{"id":38824,"date":"2026-04-27T08:50:22","date_gmt":"2026-04-27T12:50:22","guid":{"rendered":"https:\/\/www.iff.com\/?p=38824"},"modified":"2026-04-27T09:06:20","modified_gmt":"2026-04-27T13:06:20","slug":"decoding-protein-dynamics","status":"publish","type":"post","link":"https:\/\/www.iff.com\/es\/media\/stories\/decoding-protein-dynamics\/","title":{"rendered":"ProFlex as a linguistic bridge for decoding protein dynamics in normal mode analysis &#8211; Damian J. Magill."},"content":{"rendered":"<div id=\"ez-toc-container\" class=\"ez-toc-v2_0_88 counter-hierarchy ez-toc-counter ez-toc-grey ez-toc-container-direction\">\n<div class=\"ez-toc-title-container\">\n<p class=\"ez-toc-title\" style=\"cursor:inherit\">Table of Contents<\/p>\n<span class=\"ez-toc-title-toggle\"><a href=\"#\" class=\"ez-toc-pull-right ez-toc-btn ez-toc-btn-xs ez-toc-btn-default ez-toc-toggle\" aria-label=\"Toggle Table of Content\"><span class=\"ez-toc-js-icon-con\"><span class=\"\"><span class=\"eztoc-hide\" style=\"display:none;\">Toggle<\/span><span class=\"ez-toc-icon-toggle-span\"><svg style=\"fill: #999;color:#999\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" class=\"list-377408\" width=\"20px\" height=\"20px\" viewbox=\"0 0 24 24\" fill=\"none\"><path d=\"M6 6H4v2h2V6zm14 0H8v2h12V6zM4 11h2v2H4v-2zm16 0H8v2h12v-2zM4 16h2v2H4v-2zm16 0H8v2h12v-2z\" fill=\"currentColor\"><\/path><\/svg><svg style=\"fill: #999;color:#999\" class=\"arrow-unsorted-368013\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"10px\" height=\"10px\" viewbox=\"0 0 24 24\" version=\"1.2\" baseprofile=\"tiny\"><path d=\"M18.2 9.3l-6.2-6.3-6.2 6.3c-.2.2-.3.4-.3.7s.1.5.3.7c.2.2.4.3.7.3h11c.3 0 .5-.1.7-.3.2-.2.3-.5.3-.7s-.1-.5-.3-.7zM5.8 14.7l6.2 6.3 6.2-6.3c.2-.2.3-.5.3-.7s-.1-.5-.3-.7c-.2-.2-.4-.3-.7-.3h-11c-.3 0-.5.1-.7.3-.2.2-.3.5-.3.7s.1.5.3.7z\"\/><\/svg><\/span><\/span><\/span><\/a><\/span><\/div>\n<nav><ul class='ez-toc-list ez-toc-list-level-1' ><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-1\" href=\"https:\/\/www.iff.com\/es\/media\/stories\/decoding-protein-dynamics\/#Executive_Insight\" >Executive Insight<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-2\" href=\"https:\/\/www.iff.com\/es\/media\/stories\/decoding-protein-dynamics\/#Why_This_Research_Matters\" >Why This Research Matters<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-3\" href=\"https:\/\/www.iff.com\/es\/media\/stories\/decoding-protein-dynamics\/#About_the_Authors\" >About the Authors<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-4\" href=\"https:\/\/www.iff.com\/es\/media\/stories\/decoding-protein-dynamics\/#Practical_Applications_in_Food_Biosciences\" >Practical Applications in Food Biosciences<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-5\" href=\"https:\/\/www.iff.com\/es\/media\/stories\/decoding-protein-dynamics\/#How_This_Research_Was_Conducted\" >How This Research Was Conducted<\/a><\/li><li class='ez-toc-page-1 ez-toc-heading-level-2'><a class=\"ez-toc-link ez-toc-heading-6\" href=\"https:\/\/www.iff.com\/es\/media\/stories\/decoding-protein-dynamics\/#Explore_the_Full_Scientific_Paper\" >Explore the Full Scientific Paper<\/a><\/li><\/ul><\/nav><\/div>\n<h2 class=\"wp-block-heading\" id=\"h-executive-insight\"><span class=\"ez-toc-section\" id=\"Executive_Insight\"><\/span><strong>Executive Insight<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">In this work, we introduce ProFlex, a scalable and interpretable representation of protein flexibility. By compressing large scale normal mode analysis into a one-dimensional alphabet, ProFlex enables flexibility to be treated much like sequence or secondary structure data rendering it searchable, comparable, and compatible with existing bioinformatics and machine learning workflows. This makes it possible to integrate dynamic information into routine R&amp;D activities, including candidate ranking, variant prioritization, structure function analysis, and cross family comparison, while remaining computationally tractable at industrial scale.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-why-this-research-matters\"><span class=\"ez-toc-section\" id=\"Why_This_Research_Matters\"><\/span><strong>Why This Research Matters<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Advances in protein structure prediction have dramatically expanded the available structural landscape, which creates many new opportunities for innovation in enzyme discovery, strain development, and functional protein optimization.<br>However, most workflows still struggle to fully leverage this information on a scale. Static structures alone rarely explain everything, with key functional traits determined by protein flexibility. Flexibility is often assessed indirectly, experimentally, or not at all, limiting its integration into high throughput screening and computational pipelines.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-about-the-authors\"><span class=\"ez-toc-section\" id=\"About_the_Authors\"><\/span><strong>About the Authors<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">This research has been conducted by IFF\u2019s Expert Contributor Damian Magill in collaboration with Dr Timofey Skvortsov from the School of Pharmacy at\u00a0<a href=\"https:\/\/scholar.google.com\/citations?view_op=view_org&amp;hl=en&amp;org=2175268696339219833\" target=\"_blank\" rel=\"noreferrer noopener\">Queen&#8217;s University Belfast<\/a>.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Read more on this research from Damian.This research has been conducted by IFF\u2019s Expert Contributor Damian Magill in collaboration with Dr Timofey Skvortsov from the School of Pharmacy at\u00a0<a href=\"https:\/\/scholar.google.com\/citations?view_op=view_org&amp;hl=en&amp;org=2175268696339219833\" target=\"_blank\" rel=\"noreferrer noopener\">Queen&#8217;s University Belfast<\/a>.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Read more on this research from Damian.<\/p>\n\n\n<div class=\"wp-block-image\">\n<figure class=\"alignleft size-large is-resized\"><img loading=\"lazy\" decoding=\"async\" width=\"811\" height=\"1024\" src=\"https:\/\/www.iff.com\/wp-content\/uploads\/2026\/03\/P1220291-811x1024.jpg\" alt=\"\" class=\"wp-image-44671\" style=\"aspect-ratio:0.7920091929638469;width:187px;height:auto\" srcset=\"https:\/\/www.iff.com\/wp-content\/uploads\/2026\/03\/P1220291-811x1024.jpg 811w, https:\/\/www.iff.com\/wp-content\/uploads\/2026\/03\/P1220291-238x300.jpg 238w, https:\/\/www.iff.com\/wp-content\/uploads\/2026\/03\/P1220291-768x970.jpg 768w, https:\/\/www.iff.com\/wp-content\/uploads\/2026\/03\/P1220291-158x200.jpg 158w, https:\/\/www.iff.com\/wp-content\/uploads\/2026\/03\/P1220291.jpg 833w\" sizes=\"auto, (max-width: 811px) 100vw, 811px\" \/><\/figure>\n<\/div>\n\n\n<p class=\"wp-block-paragraph\"><strong>How can ProFlex help researchers make better use of protein structures for functional insight?<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Expert Contributor <a href=\"https:\/\/www.iff.com\/es\/experts\/dr-damian-magill\/\" target=\"_blank\" rel=\"noreferrer noopener\">Dr. Damian Magill<\/a><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Sr. Scientist II, R&amp;D \u2013 H&amp;B<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">AI tools such as AlphaFold have generated hundreds of thousands of high\u2011quality protein structures but translating this static structural information into functional insight remains a challenge. ProFlex addresses this gap by converting complex protein dynamics into a simple, interpretable alphabet that captures relative flexibility along the protein sequence. This enables rapid comparison, large\u2011scale screening, and sequence\u2011based analyses of protein motion without the need for computationally intensive molecular dynamics simulations. In practical terms, ProFlex can help individuals identify flexible or rigid regions linked to stability, activity, or regulation, prioritize protein variants, and integrate dynamic information into existing bioinformatics workflows. This makes protein dynamics accessible, scalable, and actionable for applied research and innovation.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-practical-applications-in-food-biosciences\"><span class=\"ez-toc-section\" id=\"Practical_Applications_in_Food_Biosciences\"><\/span><strong>Practical Applications in Food Biosciences<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">ProFlex enables the systematic exploitation of protein dynamics across multiple application domains, including:<\/p>\n\n\n\n<ul class=\"wp-block-list\">\n<li>Application of conventional bioinformatics and sequence-based algorithms to protein flexibility data.<\/li>\n\n\n\n<li>Refinement of structural models, particularly in regions of low confidence or poor experimental support.<\/li>\n\n\n\n<li>Generation of novel, dynamics-informed features for machine learning and predictive modeling.<\/li>\n\n\n\n<li>Enhancement of structural phylogenetic analyses through the integration of protein dynamics information.<\/li>\n<\/ul>\n\n\n\n<p class=\"wp-block-paragraph\">By compressing complex dynamic behavior into compact, interpretable representations, ProFlex allows organizations to extract greater value from existing protein structure data.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-how-this-research-was-conducted\"><span class=\"ez-toc-section\" id=\"How_This_Research_Was_Conducted\"><\/span><strong>How This Research Was Conducted<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Researchers conducted normal mode analysis of over 500,000 alphafold generated protein structures. These were used to empirically define an alphabet representing the relative flexibility of each structure known as ProFlex. Biological insights and applications of ProFlex were thoroughly evaluated.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\" id=\"h-explore-the-full-scientific-paper\"><span class=\"ez-toc-section\" id=\"Explore_the_Full_Scientific_Paper\"><\/span><strong>Explore the Full Scientific Paper<\/strong><span class=\"ez-toc-section-end\"><\/span><\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Read the full peer\u2011reviewed publication in Nature Communications for detailed methods, data, and results.<\/p>\n\n\n\n<div class=\"wp-block-buttons is-content-justification-center is-layout-flex wp-container-core-buttons-is-layout-fe48e5de wp-block-buttons-is-layout-flex\">\n<div class=\"wp-block-button\"><a class=\"wp-block-button__link wp-element-button\" href=\"https:\/\/www.nature.com\/articles\/s41467-025-64103-9\" target=\"_blank\" rel=\"noreferrer noopener\">Read the full paper<\/a><\/div>\n<\/div>\n\n\n\n<p class=\"wp-block-paragraph\"><\/p>","protected":false},"excerpt":{"rendered":"<p>Executive Insight In this work, we introduce ProFlex, a scalable and interpretable representation of protein flexibility. By compressing large scale normal mode analysis into a one-dimensional alphabet, ProFlex enables flexibility to be treated much like&#8230;<\/p>","protected":false},"author":69,"featured_media":38807,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"inline_featured_image":false,"footnotes":""},"categories":[414,62],"tags":[330,422],"class_list":["post-38824","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-bioscience","category-food-beverage","tag-food-biosciences","tag-scientific-papers"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v25.8 (Yoast SEO v28.6) - https:\/\/yoast.com\/product\/yoast-seo-premium-wordpress\/ -->\n<title>ProFlex I Scalable representation of protein flexibility<\/title>\n<meta name=\"description\" content=\"ProFlex transforms protein dynamics into a clear, one\u2011dimensional code, enabling fast comparison, variant prioritization, and large\u2011scale functional analysis across protein families.\" \/>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.iff.com\/es\/media\/stories\/decoding-protein-dynamics\/\" \/>\n<meta property=\"og:locale\" content=\"es_ES\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"ProFlex as a linguistic bridge for decoding protein dynamics in normal mode analysis - Damian J. 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