The DOI matches its Crossref record; 8 of the 8 references it cites were found in a registry or an index.
ConSurf‐DB: An accessible repository for the evolutionary conservation patterns of the majority of PDB proteins
Open accessAbstract
Patterns observed by examining the evolutionary relationships among proteins of common origin can reveal the structural and functional importance of specific residue positions. In particular, amino acids that are highly conserved (i.e., their positions evolve at a slower rate than other positions) are particularly likely to be of biological importance, for example, for ligand binding. ConSurf is a bioinformatics tool for accurately estimating the evolutionary rate of each position in a protein family. Here we introduce a new release of ConSurf‐DB, a database of precalculated ConSurf evolutionary conservation profiles for proteins of known structure. ConSurf‐DB provides high‐accuracy estimates of the evolutionary rates of the amino acids in each protein. A reliable estimate of a query protein's evolutionary rates depends on having a sufficiently large number of effective homologues (i.e., nonredundant yet sufficiently similar). With current sequence data, ConSurf‐DB covers 82% of the PDB proteins. It will be updated on a regular basis to ensure that coverage remains high—and that it might even increase. Much effort was dedicated to improving the user experience. The repository is available at https://consurfdb.tau.ac.il/. Broader audience: By comparing a protein to other proteins of similar origin, it is possible to determine the extent to which each amino acid position in the protein evolved slowly or rapidly. A protein's evolutionary profile can provide valuable insights: For example, amino acid positions that are highly conserved (i.e., evolved slowly) are particularly likely to be of structural and/or functional importance, for example, for ligand binding and catalysis. We introduce here a new and improved version of ConSurf‐DB, a continually updated database that provides precalculated evolutionary profiles of proteins with known structure.
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MAFFT Multiple Sequence Alignment Software Version 7: Improvements in Performance and Usability
Katoh, K., & Standley, D. M. (2013) · Molecular Biology and Evolution · doi:10.1093/molbev/mst010 · Cited by 46,209
Cd-hit: Accelerated for clustering the next-generation sequencing data
Fu, L., Niu, B., Zhu, Z., Wu, S., & Li, W. (2012) · Bioinformatics · doi:10.1093/bioinformatics/bts565 · Cited by 11,175
UniProt: a worldwide hub of protein knowledge
The UniProt Consortium (2019) · Nucleic Acids Research · doi:10.1093/nar/gky1049 · Cited by 7,698
Whelan, S., & Goldman, N. (2001) · Molecular Biology and Evolution · doi:10.1093/oxfordjournals.molbev.a003851 · Cited by 2,849
UniRef clusters: a comprehensive and scalable alternative for improving sequence similarity searches
Suzek, B. E., Wang, Y., Huang, H., McGarvey, P. B., Wu, C. H., & the UniProt Consortium (2015) · Bioinformatics · doi:10.1093/bioinformatics/btu739 · Cited by 1,928
UniRef: comprehensive and non-redundant UniProt reference clusters
Suzek, B. E., Huang, H., McGarvey, P., Mazumder, R., & Wu, C. H. (2007) · Bioinformatics · doi:10.1093/bioinformatics/btm098 · Cited by 1,613
NGL viewer: web-based molecular graphics for large complexes
Rose, A. S., Bradley, A. R., Valasatava, Y., Duarte, J. M., Prlić, A., & Rose, P. W. (2018) · Bioinformatics · doi:10.1093/bioinformatics/bty419 · Cited by 489
NGL Viewer: a web application for molecular visualization
Rose, A. S., & Hildebrand, P. W. (2015) · Nucleic Acids Research · doi:10.1093/nar/gkv402 · Cited by 462
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Metadata
- Authors
- Ben Chorin, A., Masrati, G., Kessel, A., Narunsky, A., Sprinzak, J., Lahav, S., Ashkenazy, H., & Ben‐Tal, N.
- Venue
- Protein Science
- Publisher
- Wiley
- Published
- 2019-11-22
- Volume
- 29
- Issue
- 1
- Pages
- 258-267
- ISSN
- 0961-8368 (ISSN-L)
- 1469-896X
- OpenAlex
- W2986717577
- Cited by
- 266
- References
- 8
- FWCI
- 2.94
- Type
- journal article
- Language
- en
- Open access
- hybrid
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