Computational protein–ligand docking is well-known to be prone to inaccuracies in input receptor structures, and it is challenging to obtain good docking results with computationally predicted receptor structures (e.g. through homology modeling). Here we introduce a fragment-based docking method and test if it reduces requirements on the accuracy of an input receptor structures relative to non-fragment docking approaches. In this method, small rigid fragments are docked first using AutoDock Vina to generate a large number of favorably docked poses spanning the receptor binding pocket. Then a graph theory maximum clique algorithm is applied to find combined sets of docked poses of different fragment types onto which the complete ligand can be properly aligned. On the basis of these alignments, possible binding poses of complete ligand are determined. This docking method is first tested for bound docking on a series of Cytochrome P450 (CYP450) enzyme–substrate complexes, in which experimentally determined receptor structures are used. For all complexes tested, ligand poses of less than 1 Å root mean square deviations (RMSD) from the actual binding positions can be recovered. Then the method is tested for unbound docking with modeled receptor structures for a number of protein–ligand complexes from different families including the very recent severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) protease. For all complexes, poses with RMSD less than 3 Å from actual binding positions can be recovered. Our results suggest that for docking with approximately modeled receptor structures, fragment-based methods can be more effective than common complete ligand docking approaches.

众所周知，计算性蛋白质-配体对接容易导致输入受体结构不准确，并且要通过计算预测的受体结构（例如通过同源性建模）获得良好的对接结果，这是具有挑战性的。在这里，我们介绍一种基于片段的对接方法，并测试它是否相对于非片段对接方法降低了对输入受体结构精度的要求。在这种方法中，首先使用AutoDock Vina对接小的刚性碎片，以生成跨越受体结合袋的大量有利对接的姿势。然后，应用图论最大集团算法来找到不同片段类型的对接姿势的组合集，完整的配体可以正确对齐。根据这些对齐方式，确定完整配体的可能结合姿势。这种对接方法首先经过测试，可以在一系列细胞色素P450（CYP450）酶-底物复合物中进行结合对接，其中使用了实验确定的受体结构。对于所有测试的复合物，与实际结合位置相比，均可以得到小于1Å均方根偏差（RMSD）的配体位姿。然后对该方法进行测试，以模拟的受体结构与来自不同家族的许多蛋白质-配体复合物的未结合对接，包括最近的严重急性呼吸综合症冠状病毒2（SARS-CoV-2）蛋白酶。对于所有复合物，均可以恢复RMSD距实际结合位置小于3Å的姿势。我们的结果表明，要与近似建模的受体结构对接，