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Cited by 297Protein Structure and DynamicsEnzyme Structure and FunctionComputational Drug Discovery Methods

The protein structure prediction problem could be solved using the current PDB library

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Zhang, Yang, Skolnick, Jeffrey·2005·Proceedings of the National Academy of Sciences
DOI 10.1073/pnas.0407152101PMC PMC545829
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Abstract

For single-domain proteins, we examine the completeness of the structures in the current Protein Data Bank (PDB) library for use in full-length model construction of unknown sequences. To address this issue, we employ a comprehensive benchmark set of 1,489 medium-size proteins that cover the PDB at the level of 35% sequence identity and identify templates by structure alignment. With homologous proteins excluded, we can always find similar folds to native with an average rms deviation (RMSD) from native of 2.5 Å with ≈82% alignment coverage. These template structures often contain a significant number of insertions/deletions. The tasser algorithm was applied to build full-length models, where continuous fragments are excised from the top-scoring templates and reassembled under the guide of an optimized force field, which includes consensus restraints taken from the templates and knowledge-based statistical potentials. For almost all targets (except for 2/1,489), the resultant full-length models have an RMSD to native below 6 Å (97% of them below 4 Å). On average, the RMSD of full-length models is 2.25 Å, with aligned regions improved from 2.5 Å to 1.88 Å, comparable with the accuracy of low-resolution experimental structures. Furthermore, starting from state-of-the-art structural alignments, we demonstrate a methodology that can consistently bring template-based alignments closer to native. These results are highly suggestive that the protein-folding problem can in principle be solved based on the current PDB library by developing efficient fold recognition algorithms that can recover such initial alignments.

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Authors
Zhang, Y., & Skolnick, J.
Affiliations
University at Buffalo, State University of New York (US)
ORCID
Venue
Proceedings of the National Academy of Sciences
Publisher
National Academy of Sciences
Published
2005-01-14
Volume
102
Issue
4
Pages
1029-1034
ISSN
  • 0027-8424 (ISSN-L)
  • 1091-6490
DOI
10.1073/pnas.0407152101
PMC
PMC545829
OpenAlex
W2166912610
Cited by
297
References
44
Citations by year
2025: 3 · 2024: 7 · 2023: 10 · 2022: 4 · 2021: 7 · 2020: 8 · 2019: 6 · 2018: 6 · 2017: 11 · 2016: 10 · 2015: 8 · 2014: 8 · 2013: 28 · 2012: 19
FWCI
9.07
Type
journal article
Language
en
Open access
Locations
  • Proceedings of the National Academy of Sciences (publishedVersion)
  • PubMed Central (publishedVersion)
  • PubMed (publishedVersion)
Funders
National Institute of General Medical Sciences (GM 37408, R01GM037408, GM-48835, R01GM048835)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Protein Structure and Dynamics
  • Physical Sciences › Materials Science › Materials Chemistry › Enzyme Structure and Function
  • Physical Sciences › Computer Science › Computational Theory and Mathematics › Computational Drug Discovery Methods
Keywords
protein structure prediction, Protein Data Bank, template-based modeling, single-domain proteins, structural alignment, indels, protein fold recognition, protein folding
MeSH terms
Algorithms, Cysteine Endopeptidases, Models, Molecular, Proteins, Sequence Alignment, Protein Folding, Caspases, Databases, Protein

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