{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Moi D"],"funding":["Swiss National Science Foundation"],"pagination":["2492-2502"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC12700828"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["32(12)"],"pubmed_abstract":["Recent advances in artificial-intelligence-based protein structure modeling have yielded remarkable progress in predicting protein structures. Because structures are constrained by their biological function, their geometry tends to evolve more slowly than the underlying amino acids sequences. This feature of structures could in principle be used to reconstruct phylogenetic trees over longer evolutionary timescales than sequence-based approaches; however, until now, a reliable structure-based tree-building method has been elusive. Here, we introduce a rigorous framework for empirical tree accuracy evaluation and tested multiple approaches using sequence and structure information. The best results were obtained by inferring trees from sequences aligned using a local structural alphabet-an ap"],"journal":["Nature structural & molecular biology"],"pubmed_title":["Structural phylogenetics unravels the evolutionary diversification of communication systems in gram-positive bacteria and their viruses."],"pmcid":["PMC12700828"],"funding_grant_id":["205085","216623"],"pubmed_authors":["Nevers Y","Bernard C","Dessimoz C","Langleib M","Moi D","Steinegger M"],"additional_accession":[]},"is_claimable":false,"name":"Structural phylogenetics unravels the evolutionary diversification of communication systems in gram-positive bacteria and their viruses.","description":"Recent advances in artificial-intelligence-based protein structure modeling have yielded remarkable progress in predicting protein structures. Because structures are constrained by their biological function, their geometry tends to evolve more slowly than the underlying amino acids sequences. This feature of structures could in principle be used to reconstruct phylogenetic trees over longer evolutionary timescales than sequence-based approaches; however, until now, a reliable structure-based tree-building method has been elusive. Here, we introduce a rigorous framework for empirical tree accuracy evaluation and tested multiple approaches using sequence and structure information. The best results were obtained by inferring trees from sequences aligned using a local structural alphabet-an ap","dates":{"release":"2025-01-01T00:00:00Z","publication":"2025 Dec","modification":"2026-06-06T02:08:54.806Z","creation":"2026-05-24T03:12:26.708Z"},"accession":"S-EPMC12700828","cross_references":{"pubmed":["41073779"],"doi":["10.1038/s41594-025-01649-8"]}}