{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Q1 vs Q2 contact analysis\n", "\n", "Here we calculate a Q1 vs Q2 plot, where Q1 refers to fraction of native contacts along a trajectory with reference to the first frame, and Q2 represents the fraction of native contacts with reference to the last.\n", "\n", "**Last executed:** Sep 25, 2020 with MDAnalysis 1.0.0\n", "\n", "**Last updated:** June 29, 2020 with MDAnalysis 1.0.0\n", "\n", "**Minimum version of MDAnalysis:** 0.17.0\n", "\n", "**Packages required:**\n", " \n", "* MDAnalysis (Michaud-Agrawal *et al.*, 2011, Gowers *et al.*, 2016)\n", "* MDAnalysisTests\n", "* [matplotlib](https://matplotlib.org)\n", "* [pandas](https://pandas.pydata.org)\n", "\n", "**See also**\n", "\n", "* [Fraction of native contacts over a trajectory](contacts_native_fraction.ipynb)\n", "* [Write your own contacts analysis method](contacts_custom.ipynb)\n", "* [Contact analysis: number of contacts within a cutoff](contacts_within_cutoff.ipynb)\n", "\n", "
\n", " \n", "**Note**\n", "\n", "The `contacts.q1q2` function uses the `radius_cut_q` method to calculate the fraction of native contacts for a conformation by determining that atoms *i* and *j* are in contact if they are within a given radius (Franklin *et al.*, 2007, Best *et al.*, 2013)\n", "\n", "
" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "import MDAnalysis as mda\n", "from MDAnalysis.tests.datafiles import PSF, DCD\n", "from MDAnalysis.analysis import contacts\n", "\n", "import numpy as np\n", "import pandas as pd\n", "import matplotlib.pyplot as plt\n", "%matplotlib inline" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Background\n", "\n", "Please see the [Fraction of native contacts](contacts_native_fraction.ipynb#Background) for an introduction to general native contacts analysis." ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Loading files\n", "\n", "The test files we will be working with here feature adenylate kinase (AdK), a phosophotransferase enzyme. (Beckstein *et al.*, 2009) The trajectory ``DCD`` samples a transition from a closed to an open conformation." ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "u = mda.Universe(PSF, DCD)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## Calculating Q1 vs Q2" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We choose to calculate contacts for all the alpha-carbons in the protein, and define the contact radius cutoff at 8 Angstrom. [contacts.q1q2](https://docs.mdanalysis.org/stable/documentation_pages/analysis/contacts.html#MDAnalysis.analysis.contacts.q1q2) returns a `contacts.Contacts` object, which we can run directly." ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "q1q2 = contacts.q1q2(u, 'name CA', radius=8).run()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The data is in `q1q2.timeseries`. The first column of the data is always the frame number." ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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" ], "text/plain": [ " Frame Q1 Q2\n", "0 0.0 1.000000 0.946494\n", "1 1.0 0.980926 0.949262\n", "2 2.0 0.973660 0.952952\n", "3 3.0 0.972752 0.951107\n", "4 4.0 0.970027 0.948339" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "q1q2_df = pd.DataFrame(q1q2.timeseries, \n", " columns=['Frame', \n", " 'Q1', \n", " 'Q2'])\n", "q1q2_df.head()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Plotting" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "We can plot the fraction of native contacts over time." ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "scrolled": false }, "outputs": [ { "data": { "text/plain": [ "Text(0, 0.5, 'Fraction of native contacts')" ] }, "execution_count": 5, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "q1q2_df.plot(x='Frame')\n", "plt.ylabel('Fraction of native contacts')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Alternatively, we can create a Q1 vs Q2 plot to characterise the transition of AdK from its opened to closed position. " ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "q1q2_df.plot(x='Q1', y='Q2', legend=False)\n", "plt.ylabel('Q2');" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "## References\n", "\n", "[1] Oliver Beckstein, Elizabeth J. Denning, Juan R. Perilla, and Thomas B. Woolf.\n", "Zipping and Unzipping of Adenylate Kinase: Atomistic Insights into the Ensemble of OpenClosed Transitions.\n", "Journal of Molecular Biology, 394(1):160–176, November 2009.\n", "00107.\n", "URL: https://linkinghub.elsevier.com/retrieve/pii/S0022283609011164, doi:10.1016/j.jmb.2009.09.009.\n", "\n", "[2] R. B. Best, G. Hummer, and W. A. Eaton.\n", "Native contacts determine protein folding mechanisms in atomistic simulations.\n", "Proceedings of the National Academy of Sciences, 110(44):17874–17879, October 2013.\n", "00259.\n", "URL: http://www.pnas.org/cgi/doi/10.1073/pnas.1311599110, doi:10.1073/pnas.1311599110.\n", "\n", "[3] Joel Franklin, Patrice Koehl, Sebastian Doniach, and Marc Delarue.\n", "MinActionPath: maximum likelihood trajectory for large-scale structural transitions in a coarse-grained locally harmonic energy landscape.\n", "Nucleic Acids Research, 35(suppl_2):W477–W482, July 2007.\n", "00083.\n", "URL: https://academic.oup.com/nar/article-lookup/doi/10.1093/nar/gkm342, doi:10.1093/nar/gkm342.\n", "\n", "[4] Richard J. Gowers, Max Linke, Jonathan Barnoud, Tyler J. E. Reddy, Manuel N. Melo, Sean L. Seyler, Jan Domański, David L. Dotson, Sébastien Buchoux, Ian M. Kenney, and Oliver Beckstein.\n", "MDAnalysis: A Python Package for the Rapid Analysis of Molecular Dynamics Simulations.\n", "Proceedings of the 15th Python in Science Conference, pages 98–105, 2016.\n", "00152.\n", "URL: https://conference.scipy.org/proceedings/scipy2016/oliver_beckstein.html, doi:10.25080/Majora-629e541a-00e.\n", "\n", "[5] Naveen Michaud-Agrawal, Elizabeth J. Denning, Thomas B. Woolf, and Oliver Beckstein.\n", "MDAnalysis: A toolkit for the analysis of molecular dynamics simulations.\n", "Journal of Computational Chemistry, 32(10):2319–2327, July 2011.\n", "00778.\n", "URL: http://doi.wiley.com/10.1002/jcc.21787, doi:10.1002/jcc.21787." ] } ], "metadata": { "kernelspec": { "display_name": "Python (mda-user-guide)", "language": "python", "name": "mda-user-guide" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.8.3" }, "toc": { "base_numbering": 1, "nav_menu": {}, "number_sections": false, "sideBar": true, "skip_h1_title": false, "title_cell": "Table of Contents", "title_sidebar": "Contents", "toc_cell": false, "toc_position": {}, "toc_section_display": true, "toc_window_display": true } }, "nbformat": 4, "nbformat_minor": 2 }