Fenley Andrew T, Killian Benjamin J, Hnizdo Vladimir, Fedorowicz Adam, Sharp Dan S, Gilson Michael K
Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California at San Diego , 9500 Gilman Drive, La Jolla, California 92093, United States.
J Phys Chem B. 2014 Jun 19;118(24):6447-55. doi: 10.1021/jp411588b. Epub 2014 Apr 18.
For biomolecules in solution, changes in configurational entropy are thought to contribute substantially to the free energies of processes like binding and conformational change. In principle, the configurational entropy can be strongly affected by pairwise and higher-order correlations among conformational degrees of freedom. However, the literature offers mixed perspectives regarding the contributions that changes in correlations make to changes in configurational entropy for such processes. Here we take advantage of powerful techniques for simulation and entropy analysis to carry out rigorous in silico studies of correlation in binding and conformational changes. In particular, we apply information-theoretic expansions of the configurational entropy to well-sampled molecular dynamics simulations of a model host-guest system and the protein bovine pancreatic trypsin inhibitor. The results bear on the interpretation of NMR data, as they indicate that changes in correlation are important determinants of entropy changes for biologically relevant processes and that changes in correlation may either balance or reinforce changes in first-order entropy. The results also highlight the importance of main-chain torsions as contributors to changes in protein configurational entropy. As simulation techniques grow in power, the mathematical techniques used here will offer new opportunities to answer challenging questions about complex molecular systems.
对于溶液中的生物分子,构型熵的变化被认为对诸如结合和构象变化等过程的自由能有很大贡献。原则上,构型熵会受到构象自由度之间成对及高阶相关性的强烈影响。然而,关于相关性变化对这类过程构型熵变化的贡献,文献给出了不同的观点。在此,我们利用强大的模拟和熵分析技术,对结合和构象变化中的相关性进行严格的计算机模拟研究。具体而言,我们将构型熵的信息论展开应用于一个模型主客体系统和蛋白质牛胰蛋白酶抑制剂的充分采样分子动力学模拟。这些结果与核磁共振数据的解释相关,因为它们表明相关性变化是生物相关过程熵变化的重要决定因素,并且相关性变化可能平衡或增强一阶熵的变化。结果还突出了主链扭转作为蛋白质构型熵变化贡献因素的重要性。随着模拟技术能力的提升,这里使用的数学技术将为回答有关复杂分子系统的挑战性问题提供新机会。