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COREF: A combined refinement approach for GPCRS backbone flexibility

机译：COREF：GPCRS主干灵活性的组合优化方法

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摘要

Two challenges for G-protein coupled receptor (GPCR)-ligand docking with flexibility by computational method are: (1) how to accurately model the perturbations of the backbone when docking ligand to the receptor and (2) how to sample the backbone near the binding pocket. To address the two challenges, we propose a combined refinement (coREF) approach working on the flexibility of the docking interface by integrating two different refinement protocols based on RosettaLigand (RL) platform. The first refinement protocol generates multiple initial receptors by parallelling different movements to mimic the observed simultaneous fluctuations of backbones near the binding site without ligand conformation. The second refinement protocol adds a backbone refinement step for interface residues with ligand conformation, which extending the RL docking algorithm. To validate the performance of coREF, we refined 20 GPCR Docking 2008/2010 models submitted by participants. Eight of 10 CXCR4 targets and half of D3 targets showed lower LRMSD values than the submitted models. Nine in 12 results were slightly better than those refined using the RL docking algorithm.
机译：G蛋白偶联受体（GPCR）-配体通过计算方法灵活对接的两个挑战是：（1）当配体与受体对接时如何准确建模骨架的扰动;（2）如何在接近配体的情况下对骨架进行采样装订袋。为了解决这两个挑战，我们提出了一种组合优化（coREF）方法，该方法通过集成基于RosettaLigand（RL）平台的两种不同的优化协议来实现对接接口的灵活性。第一种改进方案通过平行化不同的运动来生成多个初始受体，以模仿在没有配体构象的情况下在结合位点附近观察到的主链同时波动。第二种改进方案增加了具有配体构象的界面残基的骨架改进步骤，从而扩展了RL对接算法。为了验证coREF的性能，我们改进了参与者提交的20个GPCR Docking 2008/2010模型。 10个CXCR4目标中的8个和D3目标中的一半显示出比提交的模型更低的LRMSD值。 12个结果中有9个结果略优于使用RL对接算法精炼的结果。

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