ReviewGenome biology and evolution2025
Protein Structural Phylogenetics.
Review in Genome biology and evolution, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
11 citing papers in PubMed.
- Structural plasticity drives convergent evolution and functional diversification of GNAT polyamine acetyltransferases.Structure (London, England : 1993) · 2026Article
- Protein Structure Characters in the Light of Phylogenetic Systematics.Genome biology and evolution · 2026Article
- The Origins of GPCRs.International journal of molecular sciences · 2026Review
- Evolving strategies for virus discovery.Microbial genomics · 2026Review
- Functional evolution and rewiring of the UVR8-BES1/BIM1 module underpin the refinement of UV-B responses during plant terrestrialization.Plant communications · 2026Article
- Structural Evolution and Immunomodulatory Versatility of Fungal Immunomodulatory Proteins: Insights into Mechanisms and Bioproduction Strategies.Journal of agricultural and food chemistry · 2026Review
- Universal paralogs provide a window into evolution before the last universal common ancestor.Cell genomics · 2026Review
- Identification of novel metagenomic lipases through integrated structural and sequence-based analysis.PeerJ · 2026Article
- Addressing convergence in the emerging era of structural phylogenetics.Frontiers in molecular biosciences · 2026Article
- Structome-TM: complementing dataset assembly for structural phylogenetics by addressing size-based biases.Bioinformatics advances · 2026Article
- Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Protein structural phylogenetics is an interdisciplinary branch of molecular evolution that (i) uses 3D structural data to trace evolutionary histories, and (ii) uses these evolutionary relationships to explore the diversity of protein structures and their ancestral functions. The appeal in extracting phylogenetic information from protein structure lies in the greater conservation of protein structure compared with sequence, reflecting its resilience to mutation over long evolutionary timescales. Leveraging this information is particularly useful for examining relationships within the "twilight zone"-a region of low protein sequence similarity where it becomes challenging to resolve noise from signal. Historically, the field has been constrained by the limited availability of high-resolution structural data. However, recent breakthroughs in artificial intelligence have made high-quality protein structural data widely accessible. Although the methods for constructing phylogenetic trees from protein structures have progressed significantly from distance-based approaches used since the 1970s, this area of research still lags behind the advanced probabilistic models employed in sequence-based phylogenetics; particularly Bayesian and maximum likelihood approaches. This article reviews the current state of protein structural phylogenetics, outlines methods for extracting evolutionary insights from structural data, and highlights key applications and future directions. Due to the surge of newly available structural information, it is anticipated that sequence and structural data will become routinely integrated in phylogenetic analysis; poising us to venture further into the twilight zone and form cross-disciplinary and translational collaborations.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.