PDF(Pubmed)
Abstract：
Predicting the potency of inhibitors is key to in silico screening of promising synthetic or natural compounds. Here we describe a predictive workflow that provides calculated inhibitory values, which concord well with empirical data. Calculations of the free interaction energy ΔG with the YASARA plugin FoldX were used to derive inhibition constants Ki from PDB coordinates of protease-inhibitor complexes. At the same time, corresponding KD values were obtained from the PRODIGY server. These results correlated well with the experimental values, particularly for serine proteases. In addition, analyses were performed for inhibitory complexes of cysteine and aspartic proteases, as well as of metalloproteases, whereby the PRODIGY data appeared to be more consistent. Based on our analyses, we calculated theoretical Ki values for trypsin with sunflower trypsin inhibitor (SFTI-1) variants, which yielded the more rigid Pro14 variant, with probably higher potency than the wild-type inhibitor. Moreover, a hirudin variant with an Arg1 and Trp3 is a promising basis for novel thrombin inhibitors with high potency. Further examples from antibody interaction and a cancer-related effector-receptor system demonstrate that our approach is applicable to protein interaction studies beyond the protease field.
摘要：
预测抑制剂的效力是对有希望的合成或天然化合物进行计算机筛选的关键。在这里，我们描述了一个提供计算抑制值的预测工作流程，这与经验数据非常吻合。使用YASARA插件FoldX计算自由相互作用能ΔG，从蛋白酶-抑制剂复合物的PDB坐标得出抑制常数Ki。同时,从PRODIGY服务器获得相应的KD值。这些结果与实验值相关性很好，特别是丝氨酸蛋白酶。此外,对半胱氨酸和天冬氨酸蛋白酶的抑制复合物进行了分析，以及金属蛋白酶，由此PRODIGY数据似乎更加一致。根据我们的分析,我们计算了胰蛋白酶与向日葵胰蛋白酶抑制剂（SFTI-1）变体的理论Ki值，产生了更严格的Pro14变体，可能比野生型抑制剂更高的效力。此外，具有Arg1和Trp3的水蛭素变体是具有高效力的新型凝血酶抑制剂的有希望的基础。来自抗体相互作用和癌症相关的效应子受体系统的进一步实例表明，我们的方法适用于蛋白酶领域以外的蛋白质相互作用研究。
