School of Physics, Building A28, University of Sydney, NSW 2006, Australia.
Toxins (Basel). 2012 Feb;4(2):110-38. doi: 10.3390/toxins4020110. Epub 2012 Feb 6.
During the development of selective peptides against highly homologous targets, a reliable tool is sought that can predict information on both mechanisms of binding and relative affinities. These tools must first be tested on known profiles before application on novel therapeutic candidates. We therefore present a comparative docking protocol in HADDOCK using critical motifs, and use it to "predict" the various selectivity profiles of several major αKTX scorpion toxin families versus K(v)1.1, K(v)1.2 and K(v)1.3. By correlating results across toxins of similar profiles, a comprehensive set of functional residues can be identified. Reasonable models of channel-toxin interactions can be then drawn that are consistent with known affinity and mutagenesis. Without biological information on the interaction, HADDOCK reproduces mechanisms underlying the universal binding of αKTX-2 toxins, and K(v)1.3 selectivity of αKTX-3 toxins. The addition of constraints encouraging the critical lysine insertion confirms these findings, and gives analogous explanations for other families, including models of partial pore-block in αKTX-6. While qualitatively informative, the HADDOCK scoring function is not yet sufficient for accurate affinity-ranking. False minima in low-affinity complexes often resemble true binding in high-affinity complexes, despite steric/conformational penalties apparent from visual inspection. This contamination significantly complicates energetic analysis, although it is usually possible to obtain correct ranking via careful interpretation of binding-well characteristics and elimination of false positives. Aside from adaptations to the broader potassium channel family, we suggest that this strategy of comparative docking can be extended to other channels of interest with known structure, especially in cases where a critical motif exists to improve docking effectiveness.
在开发针对高度同源靶点的选择性肽的过程中,人们寻求一种可靠的工具,该工具能够预测结合机制和相对亲和力的信息。在将这些工具应用于新的治疗候选物之前,必须首先在已知的图谱上进行测试。因此,我们提出了一种使用关键模体的 HADDOCK 比较对接方案,并将其用于“预测”几种主要的 αKTX 蝎毒素家族与 K(v)1.1、K(v)1.2 和 K(v)1.3 的各种选择性图谱。通过对具有相似图谱的毒素的结果进行关联,可以确定一组全面的功能残基。然后可以绘制与已知亲和力和诱变一致的合理通道-毒素相互作用模型。在没有交互作用的生物学信息的情况下,HADDOCK 再现了 αKTX-2 毒素普遍结合的机制,以及 αKTX-3 毒素对 K(v)1.3 的选择性。添加鼓励关键赖氨酸插入的约束条件证实了这些发现,并为其他家族提供了类似的解释,包括 αKTX-6 的部分孔阻塞模型。虽然定性地提供了信息,但 HADDOCK 评分函数还不足以进行准确的亲和力排名。低亲和力复合物中的假最小点通常类似于高亲和力复合物中的真实结合点,尽管从视觉检查来看,空间/构象惩罚是明显的。尽管通过仔细解释结合阱特征和消除假阳性可以获得正确的排序,但这种污染极大地复杂化了能量分析。除了适应更广泛的钾通道家族外,我们建议可以将这种比较对接策略扩展到具有已知结构的其他感兴趣的通道,特别是在存在关键模体以提高对接效率的情况下。
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