ArticleJournal of molecular biology2020
MemSTATS: A Benchmark Set of Membrane Protein Symmetries and Pseudosymmetries.
Article in Journal of molecular biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 15 citations in OpenAlex.
- The molecular mechanism of fluoride export by the eukaryotic fluoride channel FEX.Nature communications · 2025Article
- Tumoral P2YPurinergic signalling · 2024Article
- Peripheral positions encode transport specificity in the small multidrug resistance exporters.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- EncoMPASS: An encyclopedia of membrane proteins analyzed by structure and symmetry.Structure (London, England : 1993) · 2024Article
- Architects of the membrane: structures of eukaryotic choline phosphotransferase 1 and choline/ethanolamine phosphotransferase 1.Nature structural & molecular biology · 2023Article
- Diverse Scientific Benchmarks for Implicit Membrane Energy Functions.Journal of chemical theory and computation · 2021Article
- Altering CLC stoichiometry by reducing non-polar side-chains at the dimerization interface.Journal of molecular biology · 2021Article
- Article
- RepeatsDB in 2021: improved data and extended classification for protein tandem repeat structures.Nucleic acids research · 2021Article
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Authors and funding
3 authors at 2 institutions in 1 country.
Funding
Abstract
In membrane proteins, symmetry and pseudosymmetry often have functional or evolutionary implications. However, available symmetry detection methods have not been tested systematically on this class of proteins because of the lack of an appropriate benchmark set. Here we present MemSTATS, a publicly available benchmark set of both quaternary- and internal-symmetries in membrane protein structures. The symmetries are described in terms of order, repeated elements, and orientation of the axis with respect to the membrane plane. Moreover, using MemSTATS, we compare the performance of four widely used symmetry detection algorithms and highlight specific challenges and areas for improvement in the future.
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