ArticlePLoS computational biology2019
A global map of the protein shape universe.
Article in PLoS computational biology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed.
- Contrastive learning unites sequence and structure in a global representation of protein space.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- PL-PatchSurfer3: improved structure-based virtual screening for structure variation using 3D Zernike descriptors.Journal of cheminformatics · 2026Article
- SHREC 2025: Protein surface shape retrieval including electrostatic potential.Computers & graphics · 2025Article
- Article
- PLO3S: Protein LOcal Surficial Similarity Screening.Computational and structural biotechnology journal · 2024Article
- Structural Outlier Detection and Zernike-Canterakis Moments for Molecular Surface Meshes-Fast Implementation in Python.Molecules (Basel, Switzerland) · 2023Article
- Quantitative comparison of protein-protein interaction interface using physicochemical feature-based descriptors of surface patches.Frontiers in molecular biosciences · 2023Article
- An overview of descriptors to capture protein properties - Tools and perspectives in the context of QSAR modeling.Computational and structural biotechnology journal · 2023Review
- Modeling the Dynamics of Protein-Protein Interfaces, How and Why?Molecules (Basel, Switzerland) · 2022Review
- Shape Complementarity Optimization of Antibody-Antigen Interfaces: The Application to SARS-CoV-2 Spike Protein.Frontiers in molecular biosciences · 2022Article
- Article
- ZEAL: protein structure alignment based on shape similarity.Bioinformatics (Oxford, England) · 2021Article
- Classification of protein domains based on their three-dimensional shapes (CPD3DS).Synthetic and systems biotechnology · 2021Article
- Ten simple rules for designing analogue science games.PLoS computational biology · 2021Article
- IDPology of the living cell: intrinsic disorder in the subcellular compartments of the human cell.Cellular and molecular life sciences : CMLS · 2021Article
- Structural Biology in the Multi-Omics Era.Journal of chemical information and modeling · 2020Article
- 2DKD: a toolkit for content-based local image search.Source code for biology and medicine · 2020Article
- FAD/NADH Dependent Oxidoreductases: From Different Amino Acid Sequences to Similar Protein Shapes for Playing an Ancient Function.Journal of clinical medicine · 2019Article
- Predicting binding poses and affinity ranking in D3R Grand Challenge using PL-PatchSurfer2.0.Journal of computer-aided molecular design · 2019Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
Proteins are involved in almost all functions in a living cell, and functions of proteins are realized by their tertiary structures. Obtaining a global perspective of the variety and distribution of protein structures lays a foundation for our understanding of the building principle of protein structures. In light of the rapid accumulation of low-resolution structure data from electron tomography and cryo-electron microscopy, here we map and classify three-dimensional (3D) surface shapes of proteins into a similarity space. Surface shapes of proteins were represented with 3D Zernike descriptors, mathematical moment-based invariants, which have previously been demonstrated effective for biomolecular structure similarity search. In addition to single chains of proteins, we have also analyzed the shape space occupied by protein complexes. From the mapping, we have obtained various new insights into the relationship between shapes, main-chain folds, and complex formation. The unique view obtained from shape mapping opens up new ways to understand design principles, functions, and evolution of proteins.
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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.