Biopolymers. 1978 Oct;17(10):2341-60. doi: 10.1002/bip.1978.360171005.
An optimized potential function for base-stacking interactions is constructed. Stacking energies between the complementary pairs of a dimer are calculated as a function of the rotational angle and separation distance. Using several different sets of atomic charges, the electrostatic component in the monopole-monopole approximation (MMA) is compared to the more refined segmented multipole-multipole representation (SMMA); the general features of the stacking minima are found to be correctly reproduced with IEHT or CNDO atomic charges. The electrostatic component is observed to control the location of stacking minima.The MMA, in general, is not a reliable approximation of the SMMA in regions away from minima; however, the MMA is reliable in predicting the location and nature of stacking minima.The attractive part of the Lennard-Jones 6-12 potential is compared to and parameterized against the expressions for the second-order interaction terms composed of multipole-bond polarizability for the polarization energy and transition-dipole bond polariz abilities for approximation of the dispersion energy. The repulsive part of the Lennard-Jones potential is compared to a Kitaygorodski-type repulsive function; changing the exponent from its usual value of 12 to 11.7 gives significantly better agreement with the more refined repulsive function.Stacking minima calculated with the optimized potential method are compared with various perturbation-type treatments. The optimized potential method yields results that compare as well with melting data as do any of the more recent and expensive perturbation methods.
构建了一种优化的碱基堆积相互作用势能函数。计算了二聚体互补对之间的堆积能作为旋转角度和分离距离的函数。使用几组不同的原子电荷,在单核-单核近似(MMA)中单极-单极静电分量与更精细的分段多极-多极表示(SMMA)进行比较;发现堆积最小值的一般特征可以用 IEHT 或 CNDO 原子电荷正确再现。静电分量控制堆积最小值的位置。MMA 通常不是 SMMA 在远离最小值区域的可靠近似;然而,MMA 可靠地预测了堆积最小值的位置和性质。比较 Lennard-Jones 6-12 势能的吸引力部分,并将其参数化,以与由多极-键极化率组成的二阶相互作用项的表达式进行比较,用于极化能,以及过渡偶极键极化率用于近似色散能。Lennard-Jones 势能的排斥部分与 Kitaygorodski 型排斥函数进行比较;将指数从通常的 12 变为 11.7,与更精细的排斥函数的一致性显著提高。用优化势能法计算的堆积最小值与各种微扰型处理进行比较。优化势能法的结果与熔化数据的比较与任何最近和更昂贵的微扰方法一样好。