZ0qyoQogCAPim0LxJkybau3fvKV97+LDUr590xhlSyZKS5a5AIDVoDBkilS8vFS4sNWwoffJJ6nsnT3bf9/77UvXqUpEiUqtW7shQkI0KHX2zKbSgTz+VGjRwQ1DZstI997htSjvl2L+/244SJdzA9PDD6X+GtFNwVaq49xdf7D5v7zedO0vt20tPPimVKydVrXr86byjbdkideggFS/u9k+7du5ol98QogAAvio0P8uGWU5hyhQpTx5p6VLbTkZ67jlpwgT3XJcu0qJF0vTp0po10k03uSFpw4bU9+/bJz3zjPTaa5LNHv78szRoUOp5C1TB28aN0nnnSc2bpwaUa6+V6teXVq+WXn5ZmjhReuyxY9toIc7a+PTT0qOPSh9+ePyfZ9ky937+fPc7Z81KPbdggbRunfve//3v1P1oP9vll7vh0H62zz5LDYrBkSy/yON1AwAAyCllypTRM5ZuTqFiRTc42ajNBRdIX33lPr7iCmnaNOmXX9yRG2PhaN48adIk6Ykn3OeSkqQxY6Rzz3Uf26iWhZzUdrj3NroVFyfFxkpjx7rPjR7tfv+LL7rfX62atHWrNHSo9NBDUq6/hz9q1bIaL/f4/PPd11sguuqqY3+eYG60UaPgdwdZELOAmC9fxvrQwqO1YcIEt33GfnYbfbMRuauvlm8QogAAvnLRRRed8jWNGqUGBNO4sTRihLRihRt8gtNeQQcPugElyOqJggHK2JTc9u3Hfs9990lLlriF3AULus/ZqJB9X9rvb9JEsllIC2+VKqWGqLRO9B2nYt2R0QBlVq50R8+KFk3//IED0qZN8hVCFAAAmZA7txsk7D4tm9IKyps3/TkLRMGaqqDXX3dHt2z0pkKF1OftdWkDVPC54Oec7DuSkzP/q7SRqMyw76hXT5o69dhzGZgpjSqEKAAAjvL558c+tikzK8w+csQd8WnWLPRus9Gn7t3dKTwb9Urrwgult95KH6YWL3ZHfqyYPRTBkSZr++mqW1eaMUMqVUoqVky+RmE5AABH2bxZuusu6dtv3RqoUaOkAQPcabyOHaVOndzi7B9+cKfihg2T5s7NWDdu2ybdcIP0j39I11zjPrbbjh3u+T593O+/4w5p/Xppzhy39snaE6yHyiwLPDZdaLVbv/0mJSaG/iu3n//MM90r8hIS3D6wqwmtf2y60U8IUQAAHMVC0v797jIDffu6gSa4+KQVUdv5u+92i87btnWvkLNi8IywYGRBxq6uszqm4M2uxjM22mSBzK6oq11b6tVL6tbNXWYhVHaloV1laCNfVhBvAShUVu9lV+VVqiTdeKO7jEPXrm5/+W1kKiZgK4+dgm3aGBsbq8TERBXzWw8BAADf2J2JzMNIFAAAQAgIUQAAACEgRAEAAISAEAUAABACQhQAAEAICFEAAAAhIEQBAACEgBAFAAAQAkIUAABACAhRAAAAISBEAQAAhIAQBQAAEAJCFAAAQAgIUQAAACEgRAEAAISAEAUAABACQhQAAEAICFEAAAAhIEQBAACEgBAFAAAQAkIUAABACAhRAAAAISBEAQAAhIAQBQAAEAJCFAAAQAgIUQAAACHIk5EXBQIB53737t2hfAcAAEBECGadYPY57RC1Z88e575ixYqn2zYAAICwZ9knNjb2pK+JCWQgaiUnJ2vr1q0qWrSoYmJisrKNAAAAYcNikQWocuXKKVeuXKcfogAAAJAeheUAAAAhIEQBAACEgBAFAAAQAkIUAABACAhRAAAAISBEAQAAhIAQBQAAoMz7fxiED85TjEhWAAAAAElFTkSuQmCC", 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" ] }, - "execution_count": 4, + "execution_count": 5, "metadata": {}, "output_type": "execute_result" } @@ -199,13 +165,13 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 6, "id": "1d9d7296-3510-44fa-98ad-d7d7e4ce36ea", "metadata": {}, "outputs": [ { "data": { - "image/png": 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", + "image/png": 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\n", "" ] @@ -436,10 +410,10 @@ { "data": { "text/plain": [ - "" + "" ] }, - "execution_count": 7, + "execution_count": 10, "metadata": {}, "output_type": "execute_result" } @@ -449,11 +423,19 @@ "\n", "view_components_3d(ligand_network.nodes)" ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "c8bd3e3f-06f5-44bb-b158-2f8b963f6cd9", + "metadata": {}, + "outputs": [], + "source": [] } ], "metadata": { "kernelspec": { - "display_name": "openfe_env", + "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, @@ -467,7 +449,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.13.8" + "version": "3.13.11" }, "widgets": { "application/vnd.jupyter.widget-state+json": { diff --git a/cookbook/network_from_orion_fepp.ipynb b/cookbook/network_from_orion_fepp.ipynb index 70fa0a0..b4d5a2d 100644 --- a/cookbook/network_from_orion_fepp.ipynb +++ b/cookbook/network_from_orion_fepp.ipynb @@ -5,7 +5,7 @@ "id": "4197d26d-c9e2-47ca-8d19-8372568371d8", "metadata": {}, "source": [ - "# Creating Ligand Networks Exported from Orion or FEP+" + "# Loading Ligand Networks Exported by Orion or FEP+" ] }, { @@ -13,7 +13,9 @@ "id": "fd2a0058-94c5-4476-9609-ab84f6a24b18", "metadata": {}, "source": [ - "OpenFE provides functions to load a ligand network from an [OpenEye Orion NES] `.dat` file or Schrödinger FEP+ `.edge` file. With this, we can create a network of transformations using their tools and then run the actual simulations with OpenFE.\n", + "OpenFE provides functions to load a ligand network from an [OpenEye Orion NES] `.dat` file or Schrödinger FEP+ `.edge` file.\n", + "\n", + "This allows for creating a network of transformations using either of these external tools, then running the actual simulations with OpenFE.\n", "\n", "[OpenEye Orion NES]: https://docs.eyesopen.com/floe/modules/oemdaffinity/docs/source/tutorials/NES_tutorial.html" ] @@ -148,7 +150,7 @@ "source": [ "from openfe.setup.ligand_network_planning import load_fepplus_network\n", "\n", - "ligand_network = load_fepplus_network(\n", + "fepp_network = load_fepplus_network(\n", " ligands=ligands,\n", " mapper=mapper,\n", " network_file=\"assets/somebenzenes_fepp.edge\",\n", @@ -190,7 +192,7 @@ "source": [ "from openfe.setup.ligand_network_planning import load_orion_network\n", "\n", - "ligand_network = load_orion_network(\n", + "orion_network = load_orion_network(\n", " ligands=ligands,\n", " mapper=mapper,\n", " network_file=\"assets/somebenzenes_nes.dat\",\n", @@ -232,7 +234,7 @@ "source": [ "from openfe.utils.atommapping_network_plotting import plot_atommapping_network\n", "\n", - "plot_atommapping_network(ligand_network)" + "plot_atommapping_network(orion_network)" ] }, { @@ -244,7 +246,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "f0394b8c95664ad3ba3424f9fa486906", + "model_id": "4dd59bc281b3482eb85a2af2de86baca", "version_major": 2, "version_minor": 0 }, @@ -257,7 +259,7 @@ } ], "source": [ - "## Similarly we can visualize the invidual mappings\n", + "## Similarly we can visualize the individual mappings\n", "\n", "from ipywidgets import interact, widgets\n", "\n", @@ -267,7 +269,7 @@ "\n", "# traverse through all views\n", "\n", - "edges = list(ligand_network.edges)\n", + "edges = list(orion_network.edges)\n", "\n", "interact(display_edge, index=widgets.IntSlider(min=0, max=len(edges)-1, step=1));" ] @@ -285,7 +287,7 @@ "id": "18bc78e1-6aae-401f-bfef-2a98d0af5672", "metadata": {}, "source": [ - "See [Creating an Alchemical Network] for how to use these defined `ligand_network` objects to create an AlchemicalNetwork, which we can then be executed using the OpenFE CLI.\n", + "See [Creating an Alchemical Network] for how to use these defined `ligand_network` objects to create an AlchemicalNetwork, which can then be executed using the OpenFE CLI.\n", "\n", "[Creating an Alchemical Network]: https://docs.openfree.energy/en/stable/cookbook/create_alchemical_network.html" ] diff --git a/networks/konnektor_kartograf_example.ipynb b/networks/konnektor_kartograf_example.ipynb new file mode 100644 index 0000000..5f58f7f --- /dev/null +++ b/networks/konnektor_kartograf_example.ipynb @@ -0,0 +1,11111 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Building Ligand Networks from Real World Data with **konnektor** and **kartograf**\n", + "\n", + "Here we build a network based on a real world case using **konnektor** along with [kartograf](https://kartograf.openfree.energy), the OpenFE ecosystem's atom mapping tool.\n", + "\n", + "We take the chemical molecules from our Kartograf publication and create mappings between them using Kartograf’s [AtomMapper](https://kartograf.openfree.energy/en/latest/guide/atom_mapping.html) and its RMSD-based [AtomMappingScorer](https://kartograf.openfree.energy/en/latest/api/kartograf.metrics.html#kartograf.mapping_metrics.metric_mapping_rmsd.MappingRMSDScorer)\n", + "\n", + "Additionally we demonstrate the interactive widget that gives immediatley insights into the ``Components`` (nodes) and ``AtomMappings`` (edges) of a ``LigandNetwork``." + ] + }, + { + "cell_type": "markdown", + "metadata": { + "collapsed": false, + "jupyter": { + "outputs_hidden": false + } + }, + "source": [ + "## Fetching the input data and building the `AtomMapper` and `AtomMappingScorer` classes" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "ExecuteTime": { + "end_time": "2024-09-04T03:21:33.744068Z", + "start_time": "2024-09-04T03:21:33.653647Z" + } + }, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "" + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "# Getting Data\n", + "from rdkit import Chem\n", + "from konnektor.data import get_benzene_ligands\n", + "\n", + "rw_components = get_benzene_ligands()\n", + "rw_components = list(\n", + " filter(lambda x: not x.name in [\"lig_2\", \"lig_3\", \"lig_4\", \"lig_7\"], rw_components)\n", + ")\n", + "Chem.Draw.MolsToGridImage([c.to_rdkit() for c in rw_components], molsPerRow=4)" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": { + "ExecuteTime": { + "end_time": "2024-09-04T03:21:33.838785Z", + "start_time": "2024-09-04T03:21:33.747166Z" + } + }, + "outputs": [], + "source": [ + "# Load AtomMapper and Scorer\n", + "from kartograf import KartografAtomMapper, MappingRMSDScorer\n", + "\n", + "mapper = KartografAtomMapper()\n", + "scorer = MappingRMSDScorer()" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Construct __Cyclic Network Layout__\n", + "We build a `CyclicNetworkGenerator` by passing the `AtomMapper` and `AtomMappingScorer` from Kartograf and use the generator with the components." + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "ExecuteTime": { + "end_time": "2024-09-04T03:21:35.495884Z", + "start_time": "2024-09-04T03:21:33.841258Z" + } + }, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "from konnektor.network_planners import CyclicNetworkGenerator\n", + "\n", + "network_planner = CyclicNetworkGenerator(\n", + " mappers=mapper, scorer=scorer, n_processes=1\n", + ")\n", + "\n", + "cyclic_network_rw = network_planner(rw_components)\n", + "cyclic_network_rw.name = \"Real World Cyclic Network\"\n", + "cyclic_network_rw" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": { + "ExecuteTime": { + "end_time": "2024-09-04T03:21:35.877633Z", + "start_time": "2024-09-04T03:21:35.500344Z" + }, + "collapsed": false, + "jupyter": { + "outputs_hidden": false + } + }, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# NBVAL_SKIP\n", + "from konnektor.visualization import draw_ligand_network\n", + "draw_ligand_network(cyclic_network_rw);" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "# note that this will only work in an interactive session\n", + "\n", + "# from konnektor.visualization import draw_network_widget\n", + "\n", + "# draw_network_widget(cyclic_network_rw, show_molecules=True, show_mappings=True);" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.13.11" + }, + "widgets": { + "application/vnd.jupyter.widget-state+json": { + "state": { + "0017892367d74b7bbfd5a48c3b43f5f4": { + "model_module": "jupyter-cytoscape", + "model_module_version": "^1.3.3", + "model_name": "EdgeModel", + "state": { + "_model_module_version": "^1.3.3", + "_view_module_version": "^1.3.3", + "data": { + "id": "ccb3c0dc-fcdf-4ed0-93ab-948f1a167d5c", + "source": "lig_CHEMBL3265019", + "target": "lig_CHEMBL3265005-lig_CHEMBL3265019" + }, + "selectable": false + } + }, + "00255ff6e23743a186d0eb983dd96d4d": { + "model_module": "jupyter-cytoscape", + "model_module_version": "^1.3.3", + "model_name": "NodeModel", + "state": { + "_model_module_version": "^1.3.3", + "_view_module_version": "^1.3.3", + "classes": "ligand", + "data": { + "col": "#2e3a31", + "id": "lig_CHEMBL3265036", + "img": 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