Cavasotto Claudio N, Abagyan Ruben A
Molsoft LLC, 3366 N Torrey Pines Ct. Suite 300, La Jolla, CA 92037, USA.
J Mol Biol. 2004 Mar 12;337(1):209-25. doi: 10.1016/j.jmb.2004.01.003.
The main complicating factor in structure-based drug design is receptor rearrangement upon ligand binding (induced fit). It is the induced fit that complicates cross-docking of ligands from different ligand-receptor complexes. Previous studies have shown the necessity to include protein flexibility in ligand docking and virtual screening. Very few docking methods have been developed to predict the induced fit reliably and, at the same time, to improve on discriminating between binders and non-binders in the virtual screening process. We present an algorithm called the ICM-flexible receptor docking algorithm (IFREDA) to account for protein flexibility in virtual screening. By docking flexible ligands to a flexible receptor, IFREDA generates a discrete set of receptor conformations, which are then used to perform flexible ligand-rigid receptor docking and scoring. This is followed by a merging and shrinking step, where the results of the multiple virtual screenings are condensed to improve the enrichment factor. In the IFREDA approach, both side-chain rearrangements and essential backbone movements are taken into consideration, thus sampling adequately the conformational space of the receptor, even in cases of large loop movements. As a preliminary step, to show the importance of incorporating protein flexibility in ligand docking and virtual screening, and to validate the merging and shrinking procedure, we compiled an extensive small-scale virtual screening benchmark of 33 crystal structures of four different protein kinases sub-families (cAPK, CDK-2, P38 and LCK), where we obtained an enrichment factor fold-increase of 1.85+/-0.65 using two or three multiple experimental conformations. IFREDA was used in eight protein kinase complexes and was able to find the correct ligand conformation and discriminate the correct conformations from the "misdocked" conformations solely on the basis of energy calculation. Five of the generated structures were used in the small-scale virtual screening stage and, by merging and shrinking the results with those of the original structure, we show an enrichment factor fold increase of 1.89+/-0.60, comparable to that obtained using multiple experimental conformations. Our cross-docking tests on the protein kinase benchmark underscore the necessity of incorporating protein flexibility in both ligand docking and virtual screening. The methodology presented here will be extremely useful in cases where few or no experimental structures of complexes are available, while some binders are known.
基于结构的药物设计中的主要复杂因素是配体结合时受体的重排(诱导契合)。正是诱导契合使得来自不同配体-受体复合物的配体交叉对接变得复杂。先前的研究表明在配体对接和虚拟筛选中纳入蛋白质柔性的必要性。很少有对接方法被开发出来能够可靠地预测诱导契合,同时在虚拟筛选过程中提高区分结合剂和非结合剂的能力。我们提出了一种名为ICM-柔性受体对接算法(IFREDA)的算法,以在虚拟筛选中考虑蛋白质柔性。通过将柔性配体对接至柔性受体,IFREDA生成一组离散的受体构象,然后用于进行柔性配体-刚性受体对接和评分。接下来是合并和缩减步骤,在此步骤中,多次虚拟筛选的结果被浓缩以提高富集因子。在IFREDA方法中,侧链重排和主链的关键移动都被考虑在内,因此即使在大环移动的情况下也能充分采样受体的构象空间。作为初步步骤,为了展示在配体对接和虚拟筛选中纳入蛋白质柔性的重要性,并验证合并和缩减程序,我们编制了一个广泛的小规模虚拟筛选基准,包含四个不同蛋白激酶亚家族(cAPK、CDK-2、P38和LCK)的33个晶体结构,在此我们使用两到三个多个实验构象获得了1.85±0.65的富集因子倍数增加。IFREDA被用于八个蛋白激酶复合物,并且仅基于能量计算就能找到正确的配体构象并将正确构象与“错误对接”构象区分开来。在小规模虚拟筛选阶段使用了生成的五个结构,通过将结果与原始结构的结果合并和缩减,我们展示了1.89±0.60的富集因子倍数增加,与使用多个实验构象获得的结果相当。我们在蛋白激酶基准上的交叉对接测试强调了在配体对接和虚拟筛选中纳入蛋白质柔性的必要性。此处介绍的方法在几乎没有或没有复合物实验结构但已知一些结合剂的情况下将极其有用。