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Protein structure prediction using sparse dipolar coupling data.

Youxing Qu·Jun-tao Guo·Victor Olman·Ying Xu
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Abstract

Residual dipolar coupling (RDC) represents one of the most exciting emerging NMR techniques for protein structure studies. However, solving a protein structure using RDC data alone is still a highly challenging problem. We report here a computer program, RDC-PROSPECT, for protein structure prediction based on a structural homolog or analog of the target protein in the Protein Data Bank (PDB), which best aligns with the (15)N-(1)H RDC data of the protein recorded in a single ordering medium. Since RDC-PROSPECT uses only RDC data and predicted secondary structure information, its performance is virtually independent of sequence similarity between a target protein and its structural homolog/analog, making it applicable to protein targets beyond the scope of current protein threading techniques. We have tested RDC-PROSPECT on all (15)N-(1)H RDC data (representing 43 proteins) deposited in the BioMagResBank (BMRB) database. The program correctly identified structural folds for 83.7% of the target proteins, and achieved an average alignment accuracy of 98.1% residues within a four-residue shift.

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Computational BiologyComputer SimulationDatabases, ProteinModels, MolecularProtein ConformationProtein FoldingProtein Structure, SecondarySensitivity and SpecificitySoftwareJournal ArticleResearch Support, U.S. Gov't, Non-P.H.S.

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Youxing Qu, Jun-tao Guo, Victor Olman, Ying Xu. 2004-01-26. Protein structure prediction using sparse dipolar coupling data.. https://doi.org/10.1093/nar%2Fgkh204

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