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首页> 外文期刊>Journal of Molecular Biology >Protein flexibility in ligand docking and virtual screening to protein kinases.
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Protein flexibility in ligand docking and virtual screening to protein kinases.

机译:配体对接和蛋白质激酶虚拟筛选中的蛋白质灵活性。

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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 enrichmentfactor. 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.
机译:基于结构的药物设计中的主要复杂因素是配体结合后的受体重排(诱导拟合)。正是这种诱导的拟合使来自不同配体-受体复合物的配体的交叉对接变得复杂。先前的研究表明,必须在配体对接和虚拟筛选中包括蛋白质灵活性。已经开发了很少的对接方法来可靠地预测诱导的配合,同时改善虚拟筛选过程中粘合剂和非粘合剂的区分。我们提出一种称为ICM柔性受体对接算法(IFREDA)的算法,以解决虚拟筛选中的蛋白质灵活性。通过将柔性配体对接至柔性受体,IFREDA产生了一组离散的受体构象,然后将其用于进行柔性配体-刚性受体对接和评分。这之后是合并和收缩步骤,在该步骤中,将多次虚拟筛选的结果压缩在一起以改善富集因子。在IFREDA方法中,考虑了侧链重排和必要的主链运动,因此即使在大环运动的情况下,也要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灵活性的重要性,并验证合并和收缩程序,我们编制了一个广泛的小规模虚拟筛选基准,该基准涵盖了四种不同蛋白激酶的33个晶体结构。家族(cAPK,CDK-2,P38和LCK),我们使用两个或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用于八种蛋白激酶复合物,仅基于能量计算,就能够找到正确的配体构象,并从“错误对接”构象中区分出正确的构象。在小型虚拟筛选阶段使用了五个生成的结构,通过将结果与原始结构合并和缩小,我们显示出富集因子倍数增加了1.89 +/- 0.60,与使用多次获得的结果相当实验构象。我们在蛋白激酶基准测试中的对接测试强调了在配体对接和虚拟筛选中都必须结合蛋白灵活性的必要性。在很少或没有可用的配合物实验结构而已知某些粘合剂的情况下,此处介绍的方法将非常有用。

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