{ "cells": [ { "attachments": {}, "cell_type": "markdown", "id": "9a0f5c0b", "metadata": {}, "source": [ "## Protein in Water\n", "\n", "*Solvating a protein structure from the PDB and running NPT dynamics*\n", "\n", "### Introduction\n", "\n", "This is the OpenMM version of [Justin A. Lemkul's Lysozyme in Water GROMACS tutorial](http://www.mdtutorials.com/gmx/lysozyme/index.html).\n", "\n", "It will cover the following steps\n", "\n", "- Load a PDB file into OpenMM\n", "- Choose the force-field \n", "- Clean-up the file\n", "- Solvate the protein with water and ions\n", "- Setup system and integrator\n", "- Run local minization\n", "- Run NVT equilibration\n", "- Run NPT production molecular dynamics\n", "- Basic analysis." ] }, { "attachments": {}, "cell_type": "markdown", "id": "5437bcbb", "metadata": {}, "source": [ "### Download the protein structure file\n", "\n", "First we need to download the PDB file of the lysozome from the RCSB Protein Data Bank https://www.rcsb.org/structure/1aki" ] }, { "cell_type": "code", "execution_count": 1, "id": "68bd18e5", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "--2022-12-23 14:47:36-- https://files.rcsb.org/download/1AKI.pdb\n", "Resolving files.rcsb.org (files.rcsb.org)... 128.6.158.66\n", "Connecting to files.rcsb.org (files.rcsb.org)|128.6.158.66|:443... connected.\n", "HTTP request sent, awaiting response... 200 OK\n", "Length: unspecified [application/octet-stream]\n", "Saving to: ‘1AKI.pdb’\n", "\n", "1AKI.pdb [ <=> ] 113.59K 456KB/s in 0.2s \n", "\n", "2022-12-23 14:47:40 (456 KB/s) - ‘1AKI.pdb’ saved [116316]\n", "\n" ] } ], "source": [ "!wget https://files.rcsb.org/download/1AKI.pdb" ] }, { "attachments": {}, "cell_type": "markdown", "id": "b28934e2", "metadata": {}, "source": [ "### Load the PDB file into OpenMM" ] }, { "cell_type": "code", "execution_count": 2, "id": "e830a81a", "metadata": {}, "outputs": [], "source": [ "from openmm.app import *\n", "from openmm import *\n", "from openmm.unit import *\n", "from sys import stdout\n", "\n", "pdb = PDBFile(\"1AKI.pdb\")\n" ] }, { "attachments": {}, "cell_type": "markdown", "id": "09dd459c", "metadata": {}, "source": [ "### Define the forcefield\n", "\n", "We need to define the forcefield we want to use. We will use the Amber14 forcefield and the TIP3P-FB water model." ] }, { "cell_type": "code", "execution_count": 3, "id": "65f73c52", "metadata": {}, "outputs": [], "source": [ "# Specify the forcefield \n", "forcefield = ForceField('amber14-all.xml', 'amber14/tip3pfb.xml')" ] }, { "attachments": {}, "cell_type": "markdown", "id": "825b9c58", "metadata": {}, "source": [ "### Clean up\n", "\n", "This PDB file contains some crystal water molecules which we want to strip out. This can be done using the Modeller class.\n", "We also add in any missing H atoms." ] }, { "cell_type": "code", "execution_count": 4, "id": "9e2f7069", "metadata": {}, "outputs": [], "source": [ "modeller = Modeller(pdb.topology, pdb.positions)\n", "modeller.deleteWater()\n", "residues=modeller.addHydrogens(forcefield)" ] }, { "attachments": {}, "cell_type": "markdown", "id": "b286b533", "metadata": {}, "source": [ "### Solvate\n", "\n", "We can use the `addSolvent` method to add water molecules" ] }, { "cell_type": "code", "execution_count": 5, "id": "0e9a63ad", "metadata": {}, "outputs": [], "source": [ "modeller.addSolvent(forcefield, padding=1.0*nanometer)" ] }, { "attachments": {}, "cell_type": "markdown", "id": "3c07c143", "metadata": {}, "source": [ "This command creates a box that has edges at least 1nm away from the solute and fills it with water molecules. Addionally it adds in the required number of CL and Na ions to make the system charge neutral." ] }, { "attachments": {}, "cell_type": "markdown", "id": "3520a945", "metadata": {}, "source": [ "### Setup system and Integrator\n", "\n", "We now need to combine our molecular topology and the forcefield to create a complete description of the system. This is done using the `ForceField` object's `createSystem()` function.\n", "We then create the integrator, and combine the integrator and system to create the `Simulation` object. Finally we set the initial atomic positions." ] }, { "cell_type": "code", "execution_count": 6, "id": "9d08a38a", "metadata": {}, "outputs": [], "source": [ "system = forcefield.createSystem(modeller.topology, nonbondedMethod=PME, nonbondedCutoff=1.0*nanometer, constraints=HBonds)\n", "integrator = LangevinMiddleIntegrator(300*kelvin, 1/picosecond, 0.004*picoseconds)\n", "simulation = Simulation(modeller.topology, system, integrator)\n", "simulation.context.setPositions(modeller.positions)" ] }, { "attachments": {}, "cell_type": "markdown", "id": "7ea42e7e", "metadata": {}, "source": [ "### Local energy minimization" ] }, { "attachments": {}, "cell_type": "markdown", "id": "d144a790", "metadata": {}, "source": [ "It is a good idea to run local energy minimization at the start of a simulation, since the coordinates in the PDB file might produce very large forces" ] }, { "cell_type": "code", "execution_count": 7, "id": "779d7617", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Minimizing energy\n" ] } ], "source": [ "print(\"Minimizing energy\")\n", "simulation.minimizeEnergy()" ] }, { "attachments": {}, "cell_type": "markdown", "id": "184761eb", "metadata": {}, "source": [ "### Setup reporting \n", "\n", "To get output from our simulation we can add reporters. We use `PDBReporter` to write the coorinates every 1000 timesteps to \"output.pdb\" and we use `StateDataReporter` to print the timestep, potential energy, temperature, and volume to the screen and to a file called \"md_log.txt\"." ] }, { "cell_type": "code", "execution_count": 8, "id": "8a1620e8", "metadata": {}, "outputs": [], "source": [ "simulation.reporters.append(PDBReporter('output.pdb', 1000))\n", "simulation.reporters.append(StateDataReporter(stdout, 1000, step=True,\n", " potentialEnergy=True, temperature=True, volume=True))\n", "simulation.reporters.append(StateDataReporter(\"md_log.txt\", 100, step=True,\n", " potentialEnergy=True, temperature=True, volume=True))" ] }, { "attachments": {}, "cell_type": "markdown", "id": "7e23a99c", "metadata": {}, "source": [ "### NVT equillibration\n", "\n", "We are using a Langevin integrator which means we are simulating in the NVT ensemble. To equilibrate the temperature we just need to run the simulation for a number of timesteps." ] }, { "cell_type": "code", "execution_count": 9, "id": "4676b438", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Running NVT\n", "#\"Step\",\"Potential Energy (kJ/mole)\",\"Temperature (K)\",\"Box Volume (nm^3)\"\n", "1000,-361152.47182837734,290.59113263667587,237.5626678984939\n", "2000,-358285.09682837734,302.79078945563003,237.5626678984939\n", "3000,-358005.84682837734,302.48286620646525,237.5626678984939\n", "4000,-358507.72182837734,298.6930169859535,237.5626678984939\n", "5000,-358184.97182837734,299.2717701713331,237.5626678984939\n", "6000,-358212.97182837734,300.75294253983,237.5626678984939\n", "7000,-359764.59682837734,300.86799019463365,237.5626678984939\n", "8000,-358504.22182837734,300.08571555582586,237.5626678984939\n", "9000,-358743.72182837734,301.49754076972073,237.5626678984939\n", "10000,-358427.47182837734,303.0196359235443,237.5626678984939\n" ] } ], "source": [ "print(\"Running NVT\")\n", "simulation.step(10000)" ] }, { "attachments": {}, "cell_type": "markdown", "id": "18726d22", "metadata": {}, "source": [ "### NPT production MD" ] }, { "attachments": {}, "cell_type": "markdown", "id": "0e0a8f38", "metadata": {}, "source": [ "To run our simulation in the NPT ensemble we need to add in a barostat to control the pressure. We can use `MonteCarloBarostat`." ] }, { "cell_type": "code", "execution_count": 10, "id": "50867f80", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Running NPT\n", "11000,-360868.2039845481,296.6271613599709,229.55243059554863\n", "12000,-360440.69597966364,299.2972740816768,227.9584335998326\n", "13000,-360306.2146281218,298.81725153096374,226.29494575252173\n", "14000,-361092.9398954578,303.07884143773134,225.42478987487024\n", "15000,-360441.3635788809,300.7599116506667,225.36581137758682\n", "16000,-360902.0646238751,298.85839880440795,224.7134712811861\n", "17000,-361590.4094829492,298.67191986774935,224.97738234573134\n", "18000,-360249.67117970064,296.2367386071592,224.69872883856726\n", "19000,-360755.6596395951,302.12766052941635,224.73491745579543\n", "20000,-361129.44742261735,298.26462186445406,225.16297011700198\n" ] } ], "source": [ "system.addForce(MonteCarloBarostat(1*bar, 300*kelvin))\n", "simulation.context.reinitialize(preserveState=True)\n", "\n", "\n", "print(\"Running NPT\")\n", "simulation.step(10000)" ] }, { "attachments": {}, "cell_type": "markdown", "id": "b4c7b6be", "metadata": {}, "source": [ "### Analysis\n", "\n", "We can now do some basic analysis using Python. We will plot the time evolution of the potential energy, temperature, and box volume. Remember that OpenMM itself is primarly an MD engine, for in-depth anaylsis of your simulations you can use other python packages such as MDtraj, or MDAnalysis." ] }, { "cell_type": "code", "execution_count": 11, "id": "5ad85795", "metadata": {}, "outputs": [ { "data": { "image/png": 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", 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", 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", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "import numpy as np\n", "import matplotlib.pyplot as plt\n", "data = np.loadtxt(\"md_log.txt\", delimiter=',')\n", "\n", "step = data[:,0]\n", "potential_energy = data[:,1]\n", "temperature = data[:,2]\n", "volume = data[:,3]\n", "\n", "plt.plot(step, potential_energy)\n", "plt.xlabel(\"Step\")\n", "plt.ylabel(\"Potential energy (kJ/mol)\")\n", "plt.show()\n", "plt.plot(step, temperature)\n", "plt.xlabel(\"Step\")\n", "plt.ylabel(\"Temperature (K)\")\n", "plt.show()\n", "plt.plot(step, volume)\n", "plt.xlabel(\"Step\")\n", "plt.ylabel(\"Volume (nm^3)\")\n", "plt.show()\n", "\n" ] } ], "metadata": { "kernelspec": { "display_name": "cookbook", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.10.8" }, "nbsphinx": { "execute": "never" }, "tags": [ "tutorial" ], "vscode": { "interpreter": { "hash": "0196bde48eca6e98b9d405f49c02d8b38bda65759256048592a275ce0440cb5b" } } }, "nbformat": 4, "nbformat_minor": 5 }