Zhang Jian, Lin Ming, Chen Rong, Wang Wei, Liang Jie
Department of Bioengineering, University of Illinois at Chicago, Chicago, Illinois 60607, USA.
J Chem Phys. 2008 Mar 28;128(12):125107. doi: 10.1063/1.2895050.
Conformational entropy makes important contribution to the stability and folding of RNA molecule, but it is challenging to either measure or compute conformational entropy associated with long loops. We develop optimized discrete k-state models of RNA backbone based on known RNA structures for computing entropy of loops, which are modeled as self-avoiding walks. To estimate entropy of hairpin, bulge, internal loop, and multibranch loop of long length (up to 50), we develop an efficient sampling method based on the sequential Monte Carlo principle. Our method considers excluded volume effect. It is general and can be applied to calculating entropy of loops with longer length and arbitrary complexity. For loops of short length, our results are in good agreement with a recent theoretical model and experimental measurement. For long loops, our estimated entropy of hairpin loops is in excellent agreement with the Jacobson-Stockmayer extrapolation model. However, for bulge loops and more complex secondary structures such as internal and multibranch loops, we find that the Jacobson-Stockmayer extrapolation model has large errors. Based on estimated entropy, we have developed empirical formulae for accurate calculation of entropy of long loops in different secondary structures. Our study on the effect of asymmetric size of loops suggest that loop entropy of internal loops is largely determined by the total loop length, and is only marginally affected by the asymmetric size of the two loops. Our finding suggests that the significant asymmetric effects of loop length in internal loops measured by experiments are likely to be partially enthalpic. Our method can be applied to develop improved energy parameters important for studying RNA stability and folding, and for predicting RNA secondary and tertiary structures. The discrete model and the program used to calculate loop entropy can be downloaded at http://gila.bioengr.uic.edu/resources/RNA.html.
构象熵对RNA分子的稳定性和折叠起着重要作用,但测量或计算与长环相关的构象熵具有挑战性。我们基于已知的RNA结构开发了优化的RNA主链离散k态模型,用于计算环的熵,环被建模为自回避行走。为了估计长长度(最长50)的发夹环、凸起环、内环和多分支环的熵,我们基于序贯蒙特卡罗原理开发了一种有效的采样方法。我们的方法考虑了排除体积效应。它具有通用性,可应用于计算更长长度和任意复杂度环的熵。对于短长度的环,我们的结果与最近的理论模型和实验测量结果吻合良好。对于长环,我们估计的发夹环熵与雅各布森 - 斯托克迈耶外推模型高度吻合。然而,对于凸起环和更复杂的二级结构,如内环和多分支环,我们发现雅各布森 - 斯托克迈耶外推模型存在较大误差。基于估计的熵,我们开发了经验公式,用于准确计算不同二级结构中长环的熵。我们对环的不对称大小效应的研究表明,内环的环熵在很大程度上由环的总长度决定,仅略微受两个环的不对称大小影响。我们的发现表明,实验测量的内环中环长度的显著不对称效应可能部分是焓效应。我们的方法可用于开发对研究RNA稳定性和折叠以及预测RNA二级和三级结构重要的改进能量参数。用于计算环熵的离散模型和程序可从http://gila.bioengr.uic.edu/resources/RNA.html下载。