首页> 外文会议>Pacific Symposium on Biocomputing 2004; Jan 6-10, 2004; Hawaii, USA >PROTEIN FOLD RECOGNITION THROUGH APPLICATION OF RESIDUAL DIPOLAR COUPLING DATA
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PROTEIN FOLD RECOGNITION THROUGH APPLICATION OF RESIDUAL DIPOLAR COUPLING DATA

机译:通过残双链耦合数据的蛋白质折叠识别

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Residual dipolar coupling (RDC) represents one of the most exciting emerging NMR techniques for studying protein structures. However, solving a protein structure using RDC data alone is a highly challenging problem as it often requires that the starting structure model be close to the actual structure of a protein, for the structure calculation procedure to be effective. We report in this paper a computer program, RDC-PROSPECT, for identification of a structural homolog or analog of a target protein in PDB, which best matches the ~(15)N-~1H RDC data of the protein recorded in a single ordering medium. The identified structural homolog/analog can then be used as a starting model for RDC-based structure calculation. 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 out of the scope of current protein threading techniques. We have tested RDC-PROSPECT on all ~(15)N- ~1H RDC data (representing 33 proteins) available in the BMRB database and the literature. The program correctly identified the structural folds for ~80% of the target proteins, significantly better than previously reported results, and achieved an average alignment accuracy of 97.9% residues within 4-residue shift. Through a careful algorithmic design, RDC-PROSPECT is at least one order of magnitude faster than previously reported algorithms for principal alignment frame search, making our algorithm fast enough for large-scale applications.
机译:残留偶极偶联(RDC)代表了最令人兴奋的新兴NMR技术,用于研究蛋白质结构。然而,仅使用RDC数据求解蛋白质结构是一个极具挑战性的问题,因为为了使结构计算过程有效,通常需要起始结构模型与蛋白质的实际结构接近。我们在本文中报告了一种计算机程序RDC-PROSPECT,用于识别PDB中靶蛋白的结构同源物或类似物,该蛋白与单次记录的蛋白的〜(15)N-〜1H RDC数据最匹配介质。所识别的结构同系物/类似物然后可以用作基于RDC的结构计算的起始模型。由于RDC-PROSPECT仅使用RDC数据和预测的二级结构信息,因此其性能实际上与目标蛋白质及其结构同源物/类似物之间的序列相似性无关,从而使其可应用于当前蛋白质穿线技术范围之外的蛋白质目标。我们已经对BMRB数据库和文献中提供的所有〜(15)N-〜1H RDC数据(代表33种蛋白质)进行了RDC-PROSPECT测试。该程序正确识别了约80%的目标蛋白质的结构折叠,明显优于先前报道的结果,并且在4个残基移位内达到了97.9%残基的平均比对准确性。通过精心的算法设计,RDC-PROSPECT比以前报道的用于主对齐框架搜索的算法至少快一个数量级,从而使我们的算法足够快地用于大规模应用。

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