Ishchenko Alexey V, Shakhnovich Eugene I
Department of Chemistry and Chemical Biology, Harvard University, 12 Oxford Street, Cambridge, MA 02138, USA.
J Med Chem. 2002 Jun 20;45(13):2770-80. doi: 10.1021/jm0105833.
Computational lead design procedures require fast and accurate scoring functions to rank millions of generated virtual ligands for protein targets. In this article, we present an improved version of the SMoG scoring function, called SMoG2001. This function is based on a knowledge-based approach-that is, the free energy parameters are derived from the observed frequencies of atom-atom contacts in the database of three-dimensional structures of protein-ligand complexes via a procedure based on statistical mechanics. We obtained the statistics from the set of 725 complexes. SMoG2001 reproduces the experimental binding constants of the majority of 119 complexes of the testing set with good accuracy. On similar testing sets, SMoG2001 performs better than two other widely used scoring functions, PMF and SCORE1(LUDI), and comparably to DrugScore. SMoG2001 poorly predicts the affinities of ligands interacting via quantum mechanical forces with metal ions and ligands that are large and flexible. We attribute significant improvement in accuracy over previous versions of the SMoG scoring function to a better description of the reference state-that is, the state of no interactions.
计算机辅助先导设计程序需要快速且准确的评分函数，以便对针对蛋白质靶点生成的数百万个虚拟配体进行排名。在本文中，我们展示了SMoG评分函数的一个改进版本，称为SMoG2001。该函数基于一种基于知识的方法，即自由能参数是通过基于统计力学的程序，从蛋白质-配体复合物三维结构数据库中原子-原子接触的观察频率推导出来的。我们从725个复合物的集合中获得了统计数据。SMoG2001能够以良好的准确性重现测试集中119个复合物中大多数的实验结合常数。在类似的测试集上，SMoG2001的表现优于另外两个广泛使用的评分函数PMF和SCORE1（LUDI），与DrugScore相当。SMoG2001难以预测通过量子力学力与金属离子相互作用的配体以及大的和柔性的配体的亲和力。我们将相对于SMoG评分函数以前版本准确性的显著提高归因于对参考状态（即无相互作用状态）的更好描述。
