Use of 13Calpha chemical shifts in protein structure determination.
Use of 13Calpha chemical shifts in protein structure determination.
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在蛋白质结构测定中使用 13Cα 化学位移。
DOI：
10.1021/jp0683871
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发表时间：
2007
期刊：
影响因子：
--
通讯作者：
Scheraga,HaroldA
中科院分区：
文献类型：
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作者：
Vila,JorgeA;Ripoll,DanielR;Scheraga,HaroldA
提出了一种基于物理学的方法，旨在确定蛋白质的结构，通过使用NOE导出的距离与观测和计算的13 C化学位移。该方法利用13 C α化学位移，在理论的密度泛函水平上计算，获得所有主链和侧链扭转角的扭转约束，而不需要优先考虑氨基酸残基对Ramachandran图任何区域的占用。扭转约束不是固定的，而是在程序的每个步骤中动态地改变，遵循迭代自洽方法，旨在确定一组计算的13 C α化学位移与实验相匹配的构象。对76个氨基酸的全α-螺旋蛋白进行试验，即枯草芽孢杆菌载体蛋白。结果表明，从随机产生的构象，最终的蛋白质模型是更准确的比现有的NMR衍生的结构模型的这种蛋白质，在预测和预测的13 C α化学位移和一些立体化学质量指标之间的协议，和类似的准确度作为一个蛋白质模型解决了高水平的分辨率。结果提供的证据表明，这种方法不仅可以用于结构测定，但也为额外的蛋白质结构的NMR衍生模型存放在蛋白质数据库的细化。
A physics-based method aimed at determining protein structures by using NOE-derived distances together with observed and computed13C chemical shifts is proposed. The approach makes use of13Cαchemical shifts, computed at the density functional level of theory, to obtain torsional constraints for all backbone and side-chain torsional angles without makinga prioriuse of the occupancy of any region of the Ramachandran map by the amino acid residues. The torsional constraints are not fixed but are changed dynamically in each step of the procedure, following an iterative self-consistent approach intended to identify a set of conformations for which the computed13Cαchemical shifts match the experimental ones. A test is carried out on a 76-amino acid, all-α-helical protein; namely, theBacillus subtilisacyl carrier protein. It is shown that, starting from randomly generated conformations, the final protein models are more accurate than an existing NMR-derived structure model of this protein, in terms of both the agreement between predicted and observed13Cαchemical shifts and some stereochemical quality indicators, and of similar accuracy as one of the protein models solved at a high level of resolution. The results provide evidence that this methodology can be used not only for structure determination but also for additional protein structure refinement of NMR-derived models deposited in the Protein Data Bank.