Rapid flexible docking using a stochastic rotamer library of ligands

By Feng Ding, Shuangye Yin, N. V. Dokholyan. 2010

97 citations recorded by the source corpus.

Existing flexible docking approaches model the ligand and receptor flexibility either separately or in a loosely-coupled manner, which captures the conformational changes inefficiently. Here, we propose a flexible docking approach, MedusaDock, which models both ligand and receptor flexibility simultaneously with sets of discrete rotamers. We develop an algorithm to build the ligand rotamer library “on-the-fly” during docking simulations. MedusaDock benchmarks demonstrate a rapid sampling efficiency and high prediction accuracy in both self-docking (to the co-crystallized state) and cross-docking (to a state co-crystallized with a different ligand), the latter of which mimics the virtual-screening procedure in computational drug discovery. We also perform a virtual-screening test of four flexible kinase targets including cyclin-dependent kinase 2, vascular endothelial growth factor receptor 2, HIV reverse transcriptase, and HIV protease. We find significant improvements of virtual-screening enrichments when compared to rigid-receptor methods. The predictive power of MedusaDock in cross-docking and preliminary virtual-screening benchmarks highlights the importance to model both ligand and receptor flexibility simultaneously in computational docking.

Subfields: Computational Theory and Mathematics, Materials Chemistry, Molecular Biology

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Citations in the corpus

Latest developments in molecular docking: 2010–2011 in review (2013, background): “[8,11,13,15,18] It is dif ﬁ cult to judge whether this indicates that signi ﬁ cant breakthroughs are about to hit the docking ﬁ eld or simply the crowding of the ﬁ eld with minor incremental developments.”
Discrete molecular dynamics distinguishes nativelike binding poses from decoys in difficult targets. (2012, methodology): “MedusaDock generates poses using the structural information in a supplied PDB file of the target and MOL2 file of the ligand.”
MedusaDock 2.0: Efficient and Accurate Protein-Ligand Docking With Constraints (2019, methodology): “First, exploring both the receptor and the ligand flexibility 4,5,13 , which is critical for simulating induced-fit phenomenon and improving the reliability of the predictions, is not computationally feasible for the ligands with a large number of rotatable bonds.”