GemSpot: A Pipeline for Robust Modeling of Ligands into Cryo-EM Maps
GemSpot: A Pipeline for Robust Modeling of Ligands into Cryo-EM Maps
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DOI：
10.1016/j.str.2020.04.018
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发表时间：
2020-06-02
期刊：
影响因子：
5.7
通讯作者：
Skiniotis, Georgios
中科院分区：
文献类型：
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作者：
Robertson, Michael J.;van Zundert, Gydo C. P.;Skiniotis, Georgios
从低温电子显微镜(Cryo-EM)生成的图谱生成准确的生物分子-配体相互作用的原子模型通常会带来方法学和配体结合的动态性质所固有的挑战，在这里，我们介绍了GemSpot，这是一个自动化的计算化学方法流水线，它考虑了EM图谱势、量子力学能量计算和水分子位置预测，以生成候选姿势并提供置信度的测量。通过几个已发表的不同分辨率范围和不同类型配体的络合物的低温EM结构来验证该流水线。在所有情况下，至少有一个确定的姿势既能与目标产生良好的互动，又能与地图保持一致。GemSpot将对通过冷冻-EM进行配基姿势的稳健识别和药物发现工作具有重要价值。
Producing an accurate atomic model of biomolecule-ligand interactions from maps generated by cryoelectron microscopy (cryo-EM) often presents challenges inherent to the methodology and the dynamic nature of ligand binding, Here, we present GemSpot, an automated pipeline of computational chemistry methods that take into account EM map potentials, quantum mechanics energy calculations, and water molecule site prediction to generate candidate poses and provide a measure of the degree of confidence. The pipeline is validated through several published cryo-EM structures of complexes in different resolution ranges and various types of ligands. In all cases, at least one identified pose produced both excellent interactions with the target and agreement with the map. GemSpot will be valuable for the robust identification of ligand poses and drug discovery efforts through cryo-EM.