Choe Han, Nah Kwang Hoon, Lee Soo Nam, Lee Han Sam, Lee Hui Sun, Jo Su Hyun, Leem Chae Hun, Jang Yeon Jin
Department of Physiology, University of Ulsan College of Medicine, 388-1 PoongNap-dong Songpa-goo, Seoul 138-736, South Korea.
Biochem Biophys Res Commun. 2006 May 26;344(1):72-8. doi: 10.1016/j.bbrc.2006.03.146. Epub 2006 Mar 31.
We present a new docking model for HERG channel blockade. Our new model suggests three key interactions such that (1) a protonated nitrogen of the channel blocker forms a hydrogen bond with the carbonyl oxygen of HERG residue T623; (2) an aromatic moiety of the channel blocker makes a pi-pi interaction with the aromatic ring of HERG residue Y652; and (3) a hydrophobic group of the channel blocker forms a hydrophobic interaction with the benzene ring of HERG residue F656. The previous model assumes two interactions such that (1) a protonated nitrogen of the channel blocker forms a cation-pi interaction with the aromatic ring of HERG residue Y652; and (2) a hydrophobic group of the channel blocker forms a hydrophobic interaction with the benzene ring of HERG residue F656. To test these models, we classified 69 known HERG channel blockers into eight binding types based on their plausible binding modes, and further categorized them into two groups based on the number of interactions our model would predict with the HERG channel (two or three). We then compared the pIC(50) value distributions between these two groups. If the old hypothesis is correct, the distributions should not differ between the two groups (i.e., both groups show only two binding interactions). If our novel hypothesis is correct, the distributions should differ between Groups 1 and 2. Consistent with our hypothesis, the two groups differed with regard to pIC(50), and the group having more predicted interactions with the HERG channel had a higher mean pIC(50) value. Although additional work will be required to further validate our hypothesis, this improved understanding of the HERG channel blocker binding mode may help promote the development of in silico predictions methods for identifying potential HERG channel blockers.
我们提出了一种用于HERG通道阻断的新对接模型。我们的新模型表明存在三种关键相互作用，即：(1)通道阻滞剂的质子化氮与HERG残基T623的羰基氧形成氢键；(2)通道阻滞剂的芳香部分与HERG残基Y652的芳香环形成π-π相互作用；(3)通道阻滞剂的疏水基团与HERG残基F656的苯环形成疏水相互作用。先前的模型假设有两种相互作用，即：(1)通道阻滞剂的质子化氮与HERG残基Y652的芳香环形成阳离子-π相互作用；(2)通道阻滞剂的疏水基团与HERG残基F656的苯环形成疏水相互作用。为了验证这些模型，我们根据69种已知的HERG通道阻滞剂可能的结合模式将它们分为八种结合类型，并根据我们的模型预测与HERG通道相互作用的数量（两种或三种）将它们进一步分为两组。然后我们比较了这两组之间的pIC(50)值分布。如果旧假说是正确的，那么两组之间的分布应该没有差异（即两组都只显示两种结合相互作用）。如果我们的新假说是正确的，那么第1组和第2组之间的分布应该不同。与我们的假说一致，两组在pIC(50)方面存在差异，并且与HERG通道预测相互作用更多的组具有更高的平均pIC(50)值。尽管需要进一步的工作来进一步验证我们的假说，但对HERG通道阻滞剂结合模式的这种更好理解可能有助于促进用于识别潜在HERG通道阻滞剂的计算机预测方法的发展。
