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AutoDock中柔性大环对接的性能评估。

Performance evaluation of flexible macrocycle docking in AutoDock.

作者信息

Holcomb Matthew, Santos-Martins Diogo, Tillack Andreas F, Forli Stefano

机构信息

Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA 92037, USA.

出版信息

QRB Discov. 2022 Oct 17;3:e18. doi: 10.1017/qrd.2022.18. eCollection 2022.

Abstract

Macrocycles represent an important class of ligands, both in natural products and designed drugs. In drug design, macrocyclizations can impart specific ligand conformations and contribute to passive permeation by encouraging intramolecular H-bonds. AutoDock-GPU and Vina can model macrocyclic ligands flexibly, without requiring the enumeration of macrocyclic conformers before docking. Here, we characterize the performance of the method for handling macrocyclic compounds, which is implemented and the default behaviour for ligand preparation with our ligand preparation pipeline, Meeko. A pseudoatom is used to encode bond geometry and produce an anisotropic closure force for macrocyclic rings. This method is evaluated on a diverse set of small molecule and peptide macrocycles, ranging from 7- to 33-membered rings, showing little accuracy loss compared to rigid redocking of the X-ray macrocycle conformers. This suggests that for conformationally flexible macrocycles with unknown binding modes, this method can be effectively used to predict the macrocycle conformation.

摘要

大环化合物在天然产物和设计药物中都是一类重要的配体。在药物设计中,大环化可以赋予特定的配体构象,并通过促进分子内氢键来有助于被动渗透。AutoDock-GPU和Vina可以灵活地对大环配体进行建模,无需在对接前枚举大环构象异构体。在此,我们表征了处理大环化合物方法的性能,该方法是通过我们的配体制备流程Meeko实现的,并且是配体制备的默认行为。使用一个伪原子来编码键几何结构,并为大环环产生各向异性的封闭力。该方法在一系列不同的小分子和肽大环化合物上进行了评估,环的大小从7元环到33元环不等,与X射线大环构象异构体的刚性重新对接相比,精度损失很小。这表明对于结合模式未知的构象灵活的大环化合物,该方法可以有效地用于预测大环构象。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7fca/10392634/1a92b685b44e/S2633289222000187_figAb.jpg

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