ArticleProceedings of the National Academy of Sciences of the United States of America2016
Tertiary alphabet for the observable protein structural universe.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers.
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42 citing papers in PubMed.
- SplitSeek-Pro: accurate prediction of splittable sites on protein structures.Nature communications · 2026Article
- Exploring the structural lexicon of the Proteome via Metric Geometry.PLoS computational biology · 2026Article
- Black-box data: a new paradigm for biomedicine in the AI era.Chemical science · 2026Review
- Protein FID: improved evaluation of protein structure generative models.Bioinformatics (Oxford, England) · 2026Article
- Designability of α-Helical Protein Filaments.Sub-cellular biochemistry · 2026Review
- Assessing generative model coverage of protein structures with SHAPES.Cell systems · 2025Article
- Unsupervised learning reveals landscape of local structural motifs across protein classes.Bioinformatics (Oxford, England) · 2025Article
- Protein language models learn evolutionary statistics of interacting sequence motifs.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Deep generative models of protein structure uncover distant relationships across a continuous fold space.Nature communications · 2024Article
- A comparison of antibody-antigen complex sequence-to-structure prediction methods and their systematic biases.Protein science : a publication of the Protein Society · 2024Article
- A Comparison of Antibody-Antigen Complex Sequence-to-Structure Prediction Methods and their Systematic Biases.bioRxiv : the preprint server for biology · 2024Article
- Sparks of function by de novo protein design.Nature biotechnology · 2024Review
- Article
- A Conserved Local Structural Motif Controls the Kinetics of PTP1B Catalysis.Journal of chemical information and modeling · 2023Article
- Neural network-derived Potts models for structure-based protein design using backbone atomic coordinates and tertiary motifs.Protein science : a publication of the Protein Society · 2023Article
- Atligator Web: A Graphical User Interface for Analysis and Design of Protein-Peptide Interactions.Biodesign research · 2023Article
- ATLIGATOR: editing protein interactions with an atlas-based approach.Bioinformatics (Oxford, England) · 2022Article
- Construction of a Deep Neural Network Energy Function for Protein Physics.Journal of chemical theory and computation · 2022Article
- Tertiary motifs as building blocks for the design of protein-binding peptides.Protein science : a publication of the Protein Society · 2022Article
- Article
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3 authors.
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Abstract
Here, we systematically decompose the known protein structural universe into its basic elements, which we dub tertiary structural motifs (TERMs). A TERM is a compact backbone fragment that captures the secondary, tertiary, and quaternary environments around a given residue, comprising one or more disjoint segments (three on average). We seek the set of universal TERMs that capture all structure in the Protein Data Bank (PDB), finding remarkable degeneracy. Only ∼600 TERMs are sufficient to describe 50% of the PDB at sub-Angstrom resolution. However, more rare geometries also exist, and the overall structural coverage grows logarithmically with the number of TERMs. We go on to show that universal TERMs provide an effective mapping between sequence and structure. We demonstrate that TERM-based statistics alone are sufficient to recapitulate close-to-native sequences given either NMR or X-ray backbones. Furthermore, sequence variability predicted from TERM data agrees closely with evolutionary variation. Finally, locations of TERMs in protein chains can be predicted from sequence alone based on sequence signatures emergent from TERM instances in the PDB. For multisegment motifs, this method identifies spatially adjacent fragments that are not contiguous in sequence-a major bottleneck in structure prediction. Although all TERMs recur in diverse proteins, some appear specialized for certain functions, such as interface formation, metal coordination, or even water binding. Structural biology has benefited greatly from previously observed degeneracies in structure. The decomposition of the known structural universe into a finite set of compact TERMs offers exciting opportunities toward better understanding, design, and prediction of protein structure.
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