Towse Clare-Louise, Akke Mikael, Daggett Valerie
Department of Bioengineering, University of Washington , Box 355013, Seattle, Washington 98195-5013, United States.
Department of Biophysical Chemistry, Lund University , PO Box 124, SE-22100 Lund, Sweden.
J Phys Chem B. 2017 Apr 27;121(16):3933-3945. doi: 10.1021/acs.jpcb.7b00577. Epub 2017 Apr 19.
Molecular dynamics (MD) simulations contain considerable information with regard to the motions and fluctuations of a protein, the magnitude of which can be used to estimate conformational entropy. Here we survey conformational entropy across protein fold space using the Dynameomics database, which represents the largest existing data set of protein MD simulations for representatives of essentially all known protein folds. We provide an overview of MD-derived entropies accounting for all possible degrees of dihedral freedom on an unprecedented scale. Although different side chains might be expected to impose varying restrictions on the conformational space that the backbone can sample, we found that the backbone entropy and side chain size are not strictly coupled. An outcome of these analyses is the Dynameomics Entropy Dictionary, the contents of which have been compared with entropies derived by other theoretical approaches and experiment. As might be expected, the conformational entropies scale linearly with the number of residues, demonstrating that conformational entropy is an extensive property of proteins. The calculated conformational entropies of folding agree well with previous estimates. Detailed analysis of specific cases identifies deviations in conformational entropy from the average values that highlight how conformational entropy varies with sequence, secondary structure, and tertiary fold. Notably, α-helices have lower entropy on average than do β-sheets, and both are lower than coil regions.
分子动力学（MD）模拟包含了有关蛋白质运动和波动的大量信息，其大小可用于估计构象熵。在这里，我们使用动态基因组学数据库（Dynameomics database）来调查整个蛋白质折叠空间的构象熵，该数据库代表了几乎所有已知蛋白质折叠代表的现有最大蛋白质MD模拟数据集。我们以前所未有的规模概述了考虑所有可能二面角自由度的MD衍生熵。尽管不同的侧链可能会对主链能够采样的构象空间施加不同的限制，但我们发现主链熵和侧链大小并非严格耦合。这些分析的一个成果是动态基因组学熵字典，其内容已与其他理论方法和实验得出的熵进行了比较。正如预期的那样，构象熵与残基数量呈线性比例关系，这表明构象熵是蛋白质的一种广延性质。计算得到的折叠构象熵与先前的估计值吻合良好。对特定案例的详细分析确定了构象熵与平均值的偏差，这些偏差突出了构象熵如何随序列、二级结构和三级折叠而变化。值得注意的是，α螺旋的平均熵低于β折叠，且两者均低于无规卷曲区域。
