Selecting an Optimal Number of Binding Site Waters To Improve Virtual Screening Enrichments Against the Adenosine A2A Receptor

A major challenge in structure-based virtual screening (VS) involves the treatment of explicit water molecules during docking in order to improve the enrichment of active compounds over decoys. Here we have investigated this in the context of the adenosine A2A receptor, where water molecules have previously been shown to be important for achieving high enrichment rates with docking, and where the positions of some binding site waters are known from a high-resolution crystal structure. The effect of these waters (both their presence and orientations) on VS enrichment was assessed using a carefully curated set of 299 high affinity A2A antagonists and 17,337 decoys. We show that including certain crystal waters greatly improves VS enrichment and that optimization of water hydrogen positions is needed in order to achieve the best results. We also show that waters derived from a molecular dynamics simulation  without any knowledge of crystallographic waters  can improve enrichments to a similar degree as the crystallographic waters, which makes this strategy applicable to structures without experimental knowledge of water positions. Finally, we used decision trees to select an ensemble of structures with different water molecule positions and orientations that outperforms any single structure with water molecules. The approach presented here is validated against independent test sets of A2A receptor antagonists and decoys from the literature. In general, this water optimization strategy could be applied to any target with waters-mediated protein–ligand interactions.

基于结构的虚拟筛选（structure-based virtual screening，VS）领域面临的一大核心挑战，在于分子对接（docking）过程中对显式水分子的处理策略，以期提升活性化合物相较于诱饵化合物（decoys）的富集效果。本研究以腺苷A2A受体为研究对象，针对该问题展开探究：此前已有研究证实，水分子对实现高分子对接富集率具有关键作用，且部分结合位点水分子的位置可通过高分辨率晶体结构获知。本研究采用经精心甄选的299种高亲和力腺苷A2A受体拮抗剂与17337种诱饵化合物，评估了此类水分子（包括其存在与否与空间取向）对虚拟筛选富集效果的影响。研究结果表明，保留部分晶体水分子可显著提升虚拟筛选的富集效果，且优化水分子的氢原子位置是获取最优结果的必要条件。此外，本研究还证实，无需依赖晶体水分子的先验知识，仅通过分子动力学模拟（molecular dynamics simulation）得到的水分子即可达到与晶体水分子相当的富集效果提升幅度，这使得该策略可推广至尚无实验水分子位置信息的蛋白结构研究中。最后，本研究采用决策树（decision trees）筛选得到包含不同水分子位置与取向的结构集合，该集合的表现优于任何单含水分子的蛋白结构。本研究所提出的方法通过独立测试集完成验证，该测试集包含来自公开文献的腺苷A2A受体拮抗剂与诱饵化合物。总体而言，该水分子优化策略可应用于所有存在水分子介导的蛋白-配体相互作用（protein–ligand interactions）的药物靶点。