{"id":644,"date":"2025-09-20T20:56:43","date_gmt":"2025-09-21T02:56:43","guid":{"rendered":"https:\/\/lab.vanderbilt.edu\/zyang-lab\/?p=644"},"modified":"2025-09-21T10:09:20","modified_gmt":"2025-09-21T16:09:20","slug":"lassohtp-lassopred-a-high-throughput-software-to-automate-lasso-peptide-structure-prediction-and-modeling","status":"publish","type":"post","link":"https:\/\/lab.vanderbilt.edu\/zyang-lab\/2025\/09\/20\/lassohtp-lassopred-a-high-throughput-software-to-automate-lasso-peptide-structure-prediction-and-modeling\/","title":{"rendered":"LassoHTP\/LassoPred for Lasso Peptide Structure Prediction and Modeling"},"content":{"rendered":"<p><img decoding=\"async\" src=\"https:\/\/pubs.acs.org\/cms\/10.1021\/acs.jcim.2c00945\/asset\/images\/medium\/ci2c00945_0010.gif\" alt=\"Abstract Image\" \/><\/p>\n<p data-start=\"92\" data-end=\"487\">Lasso peptides (LaPs) are RiPPs with a characteristic slipknot (lariat-knot) topology that confers exceptional thermal stability, protease resistance, and often potent bioactivity. Despite thousands of LaP sequences identified by bioinformatics, only ~50 have experimentally determined structures, largely because their irregular scaffold and isopeptide bond confound general-purpose predictors.<\/p>\n<p data-start=\"489\" data-end=\"1223\">LassoPred\/LassoHTP enables end-to-end prediction and modeling of LaPs from sequence. It pairs a classifier that annotates ring, loop, and tail segments from sequence with a constructor that assembles constraint-consistent 3D models. The constructor comprises a scaffold constructor for knot-correct 3D topologies, a mutant generator for targeted or random mutagenesis, and an MD simulator for ensemble generation. The tool provides a practical engine for LaP structure generation, exploration, and variant design.<\/p>\n<p data-start=\"489\" data-end=\"1223\">Reecan Juarez and Ouyang Xingyu led the development of LassoHTP and LassoPred, respectively. Both tools are modified from the code base of EnzyHTP originally developed by Qianzhen Shao.<\/p>\n<p><strong>The software code<\/strong>:<\/p>\n<p>https:\/\/github.com\/ChemBioHTP\/LassoPred<\/p>\n<p><strong>Web Interface<\/strong>:<\/p>\n<p>https:\/\/lassopred.mutexa.org\/<\/p>\n<p><strong>Publications<\/strong>:<\/p>\n<p>https:\/\/www.nature.com\/articles\/s41467-025-60544-4<\/p>\n<p>https:\/\/pubs.acs.org\/doi\/10.1021\/acs.jcim.2c00945<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Lasso peptides (LaPs) are RiPPs with a characteristic slipknot (lariat-knot) topology that confers exceptional thermal stability, protease resistance, and often potent bioactivity. Despite thousands of LaP sequences identified by bioinformatics, only ~50 have experimentally determined structures, largely because their irregular scaffold and isopeptide bond confound general-purpose predictors. LassoPred\/LassoHTP enables end-to-end prediction and modeling of LaPs&#8230;<\/p>\n","protected":false},"author":253,"featured_media":655,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":"","_links_to":"","_links_to_target":""},"categories":[9],"tags":[],"class_list":["post-644","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-software"],"acf":[],"_links":{"self":[{"href":"https:\/\/lab.vanderbilt.edu\/zyang-lab\/wp-json\/wp\/v2\/posts\/644","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/lab.vanderbilt.edu\/zyang-lab\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/lab.vanderbilt.edu\/zyang-lab\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/lab.vanderbilt.edu\/zyang-lab\/wp-json\/wp\/v2\/users\/253"}],"replies":[{"embeddable":true,"href":"https:\/\/lab.vanderbilt.edu\/zyang-lab\/wp-json\/wp\/v2\/comments?post=644"}],"version-history":[{"count":5,"href":"https:\/\/lab.vanderbilt.edu\/zyang-lab\/wp-json\/wp\/v2\/posts\/644\/revisions"}],"predecessor-version":[{"id":648,"href":"https:\/\/lab.vanderbilt.edu\/zyang-lab\/wp-json\/wp\/v2\/posts\/644\/revisions\/648"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/lab.vanderbilt.edu\/zyang-lab\/wp-json\/wp\/v2\/media\/655"}],"wp:attachment":[{"href":"https:\/\/lab.vanderbilt.edu\/zyang-lab\/wp-json\/wp\/v2\/media?parent=644"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/lab.vanderbilt.edu\/zyang-lab\/wp-json\/wp\/v2\/categories?post=644"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/lab.vanderbilt.edu\/zyang-lab\/wp-json\/wp\/v2\/tags?post=644"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}