Protein Model Discrimination Using Mutational Sensitivity Derived from Deep Sequencing
Protein Model Discrimination Using Mutational Sensitivity Derived from Deep Sequencing
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DOI：
10.1016/j.str.2011.11.021
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发表时间：
2012-02-08
期刊：
影响因子：
5.7
通讯作者：
Varadarajan, Raghavan
中科院分区：
文献类型：
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作者：
Adkar, Bharat V.;Tripathi, Arti;Varadarajan, Raghavan
蛋白质结构预测的一个主要瓶颈是从诱饵池中选择正确的模型。通过使用深度测序确定其相对群体来估计细菌毒素CcdB的饱和文库中类似于1，200个个体单位点突变体的相对活性。该表型信息用于定义与残基深度相关的每个残基的经验评分（等级评分），并鉴定活性位点残基。使用这些相关性，类似于98%的CcdB（RMSD）正确模型
A major bottleneck in protein structure prediction is the selection of correct models from a pool of decoys. Relative activities of similar to 1,200 individual single-site mutants in a saturation library of the bacterial toxin CcdB were estimated by determining their relative populations using deep sequencing. This phenotypic information was used to define an empirical score for each residue (Rank Score), which correlated with the residue depth, and identify active-site residues. Using these correlations, similar to 98% of correct models of CcdB (RMSD