{"id":13731,"date":"2025-01-16T10:22:48","date_gmt":"2025-01-16T09:22:48","guid":{"rendered":"https:\/\/www.cinam.univ-mrs.fr\/cinam\/?p=13731"},"modified":"2025-01-16T13:29:57","modified_gmt":"2025-01-16T12:29:57","slug":"how-do-particles-with-complex-interactions-self-assemble","status":"publish","type":"post","link":"https:\/\/www.cinam.univ-mrs.fr\/cinam\/en\/2025\/01\/16\/how-do-particles-with-complex-interactions-self-assemble\/","title":{"rendered":"How Do Particles with Complex Interactions Self-Assemble ?"},"content":{"rendered":"<p><strong>Authors<\/strong> : Lara Koehler, Pierre Ronceray and Martin Lenz<\/p>\n<p><strong>Summary :<\/strong><\/p>\n<p>Cells are largely powered by molecular machines made of protein components. In disease, proteins also assemble, albeit into deleterious fibrous structures. Predicting what structure will self-assemble from a collection of proteins is difficult, however, as their interactions result from a mixture of many competing physicochemical effects. Here, we use a model of this competition to show that, despite its complexity, it tends to favor a relatively small set of large-scale structures, from fibers to liquidlike droplets to crystals riddled with holes.<\/p>\n<p>We introduce a minimal model of self-assembling particles on a lattice with 21 independent interaction parameters and show that it produces a range of equilibrium aggregate morphologies in numerical simulations. We then use machine learning to show that the resulting morphologies can be grouped into a small number of categories with the same aggregate dimensionality and orientational order, and to identify a simple predictor of the outcome of the assembly process. Particles with highly asymmetric interactions can result in morphologies reminiscent of those found in proteins.<\/p>\n<p>This study helps identify features that determine the emergence of self-assembled structure from a given set of interactions, which could lead to a better understanding of proteins in disease and inspire designs for artificial self-assembling nanomachines.<\/p>\n<p><a href=\"https:\/\/doi.org\/10.1103\/PhysRevX.14.041061?_gl=1*1f0nvun*_gcl_au*MTY5NTM4MjU3MS4xNzM3MDIyODQ5*_ga*NjkzNDMxNjM0LjE3MzcwMjI4NDg.*_ga_ZS5V2B2DR1*MTczNzAyMjg0OC4xLjAuMTczNzAyMjg0OC42MC4wLjk3NzI4MzM5NA..\">https:\/\/doi.org\/10.1103\/PhysRevX.14.041061?<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>A new publication in PIV Department<\/p>\n","protected":false},"author":16,"featured_media":13729,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":[],"categories":[31],"tags":[],"aioseo_notices":[],"_links":{"self":[{"href":"https:\/\/www.cinam.univ-mrs.fr\/cinam\/en\/wp-json\/wp\/v2\/posts\/13731"}],"collection":[{"href":"https:\/\/www.cinam.univ-mrs.fr\/cinam\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.cinam.univ-mrs.fr\/cinam\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.cinam.univ-mrs.fr\/cinam\/en\/wp-json\/wp\/v2\/users\/16"}],"replies":[{"embeddable":true,"href":"https:\/\/www.cinam.univ-mrs.fr\/cinam\/en\/wp-json\/wp\/v2\/comments?post=13731"}],"version-history":[{"count":8,"href":"https:\/\/www.cinam.univ-mrs.fr\/cinam\/en\/wp-json\/wp\/v2\/posts\/13731\/revisions"}],"predecessor-version":[{"id":13742,"href":"https:\/\/www.cinam.univ-mrs.fr\/cinam\/en\/wp-json\/wp\/v2\/posts\/13731\/revisions\/13742"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.cinam.univ-mrs.fr\/cinam\/en\/wp-json\/wp\/v2\/media\/13729"}],"wp:attachment":[{"href":"https:\/\/www.cinam.univ-mrs.fr\/cinam\/en\/wp-json\/wp\/v2\/media?parent=13731"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.cinam.univ-mrs.fr\/cinam\/en\/wp-json\/wp\/v2\/categories?post=13731"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.cinam.univ-mrs.fr\/cinam\/en\/wp-json\/wp\/v2\/tags?post=13731"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}