Cited by 425Protein Structure and DynamicsMachine Learning in BioinformaticsGenomics and Phylogenetic Studies

Paircoil2: improved prediction of coiled coils from sequence.

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McDonnell, A. V., Jiang, T., Keating, A. E., Berger, B.·2006·Bioinformatics

Abstract

Summary: We introduce Paircoil2, a new version of the Paircoil program, which uses pairwise residue probabilities to detect coiled–coil motifs in protein sequence data. Paircoil2 achieves 98% sensitivity and 97% specificity on known coiled coils in leave-family-out cross-validation. It also shows superior performance compared with published methods in tests on proteins of known structure. Availability: Paircoil2 is freely available as a web application and for download at Contact: keating@mit.edu; bab@mit.edu Supplementary information: Available at Bioinformatics online and at the Paircoil website.

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  • A new coiled-coil database of 1279 dimers and 333 trimers is derived from three sources: the Paircoil2 training set, coiled coils detected in the PDB using SOCKET, and new coiled-coil families described in the literature.

    “A new coiled-coil database of 1279 dimers and 333 trimers is derived from three sources: the Paircoil2 training set [9], coiled coils detected in the PDB using SOCKET, and new coiled-coil families described in the literature.”

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Authors
McDonnell, A. V., Jiang, T., Keating, A. E., & Berger, B.
Affiliations
  • MIT Computer Science and Artificial Intelligence Laboratory (US)
  • Massachusetts Institute of Technology (US)
Corresponding author
  • Keating, A. E.
  • Berger, B.
Venue
Bioinformatics
Published
2005-11-29
Volume
22
Issue
3
Pages
356-358
ISSN
  • 1367-4803 (ISSN-L)
  • 1367-4811
OpenAlex
W2117709367
Cited by
424
References
22
Citations by year
2026: 5 · 2025: 8 · 2024: 16 · 2023: 15 · 2022: 18 · 2021: 27 · 2020: 19 · 2019: 25 · 2018: 19 · 2017: 27 · 2016: 25 · 2015: 22 · 2014: 25 · 2013: 22 · 2012: 41
FWCI
4.64
Type
journal article
Language
en
Open access
Locations
  • Bioinformatics (publishedVersion)
  • PubMed (publishedVersion)
Funders
  • National Science Foundation (0347203, CAREER)
  • National Institutes of Health
  • National Institute of General Medical Sciences (GM67681, R01GM067681)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Machine Learning in Bioinformatics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
Keywords
coiled-coil domain, protein sequence analysis, web application, structure prediction
MeSH terms
Algorithms, Amino Acid Sequence, Computer Simulation, Models, Chemical, Models, Molecular, Molecular Sequence Data, Sensitivity and Specificity, Software, Reproducibility of Results, Sequence Analysis, Protein

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