Department of Anesthesiology and Critical Care, Hospital of University of Pennsylvania, Philadelphia, PA 19104, USA.
Anesth Analg. 2012 May;114(5):947-55. doi: 10.1213/ANE.0b013e31824c4def. Epub 2012 Mar 5.
The protein targets for general anesthetics remain unclear. A tool to predict anesthetic binding for potential binding targets is needed. In this study, we explored whether a computational method, AutoDock, could serve as such a tool.
High-resolution crystal data of water-soluble proteins (cytochrome C, apoferritin, and human serum albumin), and a membrane protein (a pentameric ligand-gated ion channel from Gloeobacter violaceus [GLIC]) were used. Isothermal titration calorimetry (ITC) experiments were performed to determine anesthetic affinity in solution conditions for apoferritin. Docking calculations were performed using DockingServer with the Lamarckian genetic algorithm and the Solis and Wets local search method (http://www.dockingserver.com/web). Twenty general anesthetics were docked into apoferritin. The predicted binding constants were compared with those obtained from ITC experiments for potential correlations. In the case of apoferritin, details of the binding site and their interactions were compared with recent cocrystallization data. Docking calculations for 6 general anesthetics currently used in clinical settings (isoflurane, sevoflurane, desflurane, halothane, propofol, and etomidate) with known 50% effective concentration (EC(50)) values were also performed in all tested proteins. The binding constants derived from docking experiments were compared with known EC(50) values and octanol/water partition coefficients for the 6 general anesthetics.
All 20 general anesthetics docked unambiguously into the anesthetic binding site identified in the crystal structure of apoferritin. The binding constants for 20 anesthetics obtained from the docking calculations correlate significantly with those obtained from ITC experiments (P = 0.04). In the case of GLIC, the identified anesthetic binding sites in the crystal structure are among the docking predicted binding sites, but not the top ranked site. Docking calculations suggest a most probable binding site located in the extracellular domain of GLIC. The predicted affinities correlated significantly with the known EC(50) values for the 6 frequently used anesthetics in GLIC for the site identified in the experimental crystal data (P = 0.006). However, predicted affinities in apoferritin, human serum albumin, and cytochrome C did not correlate with these 6 anesthetics' known experimental EC(50) values. A weak correlation between the predicted affinities and the octanol/water partition coefficients was observed for the sites in GLIC.
We demonstrated that anesthetic binding sites and relative affinities can be predicted using docking calculations in an automatic docking server (AutoDock) for both water-soluble and membrane proteins. Correlation of predicted affinity and EC(50) for 6 frequently used general anesthetics was only observed in GLIC, a member of a protein family relevant to anesthetic mechanism.
全麻药物的蛋白靶标仍不清楚。我们需要一种预测潜在结合靶标麻醉结合的工具。在这项研究中，我们探讨了一种计算方法 AutoDock 是否可以作为这样的工具。
使用高分辨率水溶性蛋白（细胞色素 C、脱铁铁蛋白和人血清白蛋白）和膜蛋白（来自 Gloeobacter violaceus 的五聚体配体门控离子通道 [GLIC]）的晶体数据。使用等温滴定量热法（ITC）实验在溶液条件下确定脱铁铁蛋白中麻醉剂的亲和力。使用 DockingServer 进行对接计算，采用 Lamarckian 遗传算法和 Solis 和 Wets 局部搜索方法（http://www.dockingserver.com/web）。将 20 种全身麻醉药对接入脱铁铁蛋白。将预测的结合常数与 ITC 实验获得的结合常数进行比较，以确定潜在的相关性。在脱铁铁蛋白的情况下，将结合位点的细节及其相互作用与最近的共晶数据进行比较。还对目前在临床环境中使用的 6 种全身麻醉药（异氟烷、七氟烷、地氟烷、氟烷、异丙酚和依托咪酯）进行了所有测试蛋白的对接计算，这些麻醉药具有已知的 50%有效浓度（EC（50）值。从对接实验中得出的结合常数与已知的 EC（50）值和 6 种全身麻醉药的辛醇/水分配系数进行了比较。
所有 20 种全身麻醉药均明确对接入脱铁铁蛋白晶体结构中鉴定的麻醉结合位点。从对接计算中获得的 20 种麻醉药的结合常数与 ITC 实验获得的结合常数显著相关（P = 0.04）。在 GLIC 的情况下，晶体结构中鉴定的麻醉结合位点是对接预测结合位点之一，但不是排名最高的位点。对接计算表明，最可能的结合位点位于 GLIC 的细胞外域。预测的亲和力与实验晶体数据中鉴定的 GLIC 中 6 种常用麻醉药的已知 EC（50）值显著相关（P = 0.006）。然而，在脱铁铁蛋白、人血清白蛋白和细胞色素 C 中预测的亲和力与这些 6 种麻醉药的已知实验 EC（50）值没有相关性。在 GLIC 中，观察到预测亲和力与辛醇/水分配系数之间存在弱相关性。
我们证明了可以使用自动对接服务器（AutoDock）中的对接计算来预测水溶性和膜蛋白的麻醉结合位点和相对亲和力。仅在与麻醉机制相关的蛋白质家族的成员 GLIC 中观察到 6 种常用全身麻醉药的预测亲和力和 EC（50）的相关性。
