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. 2004 Jan 26;32(2):551-61.
doi: 10.1093/nar/gkh204. Print 2004.

Protein structure prediction using sparse dipolar coupling data

Youxing Qu  1 , Jun-tao Guo, Victor Olman, Ying Xu
Affiliations

Protein structure prediction using sparse dipolar coupling data

Youxing Qu et al. Nucleic Acids Res. .

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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Figures

Figure 1
Figure 1
Actual (left) and predicted structure (right) of the five proteins with <25% sequence identity with their best structural folds in SCOP40, plus the 263-residue protein 1d8v. The predicted structures are generated using the MODELLER program (60) based on the alignments derived from RDC-PROSPECT. The structures are displayed with RASMOL (61). Red, yellow and light blue represent helix, sheet and coil, respectively. The proteins and their respective first ranked templates and sequence identities are: (A) 1ap4, d2pvba_, 19.1%, (B) 1j7p, d2pvba_, 21.3%, (C) 1m12, d1nk1__, 19.0%, (D) 1ny9, d1ash__, 18.2%, (E) 1nya, d2sas__, 21.7% and (F) 1d8v, d1hwma_.
Figure 2
Figure 2
Fold recognition Z-score versus prediction specificity. Specificity is calculated as TP(z)/[TP(z) + FP(z)], where TP(z) and FP(z) are the numbers of true positives and false positives with a cut-off Z-score.
Figure 3
Figure 3
Structures of the four proteins that are mainly composed of coils: (A) 1o8r, (B) 1qn1, (C) 2gat and (D) 4gat (6gat).
See this image and copyright information in PMC

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