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CDOCKER 和 λ-动力学在 D₃R 大挑战 2 中的前瞻性预测。

CDOCKER and λ-dynamics for prospective prediction in D₃R Grand Challenge 2.

机构信息

Department of Computational Medicine and Bioinformatics, Univeristy of Michigan, Ann Arbor, MI, 48109, USA.

Department of Chemistry, University of Michigan, Ann Arbor, MI, 48109, USA.

出版信息

J Comput Aided Mol Des. 2018 Jan;32(1):89-102. doi: 10.1007/s10822-017-0050-5. Epub 2017 Sep 7.

Abstract

The opportunity to prospectively predict ligand bound poses and free energies of binding to the Farnesoid X Receptor in the D3R Grand Challenge 2 provided a useful exercise to evaluate CHARMM based docking (CDOCKER) and [Formula: see text]-dynamics methodologies for use in "real-world" applications in computer aided drug design. In addition to measuring their current performance, several recent methodological developments have been analyzed retrospectively to highlight best procedural practices in future applications. For pose prediction with CDOCKER, when the protein structure used for rigid receptor docking was close to the crystallographic holo structure, reliable poses were obtained. Benzimidazoles, with a known holo receptor structure, were successfully docked with an average RMSD of 0.97 [Formula: see text]. Other non-benzimidazole ligands displayed less accuracy largely because the receptor structures we chose for docking were too different from the experimental holo structures. However, retrospective analysis has shown that when these ligands were re-docked into their holo structures, the average RMSD dropped to 1.18 [Formula: see text] for all ligands. When sulfonamides and spiros were docked with the apo structure, which agrees more with their holo structure than the structures we chose, five out of six ligands were correctly docked. These docking results emphasize the need for flexible receptor docking approaches. For [Formula: see text]-dynamics techniques, including multisite [Formula: see text]-dynamics (MS[Formula: see text]D), reasonable agreement with experiment was observed for the 33 ligands investigated; root mean square errors of 2.08 and 1.67 kcal/mol were obtained for free energy sets 1 and 2, respectively. Retrospectively, soft-core potentials, adaptive landscape flattening, and biasing potential replica exchange (BP-REX) algorithms were critical to model large substituent perturbations with sufficient precision and within restrictive timeframes, such as was required with participation in Grand Challenge 2. These developments, their associated benefits, and proposed procedures for their use in future applications are discussed.

摘要

在 D3R 大挑战 2 中,有机会前瞻性地预测配体结合构象和结合法尼醇 X 受体的自由能,这为评估基于 CHARMM 的对接(CDOCKER)和 [Formula: see text]-动力学方法在计算机辅助药物设计的“实际”应用中提供了有用的练习。除了测量它们当前的性能外,还回顾性地分析了最近的一些方法学进展,以突出未来应用中最佳程序实践。对于 CDOCKER 的构象预测,当用于刚性受体对接的蛋白质结构接近晶体学的全结构时,可获得可靠的构象。具有已知全结构受体的苯并咪唑类药物成功对接,平均 RMSD 为 0.97 [Formula: see text]。其他非苯并咪唑类配体的准确性较低,主要是因为我们选择用于对接的受体结构与实验全结构差异太大。然而,回顾性分析表明,当这些配体重新对接成全结构时,所有配体的平均 RMSD 降至 1.18 [Formula: see text]。当磺酰胺和螺环化合物与 apo 结构对接时,该结构与全结构的吻合度高于我们选择的结构,六分之五的配体被正确对接。这些对接结果强调了需要采用灵活的受体对接方法。对于 [Formula: see text]-动力学技术,包括多靶点 [Formula: see text]-动力学(MS[Formula: see text]D),对于所研究的 33 种配体,观察到与实验的合理一致性;自由能集 1 和 2 的均方根误差分别为 2.08 和 1.67 kcal/mol。回顾性地,软核势、自适应景观扁平化和偏置势 replica 交换(BP-REX)算法对于在具有足够精度和在限制性时间范围内模拟大取代基扰动至关重要,例如在 Grand Challenge 2 中需要参与。讨论了这些发展、它们的相关益处以及在未来应用中使用它们的建议程序。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6408/5767529/18e5a7c93126/nihms904865f1.jpg

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