Sequence‐similar, structure‐dissimilar protein pairs in the PDB
Open accessAbstract
It is often assumed that in the Protein Data Bank (PDB), two proteins with similar sequences will also have similar structures. Accordingly, it has proved useful to develop subsets of the PDB from which “redundant” structures have been removed, based on a sequence‐based criterion for similarity. Similarly, when predicting protein structure using homology modeling, if a template structure for modeling a target sequence is selected by sequence alone, this implicitly assumes that all sequence‐similar templates are equivalent. Here, we show that this assumption is often not correct and that standard approaches to create subsets of the PDB can lead to the loss of structurally and functionally important information. We have carried out sequence‐based structural superpositions and geometry‐based structural alignments of a large number of protein pairs to determine the extent to which sequence similarity ensures structural similarity. We find many examples where two proteins that are similar in sequence have structures that differ significantly from one another. The source of the structural differences usually has a functional basis. The number of such proteins pairs that are identified and the magnitude of the dissimilarity depend on the approach that is used to calculate the differences; in particular sequence‐based structure superpositioning will identify a larger number of structurally dissimilar pairs than geometry‐based structural alignments. When two sequences can be aligned in a statistically meaningful way, sequence‐based structural superpositioning provides a meaningful measure of structural differences. This approach and geometry‐based structure alignments reveal somewhat different information and one or the other might be preferable in a given application. Our results suggest that in some cases, notably homology modeling, the common use of nonredundant datasets, culled from the PDB based on sequence, may mask important structural and functional information. We have established a data base of sequence‐similar, structurally dissimilar protein pairs that will help address this problem (http://luna.bioc.columbia.edu/rachel/seqsimstrdiff.htm). Proteins 2008. © 2007 Wiley‐Liss, Inc.
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There are examples of highly similar protein sequences having radically different structures and functions and of sequences that can form multiple folds.
“Although it is generally believed that proteins with similar sequences form similar structures, there are also interesting examples of highly similar protein sequences having radically different structures and functions 60,61 and of sequences that can form multiple folds 62.”
From Learning the protein language: Evolution, structure, and function (2021) · cites this paper as [60]
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- Authors
- Kosloff, M., & Kolodny, R.
- Affiliations
- Duke Medical Center (US)
- Howard Hughes Medical Institute (US)
- Corresponding author
- Kosloff, Mickey
- Venue
- Proteins: Structure, Function, and Bioinformatics
- Publisher
- Wiley
- Published
- 2007-11-14
- Volume
- 71
- Issue
- 2
- Pages
- 891-902
- ISSN
- 0887-3585 (ISSN-L)
- 1097-0134
- PMC
- PMC2673347
- OpenAlex
- W2131204071
- Cited by
- 124
- References
- 48
- Citations by year
- 2026: 5 · 2025: 6 · 2024: 8 · 2023: 6 · 2022: 6 · 2021: 11 · 2020: 9 · 2019: 6 · 2018: 10 · 2017: 9 · 2016: 4 · 2015: 4 · 2014: 6 · 2013: 5 · 2012: 4
- FWCI
- 2.52
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Proteins Structure Function and Bioinformatics (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
- Physical Sciences › Materials Science › Materials Chemistry › Enzyme Structure and Function
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Keywords
- protein structural similarity, protein function
- MeSH terms
- Models, Molecular, Sequence Alignment, Protein Structure, Tertiary, Databases, Protein
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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