Donald Jason E, Chen William W, Shakhnovich Eugene I
Department of Chemistry and Chemical Biology, Harvard University, 12 Oxford St. Cambridge, MA 02138, USA.
Nucleic Acids Res. 2007;35(4):1039-47. doi: 10.1093/nar/gkl1103. Epub 2007 Jan 26.
Protein-DNA interactions are vital for many processes in living cells, especially transcriptional regulation and DNA modification. To further our understanding of these important processes on the microscopic level, it is necessary that theoretical models describe the macromolecular interaction energetics accurately. While several methods have been proposed, there has not been a careful comparison of how well the different methods are able to predict biologically important quantities such as the correct DNA binding sequence, total binding free energy and free energy changes caused by DNA mutation. In addition to carrying out the comparison, we present two important theoretical models developed initially in protein folding that have not yet been tried on protein-DNA interactions. In the process, we find that the results of these knowledge-based potentials show a strong dependence on the interaction distance and the derivation method. Finally, we present a knowledge-based potential that gives comparable or superior results to the best of the other methods, including the molecular mechanics force field AMBER99.
蛋白质与DNA的相互作用对活细胞中的许多过程至关重要，尤其是转录调控和DNA修饰。为了在微观层面上进一步理解这些重要过程，理论模型必须准确描述大分子相互作用的能量学。虽然已经提出了几种方法，但尚未对不同方法预测生物学上重要的量（如正确的DNA结合序列、总结合自由能和DNA突变引起的自由能变化）的能力进行仔细比较。除了进行比较之外，我们还介绍了最初在蛋白质折叠中开发的两个重要理论模型，这些模型尚未应用于蛋白质与DNA的相互作用。在此过程中，我们发现这些基于知识的势的结果强烈依赖于相互作用距离和推导方法。最后，我们提出了一种基于知识的势，其结果与其他最佳方法（包括分子力学力场AMBER９９）相当或更优。
