diff --git a/rbfe_tutorial/cli_tutorial.md b/rbfe_tutorial/cli_tutorial.md
index 480e855..f8c6809 100644
--- a/rbfe_tutorial/cli_tutorial.md
+++ b/rbfe_tutorial/cli_tutorial.md
@@ -15,69 +15,83 @@ stages; each of which corresponds to a CLI command:
To work through this tutorial, start out with a fresh directory. You can download the tutorial materials (including this file) using the command:
```bash
-openfe fetch rhfe-tutorial
+openfe fetch rbfe-tutorial
```
Then when you run `ls`, you should see that your directory has this file,
-`cli-tutorial.md`, a notebook called `rhfe-python-tutorial.ipynb`, and `benzenes_RHFE.sdf`.
+`cli_tutorial.md`, a notebook called `python_tutorial.ipynb`, and files with
+the molecules we'll use in this tutorial: `tyk2_ligands.sdf` and
+`tyk2_protein.pdb`.
## Setting up the campaign
The CLI makes setting up the simulation very easy -- it's just a single CLI
-command. There are separate commands for binding free energy and hydration free
-energy setups.
+command. There are separate commands for relative binding free energy (RBFE)
+and relative hydration free energy setups (RHFE).
For RBFE campaigns, the relevant command is `openfe plan-rbfe-network`. For
RHFE, the command is `openfe plan-rhfe-network`. They work mostly the same,
except that the RHFE planner does not take a protein. In this tutorial, we'll
-do an RHFE calculation. The only difference for RBFE is in the setup stage --
+do an RBFE calculation. The only difference for RBFE is in the setup stage --
running the simulations and gathering the results are the same.
-To run the setup, we'll tell it search for SDF/MOL2 files in the current
-directory using `-M ./`. We'll tell it to output into the same directory that
-we're working in with the `-o ./` option.
+To run the command, we'll tell it get all the ligands from the SDF by giving
+the option `-M tyk2_ligands.sdf`. You can also use `-M` with a directory, and
+it will load all molecules found in any SDF or MOL2 file in that directory.
+We'll tell the command to use the our PDB for the protein with `-p
+tyk2_protein.pdb`. Finally, we'll tell it to output into a directory called
+`network_setup` with the `-o network_setup` option.
```bash
-openfe plan-rhfe-network -M benzenes_RHFE.sdf -o setup
+openfe plan-rbfe-network -M tyk2_ligands.sdf -p tyk2_protein.pdb -o network_setup
```
-Planning the campaign may a take a few minutes, as it tries to find the best
-network from all possible transformations. This will create a file for each
-leg that we will calculate, all within a directory called `transformations`.
-Now you're ready to run the simulations! Let's look at the structure of the
-`transformations` directory:
+Planning the campaign may take some time, as it tries to find the best
+network from all possible transformations. This will create directory called
+`network_setup`, which is structured like this:
-
-
+
```text
-setup
+network_setup
├── ligand_network.graphml
-├── setup.json
+├── network_setup.json
└── transformations
- ├── easy_rhfe_lig_10_solvent_lig_15_solvent.json
- ├── easy_rhfe_lig_10_vacuum_lig_15_vacuum.json
- ├── easy_rhfe_lig_11_solvent_lig_14_solvent.json
- ├── easy_rhfe_lig_11_vacuum_lig_14_vacuum.json
+ ├── easy_rbfe_lig_ejm_31_complex_lig_ejm_42_complex.json
+ ├── easy_rbfe_lig_ejm_31_complex_lig_ejm_46_complex.json
+ ├── easy_rbfe_lig_ejm_31_complex_lig_ejm_47_complex.json
+ ├── easy_rbfe_lig_ejm_31_complex_lig_ejm_48_complex.json
+ ├── easy_rbfe_lig_ejm_31_complex_lig_ejm_50_complex.json
+ ├── easy_rbfe_lig_ejm_31_solvent_lig_ejm_42_solvent.json
+ ├── easy_rbfe_lig_ejm_31_solvent_lig_ejm_46_solvent.json
[continues]
```
-There is a subdirectory for each edge, named according to the ligand pair.
-Within that, there are directories for the two "legs" associated with this
-ligand transformation: the ligand transformation in solvent and in vacuum.
-Each JSON file represents a single leg to run, and contains all the necessary
-information to run that leg.
+The `ligand_network.graphml` file describes the atom mappings between the
+ligands. We can visualize it with the `openfe ligand-network-viewer` command:
+
+```bash
+openfe ligand-network-viewer network_setup/ligand_network.graphml
+```
+
+This opens an interactive viewer. You can move the ligand names around to get a
+better view of the structure, and if you click on the edge, you'll see the
+mapping for that edge.
+
+The files that describe each individual process we will run are located in the
+`transformations` subdirectory. Each JSON file represents a single leg to run,
+and contains all the necessary information to run that leg.
Note that this specific setup makes a number of choices for you. All of
-these choices can be customized in the Python API, and some can be customized
-using the CLI. To see additional CLI options, use `openfe plan-rhfe-network
---help`. Here are the specifics on how these simulation are set up:
+these choices can be customized in the Python API. Here are the specifics on
+how these simulation are set up:
-1. LOMAP is used to generate the atom mappings between ligands.
+1. LOMAP is used to generate the atom mappings between ligands, with a
+ 20-second timeout, element changes disallowed, and max3d set to 1.
2. The network is a minimal spanning tree, with the default LOMAP score used to
score the mappings.
3. Solvent is water with NaCl at an ionic strength of 0.15 M (neutralized).
-4. The protocol used is OpenFE's OpenMM RFE protocol, with default settings.
+4. The protocol used is OpenFE's OpenMM-based RFE protocol, with default settings.
@@ -121,8 +135,8 @@ done
To get example data, use the following commands:
```bash
-openfe fetch rhfe-tutorial-results
-tar xzf results.tar.gz
+openfe fetch rbfe-tutorial-results
+tar xzf rbfe_results.tar.gz
```
This will create a directory called `results/` that contains files in the file
@@ -136,17 +150,28 @@ like this:
```text
results
-├── easy_rhfe_lig_10_solvent_lig_15_solvent
-│ ├── shared_RelativeHybridTopologyProtocolUnit-333f0749f2554d6794c0dfb495c32bc3
+├── easy_rbfe_lig_ejm_31_complex_lig_ejm_42_complex
+│ ├── shared_RelativeHybridTopologyProtocolUnit-3ea82011-75f0-4bb6-b415-e7d05bd012f6
+│ │ ├── checkpoint.nc
+│ │ └── simulation.nc
+│ ├── shared_RelativeHybridTopologyProtocolUnit-5262feb6-cb50-4bb2-90a2-359810c2bb9c
+│ │ ├── checkpoint.nc
+│ │ └── simulation.nc
+│ └── shared_RelativeHybridTopologyProtocolUnit-7a6def34-2967-4452-8d47-483bc7219c06
+│ ├── checkpoint.nc
+│ └── simulation.nc
+├── easy_rbfe_lig_ejm_31_complex_lig_ejm_42_complex.json
+├── easy_rbfe_lig_ejm_31_complex_lig_ejm_46_complex
+│ ├── shared_RelativeHybridTopologyProtocolUnit-ad113e55-5636-474e-9be3-ee77fe887e77
│ │ ├── checkpoint.nc
│ │ └── simulation.nc
-│ ├── shared_RelativeHybridTopologyProtocolUnit-3a17c1c3a438403a88766e2ad4986d62
+│ ├── shared_RelativeHybridTopologyProtocolUnit-ca74ad3c-2ac8-4961-be7c-fa802a1ec76b
│ │ ├── checkpoint.nc
│ │ └── simulation.nc
-│ └── shared_RelativeHybridTopologyProtocolUnit-9aa9c8b808b64f6089ef22c9c83bc89d
+│ └── shared_RelativeHybridTopologyProtocolUnit-f848e671-fdd3-4b8d-8bd2-6eb5140e3ed3
│ ├── checkpoint.nc
│ └── simulation.nc
-├── easy_rhfe_lig_10_solvent_lig_15_solvent.json
+├── easy_rbfe_lig_ejm_31_complex_lig_ejm_46_complex.json
[continues]
```
@@ -165,29 +190,33 @@ openfe gather ./results/ -o final_results.tsv
This will write out a tab-separated table of results, including both the
$\Delta G$ for each leg and the $\Delta\Delta G$ computed from pairs of legs.
-The first column labels the data, e.g., `DGvacuum(ligandB,ligandA)` for the
-$\Delta G$ of the transformation of ligand A into ligand B in vacuum, or
-`DDGsolv(ligandB,ligandA)` for the $\Delta\Delta G$ of binding ligand A vs.
-ligand B: $\Delta G$solv, $B$$ - \Delta G$solv$A$.
+The first column is a description of the data, e.g., `DGcomplex(ligandB,
+ligandA)` for the $\Delta G$ of the transformation of ligand
+A into ligand B in vacuum, or `DDGbind(ligeandB, ligandA)` for the
+$\Delta\Delta G$ of binding ligand A vs. ligand B: $\Delta G$bind,
+$B$$ - \Delta G$bind$A$. The second column tells the type of
+the result, either `RBFE` for a relative result or `solvent`/`complex` for an
+individual leg. The next two columns are the labels of the ligands, and then
+the computed result and its uncertainty.
The resulting file looks something like this:
-
+
```text
-measurement estimate (kcal/mol) uncertainty
-DDGhyd(lig_8, lig_6) 4.1 +-0.074
-DDGhyd(lig_6, lig_1) -3.5 +-0.038
-DDGhyd(lig_15, lig_14) 3.3 +-0.056
-DDGhyd(lig_14, lig_13) 0.49 +-0.038
-[snip]
-DGvacuum(lig_6, lig_8) -10.0 +-0.027
-DGsolvent(lig_6, lig_8) -6.1 +-0.069
-DGsolvent(lig_1, lig_6) 17.0 +-0.032
-DGvacuum(lig_1, lig_6) 20.0 +-0.022
-DGvacuum(lig_14, lig_15) 6.9 +-0.0028
-DGsolvent(lig_14, lig_15) 10.0 +-0.056
-DGsolvent(lig_13, lig_14) 15.0 +-0.037
+measurement type ligand_i ligand_j estimate (kcal/mol) uncertainty (kcal/mol)
+DDGbind(lig_ejm_48, lig_ejm_31) RBFE lig_ejm_31 lig_ejm_48 0.45 0.17
+DDGbind(lig_jmc_28, lig_ejm_46) RBFE lig_ejm_46 lig_jmc_28 -0.12 0.044
+DDGbind(lig_ejm_46, lig_ejm_31) RBFE lig_ejm_31 lig_ejm_46 -0.73 0.097
+DDGbind(lig_ejm_50, lig_ejm_31) RBFE lig_ejm_31 lig_ejm_50 0.94 0.072
+DDGbind(lig_ejm_42, lig_ejm_31) RBFE lig_ejm_31 lig_ejm_42 0.49 0.09
+DDGbind(lig_jmc_23, lig_ejm_46) RBFE lig_ejm_46 lig_jmc_23 -0.39 0.046
+DDGbind(lig_ejm_43, lig_ejm_42) RBFE lig_ejm_42 lig_ejm_43 1.2 0.14
+DDGbind(lig_jmc_27, lig_ejm_46) RBFE lig_ejm_46 lig_jmc_27 -0.65 0.1
+DDGbind(lig_ejm_47, lig_ejm_31) RBFE lig_ejm_31 lig_ejm_47 0.016 0.15
+DGsolvent(lig_ejm_31, lig_ejm_48) solvent lig_ejm_31 lig_ejm_48 -20.0 0.043
+DGcomplex(lig_ejm_31, lig_ejm_48) complex lig_ejm_31 lig_ejm_48 -19.0 0.17
+DGsolvent(lig_ejm_46, lig_jmc_28) solvent lig_ejm_46 lig_jmc_28 14.0 0.043
+DGcomplex(lig_ejm_46, lig_jmc_28) complex lig_ejm_46 lig_jmc_28 14.0 0.0069
[continues]
```
diff --git a/rbfe_tutorial/python_tutorial.ipynb b/rbfe_tutorial/python_tutorial.ipynb
index 3c29ac5..19d955a 100644
--- a/rbfe_tutorial/python_tutorial.ipynb
+++ b/rbfe_tutorial/python_tutorial.ipynb
@@ -7,7 +7,7 @@
"source": [
"# Setting up a relative hydration free energy network\n",
"\n",
- "This tutorial gives a step-by-step process to set up a relative hydration free energy (RHFE) simulation campaign using OpenFE. This tutorial is designed as an accompaniment to the CLI tutorial found in the same directory as this notebook.\n",
+ "This tutorial gives a step-by-step process to set up a relative binding free energy (RBFE) simulation campaign using OpenFE. This tutorial is designed as an accompaniment to the CLI tutorial found in the same directory as this notebook.\n",
"\n",
"With the CLI, all the steps here were performed by the `openfe plan-rhfe-network` command. However, that command offers little room for customization. Using the Python interface gives us the ability to customize all aspects of how our simulation runs."
]
@@ -28,7 +28,7 @@
"id": "2fea29c3",
"metadata": {},
"source": [
- "## Loading the molecules\n",
+ "## Loading the ligands\n",
"\n",
"First we must load the chemical models between which we wish to calculate free energies.\n",
"In this example these are initially stored in a molfile (`.sdf`) containing multiple molecules.\n",
@@ -43,7 +43,7 @@
"outputs": [],
"source": [
"from rdkit import Chem\n",
- "supp = Chem.SDMolSupplier(\"./molecules/rhfe/benzenes_RHFE.sdf\", removeHs=False)\n",
+ "supp = Chem.SDMolSupplier(\"tyk2_ligands.sdf\", removeHs=False)\n",
"ligands = [openfe.SmallMoleculeComponent.from_rdkit(mol) for mol in supp]\n",
"\n",
"name_to_ligand = {ligand.name: ligand for ligand in ligands}"
@@ -74,7 +74,7 @@
"metadata": {},
"outputs": [],
"source": [
- "mapper = openfe.LomapAtomMapper(element_change=False)\n",
+ "mapper = openfe.LomapAtomMapper(max3d=1.0, element_change=False)\n",
"scorer = openfe.lomap_scorers.default_lomap_score\n",
"network_planner = openfe.ligand_network_planning.generate_minimal_spanning_network"
]
@@ -117,7 +117,7 @@
"outputs": [
{
"data": {
- "image/png": "iVBORw0KGgoAAAANSUhEUgAAAoAAAAJwCAYAAAAZX9A6AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuMSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/bCgiHAAAACXBIWXMAAA9hAAAPYQGoP6dpAABSv0lEQVR4nO3deXgUVfr28TsLIQkQ1rCDQUQBEQgYlE0BCUrCDkGhEVARFRxBnXH5waiMAzOv2zDuMjoq0oAECDuyCKhEZREQUdnFCAgikSQsAiH9/nEmCWqATlLd1cv3c111penqPvVkrhFvz1PnVIjL5XIJAAAAQSPU7gIAAADgXQRAAACAIEMABAAACDIEQAAAgCBDAAQAAAgyBEAAAIAgQwAEAAAIMgRAAACAIBPuzofy8vJ08OBBVahQQSEhIZ6uCQAAAMXkcrmUk5Oj2rVrKzT04nN8bgXAgwcPql69epYUBwAAAM/54YcfVLdu3Yt+xq0AWKFChYIBY2JiSl8ZAAAALJWdna169eoV5LaLcSsA5rd9Y2JiCIAAAAA+zJ3b9VgEAgAAEGQIgAAAAEGGAAgAABBkCIAAAABBhgAIAAAQZAiAAAAAQYYACAAAEGQIgAAAAEGGAAgAABBkCIAAAABBhgAIAAAQZAiAAAAAQYYACAAAEGQIgAAAAEGGAAgAABBkCIAAAABBhgAIAAAQZAiAAAAAQYYACAAAEGQIgAAAAEGGAIhS69RJGjvWvI6LkyZPtq8WAABwaeF2F4DAsmGDVK6cdeNNnCgtXixt2SJFREjHjlk3NgAAwYoZQFgqNlaKjrZuvDNnpJQU6b77rBsTAIBgRwCEpX7fAt6+XerQQYqMlJo2lVaulEJCpHnz3BtvwgTpwQela67xQLEAAAQpWsDwmLw8qU8fqX59ad06KSdHevhhu6sCAAAEQHjM8uXSnj3SmjVSzZrmvYkTpcREW8sCACDo0QKGx+zYIdWrVxj+JKlNG/vqAQAABgEQHuNymfv9AACAbyEAwmMaN5YyMqTDhwvf27DBvnoAAIDBPYDwmMREqWFDadgw6ZlnzCKQcePMOXdnBjMypMxM8/PcObMfoCRdcYVUvrxHygYAIOAxAwiPCQsz270cPy4lJEgjRkjjx5tzkZHujfHEE1J8vPTkk2ac+HhzbNzosbIBAAh4IS6Xy3WpD2VnZ6tixYrKyspSTEyMN+pCgEpPN/sC7t5tZgcBAIA1ipPXaAHDo9LSTKu2USMT+saMkdq3J/wBAGAnWsDwqJwcadQosyBk+HDTCp4/35ybNMmEw6KO7t1tLRsAgIBGCxi2ycw0R1GioqQ6dbxbDwAA/owWMPxClSrmAAAA3kULGAAAIMgQAAEAAIIMARABqVMnaexY8zouTpo82b5aAADwNQRABLwNG6SRI60bb+dOqXdvqVo1KSbGbGuzerV14wMA4GkEQAS82FgpOtq68ZKTpdxcadUq6YsvpJYtpR49pEOHrLsGAACeRACER3z44Ydq1aqVhg0bZncpf2gBb99unkYSGSk1bSqtXGmeTTxv3qXH+vlns6H1Y49JzZubDa7/+U/p5Enp66899AsAAGAxAiA8YtOmTdq8ebNyc3PtLuU38vKkPn3MjOC6ddKUKdK4ce5/v2pVqUkTaepU6cQJMxP4xhtSjRpS69YeKxsAAEuxDyA8Yu/evZKkyy+/3OZKfmv5cmnPHmnNGqlmTfPexIlSYqJ73w8JkVasMPcAVqgghYaa8PfBB1KlSp6qGgAAazEDCI/w1QC4Y4dUr15h+JOkNm3c/77LZR5tV7269Mkn0vr1Jgz26CH9+KP19QIA4AkEQHiErwZAl8vM4pXUqlXSokXSzJlm9W+rVtKrr5pH1737rnV1AgDgSQRAWC43N1f79u2T5HsBsHFjKSNDOny48L0NG9z//smT5mfo7/7JCQ019xcCAOAPCICw3P79+5Wbm6uIiAjVrl3b7nJ+IzFRathQGjZM2rpVSk8vXATizsxg27ZS5crm+19+afYE/MtfpO++M9vDAADgDwiAsFx++zcuLk5hYWE2V/NbYWFmu5fjx6WEBGnECGn8eHMuMvLS369WzSz4OH5c6tJFuvZaae1aaf58qUULj5YOAIBlWAUMy/nC/X9r1hS+/l83ukDjxia05UtPNz+vuMK9sa+9Vlq2rDTVAQBgLwIgLJcfABs2bGhzJUVLS5PKlzebOO/eLY0ZYxZ0+Gi5AABYjhYwLOcLM4AXk5NjtnJp3FgaPty0gufPN+cmTTLhsKije3dbywYAwDLMAMJyvh4Ahw41R1HuvVcaOLDoc1FRnqsJAABvIgDCcr4eAC+mShVzAAAQyGgBw1JZWVk6evSoJKlBgwY2VwMAAIri0wGwUydp7FjzOi5OmjzZvlrgnu+++06SFBsbqwoVKnjsOvkhEwAAFJ9PB8DzbdggjRxp3XgTJ0rt2knR0VKlSkV/JiTkj8frr1tXQyDas2ePJM+1f10ul2bOnKmUlBSPjA8AQDDwmwAYG2vCmlXOnJFSUqT77rv4595+W/rxx8Jj2DDraghEnrz/79ChQ+rfv78GDRqkY8eOWT4+AADBwm8C4O9bwNu3Sx06mKc3NG0qrVxpZujmzXNvvAkTpAcflK655uKfq1RJqlmz8GAl6MV5IgC6XC5Nnz5dV199tdLS0hQeHq6hQ4fK5XJZdg0AAIKJ3wTA8+XlSX36mBnBdeukKVMKn+dqtfvvN4//Skgw7d+8PM9cJ1BYHQAPHTqkfv36yeFwKDMzU/Hx8dq4caPGjh2rEHce3gsAAP7AL7eBWb5c2rPHPO6rZk3z3sSJUmKitdd5+mnpppvMrN+HH0oPPyz9/HPhs2PxR5GRkYqPj1eLUj4Y1+VyaenSpXrmmWeUnZ2thIQE3X333Ro+fLjKlCljUbUAAAQnvwyAO3ZI9eoVhj9JatPG+uucH/RatjQ///Y3AuDFzM9/pEYphYSEKCkpSUlJSZaMBwAACvllC9jlMvf7edv110vZ2dLhw96/NgAAgFX8MgA2bixlZPw2iG3Y4Pnrbt5sFp1caNsYAAAAf+CXLeDERKlhQ7MlyzPPSDk5hYtA3J0ZzMiQMjPNz3PnpC1bzPtXXCGVLy8tXCgdOiS1bWvuAVy92lxj5EipbFmP/FoAAABe4ZcBMCzMbPcyYoRZnXv55dKzz0o9e5oZOnc88YT07ruFf46PNz9XrzZPIClTRnr1Vemhh8zK38svN/f/jR5t9W8DAADgXSEuNzZTy87OVsWKFZWVlaWYmBhv1FVs6elmX8Ddu83sIAAAQDApTl7zy3sAJSktTVqxQtq3z2wCPXKk1L494c9TeC4zAACBw28DYE6ONGqUWRAyfLhpBefvQDJpkrmPr6ije3dbyw4IVj+XedMmc19npUpS1apm7OPHrRsfAAD8VsC0gM+XmWmOokRFSXXqeLeeQNCpk9kL0eqZv4MHpWbNpFtvNTOM2dnmZ61a0uzZ1l6rKOf/XnFx5tr5M50AAPiToGgBX0yVKmY1b1EH4a/0rHwu86JFZsHNK69IV11lZnJfeUWaM8fcz+lNVs9sStLixdJ115n/8KhWTerXz9rxAQAoCb9cBQzfkf9c5vr1zXOZc3LMI/Pcdfq0FBEhhZ73nyJRUebn2rUmtHtLbKy1482ZI919t7kloUsXs4H5V19Zew0AAEoiIGcA4T35z2WeOlVq0cLMBE6c6P73u3Qx+y0++6x05oz0yy/S//2fOffjj56p+UKsnNnMzZXGjDG/1733SldeaWY4BwzwUPEAABQDARClUtrnMl99tdmP8fnnpehoM87ll0s1apj9Hu2SP7MZHW1mNqdMKdxs3B2bNkkHDpiZzfh4c09j9+7S1197rGQAANxGAESpWPFc5sGDzSzggQPS0aPSU09JR45IDRpYUmKJlHZmc+9e8/Opp6Tx4829jpUrSzfeeOEFSgAAeAv3AKJUzn8uc40a5r2SPpc5//v//a9puyYmXvo7b7zxhrKyshQdHa3o6GiVK1eu4HV0dLSqVaumRo0aFbuW0s5s5uWZn+PGSf37m9dvvy3VrSulpkr33FPskgAAsEzQBsC8vDz9+9//1nvvvSdJGjp0qCIiIvTf//5XeXl5qlWrlp5++mm1atXqD991uVzatGmTZs2apVWrVuncuXOSpGrVqql///7q06ePauSnmQDRqJEJL5Jp2+YvmEhMNI/ge/ppc8/biRNm1iw+3rRP3fHyy1K7dmafxhUrpL/8RfrnP82+gJfyxhtvaPPmzRc8Hx8fr02bNrlXyHlKO7NZq5b52bRp4Xtly5r2dkZGyccFAMAKQRsAQ0ND9eCDD+rs2bN69NFHtXnzZt1111164YUXNHz4cG3evFlLly7VY489pqeeekoREREF3w0JCVHr1q3VunVrHThwQFOmTNGUKVO0efNmrVixQvfff7/69u2r+++/Xx07dlRIaXukPuA//yl8vXhx4euwMGnu3N9+Nv8Zy//LxZe0fr305JNm8+fGjaU33pBuv9297w4cOFDNmzfXyZMnC44TJ04UvK5WrZp7A/1OaWc2W7c2gW/HDtM+lqSzZ82Tay67rEQlAQBgHZcbsrKyXJJcWVlZ7nzc7/znP/9xhYaGuiS5+vbt6/rpp59cd9xxh0uSS5KrdevWrm+//faiY5w+fdo1c+ZMV4cOHQq+J8nVrFkz12uvvebKycnx0m+D4rjxRpdrzBjz+rLLXK5//cu8zs11ua66yuW6+WaX68svXa61a12u665zuSSXa94898YeM8blqlPH5Vq2zOXavt3luusul6t6dZcrM9PyXwMAgGLlNRaBSBoxYoRSU1MVERGhtLQ03XrrrZo8ebJmz56tKlWq6IsvvlCrVq302muvyXWBB6dERETo1ltv1SeffKItW7Zo5MiRio6O1rZt23TfffepTp06euCBB7R9+3Yv/3YoibAws93L8eNmc+oRI8xiDsncn+iOZ5+VbrvNzGYmJEjffy+tWmUWgwAAYKeAfBRcSa1evVq9e/dWTk6OWrVqpaVLl+rs2bO64447tGLFCklSUlKS/vvf/7p1j9+xY8f0zjvv6NVXX9WuXbsK3u/atatGjx6tHj16KDw8sLvwb71l7g0sSseO0tKl3q2nNNLTTTt3926pYUO7qwEA4LeKk9cIgL/zxRdfqHv37jpy5IgaNWqkFStWqF69enrppZf06KOP6vTp04qNjdVbb72lnj17ujVmXl6eVq5cqZdfflmLFi0qmEWsV6+e7r33Xo0YMULVq1f35K9lm6wss6VLUXz9ucxpaWZhSqNGJvSNGWNm79autbsyAAD+iABYSjt37lRiYqIyMjJUu3ZtLV++XFdffbW2bdsmh8OhrVu3SpLuuecePf/88ypXrpzbY+/bt0+vv/663nzzTR09elSSaR//5S9/0d///neP/D4omalTzermH34wz/Ht2tVsWF21qnm826RJRX/P32Y2AQCBgQBogQMHDqhbt2765ptvVLlyZS1evFht27bV6dOnNX78eD333HOSpEaNGsnpdCohIaFY4//666+aNWuWXnnlFa1fv/6i25V06iS1bGkeUxYXJ40daw7YJzPzwhs6+/rMJgAgMBUnr7EI5ALq1KmjTz75RNdff71++eUXde3aVR988IHKli2rZ599Vh9++KHq1KmjXbt2qV27dvr73/+u3Nxct8ePjIzU0KFDtW7dOq1fv97tdvKGDdLIkSX9rf5o4kSzB1909KX33Tt61OwFGBIiHTtmXQ3+qEoV6Yorij4IfwAAX0cAvIgqVapo5cqVuvnmm3Xy5En17NlTM2bMkCR16dJFX331lQYOHKjc3Fz99a9/1Y033qi9+c8AK4aEhARNmDDBrc/Gxrq/wbI7zpyRUlKk++679Gfvuktq3ty6awMAAHsQAC+hXLlyWrBggW677Tbl5ubK4XDolVdekSRVrlxZM2fO1HvvvaeYmBh9+umnatmypd59990LbhdTWnFxphWcb/t2szI1MtI8dWLlSjNDN2+ee+NNmCA9+KB0zTUX/9xrr5lZvz//uWR1AwAA30EAdENERIScTqdGjx4tl8ul+++/X0899ZRcLpdCQkI0ZMgQffnll+rYsaNycnI0fPhwDRw4sGCRh6fk5Ul9+pgZwXXrpClTzLNnrfbNN9Lf/mYWRYTy/xgAAPwe/zp3U2hoqF566SU99dRTkqQJEyboT3/6k/Ly8iRJcXFxWr16tSZNmqTw8HDNnj1bzZs3L9g/0BOWL5f27DHBrEULMxM4caK11zh9Who0yGxqXL9+8b//z3/+09qCAABAqREAiyEkJERPPvmkXn75ZYWEhOiVV16Rw+HQmTNnJElhYWF6/PHH9fnnn+uqq67SwYMH1a1bNz344IP69ddfLa9nxw6pXj2pZs3C99q0sfYajz8uNWkiDRlSsu/PmTNHP//8s7VFAQCAUiEAlsDo0aPldDoVHh6umTNnqlevXjpx4kTB+datW2vTpk0aNWqUJGny5MlKSEgo2D/QKi6Xud/Pk1atklJTpfBwc9x0k3m/WjXpyScv/f1z584pLS3Ns0UCAIBiIQCW0KBBg7Rw4UJFR0dr2bJl6tq1qzLP2xguOjpar7zyihYtWqTq1atr27ZtSkhI0AsvvFDQNi6txo2ljAzp8OHC9zZssGToAnPmSF9+KW3ZYo433zTvf/KJNHq0e2PMmjXL2qIAAECpEABL4ZZbbtHKlStVuXJlff755+rYsaMOHDjwm88kJyfrq6++Us+ePXXmzBk9/PDDSkxM1P79+0t9/cRE80zaYcOkrVvNs2rzF4G4OzOYkWGCXUaGdO5cYdA7ftycb9hQatas8GjQwLzfpInk7tPrVq1apSMXeh4cAADwOgJgKbVt21affPKJateurW+++Ubt2rXTzp07f/OZ6tWra/78+XrjjTcUHR2tVatWqXnz5kpNTS3VtcPCzHYvx49LCQnSiBHS+PHmXGSke2M88YQUH2/aucePm9fx8dLGjaUqrUCTJk2Ul5enuXPnWjMgAAAoNR4FZ5F9+/apW7du2rVrl2JjY7V06VK1bt36D5/buXOnhgwZog3/69UOHTpUL730kmX/u6anm9XAu3eb2Tu7vfvuuxo+fLi6dOmiDz/80O5yAAAIWDwKzgZxcXFau3atWrVqpSNHjqhz585avXr1Hz535ZVXKj09XePHj1doaKimTp2qFi1aaPPmzSW6blqatGKFtG+f2QR65EipfXvfCH+S1LVrV0nSmjVrdPj8mxUBAIBtCIAWql69ulavXq3OnTsrJydHt9xyS5GtzzJlyujpp5/Wxx9/rAYNGmjfvn26++67S3TNnBxp1CizIGT4cNMKnj/fnJs0SSpfvuije/dS/KLFUKdOHSUkJNAGBgDAh9AC9oDTp09r3LhxWrVqlUJDQzV+/Hj16dOnyM8eP35czz33nHbu3Knp06dbWkdWlpSdXfS5MmV+u3+gJz377LN65JFH1KlTpyJnRQEAQOkVJ68RAOFx+/btU4MGDRQSEqKDBw+qpreSJwAAQYR7AOFT4uLi1KZNG7lcLtrAAAD4AAIgvGLgwIGS2BQaAABfQACEVwwYMECS9PHHH+vHH3+0uRoAAIIbARBecdlll+n666+Xy+XSnDlz7C4HAICgRgDEJZ09e1bz589XcnKyWrVqpVatWql79+6aPXu2zp496/Y4tIEBAPANBMBS6tRJGjvWvI6LkyZPtq8WTylTpox69+6ttLQ03XPPPTpy5Ig++OADpaSkqFGjRnrrrbfcCoL5beC1a9f+4ZnJAADAewiAFtqwwTyJwyoTJ0rt2knR0VKlSkV/ZswYqXVrqWxZqWVL665dlIiICN1zzz3atWuXXnrpJdWqVUvff/+9RowYoSZNmmjq1Kk6d+7cBb9fr149tWvXjjYwAAA2IwBaKDbWhDWrnDkjpaRI99134c+4XNKdd0q33mrddS8lMjJS999/v/bs2aPnn39esbGx2rNnj4YNG6arr75aM2fOVF5eXpHfpQ0MAID9CIAW+n0LePt2qUMHKTJSatrUPKs3JESaN8+98SZMkB58ULrmmgt/5sUXpdGjpcsvL0XhJRQVFaWHHnpIe/fu1T//+U9VqVJFO3bs0KBBg9S8eXPNmTPnD0Ewvw2cnp6u/fv3e79oAABAAPSUvDypTx8zI7hunTRlijRunN1VeUb58uX16KOP6rvvvtPTTz+tSpUq6euvv9aAAQPUunVrLViwQPkPnKlTp446dOggSZo9e7adZQMAELQIgB6yfLm0Z480darUooWZCZw40e6qPCsmJkbjx4/Xd999pyeeeEIVKlTQli1b1Lt3b7Vp00ZLly6Vy+WiDQwAgM0IgB6yY4dUr550/mNv27Sxrx5vqlSpkiZMmKDvvvtOjz/+uMqVK6eNGzcqKSlJ7du3V2xsrCTps88+U0ZGhs3VAgAQfAiAHuJymfv9glnVqlU1adIk7d27Vw8//LAiIyP12WefadCgQapYsaIk2sAAANiBAOghjRtLGRnS4cOF723YYF89dqpevbqee+457d27Vw888IAiIiKUlZUlSZowYYI+++wzmysEACC4EAA9JDFRathQGjZM2rpVSk8vXATi7sxgRoa0ZYv5ee6ceb1li3T8eOFndu827x06JJ06VfiZM2es/G2sUatWLf373/8u2DJGkrKzs9WuXTslJSVpQ7AmZAAAvIwA6CFhYWa7l+PHpYQEacQIafx4cy4y0r0xnnhCio+XnnzSjBMfb46NGws/M2KEee+NN6SdOws/c/Cg5b+SZerWrat33nlH1113nSQpNDRUS5cuVZs2bdS7d29t2bLF3gIBAAhwIa78/TkuIjs7WxUrVlRWVpZiYmK8UVdASk83q4F37zazg3Y7e/asypQpY9v1X331VY0ePVrNmzdXfHy83nvvvYJ9A/v376+nnnpKzZo1s60+AAD8SXHyGjOAHpSWJq1YIe3bZzaBHjlSat/eN8KfJN15553auXOnbdfv16+fQkNDtXXrVj311FP65ptvNGjQIIWEhGjOnDlq3ry5Hn/8cdvqAwAgUBEAPSgnRxo1yiwIGT7ctILnzzfnJk2Sypcv+uje3Tv1nTt3TnfccYfmzJkjNyaCLVezZk2lpKRIklJTU3XVVVdp+vTp2rp1qwYMGCCXy6Vly5Z5vS4AAAIdLWCbZGaaoyhRUVKdOt6txy65ubm6/PLLVaNGjT8sAtmyZYumTp2qF154wabqAADwH8XJa+Feqgm/U6WKOYJdeHi4OnbsqG+//Vb79+9X3bp1C861bNlSLVu2vOj3775buuoq6c9/lpKTpcGDJYfDw0UDAODnmAEELmDiRGnxYrOtTkSEdOzYb88fPWrC5tat5nX16lLv3qa9zz8mAABvYxEIYIEzZ6SUFOm++4o+HxpqAt+CBWYLnnfeMYt97r3Xq2UCAFBsBEAEjXXrzCbc8+a59/kJE6QHH5Suuabo85Urm3B47bXSZZdJN91kFv188ollJQMA4BEEQASNV17x7PgHD0pz50o33ujZ6wAAUFoEQA/q06ePWrVqpY8//tjj17r7bum558zr5GTJ6fT4Jf3O6NGeGXfQICk62qzcjomR3nzTM9cBAMAqBEAP+eGHHzR//nxt3br1kitZrbBrl7R/v3n9zjtS374ev6Tfufpqz4z7r39JmzaZ1vKePdJDD3nmOgAAWIUA6CGrVq2SJF177bVeXzkdG2tmpDyhUydp7FjzOi5OmjzZM9fxJzVrms2+e/c2z2R+7TXpxx/trgoAgAsjAHpIfgDs0qWL16/9+2C2fbt5BnFkpNS0qVmpWpzFEBeyYYN5vJ1VJk6U2rUz4bVSpaI/k5Eh9ewplSsnVasmPfCAWa3rjm++sazUC8rfVOn0ac9fCwCAkmIjaA9wuVy2BsDz5eVJffpI9eubVbA5OdLDD1szdmysNePky992pW1b6a23/nj+3Dlzf2NsrLR2rdl7b9gwE7peeunS4+cvAgkJca+ejAzztJaMDHPtLVvM+1dcYR7Zt2SJdPiwecRf+fImYD7yiHnec1yce9cAAMAOzAB6wO7du7V//35FRESoXbt2ttayfLm5L23qVKlFCzMTOHGiNWNbPdN4qW1Xli83IWvaNCk+XuraVXr+eek//5Gysy89/l13mZ+Rke7V88QT5jpPPikdP25ex8dLGzea81FR5todOkhNmpjWeI8e0qJF7o0PAIBdmAH0gPzZv3bt2inaUzfjuWnHDqlePXOfWr42bay/jidnGvN99pnUrJlUu3bhezffbNqtX3whde588e/n34p5xRXuXe+dd8xxIZ07S59+6t5YAAD4EgKgB/hK+1cy7VF3W56lkT/TuGZNYdicOFFKTLTuGocOSTVq/Pa9ypXNY9oOHbr09//+d9OebdjQupoAAPBHtIAtlpeXp9WrV0vyjQDYuLG5h+3w4cL3Nmyw/jremmksKsy6G3KvvlqaP9+8njTJ3LdX1NG9u7U1AwDga5gBtNi2bdt05MgRlStXTgkJCXaXo8REM+M1bJj0zDOmNTtunDln5cygN2Yaa9Y07eXz/fKLdPbsH2cGizJhQuHre++VBg4s+nNRUSWvEQAAf0AAtFh++7djx46KiIiwuRopLMwswhgxwqxWvfxy6dlnzVYq7i6GcMf5M435Yczqmca2bU1b+ccfpVq1zHvLl0tly0qtWxdvrCpVzAEAQDAiAFrMrvv/1qwpfL1v32/PNW5stk3Jl55ufrq7GMIdVsw0XmrblW7dzOri2283ITYzU/rzn81j8Ly81zYAAH6NAGih3NxcffTRR5J84/6/fGlpJkA1aiTt3i2NGWP9YggrZhqfeEJ6993CP8fHm5+rV5snkISFSYsXS6NGmfqjoqTBgwufgQwAANwT4nLlP7vgwrKzs1WxYkVlZWV5/bFm/mT9+vW67rrrVLlyZR05ckRhYWF2lyTJ7AH49NPSDz+Yp2fk759XtapZDDFpUuFnW7QonCEsrfR0s0fe7t2svAUAwNOKk9eYAbRQfvu3U6dOPhP+JGnoUHMU5feLIcqWLfl1vDHTCAAASo8AaCFf2v/PXVYuhsjJMY9C+/1Mo/THmcbzdewoLV1qTQ0AAODSaAFb5PTp06pcubJOnTqlr7/+Wk2bNrW7JJ+SmWmOokRFSXXqeLceAAACDS1gG3z++ec6deqUatSooSZNmthdjs9h2xUAAHwHTwKxyPnt3xBvPHsNAACghAiAFvHH+/8AAEBwIgBa4NSpUzp9+rTi4+PVnQfJAgAAH8c9gBaIiorS+vXr7S4DAADALcwAwuedPHlSbdu2VatWrbR9+3a7ywEAwO8RAOHzoqOjVadOHW3evFnvnv+sOAAAUCIEQPiFgf97XMmsWbPkxtaVAADgIgiA8AvJycmKiorS3r17tWnTJrvLAQDArxEAL6JTJ2nsWPM6Lk6aPNm+WoJduXLl1KNHD0lmFhAAAJQcAdBNGzZII0daN15cnBQS8tvjscesGz8Q0QYGAMAabAPjpthY68f829+ku+8u/HP58tZfI5AkJSUpOjpa+/bt08aNG5WQkGB3SQAA+CVmAN30+xbw9u1Shw5SZKTUtKm0cqWZxZs3z/0xK1SQatYsPAiAFxcdHa2ePXtKog0MAEBpEABLIC9P6tNHio6W1q2TpkyRxo0r/jj/7/9JVatKLVtKEydKZ85YXWngoQ0MAEDp0QIugeXLpT17pDVrzMydZAJcYqL7Y4wZI7VqJVWuLK1fLz3+uPTdd9Kbb3qk5IDRvXt3lStXThkZGVq/fr2uu+46u0sCAMDvMANYAjt2SPXqFYY/SWrTpnhjPPigdOONUvPm0ogR0uuvS2+9JR09am2tgSYqKkq9evWSRBsYAICSIgCWgMtl7vez0vXXm5+7d1s7biBKSUmRJKWmpiovL8/magAA8D8EwBJo3FjKyJAOHy58b8OG0o25ebP5WatW6cYJBrfccovKly+vH374QevWrbO7HAAA/A4BsAQSE6WGDaVhw6StW6X09MJFIO7MDH72mfSvf0lbtpj7/mbNku65R+rVS6pf36OlB4Tz28Cpqak2VwMAgP8hAJZAWJjZ7uX4cSkhwdzDN368ORcZeenvly0rvf++edJI06bSE0+Y/QBnzPBk1YElfzUwbWAAAIovxOXGXhrZ2dmqWLGisrKyFBMT4426/E56utkXcPduMzsIz/r1119VvXp15eTkKD09Xe3atbO7JAAAbFWcvMYMYAmlpUkrVkj79plNoEeOlNq3J/x5S2RkpHr37i2J1cAAABQXAbCEcnKkUaPMgpDhw00reP58c27SJPNUj6KO7t1tLTug0AYGAKBkaAF7QGamOYoSFSXVqePdegLV6dOnVb16dWVnZ+uTTz5Rhw4d7C4JAADb0AK2WZUq0hVXFH0Q/qxTtmxZ9enTRxJtYAAAioMACL+W3waePXu2zp07Z3M1AAD4BwIg/FpiYqIqVqyoH3/8Uenp6XaXAwCAXyAAwq9FRESob9++kmgDAwDgLgIg/B5tYAAAiocACL930003qXLlyjp8+LA++eQTu8sBAMDnEQDh92gDAwBQPARABISUlBRJ0pw5c5Sbm2tzNQAA+DYCIAJCfhv4p59+0scff2x3OQAA+DQCIAJCmTJl1K9fP0nm0XAAAODCCIAIGPmrgWkDAwBwcQRABIzOnTuratWqOnLkiD766CO7ywEAwGcRABEwzm8DsxoYAIALIwAioNAGBgDg0giACCidOnVStWrVdPToUa1evdrucgAA8EkEQASU8PBw9e/fXxJtYAAALoQAiICT3waeO3euzp49a3M1AAD4HgIgAs4NN9yg6tWrKzMzU6tWrbK7HAAAfA4BEAGHNjAAABdHAERAym8Dp6Wl6cyZMzZXAwCAbyEAIiB17NhRNWrU0C+//KIPP/zQ7nIAAPApBEAEpLCwMA0YMEASbWAAAH6PAIiAlZKSIok2MAAAv0cARMDq0KGDatasqaysLK1YscLucgAA8BkEQASs89vAqampNlcDAIDvIAAioOWvBp43b55Onz5tczUAAPgGAiACWvv27VWrVi3awAAAnIcAiIAWGhpasBiE1cAAABgEQAS8/Dbw/Pnz9euvv9pcDQAA9iMAIuC1bdtWderUUXZ2tpYvX253OQAA2I4AiIBHGxgAgN8iACIonN8GPnXqlM3VAABgLwIggsJ1112nevXq6fjx41q2bJnd5QAAYCsCIIICbWAAAAoRABE08tvACxYsoA0MAAhqBEAEjTZt2qh+/fo6ceKEli5danc5AADYhgCIoBESElIwC0gbGAAQzAiACCr59wEuXLhQJ0+etLkaAADsQQBEUElISNBll12mkydPasmSJXaXAwCALQiACCrnt4FTU1NtrgYAAHsQABF08gPgokWLdOLECZurAQDA+wiACDqtW7dWgwYNaAMDAIIWARBBh9XAAIBgRwBEUMoPgIsXL9bx48dtrgYAAO8iACIoxcfHq2HDhjp16pQWL15sdzkAAHgVARBBiTYwACCYEQARtPID4JIlS5STk2NzNQAAeA8BEEGrRYsWatSokX799VctWrTI7nIAAPAaAiCCFm1gAECwIgAiqOUHwKVLlyo7O9vmagAA8A4CIILaNddco6uuukqnT5/WwoUL7S4HAACvIAAiqNEGBgAEIwIggl5KSook6YMPPlBWVpbN1QAA4HkEQAS9Zs2aqXHjxjpz5owWLFhgdzkAAHgcARBB7/w2cGpqqs3VAADgeQRAQIWrgZctW6Zjx47ZWwwAAB5GAAQkXX311WratCltYABAUCAAAv/DamAAQLAgAAL/k78aePny5frll19srgYAAM8hAAL/07RpUzVr1kxnz57V/Pnz7S4HAACPIQAC56ENDAAIBgRA4Dz5beAVK1YoMzPT5moAAPAMAiBwnsaNG6t58+bKzc3VvHnz7C4HAACPIAACv0MbGAAQ6AiAwO/kt4FXrlypo0eP2lwNAADWIwACv3PllVeqZcuWOnfunNLS0uwuBwAAyxEAgSLQBgYABDICIFCE/DbwqlWrdOTIEZurAQDAWgRAoAhXXHGF4uPjaQMDAAISARC4gPw2cGpqqs2VAABgLQIgcAG0gQEAgYoACFxAw4YN1bp1a+Xl5Wnu3Ll2lwMAgGUIgMBFsBoYABCICIDAReS3gdesWaPDhw/bXA0AANYgAAIX0aBBAyUkJNAGBgAEFAIgcAm0gQEAgYYACFxCfhv4o48+0qFDh2yuBgCA0iMAApdw2WWX6brrrpPL5dKcOXPsLgcAgFIjAAJuoA0MAAgkBEDADQMGDJAkffLJJzp48KDN1QAAUDoEQMAN9evXV9u2bWkDAwACAgEQcBNtYABAoCAAAm7KbwOvXbtWBw4csLkaAABKjgAIuKlu3bpq166dJGn27Nk2VwMAQMkRAIFiyG8Dp6am2lwJAAAlRwAEiiG/DZyenq79+/fbXA0AACVDAASKoU6dOurQoYMk2sAAAP9FAASKidXAAAB/RwAEiql///4KCQnRZ599poyMDLvLAQCg2AiAQDHVrl1bHTt2lEQbGADgnwiAQAnQBgYA+DMCIFAC+W3gdevWad++fXaXAwBAsRAAgRKoWbOmbrzxRkm0gQEA/ocACJQQbWAAgL8iAAIl1K9fP4WGhmrDhg367rvv7C4HAAC3EQCBEqpRo4Y6deokiUfDAQD8CwEQKAXawAAAf0QABEqhb9++Cg0N1RdffKE9e/bYXQ4AAG4hAAKlUL16dXXu3FkSbWAAgP8gAAKllN8GJgACAPwFARAopb59+yosLEybNm3S7t277S4HAIBLIgACpRQbG6suXbpIYhYQAOAfCICABVgNDADwJwRAwAL5beAtW7Zo586ddpcDAMBFEQABC1StWlVdu3aVRBsYAOD7CICARWgDAwD8BQEQsEifPn0UHh6urVu3avv27XaXAwDABREAAYtUqVJFiYmJkmgDAwB8GwEQsBBtYACAPyAAAhbq3bu3ypQpo23btumbb76xuxwAAIpEAAQsVLlyZXXr1k0SbWAAgO8iAAIWow0MAPB1BEDAYr169VKZMmX0zTff6Ouvv7a7HAAA/oAACFisUqVKuvnmmyUxCwgA8E0EQMAD8tvAqampcrlcNlcDAMBvEQABD+jVq5ciIiL07bff0gYGAPgcAiDgARUrVtQtt9wiiTYwAMD3EAABDzl/NTBtYACALyEAAh7Ss2dPlS1bVjt27NBXX31ldzkAABQgAAIeEhMTo+7du0uiDQwA8C0EQMCDaAMDAHwRARDwoB49eigyMlK7du3Sl19+aXc5AABIIgACHlWhQgUlJSVJog0MAPAdBEDAw2gDAwB8DQEQ8LDk5GRFRUVpz5492rx5s93lAABAAAQ8rXz58kpOTpZEGxgA4BsIgIAX0AYGAPgSAiDgBUlJSYqKitJ3332nL774wu5yAABBjgAIeEG5cuXUo0cPSbSBAQD2IwACXpLfBk5NTaUNDACwFQEQ8JKkpCRFR0dr37592rhxo93lAACCGAEQ8JLo6Gj17NlTEm1gAIC9CICAF7EaGADgCwiAgBd1795d5cqVU0ZGhtavX293OQCAIEUABLwoKipKvXr1kkQbGABgHwIg4GXnrwbOy8uzuRoAQDAiAAJedsstt6h8+fL64YcftG7dOrvLAQAEIQIg4GWRkZHq3bu3JNrAAAB7EAABG9AGBgDYiQAI2KBbt26KiYnRgQMH9Nlnn9ldDgAgyBAAARvQBgYA2IkACNiENjAAwC4EQMAm3bp1U8eOHVWzZk1t2bLF7nIAAEEk3O4CgGAVERGhjz/+2O4yAABBiBlAAACAIEMABAAACDIEQAAAgCBDAAQAAAgyBEAAAIAgQwAEvKxTJ2nsWPM6Lk6aPNm+WgAAwYkACNhowwZp5EjrxuvVS6pfX4qMlGrVkm6/XTp40LrxAQCBgQAI2Cg2VoqOtm68zp2lWbOkHTukOXOkPXukAQOsGx8AEBgIgICNft8C3r5d6tDBzOA1bSqtXCmFhEjz5rk33oMPStdfL112mdSunfTYY9Lnn0tnz3qgeACA3+JJIICPyMuT+vQxLdx166ScHOnhh0s+Xmam5HSaIFimjGVlAgACADOAgI9Yvty0bKdOlVq0MDOBEycWf5xHH5XKlZOqVpUyMqT5862vFQDg3wiAgI/YsUOqV0+qWbPwvTZtij/OX/4ibd5sAmVYmDR0qORyWVcnAMD/0QIGfITLZe73K61q1cxx5ZVSkyYmVH7+udS2benHBgAEBmYAAR/RuLFp2R4+XPjehg2lGzN/5u/06dKNAwAILMwAAj4iMVFq2FAaNkx65hmzCGTcOHPOnZnB9evN0aGDVLmytHev9MQTZkxm/wAA52MGEPARYWFmu5fjx6WEBGnECGn8eHMuMvLS34+KkubOlW66SbrqKunOO6VmzaSPPpLKlvVo6QAAPxPicl369vDs7GxVrFhRWVlZiomJ8UZdACSlp5sZvd27zUweAAAXUpy8RgsY8CFpaVL58lKjRib0jRkjtW9P+AMAWIsWMOBDcnKkUaPMgpDhw00rOH8fv0mTTDgs6uje3dayAQB+hhYw4CcyM81RlKgoqU4d79YDAPAttICBAFSlijkAACgtWsAAAABBhgAIAAAQZAiAAAAAQYYACAAAEGQIgIAPe+utt9SqVSu1atVKn332md3lAAACBAEQ8GEJCQnavHmzNm/erClTpthdDgAgQBAAAR92zTXXqFq1apKkOXPm6OzZszZXBAAIBARAwIeFhISoV69ekqScnBytXr3a5ooAAIGAAAj4uB49ehS8Tk1NtbESAECgIAACPu6mm25SWFiYJGn27Nm0gQEApUYABHxcTEyMOnbsKEk6duwYbWAAQKkRAAE/kJycXPCaNjAAoLTC7S4AwKX17dtX06dPlyTt2rVLZ8+eVZkyZWyuCgDgrwiAgB9o2LChNm3aZHcZAIAAQQsYAAAgyBAAAQAAggwBEAAAIMgQAAEAAIIMARDwUZ06SWPHmtdxcdLkyfbVAgAILARAwA9s2CCNHGnNWPv2SXfdJTVoIEVFSQ0bSk8+KZ05Y834AADfxzYwgB+IjbVurO3bpbw86Y03pCuukLZtk+6+WzpxQnruOeuuAwDwXcwAAn7g9y3g7dulDh2kyEipaVNp5UopJESaN+/SY91yi/T221K3btLll0u9ekl//rM0d66HigcA+BxmAAE/k5cn9ekj1a8vrVsn5eRIDz9cujGzsqQqVSwpDwDgBwiAgJ9Zvlzas0das0aqWdO8N3GilJhYsvH27JFeekl6/nnLSgQA+DhawICf2bFDqlevMPxJUps2JRvr4EHTEk5JkUaMsKY+AIDvIwACfsblMvf7ldbBg1LnzlLbttKUKaUfDwDgPwiAgJ9p3FjKyJAOHy58b8OG4o1x4IDZZ7BVK7MgJJS/CQAgqPDXPuBnEhPN3n3Dhklbt0rp6dK4ceacOzODBw+a8Fevntn25cgR6dAhcwAAggOLQAA/ExZmtnsZMUJKSDBbuTz7rNSzp9kW5lKWL5d27zZH3bq/PedyeaRkAICPCXG5Lv1XfnZ2tipWrKisrCzFxMR4oy4AxZCebvYF3L3bzA4CAIJPcfIaM4CAH0pLk8qXlxo1MqFvzBipfXvCHwDAPdwDCPihnBxp1CizIGT4cNMKnj/fnJs0yYTDoo7u3W0tGwDgI2gBAwEmM9McRYmKkurU8W49AADvoAUMBLEqVXisGwDg4mgBAwAABBkCIAAAQJAhAAIAAAQZAiAAAECQIQACAAAEGQIgEEDWr1+vVq1aqXPnzjp79qzd5QAAfBQBEAggrVq10v79+7VmzRqtXr3a7nIAAD6KAAgEkPDwcPXv31+SNGvWLJurAQD4KgIgEGBSUlIkSWlpabSBAQBFIgACAeaGG25QbGysMjMzaQMDAIpEAAQCDG1gAHBfp07S2LHmdVycNHmyfbV4EwEQCEC0gQGg+DZskEaOtG68iROldu2k6GipUqULf+6dd6TmzaXISKlmTen++62r4UIIgEAAog0MAMUXG2vCmlXOnJFSUqT77rvwZ154QRo3TnrsMenrr6UPP5Ruvtm6Gi6EAAgEINrAAFB8v28Bb98udehgZuaaNpVWrpRCQqR589wbb8IE6cEHpWuuKfr8L79I48dLU6dKgwdLDRtKV18t9exZyl/EDQRAIEDRBgaAksvLk/r0MTOC69ZJU6aYmTorrVhhrnPggNSkiVS3rjRwoPTDD9ZepygEQCBA0QYGgJJbvlzas8fMzrVoYWYCJ0609hp795oAOGmSmXmcPVvKzJQSE0372JMIgECAog0MACW3Y4dUr55ZlJGvTRtrr5GXJ509K734ornv7/rrpRkzpF27JE//dzsBEAhgtIEBoGRcLnO/nyfVqmV+Nm1a+F5srFStmpSR4dlrEwCBAEYbGABKpnFjE8IOHy58b8MGa6/Rvr35uWNH4XuZmdLPP0uXXWbttX6PAAgEMNrAAFAyiYlmVe6wYdLWrVJ6euEiEHdnBjMypC1bzM9z58zrLVuk48fN+SuvlHr3lsaMkT79VNq2zVyvcWOpc2cP/FLnIQACAY42MAAUX1iY2e7l+HEpIUEaMcJs2SKZbWHc8cQTUny89OSTZpz4eHNs3Fj4malTpeuuk5KTpRtvlMqUkT74wPz0pBCXy+W61Ieys7NVsWJFZWVlKSYmxrMVAbBUbm6u6tSpo59++kkffPCBbvbGDqMAEIDS081q4N27zeygrylOXmMGEAhw4eHh6tevnyQpNTXV5moAwH+kpZm9+vbtM5tAjxxp7tvzxfBXXARAIAjQBgYQjH788Uc5nc4Sfz8nRxo1ytyTN3y4aQXPn2/OTZoklS9f9NG9uzX1exItYCAI0AYGECyys7M1d+5cOZ1OrVq1Si1atNCmTZssv05mpjmKEhUl1alj+SUvqTh5LdxLNQGwUX4b+PXXX1dqaioBEEBAOXPmjJYuXSqn06mFCxfq119/LTjXokULj1yzShVz+CtmAIEgsWrVKt10002qUqWKDh06pDKeXmIGAB6Ul5en9PR0OZ1OpaamKvO86bjGjRtryJAhGjx4sBo0aGBjld7FDCCAP7jhhhtUvXp1/fTTT1q1ahWzgAD80rZt2+R0OjV9+nRlnPe4jFq1amnQoEFyOByKj49XiKcf4+HnCIBAkKANDMBf7d+/XzNmzNC0adO0devWgvcrVKigAQMGyOFwqFOnTgoLC7OxSv9CCxgIIrSBAfiLY8eOafbs2XI6nfroo4+UH1fKlCmjpKQkORwO9ejRQ1FRUTZX6jtoAQMoEm1gAL7s119/1ZIlSzRt2jQtXrxYZ86cKTh3ww03yOFwaMCAAariz6svfAQBEAgitIEB+Jq8vDx99NFHcjqdmj17trKysgrONWvWTA6HQ4MGDdJll11mY5WBhxYwEGRoAwOwm8vl0pdffimn06kZM2bowIEDBefq1q2rwYMHy+FwqHnz5jZW6X9oAQO4INrAAOzy/fffa/r06XI6nfr6668L3q9UqZJSUlLkcDjUsWNHhYbyoDJPIwACQYY2MABvOnr0qFJTU+V0OrV27dqC98uWLasePXrI4XAoKSlJZcuWtbHK4EMLGAhCtIEBeNKpU6e0cOFCTZs2TR988EHBM8hDQkLUuXNnORwO9evXT5UqVbK30ABDCxjARdEGBmC1c+fOadWqVXI6nZo7d65ycnIKzrVs2bJgMUcdOx6Siz8gAAJBiDYwACu4XC5t2rRJ06ZN08yZM3Xo0KGCc3FxcQWLOZo2bWpjlSgKLWAgSNEGBlBSe/bsKVjMsWPHjoL3q1SpooEDB2rIkCFq164dj2PzMlrAAC6JNjCA4jhy5Ijef/99OZ1Off755wXvR0ZGqnfv3nI4HLr55psVERFhY5VwFwEQCFK0gQFcyokTJzR//nw5nU4tW7ZM586dkySFhoaqa9eucjgc6tu3rypUqGBzpSguWsBAEFu9erW6dOlCGxhAgdzcXK1YsUJOp1Pz5s3TiRMnCs5de+21cjgcuu2221SzZk0bq0RRaAEDcAttYACSWcyxfv16TZs2Te+//76OHDlScK5hw4ZyOBwaPHiwrrrqKhurhJUIgEAQCwsLow0MBLGdO3fK6XTK6XRqz549Be/Hxsbq1ltv1ZAhQ9SmTRsWcwQgWsBAkKMNDASXQ4cOaebMmXI6ndq4cWPB+9HR0erbt68cDoe6du3K3wV+iBYwALfRBgYCX05OjtLS0uR0OrVy5Url5eVJMl2Abt26aciQIerdu7fKlStnc6XwFgIgEORoAwOB6cyZM1q2bJmcTqcWLFigU6dOFZy7/vrr5XA4NHDgQFWvXt3GKmEXWsAAaAMDAcLlcunTTz+V0+nUrFmzdPTo0YJzV111VcFijoYNG9pYJTyFFjCAYqENDPi3b775Rk6nU9OnT9e+ffsK3q9Zs6Zuu+02ORwOtW7dmsUcKEAABEAbGPBDBw4c0IwZM+R0OrVly5aC9ytUqKB+/frJ4XCoS5cuCgsLs69I+CxawAAk0QYG/EFWVpbmzJkjp9Op1atXK/9f4eHh4erevbuGDBminj17KioqyuZKYQdawACKjTYw4JtOnz6tJUuWyOl0atGiRTp9+nTBuQ4dOsjhcCglJUVVq1a1sUr4GwIgAEm0gQFfkpeXp08++UROp1Opqak6duxYwbmmTZtqyJAhGjRokOLi4myrEf6NFjCAArSBAXtt3bpVTqdTM2bM0A8//FDwfp06dTRo0CA5HA61aNGCxRwoEi1gACVCGxjwvoyMDM2YMUPTpk3Ttm3bCt6vWLGiBgwYIIfDoRtuuIHFHLAUARBAAdrAgHdkZmZq9uzZcjqd+vjjjwvej4iIUHJyshwOh5KTkxUZGWljlQhktIAB/AZtYMAzTp06pUWLFsnpdGrJkiU6e/asJCkkJEQ33nijHA6H+vfvr8qVK9tcKfwVLWAAJUYbGLDOuXPntGbNGjmdTs2ZM0fZ2dkF55o3b64hQ4botttuU7169WysEsGIAAjgN2gDA6Xjcrm0efNmOZ1OzZw5UwcPHiw4V79+fQ0ePFgOh0PNmjWzsUoEO1rAAP6ANjBQfN99952mT5+uadOmafv27QXvV65cWQMHDpTD4VD79u0VGhpqY5UIZLSAAZQKbWDAPT///LNmzZolp9OpTz/9tOD9yMhI9ezZUw6HQ927d1dERISNVQJ/RAAE8AdhYWHq37+/XnvtNc2aNYsACJzn5MmTmj9/vpxOp5YtW6bc3FxJUmhoqLp06SKHw6F+/frRMYNPowUMoEi0gYFCubm5+vDDD+V0OpWWlqbjx48XnGvVqpUcDoduu+021a5d28YqEexoAQMoNdrACHYul0sbNmyQ0+nU+++/r8OHDxeca9CggRwOhxwOhxo3bmxjlUDJEAABFIk2MILV7t275XQ65XQ6tWvXroL3q1WrpltvvVUOh0PXX389j2ODX6MFDOCCaAMj2AwdOlTvvfdewZ+joqLUp08fORwOdevWjX8G4NNoAQOwBG1gBJtt27YpLCxMiYmJcjgc6tOnj8qXL293WYDl2IwIwAXlt4EladasWTZXA3jeX/7yFx04cEBLly7VkCFDCH8IWARAABeVkpIiSZo3b17Bs0uBQDVo0CDVqFHD7jIAjyMAArio/DZwZmamVq1aZXc5CBCdOkljx5rXcXHS5Mn21QIEIwIggIuiDQxP27BBGjnS+nFPn5ZatpRCQqQtW6wfH/BnBEAAl0QbGJ4UGytFR1s/7iOPSOzLDBSNAAjgkmgDw5N+3wLevl3q0EGKjJSaNpVWrjSzePPmuT/m0qXS8uXSc89ZXCwQIAiAAC6JNjC8JS9P6tPHzAiuWydNmSKNG1e8MQ4flu6+W3rvPc/MLAKBgAAIwC20geENy5dLe/ZIU6dKLVqYmcCJE93/vsslDR8u3XuvdO21HisT8HsEQABuoQ0Mb9ixQ6pXT6pZs/C9Nm3c//5LL0nZ2dLjj1tfGxBICIAA3EIbGN7gcpn7/Upq1Srp88+lsmWl8HDpiivM+9deKw0bZk2NQCAgAAJwG21geFrjxlJGhrmPL9+GDe5//8UXpS+/NNu+bNkiLVli3n///eK1koFAx7OAAbiNZwPD0xITpYYNzWzdM89IOTmFi0DcmRmsX/+3f85/klvDhlLdutbWCvgzZgABuI02MDwtLMxs93L8uJSQII0YIY0fb85FRtpaGhBQQlwul+tSH8rOzlbFihWVlZWlmJgYb9QFwEetXr1aXbp0UZUqVXTo0CGVKVPG7pIQ4NLTzWrg3bvNTB6AohUnrzEDCKBYWA0MT0tLk1askPbtM5tAjxwptW9P+AOsRAAEUCy0geFpOTnSqFFmQcjw4aYVPH++OTdpkrmvr6ije3dbywb8Ci1gAMWW3wauXLmyDh8+TBsYXpOZaY6iREVJdep4tx7AlxQnr7EKGECxnb8a+MMPP9Qtt9xid0kIElWqmANA6dACBlBs57eBU1NTba4GAFBcBEAAJZK/KXRaWhqbQgOAnyEAAiiR/DbwL7/8og8//NDucgAAxUAABFAitIEBwH8RAAGUGG1guOu1115Tq1at1KZNG33++ed2lwMEPQIggBKjDQx3vP322xo1apQ2b96se+65R9dff73dJQFBjwAIoMRoA+NSVq5cqZEjR0qSxo0bp7vuusvmigBIBEAApUQbGBfy1VdfqX///srNzdXgwYP19NNP210SgP8hAAIoFdrAKMrBgweVnJys7Oxs3Xjjjfrvf/+rkJAQu8sC8D8EQAClQhsYv5eTk6Pk5GT98MMPaty4sdLS0lS2bFm7ywJwHgIggFKjDYx8ubm5uu2227RlyxZVr15dS5YsUeXKle0uC8DvEAABlBptYEiSy+XSn/70Jy1ZskRRUVFauHChGjRoYHdZAIpAAARQarSBIUnPPfecXn/9dYWEhGj69Olq06aN3SUBuAACIABL0AYObqmpqXrkkUckSf/617/Up08fewsCcFEEQACWoA0cvNLT03X77bdLkh544AGNGTPG5ooAXAoBEIAlaAMHp127dql37946ffq0evfurRdeeMHukgC4gQAIwDK0gYPLzz//rKSkJB09elQJCQlyOp0KCwuzuywAbiAAArAMbeDgcerUKfXu3Vu7d+9WXFycFi5cqHLlytldFgA3EQABWIY2cHDIy8vTsGHD9Omnn6pSpUpasmSJatSoYXdZAIqBAAjAUgMHDpREGziQPfbYY0pNTVWZMmU0b948NWnSxO6SABQTARCApTp27KgaNWrQBg5Qr732mp599llJ0ttvv60bb7zR5ooAlAQBEIClwsLC1K9fP0m0gQPNkiVLdP/990uSnn76aTkcDpsrAlBSBEAAlqMNHHg2bdqkgQMHKi8vT3feeafGjRtnd0kASoEACMBytIEDS0ZGhnr06KETJ06oa9euBY97A+C/CIAALEcbOHBkZWUpOTlZP/74o5o1a6bZs2erTJkydpcFoJQIgAA8gjaw/zt79qwGDBigbdu2qVatWlqyZIkqVqxod1kALEAABOARtIH9m8vl0j333KOVK1eqXLlyWrx4serVq2d3WQAsQgAE4BG0gf3b3//+d7399tsKDQ3VrFmzFB8fb3dJACxEAATgMbSB/dO0adP0xBNPSJJeeeUVJSUl2VwRAKsRAAF4DG1g/7NmzRrdeeedkqRHHnlE9957r80VAfAEAiAAj6EN7F++/fZb9e3bV2fPntXAgQP1j3/8w+6SAHgIARCAR9EG9g+HDh1S9+7ddezYMbVr107vvvuuQkP5VwQQqPinG4BH0Qb2fSdOnFDPnj31/fff64orrtD8+fMVGRlpd1kAPIgACMCjaAP7tnPnzmnw4MHauHGjqlatqqVLl6patWp2lwXAwwiAADyONrDveuihh7RgwQKVLVtWCxYs0BVXXGF3SQC8gAAIwONoA/umf//733rxxRclSe+9957atWtnc0UAvIUACMDjaAP7nrS0ND344IOSpGeeeUYpKSk2VwTAmwiAALyCNrDvWLdunRwOh1wul+677z79+c9/trskAF5GAATgFbSBfcPevXvVs2dPnTp1SsnJyXrxxRcVEhJid1kAvIwACMArwsLC1L9/f0nSrFmzbK4mOGVmZiopKUlHjhxRfHy8Zs6cqfDwcLvLAmADAiAAr8m/z2zevHm0gb3s9OnT6tu3r3bs2KF69epp0aJFKl++vN1lAbAJARCA19AGtkdeXp7uvPNOffzxx4qJidGSJUtUu3Ztu8sCYCMCIACvoQ1sjyeeeELTp09XeHi45syZo2bNmtldEgCbEQABeBVtYO966623NHHiREnSlClT1LVrV5srAuALCIAAvIo2sPcsX75c99xzjyTpr3/9q+644w6bKwLgKwiAALyKNrB3bN26VQMGDNC5c+d0++23a8KECXaXBMCHEAABeB1tYM86cOCAkpOTlZOTo06dOunNN99krz8Av0EABOB1tIE9JycnR8nJydq/f7+aNGmiuXPnKiIiwu6yAPgYAiAAr6MN7Bm5ubkaOHCgvvzyS1WvXl1LlixR5cqV7S4LgA8iAAKwBW1ga7lcLo0ePVoffPCBoqOjtWjRIsXFxdldFgAfRQAEYAvawNZ65plnNGXKFIWEhGjGjBlKSEiwuyQAPowACMAWtIGt8/777+uxxx6TJP373/9Wr169bK4IgK8jAAKwDW3g0lu7dq2GDh0qSRo7dqz+9Kc/2VwRAH9AAARgG9rApbNz50717t1bZ86cUd++ffXcc8/ZXRIAP0EABGAb2sAld+TIESUlJSkzM1Nt2rTRtGnTFBYWZndZAPwEARCArWgDF9+pU6fUq1cv7dmzRw0aNNDChQsVHR1td1kA/AgBEICtaAMXT15enm6//XZ9/vnnqly5spYsWaLq1avbXRYAP0MABGAr2sDF88gjj2jOnDmKiIjQvHnz1LhxY7tLAuCHCIAAbHd+G/jMmTM2V+O7XnnlFT3//POSpLfffls33HCDzRUB8FcEQAC2ow18aYsWLdIDDzwgSZo4caIGDx5sc0UA/BkBEIDtzm8Dp6am2lyN7/niiy906623Ki8vTyNGjNDjjz9ud0kA/BwBEIBPoA1ctO+//149evTQyZMn1a1bN7366qsKCQmxuywAfo4ACMAn0Ab+o2PHjik5OVmHDh3SNddco9TUVJUpU8busgAEAAIgAJ9AG/i3zpw5o/79++vrr79W7dq1tWTJEsXExNhdFoAAQQAE4DNoAxsul0sjR47UqlWrVL58eS1evFh169a1uywAAYQACMBn0AY2nn76ab377rsKCwvTrFmz1LJlS7tLAhBgCIAAfAZtYGnq1Kl68sknJUmvvvqqunfvbnNFAAIRARCATwnmNvCqVat01113SZIee+wxjRw50uaKAAQqAiAAnxKsbeCvv/5a/fr1U25urm677TZNnDjR7pIABDACIACfEoxt4EOHDikpKUlZWVnq0KGD3n77bYWG8tczAM/hbxgAPieY2sAnTpxQjx49lJGRoUaNGmnevHmKjIy0uywAAY4ACMDnBEsb+Ny5cxo0aJC++OILVatWTUuXLlXVqlXtLgtAECAAAvA5wdAGdrlcGjNmjBYuXKjIyEgtWLBADRs2tLssAEGCAAjAJwV6G3jy5Ml65ZVXFBISomnTpqlt27Z2lwQgiBAAAfikQG4Dz5kzRw8//LAk6dlnny2Y7QQAbyEAAvBJgdoG/vzzzzVkyBC5XC6NHj1aDz30kN0lAQhCBEAAPivQ2sB79uxRz5499euvv6pHjx6aPHmyQkJC7C4LQBAiAALwWYHUBj569KiSkpL0888/q1WrVpoxY4bCw8PtLgtAkCIAAvBZgdIG/vXXX9WnTx/t3LlT9evX16JFi1S+fHm7ywIQxAiAAHyav7eB8/LydMcdd2jt2rWqWLGilixZolq1atldFoAgRwAE4NP8vQ08fvx4zZw5U+Hh4Zo7d66uvvpqu0sCAAIgAN/mz23g//znP/rHP/4hSXrzzTfVpUsXmysCAIMACMDnDRw4UJKUlpbmN23gDz74QPfdd58k6cknn9SwYcNsrggAChEAAfi8Dh06qEaNGjp27JhftIG//PJLpaSk6Ny5cxo6dKiefPJJu0sCgN8gAALwef7UBt6/f7+Sk5N1/Phxde7cWf/5z3/Y6w+AzyEAAvAL/tAGzs7OVnJysg4cOKCmTZtq7ty5ioiIsLssAPgDAiAAv+DrbeCzZ89q4MCB2rp1q2rWrKklS5aoUqVKdpcFAEUiAALwC77cBna5XBo1apSWLVum6OhoLVy4UJdddpndZQHABREAAfgNX20D//Of/9Sbb76p0NBQzZw5U9dee63dJQHARREAAfgNX2wDz5gxQ//3f/8nSXrxxRfVs2dPmysCgEsjAALwG77WBv744481fPhwSdJDDz2k0aNH21sQALiJAAjAr/hKG3jHjh3q06ePzpw5o/79++vZZ5+1rRYAKC4CIAC/4gtt4J9++klJSUn65ZdfdP311+u9995TaCh/nQLwH/yNBcCv2N0GPnnypHr16qW9e/fq8ssv1/z58xUVFeX1OgCgNAiAAPyOXW3gc+fOaciQIVq3bp2qVKmipUuXqnr16l67PgBYhQAIwO/Y1QZ+5JFHlJaWpoiICM2bN09XXnml164NAFYiAALwO3a0gV9++WW98MILkqR3331XHTt29Mp1AcATCIAA/JI328ALFizQmDFjJEn/+Mc/dNttt3n0egDgaQRAAH7JW23gjRs3atCgQcrLy9Pdd9+tRx991GPXAgBvIQAC8EveaAPv27dPPXr00MmTJ3XLLbfo1VdfVUhIiEeuBQDeRAAE4Lc82QY+duyYkpKSdPjwYbVo0UKzZs1SeHi4pdcAALsQAAH4LU+1gc+cOaN+/frp22+/VZ06dbRo0SJVqFDBsvEBwG4EQAB+KywsTAMGDJAkzZo1y5IxXS6XRowYodWrV6tChQpasmSJ6tata8nYAOArCIAA/FpKSookad68eZa0gSdMmKD33ntPYWFhSk1NVfPmzUs9JgD4GgIgAL9mZRv4nXfe0YQJEyRJr7/+um6++WYrSgQAn0MABODXwsLCNHbsWMXHx2vdunUlHmf9+vV69dVXFR8fr5dfflkjRoywsEoA8C0hLpfLdakPZWdnq2LFisrKylJMTIw36gIAAEAxFCevMQMIAAAQZAiAAAAAQYYACAAAEGQIgAAAAEGGAAgAABBkCIAA/FanTtLYseZ1XJw0ebJ9tQCAPyEAAggIGzZII0daM9aaNVJISNHHhg3WXAMA7BRudwEAYIXYWOvGatdO+vHH3773179KK1dK115r3XUAwC7MAAIICL9vAW/fLnXoIEVGSk2bmvAWEiLNm3fpsSIipJo1C4+qVaUFC6Q77zRjAIC/YwYQQMDJy5P69JHq15fWrZNycqSHHy75eAsWSD//LA0fblWFAGAvAiCAgLN8ubRnj7mXr2ZN897EiVJiYsnGe+st6eabpXr1LCsRAGxFAAQQcHbsMGEtP/xJUps2JRtr/35p2TJp1ixragMAX8A9gAACjstl3b16b79t7gHs1cua8QDAFxAAAQScxo2ljAzp8OHC90qyfYvLZQLg0KFSmTLW1QcAdiMAAgg4iYlSw4bSsGHS1q1Sero0bpw5V5yZwVWrpO++k+66yzN1AoBdCIAAAk5YmNnu5fhxKSFBGjFCGj/enIuMdH+ct94yewI2aeKRMgHANiEul8t1qQ9lZ2erYsWKysrKUkxMjDfqAgBLpaebfQF37zazgwAQaIqT11gFDCAgpaVJ5ctLjRqZ0DdmjNS+PeEPACRawAACVE6ONGqUWRAyfLhpBc+fb85NmmTCYVFH9+62lg0AXkELGEDQycw0R1GioqQ6dbxbDwBYgRYwAFxElSrmAIBgRQsYAAAgyBAAAQAAggwBEAAAIMgQAAEAAIIMARAAACDIEAABAACCDAEQAAAgyBAAAQAAggwBEAAAIMgQAAEAAIIMARAAACDIEAABAACCDAEQAAAgyBAAAQAAggwBEAAAIMgQAAEAAIIMARAAACDIEAABAACCDAEQAAAgyBAAAQAAggwBEAAAIMgQAAEAAIIMARAAACDIhLvzIZfLJUnKzs72aDEAAAAomfyclp/bLsatAJiTkyNJqlevXinKAgAAgKfl5OSoYsWKF/1MiMuNmJiXl6eDBw+qQoUKCgkJsaxAAAAAWMPlciknJ0e1a9dWaOjF7/JzKwACAAAgcLAIBAAAIMgQAAEAAIIMARAAACDIEAABAACCDAEQAAAgyBAAAQAAggwBEAAAIMj8fwkNHlHEaIrVAAAAAElFTkSuQmCC",
+ "image/png": "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",
"text/plain": [
""
]
@@ -148,7 +148,7 @@
"outputs": [
{
"data": {
- "image/png": "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",
+ "image/png": "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",
"text/plain": [
""
]
@@ -174,7 +174,9 @@
"\n",
"That information in included in a `Transformation`. Each of these transformations corresponds to a single leg of the simulation campaign, so for each edge in the `LigandNetwork`, we will create two `Transformation`s: one for vacuum and one for solvent.\n",
"\n",
- "In practice, this will be done for each edge of the `LigandNetwork` in a loop, but for illustrative purposes we'll dive into the details of creating a single transformation. In particular, we'll create the solvent leg for the pair of molecules we selecting for the mapping above."
+ "In practice, this will be done for each edge of the `LigandNetwork` in a loop, but for illustrative purposes we'll dive into the details of creating a single transformation. In particular, we'll create the solvent leg for the pair of molecules we selecting for the mapping above.\n",
+ "\n",
+ "TODO: SWITCH TO PROTEIN COMPLEX LEG"
]
},
{
@@ -203,17 +205,29 @@
{
"cell_type": "code",
"execution_count": 8,
+ "id": "3f1706ee",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "protein = openfe.ProteinComponent.from_pdb_file(\"./tyk2_protein.pdb\")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 9,
"id": "710285ca",
"metadata": {},
"outputs": [],
"source": [
"systemA = openfe.ChemicalSystem({\n",
" 'ligand': mapping.componentA,\n",
- " 'solvent': solvent\n",
+ " 'solvent': solvent,\n",
+ " 'protein': protein\n",
"})\n",
"systemB = openfe.ChemicalSystem({\n",
" 'ligand': mapping.componentB,\n",
- " 'solvent': solvent\n",
+ " 'solvent': solvent,\n",
+ " 'protein': protein \n",
"})"
]
},
@@ -229,14 +243,14 @@
},
{
"cell_type": "code",
- "execution_count": 9,
+ "execution_count": 10,
"id": "3f394a0d",
"metadata": {
"scrolled": true
},
"outputs": [],
"source": [
- "from openfe.protocols.openmm_rfe import RelativeHybridTopologyProtocol\n"
+ "from openfe.protocols.openmm_rfe import RelativeHybridTopologyProtocol"
]
},
{
@@ -249,7 +263,7 @@
},
{
"cell_type": "code",
- "execution_count": 10,
+ "execution_count": 11,
"id": "fb839094",
"metadata": {},
"outputs": [
@@ -265,7 +279,7 @@
"298.15 "
]
},
- "execution_count": 10,
+ "execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
@@ -277,7 +291,7 @@
},
{
"cell_type": "code",
- "execution_count": 11,
+ "execution_count": 12,
"id": "e83630f0",
"metadata": {},
"outputs": [],
@@ -298,7 +312,7 @@
},
{
"cell_type": "code",
- "execution_count": 12,
+ "execution_count": 13,
"id": "7adf42d6",
"metadata": {},
"outputs": [],
@@ -319,7 +333,7 @@
},
{
"cell_type": "code",
- "execution_count": 13,
+ "execution_count": 14,
"id": "44ba94ca",
"metadata": {},
"outputs": [],
@@ -355,20 +369,23 @@
},
{
"cell_type": "code",
- "execution_count": 14,
+ "execution_count": 15,
"id": "66666a80",
"metadata": {},
"outputs": [],
"source": [
"transformations = []\n",
"for mapping in ligand_network.edges:\n",
- " for leg in ['solvent', 'vacuum']:\n",
- " sysA_dict = {'ligand': mapping.componentA}\n",
- " sysB_dict = {'ligand': mapping.componentB}\n",
- " if leg == 'solvent':\n",
- " # use the solvent created above\n",
- " sysA_dict['solvent'] = solvent\n",
- " sysB_dict['solvent'] = solvent\n",
+ " for leg in ['solvent', 'complex']:\n",
+ " # use the solvent and protein created above\n",
+ " sysA_dict = {'ligand': mapping.componentA,\n",
+ " 'solvent': solvent}\n",
+ " sysB_dict = {'ligand': mapping.componentB,\n",
+ " 'solvent': solvent}\n",
+ " \n",
+ " if leg == 'complex':\n",
+ " sysA_dict['protein'] = protein\n",
+ " sysB_dict['protein'] = protein\n",
" \n",
" # we don't have to name objects, but it can make things (like filenames) more convenient\n",
" sysA = openfe.ChemicalSystem(sysA_dict, name=f\"{mapping.componentA.name}_{leg}\")\n",
@@ -398,7 +415,7 @@
},
{
"cell_type": "code",
- "execution_count": 15,
+ "execution_count": 16,
"id": "d6cebd9a",
"metadata": {},
"outputs": [],
@@ -415,7 +432,7 @@
},
{
"cell_type": "code",
- "execution_count": 16,
+ "execution_count": 17,
"id": "b96b57a9",
"metadata": {},
"outputs": [
@@ -423,30 +440,24 @@
"name": "stdout",
"output_type": "stream",
"text": [
- "lig_10_solvent_lig_15_solvent.json lig_3_vacuum_lig_7_vacuum.json\r\n",
- "lig_10_vacuum_lig_15_vacuum.json lig_3_vacuum_lig_9_vacuum.json\r\n",
- "lig_11_solvent_lig_14_solvent.json lig_4_solvent_lig_16_solvent.json\r\n",
- "lig_11_solvent_lig_16_solvent.json lig_4_solvent_lig_7_solvent.json\r\n",
- "lig_11_vacuum_lig_14_vacuum.json lig_4_vacuum_lig_16_vacuum.json\r\n",
- "lig_11_vacuum_lig_16_vacuum.json lig_4_vacuum_lig_7_vacuum.json\r\n",
- "lig_12_solvent_lig_15_solvent.json lig_5_solvent_lig_10_solvent.json\r\n",
- "lig_12_vacuum_lig_15_vacuum.json lig_5_solvent_lig_11_solvent.json\r\n",
- "lig_13_solvent_lig_14_solvent.json lig_5_vacuum_lig_10_vacuum.json\r\n",
- "lig_13_vacuum_lig_14_vacuum.json lig_5_vacuum_lig_11_vacuum.json\r\n",
- "lig_14_solvent_lig_15_solvent.json lig_6_solvent_lig_14_solvent.json\r\n",
- "lig_14_vacuum_lig_15_vacuum.json lig_6_solvent_lig_9_solvent.json\r\n",
- "lig_15_solvent_lig_16_solvent.json lig_6_vacuum_lig_14_vacuum.json\r\n",
- "lig_15_vacuum_lig_16_vacuum.json lig_6_vacuum_lig_9_vacuum.json\r\n",
- "lig_1_solvent_lig_14_solvent.json lig_7_solvent_lig_13_solvent.json\r\n",
- "lig_1_solvent_lig_9_solvent.json lig_7_vacuum_lig_13_vacuum.json\r\n",
- "lig_1_vacuum_lig_14_vacuum.json lig_8_solvent_lig_14_solvent.json\r\n",
- "lig_1_vacuum_lig_9_vacuum.json\t lig_8_solvent_lig_9_solvent.json\r\n",
- "lig_2_solvent_lig_3_solvent.json lig_8_vacuum_lig_14_vacuum.json\r\n",
- "lig_2_vacuum_lig_3_vacuum.json\t lig_8_vacuum_lig_9_vacuum.json\r\n",
- "lig_3_solvent_lig_13_solvent.json lig_9_solvent_lig_10_solvent.json\r\n",
- "lig_3_solvent_lig_7_solvent.json lig_9_solvent_lig_14_solvent.json\r\n",
- "lig_3_solvent_lig_9_solvent.json lig_9_vacuum_lig_10_vacuum.json\r\n",
- "lig_3_vacuum_lig_13_vacuum.json lig_9_vacuum_lig_14_vacuum.json\r\n"
+ "lig_ejm_31_complex_lig_ejm_42_complex.json\r\n",
+ "lig_ejm_31_complex_lig_ejm_46_complex.json\r\n",
+ "lig_ejm_31_complex_lig_ejm_47_complex.json\r\n",
+ "lig_ejm_31_complex_lig_ejm_48_complex.json\r\n",
+ "lig_ejm_31_complex_lig_ejm_50_complex.json\r\n",
+ "lig_ejm_31_solvent_lig_ejm_42_solvent.json\r\n",
+ "lig_ejm_31_solvent_lig_ejm_46_solvent.json\r\n",
+ "lig_ejm_31_solvent_lig_ejm_47_solvent.json\r\n",
+ "lig_ejm_31_solvent_lig_ejm_48_solvent.json\r\n",
+ "lig_ejm_31_solvent_lig_ejm_50_solvent.json\r\n",
+ "lig_ejm_42_complex_lig_ejm_43_complex.json\r\n",
+ "lig_ejm_42_solvent_lig_ejm_43_solvent.json\r\n",
+ "lig_ejm_46_complex_lig_jmc_23_complex.json\r\n",
+ "lig_ejm_46_complex_lig_jmc_27_complex.json\r\n",
+ "lig_ejm_46_complex_lig_jmc_28_complex.json\r\n",
+ "lig_ejm_46_solvent_lig_jmc_23_solvent.json\r\n",
+ "lig_ejm_46_solvent_lig_jmc_27_solvent.json\r\n",
+ "lig_ejm_46_solvent_lig_jmc_28_solvent.json\r\n"
]
}
],
@@ -479,7 +490,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
- "version": "3.10.10"
+ "version": "3.9.16"
}
},
"nbformat": 4,