Evidence map›Paper›PMID 20463972›Full record

ArticlePloS one2010

Computational protein design: validation and possible relevance as a tool for homology searching and fold recognition.

Marcel Schmidt Am Busch, Audrey Sedano, Thomas Simonson

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In one paragraph

Article in PloS one, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Marcel Schmidt Am BuschLaboratoire de Biochimie (CNRS UMR7654), Department of Biology, Ecole Polytechnique, Palaiseau, France.
Audrey Sedano
Thomas Simonson

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundProtein fold recognition usually relies on a statistical model of each fold; each model is constructed from an ensemble of natural sequences belonging to that fold. A complementary strategy may be to employ sequence ensembles produced by computational protein design. Designed sequences can be more diverse than natural sequences, possibly avoiding some limitations of experimental databases. METHODOLOGY/PRINCIPAL

findingsWE EXPLORE THIS STRATEGY FOR FOUR SCOP FAMILIES: Small Kunitz-type inhibitors (SKIs), Interleukin-8 chemokines, PDZ domains, and large Caspase catalytic subunits, represented by 43 structures. An automated procedure is used to redesign the 43 proteins. We use the experimental backbones as fixed templates in the folded state and a molecular mechanics model to compute the interaction energies between sidechain and backbone groups. Calculations are done with the Proteins@Home volunteer computing platform. A heuristic algorithm is used to scan the sequence and conformational space, yielding 200,000-300,000 sequences per backbone template. The results confirm and generalize our earlier study of SH2 and SH3 domains. The designed sequences ressemble moderately-distant, natural homologues of the initial templates; e.g., the SUPERFAMILY, profile Hidden-Markov Model library recognizes 85% of the low-energy sequences as native-like. Conversely, Position Specific Scoring Matrices derived from the sequences can be used to detect natural homologues within the SwissProt database: 60% of known PDZ domains are detected and around 90% of known SKIs and chemokines. Energy components and inter-residue correlations are analyzed and ways to improve the method are discussed. CONCLUSIONS/SIGNIFICANCE: For some families, designed sequences can be a useful complement to experimental ones for homologue searching. However, improved tools are needed to extract more information from the designed profiles before the method can be of general use.

Indexed as

Models, MolecularStructural Homology, ProteinAmino AcidsComputational BiologyDatabases, ProteinEntropyMutationPDZ DomainsPosition-Specific Scoring MatricesProteinsProtein StabilityProtein Structure, SecondaryReproducibility of ResultsSequence Analysis, ProteinAmino AcidsProteins

Identifiers

PMID20463972
PMCPMC2864755

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.