Department of Computer Science & Engineering, University of South Carolina, Columbia, SC 29208, USA.
Molecules. 2013 Aug 22;18(9):10162-88. doi: 10.3390/molecules180910162.
More than 90% of protein structures submitted to the PDB each year are homologous to some previously characterized protein structure. The extensive resources that are required for structural characterization of proteins can be justified for the 10% of the novel structures, but not for the remaining 90%. This report presents the 2D-PDPA method, which utilizes unassigned residual dipolar coupling in order to address the economics of structure determination of routine proteins by reducing the data acquisition and processing time. 2D-PDPA has been demonstrated to successfully identify the correct structure of an array of proteins that range from 46 to 445 residues in size from a library of 619 decoy structures by using unassigned simulated RDC data. When using experimental data, 2D-PDPA successfully identified the correct NMR structures from the same library of decoy structures. In addition, the most homologous X-ray structure was also identified as the second best structural candidate. Finally, success of 2D-PDPA in identifying and evaluating the most appropriate structure from a set of computationally predicted structures in the case of a previously uncharacterized protein Pf2048.1 has been demonstrated. This protein exhibits less than 20% sequence identity to any protein with known structure and therefore presents a compelling and practical application of our proposed work.
每年提交给 PDB 的蛋白质结构中,超过 90%与某些先前具有特征的蛋白质结构具有同源性。对于 10%的新型结构,结构表征所需的广泛资源是合理的,但对于其余 90%则不然。本报告介绍了 2D-PDPA 方法,该方法利用未分配的残差偶极耦合,以通过减少数据采集和处理时间来解决常规蛋白质结构测定的经济性问题。2D-PDPA 已成功地从 619 个诱饵结构库中鉴定出一系列大小为 46 到 445 个残基的蛋白质的正确结构,这些蛋白质使用未分配的模拟 RDC 数据。当使用实验数据时,2D-PDPA 成功地从相同的诱饵结构库中鉴定出正确的 NMR 结构。此外,最同源的 X 射线结构也被鉴定为第二个最佳结构候选。最后,在 Pf2048.1 这种先前未表征的蛋白质的情况下,2D-PDPA 从一组计算预测结构中成功地识别和评估最合适的结构,这也证明了它的有效性。该蛋白质与任何具有已知结构的蛋白质的序列同一性小于 20%,因此是对我们提出的工作的一个引人注目的实际应用。