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Structure-based prediction of C2H2 zinc-finger binding specificity: sensitivity to docking geometry

机译:基于结构的C2H2锌指结合特异性预测:对接几何的敏感性

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Predicting the binding specificity of transcription factors is a critical step in the characterization and computational identification and of cis-regulatory elements in genomic sequences. Here we use protein-DNA structures to predict binding specificity and consider the possibility of predicting position weight matrices (PWM) for an entire protein family based on the structures of just a few family members. A particular focus is the sensitivity of prediction accuracy to the docking geometry of the structure used. We investigate this issue with the goal of determining how similar two docking geometries must be for binding specificity predictions to be accurate. Docking similarity is quantified using our recently described interface alignment score (IAS). Using a molecular-mechanics force field, we predict high-affinity nucleotide sequences that bind to the second zinc-finger (ZF) domain from the Zif268 protein, using different C2H2 ZF domains as structural templates. We identify a strong relationship between IAS values and prediction accuracy, and define a range of IAS values for which accurate structure-based predictions of binding specificity is to be expected. The implication of our results for large-scale, structure-based prediction of PWMs is discussed.
机译:预测转录因子的结合特异性是表征和计算鉴定以及基因组序列中顺式调节元件的关键步骤。在这里,我们使用蛋白质-DNA结构来预测结合特异性,并考虑基于仅几个家族成员的结构来预测整个蛋白质家族的位置权重矩阵(PWM)的可能性。特别关注的是预测精度对所使用结构的对接几何的敏感性。我们调查此问题的目的是确定要使结合特异性预测准确无误,必须有两个相似的对接几何形状。使用我们最近描述的界面对齐评分(IAS)量化对接相似性。使用分子力学力场,我们使用不同的C2H2 ZF域作为结构模板,预测与Zif268蛋白中第二个锌指(ZF)域结合的高亲和力核苷酸序列。我们确定IAS值和预测准确性之间的密切关系,并定义一系列IAS值,对于这些范围,可以预期基于结构的结合特异性的准确预测。讨论了我们的结果对于大规模,基于结构的PWM预测的含义。

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