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KScons: a Bayesian approach for protein residue contact prediction using the knob-socket model of protein tertiary structure

机译:KScons:使用蛋白质三级结构的纽扣模型预测蛋白质残基接触的贝叶斯方法

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Motivation: By simplifying the many-bodied complexity of residue packing into patterns of simple pairwise secondary structure interactions between a single knob residue with a three-residue socket, the knob-socket construct allows a more direct incorporation of structural information into the prediction of residue contacts. By modeling the preferences between the amino acid composition of a socket and knob, we undertake an investigation of the knob-socket construct's ability to improve the prediction of residue contacts. The statistical model considers three priors and two posterior estimations to better understand how the input data affects predictions. This produces six implementations of KScons that are tested on three sets: PSICOV, CASP10 and CASP11. We compare against the current leading contact prediction methods.
机译:动机:通过将残基堆积的复杂程度简化为单个纽扣残基与三个残基的插座之间简单的成对二级结构相互作用的模式,纽扣-插座结构可将结构信息更直接地整合到残基的预测中联系人。通过对插座和旋钮的氨基酸组成之间的偏好进行建模,我们对旋钮插座构建体改善残基接触预测的能力进行了研究。统计模型考虑了三个先验和两个后验估计,以更好地理解输入数据如何影响预测。这将产生KScons的六个实现,并在三组上进行了测试:PSICOV,CASP10和CASP11。我们将其与当前的领先联系预测方法进行比较。

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