Prediction of binding affinities between the human amphiphysin-1 SH3 domain and its peptide ligands using homology modeling, molecular dynamics and molecular field analysis
Prediction of binding affinities between the human amphiphysin-1 SH3 domain and its peptide ligands using homology modeling, molecular dynamics and molecular field analysis
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DOI：
10.1021/pr0502267
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发表时间：
2006-01-01
影响因子：
4.4
通讯作者：
Wang, W
中科院分区：
文献类型：
--
作者：
Hou, TJ;McLaughlin, W;Wang, W
人蛋白amphiphysin-1的SH3结构域在网格蛋白介导的内吞作用、肌动蛋白功能和信号转导中发挥重要作用，能够以高亲和力和特异性识别肽基序PXRPXR（X是任何氨基酸）。我们利用同源建模和分子对接构建了amphiphysin-1 SH3结构域和高亲和力肽配体PLPRRPPPRA的复杂结构，并通过分子动力学（MD）进行了优化。然后使用比较分子场分析 (CoMFA) 和比较分子相似性指数分析 (CoMSIA) 对 200 种与 amphiphyn-1 SH3 结构域具有已知结合亲和力的肽进行三维定量结构亲和关系 (3D-QSAR) 分析。最好的 CoMSIA 模型显示出有希望的预测能力，对测试集中约 95% 的肽给出了良好的预测（绝对预测误差小于 1.0）。它用于验证肽-SH3 结合结构，并深入了解肽与 SH3 结构域结合的结构要求。最后，进行MD模拟来分析SH3结构域和另一个包含PXRPXsR（s代表具有小侧链的残基）基序的肽GFPRRPPPRG之间的相互作用。 MD模拟表明，GFPRRPPRG的结合构象与PLPRRPRAA的结合构象有很大不同，尤其是C端的四个残基，这可能解释了为什么CoMSIA模型不能对PXRPXsR基序的肽给出良好的预测。由于其效率和预测能力，3D-QSAR 模型可用作预测与 SH3 结构域结合的肽序列的评分过滤器。
The SH3 domain of the human protein amphiphysin-1, which plays important roles in clathrin-mediated endocytosis, actin function and signaling transduction, can recognize peptide motif PXRPXR (X is any amino acid) with high affinity and specificity. We have constructed a complex structure of the amphiphysin-1 SH3 domain and a high-affinity peptide ligand PLPRRPPRA using homology modeling and molecular docking, which was optimized by molecular dynamics (MD). Three-dimensional quantitative structure-affinity relationship (3D-QSAR) analyses on the 200 peptides with known binding affinities to the amphiphysin-1 SH3 domain was then performed using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). The best CoMSIA model showed promising predictive power, giving good predictions for about 95% of the peptides in the test set (absolute prediction errors less than 1.0). It was used to validate peptide-SH3 binding structure and provide insight into the structural requirements for binding of peptides to SH3 domains. Finally, MD simulations were performed to analyze the interaction between the SH3 domain and another peptide GFPRRPPPRG that contains with the PXRPXsR (s represents residues with small side chains) motif. MD simulations demonstrated that the binding conformation of GFPRRPPPRG is quite different from that of PLPRRPPRAA especially the four residues at the C terminal, which may explain why the CoMSIA model cannot give good predictions on the peptides of the PXRPXsR motif. Because of its efficiency and predictive power, the 3D-QSAR model can be used as a scoring filter for predicting peptide sequences bound to SH3 domains.