N D Zelinsky Institute Of Organic Chemistry (ZIOC RAS), Moscow, Russia.
J Mol Model. 2012 Jun;18(6):2553-66. doi: 10.1007/s00894-011-1280-4. Epub 2011 Nov 9.
Virtual fragment screening could be a promising alternative to existing experimental screening techniques. However, reliable methods of in silico fragment screening are yet to be established and validated. In order to develop such an approach we first checked how successful the existing molecular docking methods can be in predicting fragment binding affinities and poses. Using our Lead Finder docking software the RMSD of the binding energy prediction was observed to be 1.35 kcal/mol(-1) on a set of 26 experimentally characterized fragment inhibitors, and the RMSD of the predicted binding pose from the experimental one was <1.5 Å. Then, we explored docking of 68 fragments obtained from 39 drug molecules for which co-crystal structures were available from the PDB. It appeared that fragments that participate in oriented non-covalent interactions, such as hydrogen bonds and metal coordination, could be correctly docked in 70-80% of cases suggesting the potential success of rediscovering of corresponding drugs by in silico fragment approach. Based on these findings we've developed a virtual fragment screening technique which involved structural filtration of protein-ligand complexes for specific interactions and subsequent clustering in order to minimize the number of preferable starting fragment candidates. Application of this method led to 2 millimolar-scale fragment PARP1 inhibitors with a new scaffold.
虚拟片段筛选可能是现有实验筛选技术的一种有前途的替代方法。然而,可靠的计算片段筛选方法尚未建立和验证。为了开发这种方法,我们首先检查了现有的分子对接方法在预测片段结合亲和力和构象方面的成功程度。使用我们的 Lead Finder 对接软件,在一组 26 种经过实验表征的片段抑制剂上,观察到结合能预测的 RMSD 为 1.35 kcal/mol(-1),预测的结合构象与实验构象的 RMSD 小于 1.5 Å。然后,我们探索了 68 个片段的对接,这些片段来自 39 个药物分子,这些药物分子的共晶结构可从 PDB 获得。结果表明,参与定向非共价相互作用(如氢键和金属配位)的片段可以在 70-80%的情况下正确对接,这表明通过计算片段方法重新发现相应药物的潜在成功。基于这些发现,我们开发了一种虚拟片段筛选技术,该技术涉及对特定相互作用的蛋白质-配体复合物进行结构过滤,然后进行聚类,以最小化优选起始片段候选物的数量。该方法的应用导致了具有新骨架的 2 毫摩尔级 PARP1 片段抑制剂。