

{"id":669,"date":"2025-06-03T10:47:00","date_gmt":"2025-06-03T14:47:00","guid":{"rendered":"https:\/\/sites.temple.edu\/voelzlab\/?p=669"},"modified":"2025-08-26T10:50:02","modified_gmt":"2025-08-26T14:50:02","slug":"new-jcim-paper-on-optimizing-alchemical-intermediates","status":"publish","type":"post","link":"https:\/\/sites.temple.edu\/voelzlab\/2025\/06\/03\/new-jcim-paper-on-optimizing-alchemical-intermediates\/","title":{"rendered":"New JCIM paper on optimizing alchemical intermediates"},"content":{"rendered":"\n<p>Excited to share work now out in <em>Journal of Chemical Information and Modeling<\/em> :<\/p>\n\n\n\n<p>Novack, Dylan, Robert M. Raddi, Si Zhang, Matthew F. D. Hurley, and Vincent A. Voelz.<strong>Simple Method to Optimize the Spacing and Number of Alchemical Intermediates in Expanded Ensemble Free Energy Calculations.<\/strong> <em>Journal of Chemical Information and Modeling<\/em> 65, no. 12 (2025): 6089\u20136101. <a href=\"https:\/\/doi.org\/10.1021\/acs.jcim.5c00704\">https:\/\/doi.org\/10.1021\/acs.jcim.5c00704<\/a><\/p>\n\n\n\n<p>First, we estimate the thermodynamic length between intermediates using a short expanded-ensemble (EE) simulation, and then use a cubic spline fit to do gradient-based optimization of the spacing.<\/p>\n\n\n\n<figure class=\"wp-block-image size-full is-resized\"><img loading=\"lazy\" decoding=\"async\" width=\"958\" height=\"738\" src=\"https:\/\/sites.temple.edu\/voelzlab\/files\/2025\/08\/L_alpha.png\" alt=\"\" class=\"wp-image-670\" style=\"width:303px;height:auto\" srcset=\"https:\/\/sites.temple.edu\/voelzlab\/files\/2025\/08\/L_alpha.png 958w, https:\/\/sites.temple.edu\/voelzlab\/files\/2025\/08\/L_alpha-300x231.png 300w, https:\/\/sites.temple.edu\/voelzlab\/files\/2025\/08\/L_alpha-768x592.png 768w\" sizes=\"auto, (max-width: 767px) 89vw, (max-width: 1000px) 54vw, (max-width: 1071px) 543px, 580px\" \/><\/figure>\n\n\n\n<p>Using the same approach, we also optimize the <em>number<\/em> of intermediates used in EE simulations, which sample all intermediates during a simulation by proposing\/accepting transitions between ensembles using Monte Carlo. Modeling this Markov process reveals the optimal number of intermediates that minimize the mixing time.<\/p>\n\n\n\n<p>Here\u2019s a result for a toy system of 1D harmonic potentials:<\/p>\n\n\n\n<figure class=\"wp-block-image size-large is-resized\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"795\" src=\"https:\/\/sites.temple.edu\/voelzlab\/files\/2025\/08\/mixing_time_toy-1024x795.png\" alt=\"\" class=\"wp-image-671\" style=\"width:308px;height:auto\" srcset=\"https:\/\/sites.temple.edu\/voelzlab\/files\/2025\/08\/mixing_time_toy-1024x795.png 1024w, https:\/\/sites.temple.edu\/voelzlab\/files\/2025\/08\/mixing_time_toy-300x233.png 300w, https:\/\/sites.temple.edu\/voelzlab\/files\/2025\/08\/mixing_time_toy-768x597.png 768w, https:\/\/sites.temple.edu\/voelzlab\/files\/2025\/08\/mixing_time_toy.png 1290w\" sizes=\"auto, (max-width: 767px) 89vw, (max-width: 1000px) 54vw, (max-width: 1071px) 543px, 580px\" \/><\/figure>\n\n\n\n<p>More mixing leads to smaller uncertainties. Sure enough, EE sampling with the optimal number of intermediates (K*=25) gives the lowest uncertainty.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large is-resized\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"751\" src=\"https:\/\/sites.temple.edu\/voelzlab\/files\/2025\/08\/error_vs_K-1024x751.png\" alt=\"\" class=\"wp-image-672\" style=\"width:344px;height:auto\" srcset=\"https:\/\/sites.temple.edu\/voelzlab\/files\/2025\/08\/error_vs_K-1024x751.png 1024w, https:\/\/sites.temple.edu\/voelzlab\/files\/2025\/08\/error_vs_K-300x220.png 300w, https:\/\/sites.temple.edu\/voelzlab\/files\/2025\/08\/error_vs_K-768x563.png 768w, https:\/\/sites.temple.edu\/voelzlab\/files\/2025\/08\/error_vs_K.png 1028w\" sizes=\"auto, (max-width: 767px) 89vw, (max-width: 1000px) 54vw, (max-width: 1071px) 543px, 580px\" \/><\/figure>\n\n\n\n<p>Does it work in realistic systems?\u00a0 You bet! \u00a0 Here\u2019s a relative binding free energy calculation where we alchemically transform Ala to Phe using <a href=\"https:\/\/github.com\/deGrootLab\/pmx\">pmx<\/a> in GROMACS.\u00a0 Optimized intermediates yield EE simulations that converge faster to accurate estimates.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large is-resized\"><img loading=\"lazy\" decoding=\"async\" width=\"811\" height=\"1024\" src=\"https:\/\/sites.temple.edu\/voelzlab\/files\/2025\/08\/A16F-811x1024.png\" alt=\"\" class=\"wp-image-674\" style=\"width:390px;height:auto\" srcset=\"https:\/\/sites.temple.edu\/voelzlab\/files\/2025\/08\/A16F-811x1024.png 811w, https:\/\/sites.temple.edu\/voelzlab\/files\/2025\/08\/A16F-238x300.png 238w, https:\/\/sites.temple.edu\/voelzlab\/files\/2025\/08\/A16F-768x969.png 768w, https:\/\/sites.temple.edu\/voelzlab\/files\/2025\/08\/A16F.png 1144w\" sizes=\"auto, (max-width: 767px) 89vw, (max-width: 1000px) 54vw, (max-width: 1071px) 543px, 580px\" \/><\/figure>\n\n\n\n<p>Want to try it yourself? Check out our freely available Python scripts at <a href=\"https:\/\/github.com\/vvoelz\/pylambdaopt\">https:\/\/github.com\/vvoelz\/pylambdaopt<\/a>.\u00a0<\/p>\n\n\n\n<p>We also note that this approach should also work well for other methods using exchanges between thermodynamic ensembles (REMD or HREX), with some adjustments. It could also improve uncertainties in NEW.\u00a0 If you are interested, let us know!<\/p>\n\n\n\n<p>&#8211;Vincent Voelz<br><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Excited to share work now out in Journal of Chemical Information and Modeling : Novack, Dylan, Robert M. Raddi, Si Zhang, Matthew F. D. Hurley, and Vincent A. Voelz.Simple Method to Optimize the Spacing and Number of Alchemical Intermediates in Expanded Ensemble Free Energy Calculations. Journal of Chemical Information and Modeling 65, no. 12 (2025): &hellip; <\/p>\n<p class=\"link-more\"><a href=\"https:\/\/sites.temple.edu\/voelzlab\/2025\/06\/03\/new-jcim-paper-on-optimizing-alchemical-intermediates\/\" class=\"more-link\">Continue reading<span class=\"screen-reader-text\"> &#8220;New JCIM paper on optimizing alchemical intermediates&#8221;<\/span><\/a><\/p>\n","protected":false},"author":1258,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"class_list":["post-669","post","type-post","status-publish","format-standard","hentry","category-uncategorized"],"_links":{"self":[{"href":"https:\/\/sites.temple.edu\/voelzlab\/wp-json\/wp\/v2\/posts\/669","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/sites.temple.edu\/voelzlab\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/sites.temple.edu\/voelzlab\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/sites.temple.edu\/voelzlab\/wp-json\/wp\/v2\/users\/1258"}],"replies":[{"embeddable":true,"href":"https:\/\/sites.temple.edu\/voelzlab\/wp-json\/wp\/v2\/comments?post=669"}],"version-history":[{"count":2,"href":"https:\/\/sites.temple.edu\/voelzlab\/wp-json\/wp\/v2\/posts\/669\/revisions"}],"predecessor-version":[{"id":675,"href":"https:\/\/sites.temple.edu\/voelzlab\/wp-json\/wp\/v2\/posts\/669\/revisions\/675"}],"wp:attachment":[{"href":"https:\/\/sites.temple.edu\/voelzlab\/wp-json\/wp\/v2\/media?parent=669"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/sites.temple.edu\/voelzlab\/wp-json\/wp\/v2\/categories?post=669"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/sites.temple.edu\/voelzlab\/wp-json\/wp\/v2\/tags?post=669"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}