Sheridan Robert P, McGaughey Georgia B, Cornell Wendy D
Molecular Systems Department, Merck Research Laboratories, RY50SW-100, Rahway, NJ 07065, USA.
J Comput Aided Mol Des. 2008 Mar-Apr;22(3-4):257-65. doi: 10.1007/s10822-008-9168-9. Epub 2008 Feb 14.
As an extension to a previous published study (McGaughey et al., J Chem Inf Model 47:1504-1519, 2007) comparing 2D and 3D similarity methods to docking, we apply a subset of those virtual screening methods (TOPOSIM, SQW, ROCS-color, and Glide) to a set of protein/ligand pairs where the protein is the target for docking and the cocrystallized ligand is the target for the similarity methods. Each protein is represented by a maximum of five crystal structures. We search a diverse subset of the MDDR as well as a diverse small subset of the MCIDB, Merck's proprietary database. It is seen that the relative effectiveness of virtual screening methods, as measured by the enrichment factor, is highly dependent on the particular crystal structure or ligand, and on the database being searched. 2D similarity methods appear very good for the MDDR, but poor for the MCIDB. However, ROCS-color (a 3D similarity method) does well for both databases.
作为对之前发表的一项研究(McGaughey等人,《化学信息与建模杂志》47:1504 - 1519,2007年)的扩展,该研究比较了二维和三维相似性方法与对接方法,我们将那些虚拟筛选方法的一个子集(TOPOSIM、SQW、ROCS - color和Glide)应用于一组蛋白质/配体对,其中蛋白质是对接的目标,而共结晶配体是相似性方法的目标。每个蛋白质最多由五个晶体结构表示。我们搜索了MDDR的一个多样化子集以及默克公司的专有数据库MCIDB的一个多样化小子集。可以看出,通过富集因子衡量的虚拟筛选方法的相对有效性高度依赖于特定的晶体结构或配体,以及所搜索的数据库。二维相似性方法在MDDR中表现非常好,但在MCIDB中表现不佳。然而,ROCS - color(一种三维相似性方法)在两个数据库中都表现良好。