Killian Benjamin J, Kravitz Joslyn Yudenfreund, Somani Sandeep, Dasgupta Paramita, Pang Yuan-Ping, Gilson Michael K
Center for Advanced Research in Biotechnology, University of Maryland Biotechnology Institute, 9600 Gudelsky Drive, Rockville, MD 20850, USA.
J Mol Biol. 2009 Jun 5;389(2):315-35. doi: 10.1016/j.jmb.2009.04.003. Epub 2009 Apr 9.
Configurational entropy is thought to influence biomolecular processes, but there are still many open questions about this quantity, including its magnitude, its relationship to molecular structure, and the importance of correlation. The mutual information expansion (MIE) provides a novel and systematic approach to extracting configurational entropy changes due to correlated motions from molecular simulations. We present the first application of the MIE method to protein-ligand binding using multiple molecular dynamics simulations to study the association of the ubiquitin E2 variant domain of the protein Tsg101 and an HIV-derived nonapeptide. This investigation utilizes the second-order MIE approximation, which accounts for correlations between all pairs of degrees of freedom. The computed change in configurational entropy is large and has a major contribution from changes in pairwise correlation. The results also reveal intricate structure-entropy relationships. Thus, the present analysis suggests that in order for a model of binding to be accurate, it must include a careful accounting of configurational entropy changes.
构象熵被认为会影响生物分子过程,但关于这个量仍有许多悬而未决的问题,包括其大小、与分子结构的关系以及相关性的重要性。互信息展开(MIE)提供了一种新颖且系统的方法,用于从分子模拟中提取由于相关运动引起的构象熵变化。我们首次将MIE方法应用于蛋白质-配体结合,使用多个分子动力学模拟来研究蛋白质Tsg101的泛素E2变体结构域与一种HIV衍生的九肽之间的结合。这项研究采用了二阶MIE近似,该近似考虑了所有自由度对之间的相关性。计算得到的构象熵变化很大,且成对相关性的变化起主要作用。结果还揭示了复杂的结构-熵关系。因此,目前的分析表明,为了使结合模型准确,必须仔细考虑构象熵的变化。