Theoretical assessment of the oligolysine model for ionic interactions in protein-DNA complexes.
Theoretical assessment of the oligolysine model for ionic interactions in protein-DNA complexes.
复制标题
DOI：
10.1021/jp204915y
复制
发表时间：
2011-08-18
影响因子：
3.3
通讯作者：
Manning, Gerald S.
中科院分区：
文献类型：
--
作者：
Fenley, Marcia O.;Russo, Cristina;Manning, Gerald S.
所观察到的带电配体与聚电解质结合的盐依赖性，例如蛋白质与DNA或抗凝血酶与肝素的结合，通常通过“寡聚赖氨酸模型”来解释。我们回顾这个模型完全来自框架内的聚电解质的反凝聚理论，没有引入外界的假设。我们更新它的比较与实验数据的结构简单的系统，它最初的目的。然后，我们计算了各种蛋白质-DNA复合物的结合自由能的盐依赖性与非线性泊松-玻尔兹曼（NLPB）模拟方法。NLPB计算的结果证实了寡聚赖氨酸模型的中心预测，即DNA的净电荷密度对蛋白质结合保持不变。具体来说，当阳离子蛋白质残基穿透凝聚在DNA上的反离子层时，反离子被释放到本体溶液中;当阴离子蛋白质残基穿透凝聚的反离子层时，额外的反离子从本体溶液中凝聚出来。然而，我们也得出结论，带电的蛋白质残基远离结合界面的累积效应，使显着的贡献的盐依赖性的结合，观察不容纳的寡聚赖氨酸模型。
The observed salt dependence of charged ligand binding to polyelectrolytes, such as proteins to DNA or antithrombin to heparin, is often interpreted by means of the “oligolysine model.” We review this model as derived entirely within the framework of the counterion condensation theory of polyelectrolytes with no introduction of outside assumptions. We update its comparison with experimental data on the structurally simple systems for which it was originally intended. We then compute the salt-dependence of the binding free energy for a variety of protein-DNA complexes with nonlinear Poisson-Boltzmann (NLPB) simulation methods. The results of the NLPB calculations confirm the central prediction of the oligolysine model that the net charge density of DNA remains invariant to protein binding. Specifically, when a cationic protein residue penetrates the layer of counterions condensed on DNA, a counterion is released to bulk solution; and when an anionic protein residue penetrates the condensed counterion layer, an additional counterion is condensed from bulk solution. We also conclude, however, that the cumulative effect of charged protein residues distant from the binding interface makes a significant contribution to the salt dependence of binding, an observation not accommodated by the oligolysine model.
登录
查看更多内容
影响因子：
3
作者：
Boschitsch, Alexander H.;Fenley, Marcia O.
通讯作者：
Fenley, Marcia O.
影响因子：
2.9
作者：
GRANOT, J;KEARNS, DR
通讯作者：
KEARNS, DR
影响因子：
8.6
作者：
Qiu, XY;Kwok, LW;Pollack, L
通讯作者：
Pollack, L
影响因子：
3
作者：
Jayaram, B;McConnell, K;Beveridge, DL
通讯作者：
Beveridge, DL
影响因子：
4.4
作者：
RAMANATHAN, GV
通讯作者：
RAMANATHAN, GV