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Updates based on feedback from...
* Sander Roet * Peter Bolhuis * UvA BioMolSim 2020
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4 files changed

+14
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1_tps_sampling_tutorial.ipynb

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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"There's only one pair of Ramachandran angles of interest here: the ones for residue 1, alanine. To figure out which atoms are needed, we use the definition of $\\phi_i$, which tells us we need C$^{(0)}$, N$^{(1)}$, C$_\\alpha^{(1)}$, and C$^{(1)}$; i.e., `ACE0-C`, `ALA1-N`, `ALA1-CA`, and `ALA1-C`. We can find the correct atom indices from the result of the previous cell. "
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"There's only one pair of Ramachandran angles of interest here: the ones for residue 1, alanine. To figure out which atoms are needed, we use the definition of $\\phi_i$, which tells us we need C$^{(0)}$, N$^{(1)}$, C$_\\alpha^{(1)}$, and C$^{(1)}$; i.e., `ACE1-C`, `ALA2-N`, `ALA2-CA`, and `ALA2-C`. We can find the correct atom indices from the result of the previous cell. "
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]
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},
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{
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"metadata": {},
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"outputs": [],
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"source": [
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"# ACE0-C, ALA1-N, ALA1-CA, ALA1-C: 4,6,8,14\n",
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"# ACE1-C, ALA2-N, ALA2-CA, ALA2-C: 4,6,8,14\n",
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"phi = paths.MDTrajFunctionCV(\"phi\", md.compute_dihedrals, engine.topology, indices=[[4,6,8,14]])"
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]
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},

2_tps_analysis_tutorial.ipynb

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"source": [
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"md_traj = traj.to_mdtraj().image_molecules()\n",
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"view = nv.show_mdtraj(md_traj)\n",
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"view.clear()\n",
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"view.add_ball_and_stick(\"ACE ALA NME\")\n",
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"view.center()\n",
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"view"
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Double-clicking the viewing window makes it go full screen. You can also pan, zoom, and rotate using the mouse.\n",
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"Click the two arrows in the upper right to go full screen. You can also pan, zoom, and rotate using the mouse.\n",
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"\n",
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"If you do not see the widget, you may still need to run the command to enable the widget (and to restart Jupyter):\n",
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"`jupyter-nbextension enable nglview --py --sys-prefix`\n",
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"\n",
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"Note that you can also save the trajectory in a format that VMD can read, and then you could use VMD instead.\n",
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"\n",
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"If you have the full simulation data, you can visualize these trajectories with NGLView. (Full simulation data not provided online, due to size)."
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"If you have the full simulation data, you could visualize these trajectories with NGLView. (Full simulation data not provided online, due to size), using the same approach as above."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"#md_trajA = trajA.to_mdtraj().image_molecules()\n",
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"#view_A = nv.show_mdtraj(md_trajA)\n",
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"#view_A.add_ball_and_stick(\"ACE ALA NME\")\n",
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"#view_A.center()\n",
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"#view_A"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"#md_trajB = trajB.to_mdtraj().image_molecules()\n",
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"#view_B = nv.show_mdtraj(md_trajB)\n",
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"#view_B.add_ball_and_stick(\"ACE ALA NME\")\n",
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"#view_B.center()\n",
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"#view_B"
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]
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"source": []
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}
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],
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"metadata": {

3_committor_analysis_tutorial.ipynb

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"source": [
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"You'll notice that this is *not* very sharply peaked in $\\psi$. This means that $\\psi$ alone probably doesn't define the transition state.\n",
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"\n",
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"If $\\psi$ did define the transition state, we'd probably expect the transition state to be around $\\psi = 0.6$ (~35 degrees) to $\\psi = 1.0$ (~60 degrees). Now, instead of keeping the committor probability fixed and histogramming the values of $\\psi$, let's see what the values of the committor are for a fixed value of $\\psi = \\psi^*$. If $\\psi^*$ defined the transition state, then the committor would always be 0.5 here."
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"If $\\psi$ did define the transition state, we'd probably expect the transition state to be around $\\psi = 0.6$ (\\~35 degrees) to $\\psi = 1.0$ (\\~60 degrees). Now, instead of keeping the committor probability fixed and histogramming the values of $\\psi$, let's see what the values of the committor are for a fixed value of $\\psi = \\psi^*$. If $\\psi^*$ defined the transition state, then the committor would always be 0.5 here."
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]
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},
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{
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"# YOUR TURN: modify the snapshot number; compare the conformations\n",
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"md_traj_A = paths.Trajectory([isocommittor_0x5[2]]).to_mdtraj().image_molecules()\n",
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"view_A = nv.show_mdtraj(md_traj_A)\n",
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"view_A.clear()\n",
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"view_A.add_ball_and_stick(\"ACE ALA NME\")\n",
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"view_A.center()\n",
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"view_A"

5_advanced_customize_shooting.ipynb

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"source": [
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"## Comparing two-way shooting to biased shooting\n",
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"\n",
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"Let's open the "
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"Let's open the output file and analyze the results."
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{
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"outputs": [],
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"source": [
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"ens_0_strategy = strategies.OneWayShootingStrategy(\n",
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" ensembles=[tis_network.sampling_ensembles[0]]\n",
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" ensembles=[tis_network.sampling_ensembles[0]],\n",
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" engine=engine\n",
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")"
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]
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},

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