Fully Flexible Docking of Medium Sized Ligand Libraries with RosettaLigand.
Fully Flexible Docking of Medium Sized Ligand Libraries with RosettaLigand.
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DOI：
10.1371/journal.pone.0132508
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发表时间：
2015
期刊：
影响因子：
3.7
通讯作者：
Meiler J
中科院分区：
文献类型：
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作者：
DeLuca S;Khar K;Meiler J
RosettaLigand已成功用于预测蛋白质-小分子复合物的结合位姿。然而，RosettaLigand对接方案在识别小分子（配体）的初始起始姿态方面相对较慢，使得其不可行用于虚拟高通量筛选（vHTS）。为了克服这一限制，我们开发了一种新的采样方法，用于在最初的“低分辨率”对接步骤中将配体放置在蛋白质结合位点。它在单个变换步骤中结合了对配体位姿的平移和旋转调整。新算法更准确，更省时。在43种蛋白质/配体复合物的基准组中，对接成功率提高了10-15%，将通常需要生成的模型数量从1000减少到150。生成模型的平均时间从50秒减少到10秒。因此，我们观察到有效的30倍速度增加，使RosettaLigand适合对接中等大小的配体文库。我们证明，这种改进的配体的初始位置是成功预测的准确的结合位置在“高分辨率”的全原子细化步骤的关键。
RosettaLigand has been successfully used to predict binding poses in protein-small molecule complexes. However, the RosettaLigand docking protocol is comparatively slow in identifying an initial starting pose for the small molecule (ligand) making it unfeasible for use in virtual High Throughput Screening (vHTS). To overcome this limitation, we developed a new sampling approach for placing the ligand in the protein binding site during the initial ‘low-resolution’ docking step. It combines the translational and rotational adjustments to the ligand pose in a single transformation step. The new algorithm is both more accurate and more time-efficient. The docking success rate is improved by 10–15% in a benchmark set of 43 protein/ligand complexes, reducing the number of models that typically need to be generated from 1000 to 150. The average time to generate a model is reduced from 50 seconds to 10 seconds. As a result we observe an effective 30-fold speed increase, making RosettaLigand appropriate for docking medium sized ligand libraries. We demonstrate that this improved initial placement of the ligand is critical for successful prediction of an accurate binding position in the ‘high-resolution’ full atom refinement step.