ArticleNature structural & molecular biology2025
Structural phylogenetics unravels the evolutionary diversification of communication systems in gram-positive bacteria and their viruses.
Article in Nature structural & molecular biology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 53 papers.
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Who cites it
53 citing papers in PubMed.
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- Uncovering viral protein acquisition events and human-specific folds with pairwise comparisons of predicted protein structures.Molecular biology and evolution · 2026Article
- Novel Knotted Solenoid fold with order-shifted coil arrangement leads to nontrivial 3Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Protein folds and catalytic strategies at the origin of biological CO2 fixation.FEMS microbiology ecology · 2026Article
- Revealing deep evolutionary relationships between RNA viruses using predicted structural models of viral RNA polymerases.Molecular biology and evolution · 2026Article
- Cetacean coronavirus spikes highlight S glycoprotein structural plasticity.PLoS pathogens · 2026Article
- Regulated transformation system (RTS): sddi-mediated programmable shut-off and mode switching of base editors.Nucleic acids research · 2026Article
- Toward a genomic understanding of the tree of life.Molecular biology and evolution · 2026Article
- Non-peptide dysbiosis metabolites reprogram a peptide quorum-sensing receptor to induce sustained predation in beneficial streptococci.PLoS biology · 2026Article
- The first single-stranded DNA virus targeting Pectobacterium belongs to the family Microviridae and demonstrates a broad host range to Pectobacterium brasiliense soft rot pathogens.Archives of virology · 2026Article
- An ancient lysozyme in placozoans participates in acidic extracellular digestion.Communications biology · 2026Article
- Structome-AlignViewer: On Confidence Assessment in Structure-Aware Alignments.Genome biology and evolution · 2026Article
- Exploring the protein universe with distant similarity detection methods.Protein science : a publication of the Protein Society · 2026Review
- Comprehensive hallmark gene sequence, genomic and structural analysis clarifies new and established taxa within theVirus evolution · 2026Article
- Addressing convergence in the emerging era of structural phylogenetics.Frontiers in molecular biosciences · 2026Article
- AmpliPhy improves gene trees by adding homologous sequences without affecting alignments.Bioinformatics advances · 2026Article
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6 authors.
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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 approach robust to conformational changes that confound traditional structural distance measures. We illustrate the power of structure-informed phylogenetics by deciphering the evolutionary diversification of a particularly challenging family: the fast-evolving RRNPPA quorum-sensing receptors. We were able to propose a more parsimonious evolutionary history for this critical protein family that enables gram-positive bacteria, plasmids and bacteriophages to communicate and coordinate key behaviors. The advent of high-accuracy structural phylogenetics enables a myriad of applications across biology, such as uncovering deeper evolutionary relationships, elucidating unknown protein functions or refining the design of bioengineered molecules.
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