{"id":4514,"date":"2025-11-07T12:59:23","date_gmt":"2025-11-07T03:59:23","guid":{"rendered":"https:\/\/bdsl.jbnu.ac.kr\/blog\/?p=4514"},"modified":"2026-10-27T16:59:47","modified_gmt":"2026-10-27T07:59:47","slug":"autodock-vina-simple-example","status":"publish","type":"post","link":"https:\/\/bdsl.jbnu.ac.kr\/blog\/autodock-vina-simple-example\/","title":{"rendered":"AutoDock Vina &#8211; simple example"},"content":{"rendered":"\n<h2 class=\"wp-block-heading\">Introduction <\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">In this exercise, we will perform a molecular docking simulation using <strong>AutoDock Vina<\/strong> to predict the binding orientation of a ligand within the binding site of a receptor protein.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Molecular docking explores possible ligand conformations and orientations within a defined region of the receptor. AutoDock Vina evaluates these binding poses using a scoring function that estimates binding affinity.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">We will use the <strong>Python interface of AutoDock Vina<\/strong> to perform docking, examine predicted binding affinities, and save the resulting ligand conformations for subsequent structural analysis using PyMOL.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">1. Download the input files<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">The receptor and ligand structures have already been prepared in PDBQT format.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Download the following files and place them in your Jupyter notebook working directory.<\/p>\n\n\n\n<div class=\"wp-block-file\"><a id=\"wp-block-file--media-983cb727-42a3-436d-bbc2-f5bc44239bcc\" href=\"https:\/\/bdsl.jbnu.ac.kr\/blog\/wp-content\/uploads\/2025\/11\/ligand.pdbqt\">ligand<\/a><a href=\"https:\/\/bdsl.jbnu.ac.kr\/blog\/wp-content\/uploads\/2025\/11\/ligand.pdbqt\" class=\"wp-block-file__button wp-element-button\" download aria-describedby=\"wp-block-file--media-983cb727-42a3-436d-bbc2-f5bc44239bcc\">Download<\/a><\/div>\n\n\n\n<div class=\"wp-block-file\"><a id=\"wp-block-file--media-124c6a0b-2d29-4938-9649-a3b2a89b2285\" href=\"https:\/\/bdsl.jbnu.ac.kr\/blog\/wp-content\/uploads\/2025\/11\/receptor.pdbqt\">receptor<\/a><a href=\"https:\/\/bdsl.jbnu.ac.kr\/blog\/wp-content\/uploads\/2025\/11\/receptor.pdbqt\" class=\"wp-block-file__button wp-element-button\" download aria-describedby=\"wp-block-file--media-124c6a0b-2d29-4938-9649-a3b2a89b2285\">Download<\/a><\/div>\n\n\n\n<figure class=\"wp-block-table\"><table class=\"has-fixed-layout\"><tbody><tr><th>File<\/th><th>Description<\/th><\/tr><tr><td><code>receptor.pdbqt<\/code><\/td><td>Prepared protein receptor containing atomic coordinates, atom types, and partial charges<\/td><\/tr><tr><td><code>ligand.pdbqt<\/code><\/td><td>Prepared ligand containing atomic coordinates, atom types, partial charges, and rotatable bond information<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<p class=\"wp-block-paragraph\"><\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Preparation of files for docking simulation<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">The procedure to prepare docking can be found: <\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><a href=\"https:\/\/bdsl.jbnu.ac.kr\/blog\/prepare-docking-simulation-for-autodock-vina\/\" data-type=\"post\" data-id=\"5053\">Prepare docking simulation for autodock vina<\/a><\/p>\n\n\n\n<h2 class=\"wp-block-heading\">2. Perform molecular docking<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Execute the following Python code in a Jupyter notebook.<\/p>\n\n\n\n<pre class=\"wp-block-code\"><code lang=\"python\" class=\"language-python\">from vina import Vina\n# Load Vina object\nv = Vina(sf_name='vina')\n\n# Set the receptor and ligand\nv.set_receptor('receptor.pdbqt')\nv.set_ligand_from_file('ligand.pdbqt')\n\n# Define the docking box\nv.compute_vina_maps(center=[63.051, &nbsp;22.770, &nbsp;15.879], box_size=[20, 20, 20])\n\n# Perform docking\nv.dock(exhaustiveness=32, n_poses=50)\n\n# Save the results\nv.write_poses('docked_ligand.pdbqt', n_poses=50, overwrite=True)\n<\/code><\/pre>\n\n\n\n<h4 class=\"wp-block-heading\">Explanation of the parameters<\/h4>\n\n\n\n<figure class=\"wp-block-table\"><table class=\"has-fixed-layout\"><tbody><tr><th>Parameter<\/th><th>Description<\/th><\/tr><tr><td><code>sf_name='vina'<\/code><\/td><td>Selects the AutoDock Vina scoring function<\/td><\/tr><tr><td><code>set_receptor()<\/code><\/td><td>Loads the prepared receptor structure<\/td><\/tr><tr><td><code>set_ligand_from_file()<\/code><\/td><td>Loads the prepared ligand structure<\/td><\/tr><tr><td><code>center<\/code><\/td><td>Specifies the center of the docking search box in \u00c5<\/td><\/tr><tr><td><code>box_size<\/code><\/td><td>Specifies the dimensions of the search box in \u00c5<\/td><\/tr><tr><td><code>exhaustiveness=32<\/code><\/td><td>Controls the thoroughness of the conformational search<\/td><\/tr><tr><td><code>n_poses=50<\/code><\/td><td>Requests up to 50 predicted binding poses<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<p class=\"wp-block-paragraph\">The docking box defines the three-dimensional region in which AutoDock Vina searches for possible ligand-binding conformations. In this example, a cubic search box of 20 \u00d7 20 \u00d7 20 \u00c5 is centered at the specified coordinates.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The <code>exhaustiveness<\/code> parameter controls the computational effort devoted to searching for binding poses. Higher values generally increase computational time and may improve the thoroughness of the search.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">3. Examine the docking results<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">After docking, the predicted binding poses can be evaluated using their estimated binding affinities.<\/p>\n\n\n\n<pre class=\"wp-block-code\"><code lang=\"python\" class=\"language-python\"># Retrieve predicted binding energies and RMSD values\nenergies = v.energies(n_poses=50)\n\n# Display the results\nprint(energies)<\/code><\/pre>\n\n\n\n<p class=\"wp-block-paragraph\">The output contains the estimated binding energy (kcal\/mol) and RMSD-related values for each predicted pose.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Interpretation<\/h3>\n\n\n\n<ul class=\"wp-block-list\">\n<li>More negative binding energies indicate more favorable predicted binding according to the Vina scoring function.<\/li>\n\n\n\n<li>RMSD values describe the structural differences between predicted ligand poses.<\/li>\n\n\n\n<li>The lowest-energy pose is generally ranked as the most favorable predicted binding conformation.<\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\">Note that docking scores are approximate and should not be interpreted as experimentally measured binding affinities.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">4. Save and visualize the docking results<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">The predicted ligand conformations are saved in:<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><code>docked_ligand.pdbqt<\/code><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">This file can be converted into PDB format using Open Babel for visualization in PyMOL.<\/p>\n\n\n\n<pre class=\"wp-block-code\"><code lang=\"python\" class=\"language-python\">!obabel docked_ligand.pdbqt -O docked_ligand.pdb<\/code><\/pre>\n\n\n\n<p class=\"wp-block-paragraph\">Open the receptor structure and the predicted ligand poses in PyMOL to examine their spatial relationships.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">For detailed analysis, students should compare the predicted ligand-binding orientations, identify amino acid residues near the ligand, and examine possible interactions such as hydrogen bonds and hydrophobic contacts.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">5. Questions for discussion <\/h2>\n\n\n\n<ol start=\"1\" class=\"wp-block-list\">\n<li>What is the predicted binding affinity of the highest-ranked ligand pose?<\/li>\n\n\n\n<li>How do the predicted ligand conformations differ from one another?<\/li>\n\n\n\n<li>Which amino acid residues are located near the predicted ligand-binding site?<\/li>\n\n\n\n<li>How does changing the docking search box or exhaustiveness parameter affect the docking results?<\/li>\n\n\n\n<li>What are the major limitations of molecular docking in predicting protein\u2013ligand interactions?<\/li>\n<\/ol>\n","protected":false},"excerpt":{"rendered":"<p>Introduction In this exercise, we will perform a molecular docking simulation using AutoDock Vina to predict the binding orientation of a ligand within the binding site of a receptor protein. Molecular docking explores possible ligand conformations and orientations within a defined region of the receptor. AutoDock Vina evaluates these binding poses using a scoring function [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_uag_custom_page_level_css":"","site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"default","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","ast-disable-related-posts":"","theme-transparent-header-meta":"","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"set","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"ast-content-background-meta":{"desktop":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"footnotes":""},"categories":[1],"tags":[],"class_list":["post-4514","post","type-post","status-publish","format-standard","hentry","category-uncategorized"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v28.8 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>AutoDock Vina - simple example - Biomedical Data Science Laboratory<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/bdsl.jbnu.ac.kr\/blog\/autodock-vina-simple-example\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"AutoDock Vina - simple example - Biomedical Data Science Laboratory\" \/>\n<meta property=\"og:description\" content=\"Introduction In this exercise, we will perform a molecular docking simulation using AutoDock Vina to predict the binding orientation of a ligand within the binding site of a receptor protein. 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Molecular docking explores possible ligand conformations and orientations within a defined region of the receptor. AutoDock Vina evaluates these binding poses using a scoring function&hellip;","_links":{"self":[{"href":"https:\/\/bdsl.jbnu.ac.kr\/blog\/wp-json\/wp\/v2\/posts\/4514","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/bdsl.jbnu.ac.kr\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/bdsl.jbnu.ac.kr\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/bdsl.jbnu.ac.kr\/blog\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/bdsl.jbnu.ac.kr\/blog\/wp-json\/wp\/v2\/comments?post=4514"}],"version-history":[{"count":4,"href":"https:\/\/bdsl.jbnu.ac.kr\/blog\/wp-json\/wp\/v2\/posts\/4514\/revisions"}],"predecessor-version":[{"id":5061,"href":"https:\/\/bdsl.jbnu.ac.kr\/blog\/wp-json\/wp\/v2\/posts\/4514\/revisions\/5061"}],"wp:attachment":[{"href":"https:\/\/bdsl.jbnu.ac.kr\/blog\/wp-json\/wp\/v2\/media?parent=4514"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/bdsl.jbnu.ac.kr\/blog\/wp-json\/wp\/v2\/categories?post=4514"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/bdsl.jbnu.ac.kr\/blog\/wp-json\/wp\/v2\/tags?post=4514"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}