Jacobs Donald J, Dallakyan S, Wood G G, Heckathorne A
Physics and Astronomy Department, California State University, Northridge, California 91330, USA.
Phys Rev E Stat Nonlin Soft Matter Phys. 2003 Dec;68(6 Pt 1):061109. doi: 10.1103/PhysRevE.68.061109. Epub 2003 Dec 31.
A statistical mechanical distance constraint model (DCM) is presented that explicitly accounts for network rigidity among constraints present within a system. Constraints are characterized by local microscopic free-energy functions. Topological rearrangements of thermally fluctuating constraints are permitted. The partition function is obtained by combining microscopic free energies of individual constraints using network rigidity as an underlying long-range mechanical interaction, giving a quantitative explanation for the nonadditivity in component entropies exhibited in molecular systems. Two exactly solved two-dimensional toy models representing flexible molecules that can undergo conformational change are presented to elucidate concepts, and to outline a DCM calculation scheme applicable to many types of physical systems. It is proposed that network rigidity plays a central role in balancing the energetic and entropic contributions to the free energy of biopolymers, such as proteins. As a demonstration, the distance constraint model is solved exactly for the alpha-helix to coil transition in homogeneous peptides. Temperature and size independent model parameters are fitted to Monte Carlo simulation data, which includes peptides of length 10 for gas phase, and lengths 10, 15, 20, and 30 in water. The DCM is compared to the Lifson-Roig model. It is found that network rigidity provides a mechanism for cooperativity in molecular structures including their ability to spontaneously self-organize. In particular, the formation of a characteristic topological arrangement of constraints is associated with the most probable microstates changing under different thermodynamic conditions.
提出了一种统计力学距离约束模型(DCM),该模型明确考虑了系统内存在的约束之间的网络刚性。约束由局部微观自由能函数表征。允许热涨落约束的拓扑重排。通过将各个约束的微观自由能结合起来,以网络刚性作为潜在的长程力学相互作用来获得配分函数,从而对分子系统中组分熵的非加和性给出定量解释。给出了两个精确求解的二维玩具模型,它们代表了可以发生构象变化的柔性分子,以阐明概念,并概述适用于多种物理系统的DCM计算方案。有人提出,网络刚性在平衡对生物聚合物(如蛋白质)自由能的能量和熵贡献方面起着核心作用。作为一个例证,对均匀肽段中α-螺旋到卷曲的转变精确求解了距离约束模型。将与温度和尺寸无关的模型参数拟合到蒙特卡罗模拟数据,这些数据包括气相中长度为10的肽段以及水中长度为10、15、20和30的肽段。将DCM与利夫森-罗伊格模型进行了比较。发现网络刚性为分子结构中的协同性提供了一种机制,包括它们自发自组装的能力。特别是,约束的特征拓扑排列的形成与在不同热力学条件下最可能的微观状态变化相关。