Efficient prediction of nucleic acid binding function from low-resolution protein structures
Efficient prediction of nucleic acid binding function from low-resolution protein structures
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DOI：
10.1016/j.jmb.2006.02.053
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发表时间：
2006-05-05
影响因子：
5.6
通讯作者：
Skolnick, J
中科院分区：
文献类型：
--
作者：
Szilagyi, A;Skolnick, J
结构基因组学项目以及从头算蛋白结构预测方法提供了与具有已知功能的蛋白质序列或折叠相似性的蛋白质结构。这些通常是低分辨率结构，可能仅包括C-α原子的位置。我们提出了一种快速有效的方法，可以预测仅从氨基酸序列和低分辨率，仅C-α的蛋白质模型的DNA结合蛋白。该方法使用蛋白质序列中某些氨基酸的相对比例，某些其他氨基酸的空间分布的不对称性以及分子的偶极矩。这些量用于线性公式，其系数源自训练集上的逻辑回归，并且根据结果是否高于一定阈值，可以预测DNA结合。我们表明该方法对原子坐标中的误差不敏感，即使在不准确的蛋白质模型上也提供了正确的预测。我们证明该方法能够用新颖的结合位点基序和结构以未结合的状态来预测蛋白质。我们方法的准确性接近另一种使用全原子结构，耗时的计算以及有关保守残基的信息的方法。 （c）2006 Elsevier Ltd.保留所有权利。
Structural genomics projects as well as ab initio protein structure prediction methods provide structures of proteins with no sequence or fold similarity to proteins with known functions. These are often low-resolution structures that may only include the positions of C-alpha atoms. We present a fast and efficient method to predict DNA-binding proteins from just the amino acid sequences and low-resolution, C-alpha-only protein models. The method uses the relative proportions of certain amino acids in the protein sequence, the asymmetry of the spatial distribution of certain other amino acids as well as the dipole moment of the molecule. These quantities are used in a linear formula, with coefficients derived from logistic regression performed on a training set, and DNA-binding is predicted based on whether the result is above a certain threshold. We show that the method is insensitive to errors in the atomic coordinates and provides correct predictions even on inaccurate protein models. We demonstrate that the method is capable of predicting proteins with novel binding site motifs and structures solved in an unbound state. The accuracy of our method is close to another, method that uses all-atom structures, time-consuming calculations and information on conserved residues. (c) 2006 Elsevier Ltd. All rights reserved.