notebooks/09.00-Loop-Modeling.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<!--NOTEBOOK_HEADER-->\n",
    "*This notebook contains material from [PyRosetta](https://RosettaCommons.github.io/PyRosetta.notebooks);\n",
    "content is available [on Github](https://github.com/RosettaCommons/PyRosetta.notebooks.git).*"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<!--NAVIGATION-->\n",
    "< [`GALigandDock` Protocol with `pyrosetta.distributed` Using the `beta_cart.wts` Scorefunction](http://nbviewer.jupyter.org/github/RosettaCommons/PyRosetta.notebooks/blob/master/notebooks/08.02-Ligand-Docking-pyrosetta.distributed.ipynb) | [Contents](toc.ipynb) | [Index](index.ipynb) | [Using Rosetta Gen KIC](http://nbviewer.jupyter.org/github/RosettaCommons/PyRosetta.notebooks/blob/master/notebooks/09.01-Using-Gen-KIC.ipynb) ><p><a href=\"https://colab.research.google.com/github/RosettaCommons/PyRosetta.notebooks/blob/master/notebooks/09.00-Loop-Modeling.ipynb\"><img align=\"left\" src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open in Colab\" title=\"Open in Google Colaboratory\"></a>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Loop Modeling\n",
    "Keywords: loops, fold_tree_from_loops, CCD, KIC, cut-point variant, FoldTree, MoveMap"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Loop modeling is an important step in building homology models, designing enzymes, or docking with flexible loops. The goal of loop modeling is to predict the conformation of a short stretch of protein backbone and sidechains. Loop modeling can be used to predict structures of regions with missing density in crystal structures. Additionally, homology models often need to account for short insertions or deletions, and loop modeling can be used to predict how these sequence changes affect structure.\n",
    "\n",
    "There are a lot of different methods for loop modeling, but the basic algorithm goes like this:\n",
    "\n",
    "**Inputs:**\n",
    "\n",
    "The inputs are a protein structure and a set of indices specifying where one or more regions to model (i.e. the loop or loops) start and stop. In this notebook, you'll learn how to manually set up a loop FoldTree, which will allow you to specify the regions you want to model. However, in practice, you will not need to make the FoldTree from scratch, and you will see examples of how to do this as well.\n",
    "\n",
    "**Step 1: Initial build**\n",
    "\n",
    "The algorithm starts by building an initial backbone for each loop being sampled. This backbone is just a starting point for the rest of the algorithm, so it's only realistic in the sense of having reasonable bond lengths and not completely clashing with anything. Note that by skipping this step, you can use the loop modeling algorithm to generate ensembles.\n",
    "\n",
    "**Step 2: Centroid refinement**\n",
    "\n",
    "The algorithm continues by refining the loop conformation in the context of the centroid score function. The centroid score function represents the backbone atoms in full detail, but abstracts the sidechains into spherical blobs. This creates a smoother energy landscape that is easier to explore broadly. The landscape is sampled using Monte Carlo \"local backbone moves\", i.e. moves that perturb the backbone within the region being sampled but not outside of it.\n",
    "\n",
    "**Step 3: Full-atom refinement**\n",
    "\n",
    "The algorithm finishes by refining the loop conformation in the context of the fullatom score function. This is conceptually very similar to the centroid refinement discussed above, except now all the atoms are represented in full detail and both sidechain and local backbone Monte Carlo moves are employed.\n",
    "\n",
    "**Outputs:**\n",
    "\n",
    "Typically, to predict a structure for a single loop, you would generate at least 500 such models and take whichever has the lowest energy. You might also calculate an RMSD for each model relative to the lowest scoring one and look for funnels in score vs. RMSD space.\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "## Suggested Readings\n",
    "\n",
    "* A. Canutescu & R. L. Dunbrack, “Cyclic coordinate descent: A robotics algorithm for protein loop closure,” Protein Sci. 12, 963-972 (2003).\n",
    "\n",
    "* Wang, P. Bradley & D. Baker, “Protein-protein docking with backbone flexibility,” J. Mol. Biol. 373, 503-519 (2007).\n",
    "\n",
    "* J. Mandell,  E. A. Coutsias & T. Kortemme, “Sub-angstrom accuracy in protein loop reconstruction by robotics-inspired conformational sampling,” Nature Meth. 6, 551-552 (2009)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Notebook setup\n",
    "import sys\n",
    "if 'google.colab' in sys.modules:\n",
    "    !pip install pyrosettacolabsetup\n",
    "    import pyrosettacolabsetup\n",
    "    pyrosettacolabsetup.setup()\n",
    "    print (\"Notebook is set for PyRosetta use in Colab.  Have fun!\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "PyRosetta-4 2020 [Rosetta PyRosetta4.Release.python38.mac 2020.36+release.fd1c8ced991b69b754b632e54343720a59e87137 2020-08-30T11:28:06] retrieved from: http://www.pyrosetta.org\n",
      "(C) Copyright Rosetta Commons Member Institutions. Created in JHU by Sergey Lyskov and PyRosetta Team.\n",
      "\u001b[0mcore.init: \u001b[0mChecking for fconfig files in pwd and ./rosetta/flags\n",
      "\u001b[0mcore.init: \u001b[0mRosetta version: PyRosetta4.Release.python38.mac r263 2020.36+release.fd1c8ced991 fd1c8ced991b69b754b632e54343720a59e87137 http://www.pyrosetta.org 2020-08-30T11:28:06\n",
      "\u001b[0mcore.init: \u001b[0mcommand: PyRosetta -ex1 -ex2aro -database /Users/kathyle/PyRosetta4.Release.python38.mac.release-263/pyrosetta/database\n",
      "\u001b[0mbasic.random.init_random_generator: \u001b[0m'RNG device' seed mode, using '/dev/urandom', seed=1220972881 seed_offset=0 real_seed=1220972881\n",
      "\u001b[0mbasic.random.init_random_generator: \u001b[0mRandomGenerator:init: Normal mode, seed=1220972881 RG_type=mt19937\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-2-e0f5087144dd>:5: UserWarning: Import of 'rosetta' as a top-level module is deprecated and may be removed in 2018, import via 'pyrosetta.rosetta'.\n",
      "  from rosetta.core.kinematics import FoldTree\n"
     ]
    }
   ],
   "source": [
    "from pyrosetta import *\n",
    "from pyrosetta.rosetta import *\n",
    "from pyrosetta.teaching import *\n",
    "\n",
    "from rosetta.core.kinematics import FoldTree\n",
    "pyrosetta.init()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Lever-Arm Effect\n",
    "\n",
    "When you change the torsion angles in a given set of residues but you set the rest to not move, what will happen? Let's see the simple scheme below:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 3,
     "metadata": {
      "image/png": {
       "width": "700"
      }
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from IPython.display import Image\n",
    "Image('./Media/small_moves.png',width='700')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can see that in order to change one specific torsion angle in the cyan residue, all of the atoms that are to the right of that change should all move. \n",
    "Below is another example where one torsion angle at the N-terminus of the protein can cause huge movements in the rest of the protein. This is called the lever arm effect."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 4,
     "metadata": {
      "image/png": {
       "width": "700"
      }
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Image('./Media/big_moves.png',width='700')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Fold Tree\n",
    "\n",
    "Because we typically want to isolate the conformational changes to just our target loop region, we need a way to prevent lever-arm effects and control the movements of residues with respect to each other. This is accomplished—as was the case with protein-protein docking—with a fold tree, which is a graph that dictates the propagation of conformational changes throughout the Pose. \n",
    "\n",
    "The fold tree stores connections in between residues as \"jump edges\" and \"protein edges.\" Because Rosetta uses internal coordinates rather than Cartesian coordinates, the entire structure that you're working with has to be connected. Protein edges simply describe the connectivity of a covalently-linked peptide chain by stating the starting and ending residues. On the other hand, jump edges are the \"imaginary links\" that describe noncovalent connections, such as those between separate chains.\n",
    "\n",
    "One consequence of using a fold tree is that you can tell Rosetta which residues are upstream and which are downstream. This is important because it will determine the direction in which changes propagate.\n",
    "\n",
    "For the following exercises, you can find the working PDB, `test_in.pdb`, and a 3mer fragment file, `test_in.frag3` in the `inputs` folder."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Make sure you are in the directory with the pdb files:**\n",
    "\n",
    "`cd google_drive/My\\ Drive/student-notebooks/`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "#cd google_drive/My\\ Drive/student-notebooks/"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Fold Tree (from scratch)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Load the `test_in.pdb` structure (116 residues).\n",
    "```\n",
    "start_pose = pyrosetta.pose_from_file(\"inputs/test_in.pdb\")\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[0mcore.chemical.GlobalResidueTypeSet: \u001b[0mFinished initializing fa_standard residue type set.  Created 981 residue types\n",
      "\u001b[0mcore.chemical.GlobalResidueTypeSet: \u001b[0mTotal time to initialize 0.860046 seconds.\n",
      "\u001b[0mcore.import_pose.import_pose: \u001b[0mFile 'inputs/test_in.pdb' automatically determined to be of type PDB\n"
     ]
    }
   ],
   "source": [
    "start_pose = pyrosetta.pose_from_file(\"inputs/test_in.pdb\")\n",
    "pose = start_pose.clone()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We want to operate on the first loop, residues 15–24. For the fold tree, we place the jump anchors two residues outside of the loop range, i.e., residues 13–26. In loop modeling, the jump points are set at i-2 and j+2, where i and j are the beginning and end residues of the loop, respectively."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 7,
     "metadata": {
      "image/png": {
       "width": "700"
      }
     },
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from IPython.display import Image\n",
    "Image('./Media/fold-tree1.png',width='700')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "That is, we want a cut between residues 19 and 20, to allow motions in the loop that do not propagate through the rest of the protein. To tie the pieces together, we use a jump between residues 13 and 26. These residues will stay connected to each other.\n",
    "\n",
    "To make such a tree in PyRosetta, first we create a `FoldTree` object:\n",
    "\n",
    "```\n",
    "ft = FoldTree()\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "ft = FoldTree()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "__Be careful that you don't re-run the same cell multiple times as you will keep adding these pieces to the FoldTree, which will mess it up.__\n",
    "\n",
    "Then we add the \"edges” and the jump. Both `EDGE`s and `Jump`s are entered using the `FoldTree`’s `add_edge(start, end, code)` command, with peptide edges coded with a “-1” and jumps enumerated with the positive integers. (The first jump is coded “1”, the second “2”, etc.) The first edge is from residues 1 to 13:\n",
    "\n",
    "```\n",
    "ft.add_edge(1, 13, -1)\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "ft.add_edge(1, 13, -1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "(Note that this is different than saying `ft.add_edge(13, 1, -1))` because changes will propagate in the opposite direction.)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Then the second edge is from 13 to 19. __An `EDGE` must always start from a residue that has already been defined in another `EDGE`__, thus we use 13 here and not 14. (The one exception is the first edge, which starts from the graph’s “root”).\n",
    "\n",
    "```\n",
    "ft.add_edge(13, 19, -1)\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "ft.add_edge(13, 19, -1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Next, the `Jump`, which is specified with the integer code 1, tells Rosetta that this is a rigid-body connection, not a peptide `EDGE`:\n",
    "\n",
    "```\n",
    "ft.add_edge(13, 26, 1)\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "ft.add_edge(13, 26, 1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Finally, we add the last two `EDGE`s, both starting from 26, which is the residue that has been previously defined in the tree:\n",
    "\n",
    "```\n",
    "ft.add_edge(26, 20, -1)\n",
    "ft.add_edge(26, 116, -1)\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "ft.add_edge(26, 20, -1)\n",
    "ft.add_edge(26, 116, -1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Print the fold tree and check that this tree is valid:\n",
    "\n",
    "```\n",
    "print(ft)\n",
    "ft.check_fold_tree()\n",
    "```\n",
    "\n",
    "The latter command will return `False` if there are any invalid connections, disconnected parts, or undefined residues."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "FOLD_TREE  EDGE 1 13 -1  EDGE 13 19 -1  EDGE 13 26 1  EDGE 26 20 -1  EDGE 26 116 -1 \n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(ft)\n",
    "ft.check_fold_tree()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Finally, we attach this fold tree to the pose, overwriting its default fold tree. Print the `Pose`'s `FoldTree` to confirm you changed it:\n",
    "\n",
    "```\n",
    "print(pose.fold_tree())\n",
    "pose.fold_tree(ft)\n",
    "print(pose.fold_tree())\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "FOLD_TREE  EDGE 1 116 -1 \n",
      "FOLD_TREE  EDGE 1 13 -1  EDGE 13 19 -1  EDGE 13 26 1  EDGE 26 20 -1  EDGE 26 116 -1 \n"
     ]
    }
   ],
   "source": [
    "print(pose.fold_tree())\n",
    "pose.fold_tree(ft)\n",
    "print(pose.fold_tree())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Fold Tree (using functions)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In the previous section, we created a FoldTree and manually created the cutpoint variants. However, it is often more practical to use the pre-made functions. In order to use these functions, we first need to make a `Loop` object."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "loop1 = Loop(15,24,19)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Single loop"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Once you have a loop defined in a `Loop` object, you can set your fold tree with the `set_single_loop_fold_tree` command.  Note that the `FoldTree` will look slightly different compared to the one we manually created:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "FOLD_TREE  EDGE 1 116 -1 \n"
     ]
    }
   ],
   "source": [
    "pose.assign(start_pose)\n",
    "print(pose.fold_tree())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[0mprotocols.loops.loops_main: \u001b[0m\u001b[1m[ WARNING ]\u001b[0m Pose fold tree FOLD_TREE  EDGE 1 14 -1  EDGE 14 19 -1  EDGE 14 25 1  EDGE 25 20 -1  EDGE 25 116 -1\n",
      "FOLD_TREE  EDGE 1 14 -1  EDGE 14 19 -1  EDGE 14 25 1  EDGE 25 20 -1  EDGE 25 116 -1 \n"
     ]
    }
   ],
   "source": [
    "set_single_loop_fold_tree(pose, loop1)\n",
    "print(pose.fold_tree())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Multiple Loops\n",
    "\n",
    "Multiple loops can be stored in a `Loops` object. We can create a `loop2` object for the 78–83 loop and then create a `Loops` object:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "loop2 = Loop(78, 83, 80)\n",
    "\n",
    "loops = Loops()\n",
    "loops.add_loop(loop1)\n",
    "loops.add_loop(loop2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Next, we can use the `fold_tree_from_loops` function, which requires a pose, a Loops object, and an empty `FoldTree`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[0mprotocols.loops.loops_main: \u001b[0mAdded cutpoint variant to residue 19\n",
      "\u001b[0mprotocols.loops.loops_main: \u001b[0mAdded cutpoint variant to residue 20\n",
      "\u001b[0mprotocols.loops.loops_main: \u001b[0mAdded cutpoint variant to residue 80\n",
      "\u001b[0mprotocols.loops.loops_main: \u001b[0mAdded cutpoint variant to residue 81\n"
     ]
    }
   ],
   "source": [
    "pose.assign(start_pose) # start with our original pose\n",
    "ft = FoldTree() # start with an empty FoldTree\n",
    "\n",
    "fold_tree_from_loops(pose, loops, ft);\n",
    "pose.fold_tree(ft); # attaching our new FoldTree to our working pose\n",
    "add_cutpoint_variants(pose);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Exercises"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "1. **Optional PyMOL Exercise:** Test out your fold tree. Do `pose.set_phi(res, 180)` for res values of 10, 13, 16, 23, 26 and 29. View each in PyMOL with the `PyMOLMover`.\n",
    "\n",
    "```\n",
    "pose.assign(start_pose)\n",
    "pmm = PyMOLMover()  # unique port number here, if needed\n",
    "pmm.keep_history(True)\n",
    "pmm.apply(pose)\n",
    "for res in (10, 13, 16, 23, 26, 29):\n",
    "    pose.set_phi(res, 180)\n",
    "pmm.apply(pose)\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "2. Sketch a fold tree that you could use for modeling a loop from residues 78–83. Remember that a loop from residues i to j uses a fold tree with a jump from residues i-2 to j+2."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "3. What edges would you use to generate the above fold tree? See the above steps for how to add `EDGE`s to the `FoldTree`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To save some time and help avoid mistakes, there are a couple functions that will assist in the creation of fold trees:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "4. Try each of the following and print the fold tree. What does each of the following do?\n",
    "\n",
    "```\n",
    "ft.clear()\n",
    "print(ft)\n",
    "\n",
    "ft.simple_tree(116)\n",
    "print(ft)\n",
    "\n",
    "ft.new_jump(76, 85, 80)\n",
    "print(ft)\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "5. Use these FoldTree methods to check your answer to question 3."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "6. Use the above commands to make a fold tree to model both loops (15–24 and 78–83) simultaneously. Note you'll need more than one `Jump`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Cyclic Coordination Descent (CCD) Loop Closure\n",
    "\n",
    "Canutescu & Dunbrack’s CCD routine is implemented as a `Mover`. It first requires that the loop is defined using the `Loop` class. In addition to the FoldTree that you created in the previous section (whether by hand or using a function), you will also need to create a `MoveMap` with the loop residues marked as flexible (both backbone and side-chain torsion angles). Like many specialty objects in Rosetta, the CCD `Mover` is located in its own namespace and is not loaded in by default when the rest of Rosetta is imported into Python. You can either import the module or refer to its namespace when calling it. Here we show the module import:\n",
    "\n",
    "```\n",
    "from pyrosetta.rosetta.protocols.loops import Loop, Loops, set_single_loop_fold_tree, loop_rmsd\n",
    "from pyrosetta.rosetta.protocols.loops.loop_closure.ccd import *\n",
    "\n",
    "loop1 = Loop(15, 24, 19)\n",
    "\n",
    "loop_mm = MoveMap()\n",
    "loop_mm.set_bb_true_range(15, 24)\n",
    "loop_mm.set_chi_true_range(15, 24)\n",
    "\n",
    "ccd = CCDLoopClosureMover(loop1, loop_mm)\n",
    "print(ccd)\n",
    "```\n",
    "\n",
    "__Question:__ When declaring the `Loop` object, what do 15, 24, and 19 mean, respectively? See what is written out when you `print` the `ccd` object"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[0mcore.scoring.ramachandran: \u001b[0mshapovalov_lib::shap_rama_smooth_level of 4( aka highest_smooth ) got activated.\n",
      "\u001b[0mbasic.io.database: \u001b[0mDatabase file opened: scoring/score_functions/rama/shapovalov/kappa25/all.ramaProb\n",
      "Mover name: CCDLoopClosureMover, Mover type: CCDLoopClosureMover, Mover current tag:NoTag\n",
      "LOOP start: 15  stop: 24  cut: 19  size: 10  skip rate: 0  extended?: False\n",
      "\n",
      "Number of CCD cycles:    100\n",
      "Tolerance:               0.08\n",
      "bRama check:             True\n",
      "Max total delta helix:   10\n",
      "Max total delta strand:  50\n",
      "Max total delta loop:    75\n",
      "Movemap: \n",
      "\n",
      "-------------------------------\n",
      "  resnum     Type  TRUE/FALSE \n",
      "-------------------------------\n",
      " DEFAULT      BB     FALSE\n",
      " DEFAULT      SC     FALSE\n",
      " DEFAULT      NU     FALSE\n",
      " DEFAULT  BRANCH     FALSE\n",
      "     015      BB      TRUE\n",
      "              SC      TRUE\n",
      "     016      BB      TRUE\n",
      "              SC      TRUE\n",
      "     017      BB      TRUE\n",
      "              SC      TRUE\n",
      "     018      BB      TRUE\n",
      "              SC      TRUE\n",
      "     019      BB      TRUE\n",
      "              SC      TRUE\n",
      "     020      BB      TRUE\n",
      "              SC      TRUE\n",
      "     021      BB      TRUE\n",
      "              SC      TRUE\n",
      "     022      BB      TRUE\n",
      "              SC      TRUE\n",
      "     023      BB      TRUE\n",
      "              SC      TRUE\n",
      "     024      BB      TRUE\n",
      "              SC      TRUE\n",
      "-------------------------------\n",
      " jumpnum     Type  TRUE/FALSE \n",
      "-------------------------------\n",
      " DEFAULT     JUMP    FALSE\n",
      "-------------------------------\n",
      "  resnum  atomnum     Type  TRUE/FALSE \n",
      "-------------------------------\n",
      " DEFAULT               PHI    FALSE\n",
      " DEFAULT             THETA    FALSE\n",
      " DEFAULT                 D    FALSE\n",
      " DEFAULT               RB1    FALSE\n",
      " DEFAULT               RB2    FALSE\n",
      " DEFAULT               RB3    FALSE\n",
      " DEFAULT               RB4    FALSE\n",
      " DEFAULT               RB5    FALSE\n",
      " DEFAULT               RB6    FALSE\n",
      "-------------------------------\n",
      "\n",
      "RamaCheck: \n",
      "RamaCheck1B:\n",
      "\n",
      "Temperature:                                   0.25\n",
      "Maximum Ramachandran Score Increase Tolerated: 2\n",
      "\n"
     ]
    }
   ],
   "source": [
    "from pyrosetta.rosetta.protocols.loops import Loop, Loops, set_single_loop_fold_tree, loop_rmsd\n",
    "from pyrosetta.rosetta.protocols.loops.loop_closure.ccd import *\n",
    "\n",
    "loop1 = Loop(15, 24, 19)\n",
    "\n",
    "loop_mm = MoveMap()\n",
    "loop_mm.set_bb_true_range(15, 24)\n",
    "loop_mm.set_chi_true_range(15, 24)\n",
    "\n",
    "ccd = CCDLoopClosureMover(loop1, loop_mm)\n",
    "print(ccd)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Before running the CCD algorithm, it is important to convert the residues around the cut site of the loop to “cut-point variants”:\n",
    "\n",
    "```\n",
    "add_single_cutpoint_variant(pose, loop1)\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[0mprotocols.loops.loops_main: \u001b[0mAdded cutpoint variant to residue 19\n",
      "\u001b[0mprotocols.loops.loops_main: \u001b[0mAdded cutpoint variant to residue 20\n"
     ]
    }
   ],
   "source": [
    "add_single_cutpoint_variant(pose, loop1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "7. Now that the cutpoint variant has been added, open the loop using `set_phi`, and `apply` the CCD `Mover` on the `Pose`. Does it close the loop? Is the bond across the cut point protein-like?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Break the loop\n",
    "pose.set_phi(16, 10) # 10 degrees is arbitrary\n",
    "pose.set_phi(17, 10)\n",
    "pose.set_phi(18, 10)\n",
    "pose.set_phi(19, 10)\n",
    "pose.dump_pdb(\"outputs/brokenloop.pdb\") # Be sure to look at it in PyMOL!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Apply CCD Mover\n",
    "ccd.apply(pose)\n",
    "pose.dump_pdb(\"outputs/ccdloop.pdb\") # Compare this to brokenloop.pdb and test_in.pdb in PyMOL. What's the difference?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Note:** To use CCD on multiple loops, you have to iterate over each one."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Loop Building\n",
    "\n",
    "The `MoveMap` and the `FoldTree` work together. By using a `MoveMap`, you can ensure that a `Mover` will only operate inside the loop region."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "At this point, you should be able to write your own loop protocol that will build the loop at low-resolution using fragments. Some tips:\n",
    "\n",
    "\n",
    "* Create a MoveMap that will allow motions only in the two loop regions defined in our MoveMap above.\n",
    "* Create a ClassicFragmentMover using your MoveMap and the 3-residue fragment file provided, test_in.frag3. \n",
    "* Use the cen_std score function, but add the chainbreak score component with a weight of 1.\n",
    "* Do 100 fragment insertions.\n",
    "* After each fragment insertion, close the loop with CCD, then use a MonteCarlo object to accept or reject the combination move.\n",
    "* Bonus: use SequenceMover and TrialMover to tighten up your code.\n",
    "* Further bonus: use the JobDistributor to allow your program to make multiple structures."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "`Loop` RMSD is typically measured in a fixed reference frame of the whole protein, and it can be computed on Cα atoms or all backbone atoms. PyRosetta has a built-in function for calculating deviation of all the loops, and its output can be added as additional info in the `PyJobDistributor`. __If the `lrms` comes out to zero, return to the above cells and move one of the loops__:\n",
    "\n",
    "```\n",
    "lrms = loop_rmsd(pose, start_pose, loops, True)\n",
    "print(lrms)\n",
    "sfxn = get_score_function()\n",
    "\n",
    "jd = PyJobDistributor(\"loop_test\", 1, sfxn)\n",
    "jd.additional_decoy_info = \" LRMSD: \" + str(lrms)\n",
    "jd.output_decoy(pose)\n",
    "```\n",
    "\n",
    "(The fourth argument in `loop_rmsd()` tells whether or not the RMSD is calculated for Cα atoms only.)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2.4983616460639855\n",
      "\u001b[0mcore.scoring.ScoreFunctionFactory: \u001b[0mSCOREFUNCTION: \u001b[32mref2015\u001b[0m\n",
      "\u001b[0mcore.scoring.etable: \u001b[0mStarting energy table calculation\n",
      "\u001b[0mcore.scoring.etable: \u001b[0msmooth_etable: changing atr/rep split to bottom of energy well\n",
      "\u001b[0mcore.scoring.etable: \u001b[0msmooth_etable: spline smoothing lj etables (maxdis = 6)\n",
      "\u001b[0mcore.scoring.etable: \u001b[0msmooth_etable: spline smoothing solvation etables (max_dis = 6)\n",
      "\u001b[0mcore.scoring.etable: \u001b[0mFinished calculating energy tables.\n",
      "\u001b[0mbasic.io.database: \u001b[0mDatabase file opened: scoring/score_functions/hbonds/ref2015_params/HBPoly1D.csv\n",
      "\u001b[0mbasic.io.database: \u001b[0mDatabase file opened: scoring/score_functions/hbonds/ref2015_params/HBFadeIntervals.csv\n",
      "\u001b[0mbasic.io.database: \u001b[0mDatabase file opened: scoring/score_functions/hbonds/ref2015_params/HBEval.csv\n",
      "\u001b[0mbasic.io.database: \u001b[0mDatabase file opened: scoring/score_functions/hbonds/ref2015_params/DonStrength.csv\n",
      "\u001b[0mbasic.io.database: \u001b[0mDatabase file opened: scoring/score_functions/hbonds/ref2015_params/AccStrength.csv\n",
      "\u001b[0mbasic.io.database: \u001b[0mDatabase file opened: scoring/score_functions/rama/fd/all.ramaProb\n",
      "\u001b[0mbasic.io.database: \u001b[0mDatabase file opened: scoring/score_functions/rama/fd/prepro.ramaProb\n",
      "\u001b[0mbasic.io.database: \u001b[0mDatabase file opened: scoring/score_functions/omega/omega_ppdep.all.txt\n",
      "\u001b[0mbasic.io.database: \u001b[0mDatabase file opened: scoring/score_functions/omega/omega_ppdep.gly.txt\n",
      "\u001b[0mbasic.io.database: \u001b[0mDatabase file opened: scoring/score_functions/omega/omega_ppdep.pro.txt\n",
      "\u001b[0mbasic.io.database: \u001b[0mDatabase file opened: scoring/score_functions/omega/omega_ppdep.valile.txt\n",
      "\u001b[0mbasic.io.database: \u001b[0mDatabase file opened: scoring/score_functions/P_AA_pp/P_AA\n",
      "\u001b[0mbasic.io.database: \u001b[0mDatabase file opened: scoring/score_functions/P_AA_pp/P_AA_n\n",
      "\u001b[0mcore.scoring.P_AA: \u001b[0mshapovalov_lib::shap_p_aa_pp_smooth_level of 1( aka low_smooth ) got activated.\n",
      "\u001b[0mbasic.io.database: \u001b[0mDatabase file opened: scoring/score_functions/P_AA_pp/shapovalov/10deg/kappa131/a20.prop\n"
     ]
    }
   ],
   "source": [
    "lrms = loop_rmsd(pose, start_pose, loops, True)\n",
    "print(lrms)\n",
    "sfxn = get_score_function()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If you first perturb the loop residues by setting all the residues to extended conformations (φ=ψ=180°), can your code close the two loops and find reasonable conformations? What is the loop RMS?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## High-Resolution Loop Protocol\n",
    "\n",
    "In high-resolution, loop optimization needs smaller perturbations such as that from `Small` and `Shear` moves. The classic Rosetta loop refinement protocol is available as a `Mover` and is located in the `pyrosetta.rosetta.protocols.loops.loop_mover.refine` namespace:\n",
    "\n",
    "```\n",
    "from pyrosetta.rosetta.protocols.loops.loop_mover.refine import *\n",
    "loop_refine = LoopMover_Refine_CCD(loops)\n",
    "```\n",
    "\n",
    "The `Mover` uses its own default, high-resolution score function, and it will generate its own `MoveMap` based on the definition of the loops."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[0mcore.scoring.ScoreFunctionFactory: \u001b[0mSCOREFUNCTION: \u001b[32mref2015\u001b[0m\n"
     ]
    }
   ],
   "source": [
    "from pyrosetta.rosetta.protocols.loops.loop_mover.refine import *\n",
    "loop_refine = LoopMover_Refine_CCD(loops)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "`apply` this `Mover` to a few of your low-resolution loop models after switching them to full atom versions. How far does refinement move the loops? Do the loops remain closed? Note: `loop_refine.apply(pose)` might take a while."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Kinematic Closure (KIC) Protocol\n",
    "\n",
    "The kinematic loop closure methods of Mandell et al. are also available in several prepared `Movers` and protocols."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A single closure of a loop using the direct mathematical solution using polynomial resultants can be performed by applying the `KinematicMover`. Rather than using a `Loop` object, this `Mover` is set up by specifying the three “pivot” residues. The `KinematicMover` determines new torsion angles for the pivot residues by solving the closure equations.\n",
    "\n",
    "```\n",
    "from pyrosetta.rosetta.protocols.loops.loop_closure.kinematic_closure import *\n",
    "\n",
    "set_single_loop_fold_tree(pose, loop1)\n",
    "pmm.apply(pose)        #if viewing in PyMOL\n",
    "kic_mover = KinematicMover()\n",
    "kic_mover.set_pivots(16, 20, 24)\n",
    "kic_mover.apply(pose)\n",
    "pmm.apply(pose)        #if viewing in PyMOL\n",
    "```\n",
    "\n",
    "Like the `CCDLoopClosureMover`, the `KinematicMover` can be applied after various perturbations that alter or open the loop."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[0mprotocols.loops.loops_main: \u001b[0m\u001b[1m[ WARNING ]\u001b[0m Pose fold tree FOLD_TREE  EDGE 1 14 -1  EDGE 14 19 -1  EDGE 14 25 1  EDGE 25 20 -1  EDGE 25 116 -1\n"
     ]
    }
   ],
   "source": [
    "from pyrosetta.rosetta.protocols.loops.loop_closure.kinematic_closure import *\n",
    "\n",
    "set_single_loop_fold_tree(pose, loop1)\n",
    "\n",
    "kic_mover = KinematicMover()\n",
    "kic_mover.set_pivots(16, 20, 24)\n",
    "kic_mover.apply(pose)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The full loop prediction protocol of Mandell et al. has been implemented as separate `Movers` for the low- and high-resolution stages. The `LoopMover_Perturb_KIC` operates on a centroid representation `Pose`, and it is designed to predict a loop de novo. The `LoopMover_Refine_KIC` operates in the full-atom representation, and it is designed to refine a loop making small perturbations from a starting conformation such as one output by the `LoopMover_Perturb_KIC` `Mover`. Here is an example of the usage of both:\n",
    "```\n",
    "from pyrosetta.rosetta.protocols.loops.loop_mover.perturb import *\n",
    "from pyrosetta.rosetta.protocols.loops.loop_mover.refine import *\n",
    "\n",
    "loops = Loops()\n",
    "loops.add_loop(loop1)\n",
    "\n",
    "set_single_loop_fold_tree(pose, loop1)\n",
    "\n",
    "sw = SwitchResidueTypeSetMover(\"centroid\")\n",
    "sw.apply(pose)\n",
    "kic_perturb = LoopMover_Perturb_KIC(loops)\n",
    "#kic_perturb.apply(pose)\n",
    "sw = SwitchResidueTypeSetMover(\"fa_standard\")\n",
    "sw.apply(pose)\n",
    "kic_refine = LoopMover_Refine_KIC(loops)\n",
    "#kic_refine.apply(pose)\n",
    "```\n",
    "\n",
    "__Because these are full prediction protocols, they will require some time to perform on your computer.__ Each will result in a single decoy structure; note that Mandell et al. generated 1000 decoy structures for blind predictions of 12-residue loops."
   ]
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    "11. Time permitting, repeat exercises 8–10, replacing the CCD `Mover` with the appropriate kinematic `Movers`."
   ]
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    "## Simultaneous Loop Modeling and Docking\n",
    "\n",
    "Antibodies have two chains, light (L) and heavy (H), which can move relative to each other. They also have a long, hypervariable H3 loop, typically residues 95–102. Antibodies are common protein drugs, and they are often created by exploiting the immune system of a mouse. There is a need for high-quality homology models of antibodies."
   ]
  },
  {
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   "source": [
    "12. Sketch a fold tree that you could use to model an antibody with a flexible H3 loop and H and L chains that can move relative to each other."
   ]
  },
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   "source": [
    "13. Write a low-resolution protocol to alternate docking and loop modeling steps. Use your code to model cetuximab. Use the job distributor to track your decoys. What is the lowest RMSD you can create in 100 decoys?"
   ]
  },
  {
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   "source": [
    "**Chapter contributors:**\n",
    "\n",
    "- Jared Adolf-Bryfogle (Scripps; Institute for Protein Innovation)\n",
    "- Kathy Le (Johns Hopkins University); parts of this chapter were adapted from the PyRosetta book (J. J. Gray, S. Chaudhury, S. Lyskov, J. Labonte) and the [Rosetta Commons docs page](https://www.rosettacommons.org/docs/latest/Home)"
   ]
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   "source": [
    "<!--NAVIGATION-->\n",
    "< [`GALigandDock` Protocol with `pyrosetta.distributed` Using the `beta_cart.wts` Scorefunction](http://nbviewer.jupyter.org/github/RosettaCommons/PyRosetta.notebooks/blob/master/notebooks/08.02-Ligand-Docking-pyrosetta.distributed.ipynb) | [Contents](toc.ipynb) | [Index](index.ipynb) | [Using Rosetta Gen KIC](http://nbviewer.jupyter.org/github/RosettaCommons/PyRosetta.notebooks/blob/master/notebooks/09.01-Using-Gen-KIC.ipynb) ><p><a href=\"https://colab.research.google.com/github/RosettaCommons/PyRosetta.notebooks/blob/master/notebooks/09.00-Loop-Modeling.ipynb\"><img align=\"left\" src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open in Colab\" title=\"Open in Google Colaboratory\"></a>"
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