Prediction of functionally important residues in globular proteins from unusual central distances of amino acids.
Prediction of functionally important residues in globular proteins from unusual central distances of amino acids.
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DOI：
10.1186/1472-6807-11-34
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发表时间：
2011-09-18
影响因子：
--
通讯作者：
Kochańczyk M
中科院分区：
文献类型：
--
作者：
Kochańczyk M
性能良好的自动化蛋白质功能识别方法通常包括几种互补技术。除了构建更好的共识，它们的预测能力还可以通过添加或改进探索蛋白质正交特征的独立模块来提高。在这项工作中，我们展示了如何探索全球原子分布可以用来指示功能上重要的残基。使用一组精心挑选的球状蛋白质，我们参数化连续的概率密度函数，描述个别蛋白质原子的首选中心距离。相对优选的埋葬估计使用混合模型的径向密度函数依赖于所考虑的蛋白质的氨基酸组成。用信息论的方法评价了原子异常位置的意外性，并直接用于关键氨基酸的鉴定。在验证研究中，我们通过搜索与配体相互作用的结合位点来测试基于我们的方法构建的工具SurpResi的能力。该工具表明，多个候选网站实现的成功率与几种几何方法相当。我们还表明，意外性是蛋白质-蛋白质相互作用所涉及的区域的属性，因此可以用于蛋白质对接预测的排名。在这项工作中实现的计算方法可以通过http://www.bioinformatics.org/surpresi的Web界面免费获得。球状蛋白质中原子中心距离的概率分析能够捕获由于其侧链的不同大小、电荷和疏水特性而导致的氨基酸的不同取向偏好。当理想化的空间偏好可以从蛋白质的唯一氨基酸组成推断时，位于疏水不利环境中的残基可以容易地检测到。这样的残基往往直接参与结合配体或与其他蛋白质的接口。
Well-performing automated protein function recognition approaches usually comprise several complementary techniques. Beside constructing better consensus, their predictive power can be improved by either adding or refining independent modules that explore orthogonal features of proteins. In this work, we demonstrated how the exploration of global atomic distributions can be used to indicate functionally important residues. Using a set of carefully selected globular proteins, we parametrized continuous probability density functions describing preferred central distances of individual protein atoms. Relative preferred burials were estimated using mixture models of radial density functions dependent on the amino acid composition of a protein under consideration. The unexpectedness of extraordinary locations of atoms was evaluated in the information-theoretic manner and used directly for the identification of key amino acids. In the validation study, we tested capabilities of a tool built upon our approach, called SurpResi, by searching for binding sites interacting with ligands. The tool indicated multiple candidate sites achieving success rates comparable to several geometric methods. We also showed that the unexpectedness is a property of regions involved in protein-protein interactions, and thus can be used for the ranking of protein docking predictions. The computational approach implemented in this work is freely available via a Web interface at http://www.bioinformatics.org/surpresi. Probabilistic analysis of atomic central distances in globular proteins is capable of capturing distinct orientational preferences of amino acids as resulting from different sizes, charges and hydrophobic characters of their side chains. When idealized spatial preferences can be inferred from the sole amino acid composition of a protein, residues located in hydrophobically unfavorable environments can be easily detected. Such residues turn out to be often directly involved in binding ligands or interfacing with other proteins.
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影响因子：
5.6
作者：
Gabb, HA;Jackson, RM;Sternberg, MJE
通讯作者：
Sternberg, MJE
DOI：
10.1093/protein/2.3.185
发表时间：
1988-09-01
期刊：
PROTEIN ENGINEERING
影响因子：
--
作者：
BIOU, V;GIBRAT, JF;GARNIER, J
通讯作者：
GARNIER, J
影响因子：
4.4
作者：
BAUMGARTNER, A
通讯作者：
BAUMGARTNER, A
影响因子：
4.3
作者：
Brylinski, Michal;Prymula, Katarzyna;Roterman, Irena
通讯作者：
Roterman, Irena
影响因子：
5.6
作者：
Feldman, Howard J.;Labute, Paul
通讯作者：
Labute, Paul