diff --git a/03_steered_md/01_setup_sMD.ipynb b/03_steered_md/01_setup_sMD.ipynb index 7c85190..b9d4358 100644 --- a/03_steered_md/01_setup_sMD.ipynb +++ b/03_steered_md/01_setup_sMD.ipynb @@ -128,6 +128,7 @@ "outputs": [], "source": [ "from get_tutorial import download\n", + "\n", "download(\"01\")" ] }, @@ -200,22 +201,7 @@ "metadata": {}, "outputs": [], "source": [ - "reference = BSS.IO.readMolecules(\"data/reference.pdb\").getMolecule(0)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "9f45911c", - "metadata": {}, - "outputs": [], - "source": [ - "rmsd_indices = []\n", - "for residue in reference.getResidues():\n", - " if 178 <= residue.index() <= 184:\n", - " for atom in residue.getAtoms():\n", - " if atom.element() != \"Hydrogen (H, 1)\":\n", - " rmsd_indices.append(atom.index())" + "reference = BSS.IO.readMolecules(\"data/reference.pdb\")" ] }, { @@ -225,7 +211,13 @@ "metadata": {}, "outputs": [], "source": [ - "rmsd_cv = BSS.Metadynamics.CollectiveVariable.RMSD(system, reference, rmsd_indices)" + "rmsd_cv = BSS.Metadynamics.CollectiveVariable.RMSD(\n", + " system,\n", + " reference,\n", + " \"molidx 0 and (not residx 178:185) and (not element H)\",\n", + " \"residx 178:185 and not element H\",\n", + " reference_mapping={0: 0},\n", + ")" ] }, { @@ -336,9 +328,7 @@ "metadata": {}, "outputs": [], "source": [ - "process = BSS.Process.Gromacs(\n", - " system,\n", - " protocol)" + "process = BSS.Process.Gromacs(system, protocol)" ] }, { @@ -390,8 +380,7 @@ "metadata": {}, "outputs": [], "source": [ - "process = BSS.Process.Amber(\n", - " system, protocol)" + "process = BSS.Process.Amber(system, protocol)" ] }, { @@ -617,8 +606,7 @@ "outputs": [], "source": [ "# pass exe=f'{os.environ[\"AMBERHOME\"]}/bin/pmemd.cuda to use the faster MD engine pmemd\n", - "process = BSS.Process.Amber(\n", - " system, protocol)" + "process = BSS.Process.Amber(system, protocol)" ] }, { @@ -696,8 +684,7 @@ "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.9.13" + "pygments_lexer": "ipython3" }, "vscode": { "interpreter": { diff --git a/04_fep/02_RBFE/02_analysis_rbfe.ipynb b/04_fep/02_RBFE/02_analysis_rbfe.ipynb index 783ee13..46442ba 100644 --- a/04_fep/02_RBFE/02_analysis_rbfe.ipynb +++ b/04_fep/02_RBFE/02_analysis_rbfe.ipynb @@ -93,6 +93,7 @@ "outputs": [], "source": [ "from get_tutorial import download\n", + "\n", "download(\"02\")" ] }, @@ -221,7 +222,9 @@ " new_file_name = f\"analysis/outputs/results_{results_all_files.index(file)}.csv\"\n", " with open(new_file_name, \"w\") as result_file:\n", " writer = csv.writer(result_file, delimiter=\",\")\n", - " writer.writerow([\"lig_1\", \"lig_2\", \"freenrg(kcal/mol)\", \"error(kcal/mol)\", \"engine\"])\n", + " writer.writerow(\n", + " [\"lig_1\", \"lig_2\", \"freenrg(kcal/mol)\", \"error(kcal/mol)\", \"engine\"]\n", + " )\n", "\n", " for row, index in pd.read_csv(file).iterrows():\n", " pert = f\"{index['lig_1']}~{index['lig_2']}\"\n", @@ -290,7 +293,9 @@ "# write these to a csv file\n", "with open(\"analysis/outputs/computed_perturbations_average.csv\", \"w\") as comp_pert_file:\n", " writer = csv.writer(comp_pert_file, delimiter=\",\")\n", - " writer.writerow([\"lig_1\", \"lig_2\", \"freenrg(kcal/mol)\", \"error(kcal/mol)\", \"engine\"])\n", + " writer.writerow(\n", + " [\"lig_1\", \"lig_2\", \"freenrg(kcal/mol)\", \"error(kcal/mol)\", \"engine\"]\n", + " )\n", " for pert in perturbations:\n", " ddGs = comp_dict_list[pert]\n", " lig_0 = pert.split(\"~\")[0]\n", @@ -360,7 +365,9 @@ "# write these to a csv file\n", "with open(\"analysis/outputs/experimental_perturbations.csv\", \"w\") as exp_pert_file:\n", " writer = csv.writer(exp_pert_file, delimiter=\",\")\n", - " writer.writerow([\"lig_1\", \"lig_2\", \"freenrg(kcal/mol)\", \"error(kcal/mol)\", \"engine\"])\n", + " writer.writerow(\n", + " [\"lig_1\", \"lig_2\", \"freenrg(kcal/mol)\", \"error(kcal/mol)\", \"engine\"]\n", + " )\n", "\n", " for pert in perturbations:\n", " lig_0 = pert.split(\"~\")[0]\n", @@ -527,7 +534,15 @@ "metadata": {}, "outputs": [], "source": [ - "from cinnabar import wrangle, plotting" + "# Import cinnbar, API changes depending on version\n", + "try:\n", + " from cinnabar import wrangle, plotting\n", + "\n", + " cinnabar_is_old = True\n", + "except:\n", + " from cinnabar import FEMap, plotting\n", + "\n", + " cinnabar_is_old = False" ] }, { @@ -644,11 +659,32 @@ "metadata": {}, "outputs": [], "source": [ - "network = wrangle.FEMap(f\"analysis/outputs/cinnabar_data.csv\")\n", - "# plot the perturbations\n", - "plotting.plot_DDGs(network.graph, title=\"DDGs\", filename=f\"analysis/outputs/DDGs.png\", figsize=6)\n", - "# plot the ligands\n", - "plotting.plot_DGs(network.graph, title=\"DGs\", filename=f\"analysis/outputs/DGs.png\", figsize=6)" + "if cinnabar_is_old:\n", + " network = wrangle.FEMap(f\"analysis/outputs/cinnabar_data.csv\")\n", + " # plot the perturbations\n", + " plotting.plot_DDGs(\n", + " network.graph, title=\"DDGs\", filename=f\"analysis/outputs/DDGs.png\", figsize=6\n", + " )\n", + " # plot the ligands\n", + " plotting.plot_DGs(\n", + " network.graph, title=\"DGs\", filename=f\"analysis/outputs/DGs.png\", figsize=6\n", + " )\n", + "else:\n", + " network = FEMap.from_csv(f\"analysis/outputs/cinnabar_data.csv\")\n", + " # plot the perturbations\n", + " plotting.plot_DDGs(\n", + " network.to_legacy_graph(),\n", + " title=\"DDGs\",\n", + " filename=f\"analysis/outputs/DDGs.png\",\n", + " figsize=6,\n", + " )\n", + " # plot the ligands\n", + " plotting.plot_DGs(\n", + " network.to_legacy_graph(),\n", + " title=\"DGs\",\n", + " filename=f\"analysis/outputs/DGs.png\",\n", + " figsize=6,\n", + " )" ] }, { @@ -737,7 +773,7 @@ "Exercise 2.1.1: Excluding intermediates from the Network analysis\n", "\n", "\n", - "Try exculding this perturbation and rerunning the above Network analysis. First, we need to remove the perturbation. Then, we need to make sure that our new output image is being saved using a different file path. Adjust these in the cells below where the #FIXME is. \n" + "Try excluding this perturbation and rerunning the above Network analysis. First, we need to remove the perturbation. Then, we need to make sure that our new output image is being saved using a different file path. Adjust these in the cells below where the #FIXME is. \n" ] }, { @@ -876,11 +912,19 @@ " if pert in perturbations:\n", " writer.writerow([lig_0, lig_1, comp_ddG, comp_err, \"0.0\"])\n", "\n", - "network = wrangle.FEMap(f\"analysis/outputs/cinnabar_data_outliers_removed.csv\")\n", - "# plot the perturbations\n", - "plotting.plot_DDGs(network.graph, title=\"DDGs\", filename=f\"analysis/outputs/DDGs_outliers_removed.png\", figsize=6)\n", - "# plot the ligands\n", - "plotting.plot_DGs(network.graph, title=\"DGs\", filename=f\"analysis/outputs/DGs_outliers_removed.png\", figsize=6)\n", + "if cinnabar_is_old:\n", + " network = wrangle.FEMap(f\"analysis/outputs/cinnabar_data_outliers_removed.csv\")\n", + " # plot the perturbations\n", + " plotting.plot_DDGs(network.graph, title=\"DDGs\", filename=f\"analysis/outputs/DDGs_outliers_removed.png\", figsize=6)\n", + " # plot the ligands\n", + " plotting.plot_DGs(network.graph, title=\"DGs\", filename=f\"analysis/outputs/DGs_outliers_removed.png\", figsize=6)\n", + "else:\n", + " network = FEMap.from_csv(f\"analysis/outputs/cinnabar_data_outliers_removed.csv\")\n", + " # plot the perturbations\n", + " plotting.plot_DDGs(network.to_legacy_graph(), title=\"DDGs\", filename=f\"analysis/outputs/DDGs_outliers_removed.png\", figsize=6)\n", + " # plot the ligands\n", + " plotting.plot_DGs(network.to_legacy_graph(), title=\"DGs\", filename=f\"analysis/outputs/DGs_outliers_removed.png\", figsize=6)\n", + "\n", "```\n", "\n", "" @@ -924,11 +968,16 @@ "
Click here to see solution to Exercise. \n", "\n", "```python\n", - "\n", - "lig_dict = {entry[1]['name']:entry[1]['calc_DG'] for entry in network.graph.nodes.data()}\n", - "lig_df = pd.DataFrame.from_dict(lig_dict, orient=\"index\", columns=[\"calc_DG\"])\n", - "lig_df.to_csv(\"analysis/outputs/ligand_calc_DG.csv\")\n", - "lig_df.sort_values(\"calc_DG\")\n", + "if cinnabar_is_old:\n", + " lig_dict = {entry[1]['name']:entry[1]['calc_DG'] for entry in network.graph.nodes.data()}\n", + " lig_df = pd.DataFrame.from_dict(lig_dict, orient=\"index\", columns=[\"calc_DG\"])\n", + " lig_df.to_csv(\"analysis/outputs/ligand_calc_DG.csv\")\n", + " lig_df.sort_values(\"calc_DG\")\n", + "else:\n", + " lig_dict = {entry[0]:entry[1]['calc_DG'] for entry in network.to_legacy_graph().nodes.data()}\n", + " lig_df = pd.DataFrame.from_dict(lig_dict, orient=\"index\", columns=[\"calc_DG\"])\n", + " lig_df.to_csv(\"analysis/outputs/ligand_calc_DG.csv\")\n", + " lig_df.sort_values(\"calc_DG\")\n", "\n", "```\n", "\n", @@ -978,8 +1027,7 @@ "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.10.11" + "pygments_lexer": "ipython3" }, "varInspector": { "cols": { diff --git a/README.md b/README.md index 07c11f7..36a8125 100644 --- a/README.md +++ b/README.md @@ -7,7 +7,7 @@ These tutorials have been tested with BioSimSpace 2023.5.0 on a linux-64 platfor * Gromacs (tested with 2023.1) * AmberTools (tested with 23.3) * PLUMED (tested with 2.9.0) -* cinnabar (tested with 0.3.0) +* cinnabar (tested with 0.4.1) * alchemlyb (tested with 1.0.1) # Installation instructions