Department of Chemistry and Center for Structural Biology, Vanderbilt University, Nashville, Tennessee, United States of America.
Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, Tennessee, United States of America.
PLoS Comput Biol. 2021 Jun 16;17(6):e1009107. doi: 10.1371/journal.pcbi.1009107. eCollection 2021 Jun.
We describe an approach for integrating distance restraints from Double Electron-Electron Resonance (DEER) spectroscopy into Rosetta with the purpose of modeling alternative protein conformations from an initial experimental structure. Fundamental to this approach is a multilateration algorithm that harnesses sets of interconnected spin label pairs to identify optimal rotamer ensembles at each residue that fit the DEER decay in the time domain. Benchmarked relative to data analysis packages, the algorithm yields comparable distance distributions with the advantage that fitting the DEER decay and rotamer ensemble optimization are coupled. We demonstrate this approach by modeling the protonation-dependent transition of the multidrug transporter PfMATE to an inward facing conformation with a deviation to the experimental structure of less than 2Å Cα RMSD. By decreasing spin label rotamer entropy, this approach engenders more accurate Rosetta models that are also more closely clustered, thus setting the stage for more robust modeling of protein conformational changes.
我们描述了一种将双电子-电子共振(DEER)光谱学中的距离约束整合到 Rosetta 中的方法,目的是从初始实验结构中建模替代的蛋白质构象。该方法的基础是一种多边测量算法,该算法利用一组相互连接的自旋标记对来识别每个残基的最佳旋转体组合,以适应时域中的 DEER 衰减。与数据分析软件包相比,该算法产生了可比的距离分布,其优点是结合了 DEER 衰减和旋转体组合优化。我们通过对内向转运蛋白 PfMATE 的质子依赖性构象转变进行建模来证明这种方法,该模型与实验结构的偏差小于 2Å Cα RMSD。通过降低自旋标记旋转体熵,这种方法产生了更准确的 Rosetta 模型,这些模型也更加聚集,从而为更稳健的蛋白质构象变化建模奠定了基础。