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Improved Virus Isoelectric Point Estimation by Exclusion of Known and Predicted Genome-Binding Regions

机译:通过排除已知和预测的基因组结合区域来改进病毒等电点估计

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摘要

Knowledge of the isoelectric points (pIs) of viruses is beneficial for predicting virus behavior in environmental transport and physical/chemical treatment applications. However, the empirically measured pIs of many viruses have thus far defied simple explanation, let alone prediction, based on the ionizable amino acid composition of the virus capsid. Here, we suggest an approach for predicting the pI of nonenveloped viruses by excluding capsid regions that stabilize the virus polynucleotide via electrostatic interactions. This method was applied first to viruses with known polynucleotide-binding regions (PBRs) and/or three-dimensional (3D) structures. Then, PBRs were predicted in a group of 32 unique viral capsid proteome sequences via conserved structures and sequence motifs. Removing predicted PBRs resulted in a significantly better fit to empirical pI values. After modification, mean differences between theoretical and empirical pI values were reduced from 2.1 +/- 2.4 to 0.1 +/- 1.7 pH units.
机译:了解病毒的等电点 (pI) 有助于预测病毒在环境运输和物理/化学处理应用中的行为。然而,迄今为止,许多病毒的经验测量的pI都无法根据病毒衣壳的可电离氨基酸组成进行简单的解释,更不用说预测了。在这里,我们提出了一种通过排除通过静电相互作用稳定病毒多核苷酸的衣壳区域来预测非包膜病毒的pI的方法。该方法首先应用于具有已知多核苷酸结合区(PBR)和/或三维(3D)结构的病毒。然后,通过保守结构和序列基序在一组 32 个独特的病毒衣壳蛋白质组序列中预测 PBR。去除预测的 PBR 后,与经验 pI 值的拟合度明显更好。修改后,理论和经验 pI 值之间的平均差异从 2.1 +/- 2.4 降低到 0.1 +/- 1.7 pH 单位。

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