Binding Space Concept: A New Approach To Enhance the Reliability of Docking Scores and Its Application to Predicting Butyrylcholinesterase Hydrolytic Activity

Docking
simulations are very popular approaches able to assess
the capacity of a given ligand to interact with a target. Docking
simulations are usually focused on a single best complex even though
many studies showed that ligands retain a significant mobility within
a binding pocket by assuming different binding modes all of which
may contribute to the monitored ligand affinity. The present study
describes an innovative concept, the binding space, which allows an
exploration of the ligand mobility within the binding pocket by simultaneously
considering several ligand poses as generated by docking simulations.
The multiple poses and the relative docking scores can then be analyzed
by taking advantage of the same concepts already used in the property
space analysis; hence the binding space can be parametrized by (a)
mean scores, (b) score ranges, and (c) score sensitivity values. The
first parameter represents a very simple procedure to account for
the contribution of the often neglected alternative binding modes,
while the last two descriptors encode the degree of mobility which
a given ligand retains within the binding cavity (score range) as
well as the ease with which a ligand explores such a mobility (score
sensitivity). Here, the binding space concept is applied to the prediction
of the hydrolytic activity of BChE by synergistically considering
multiple poses and multiple protein structures. The obtained results
shed light on the remarkable potential of the binding space concept,
whose parameters allow a significant increase of the predictive power
of the docking results as revealed by extended correlative analyses.
Mean scores are the parameters affording the largest statistical improvement,
and all the here proposed docking-based descriptors show enhancing
effects in developing predictive models. Finally, the study describes
a new score function (Contacts score) simply based on the number of
surrounding residues which appears to be particularly productive in
the framework of the binding space.

对接模拟作为一种流行的方法，能够评估给定配体与靶标相互作用的潜力。尽管许多研究表明，配体在结合口袋中通过采取不同的结合模式而保持显著的移动性，所有这些模式都可能对监测到的配体亲和力有所贡献，但对接模拟通常仅关注单个最佳复合体。本研究提出了一种创新的概念——结合空间，该空间通过同时考虑由对接模拟生成的多个配体构象，允许对配体在结合口袋中的移动性进行探索。随后，通过利用已在属性空间分析中使用的相同概念，可以对多个构象及其相对对接分数进行分析；因此，结合空间可以通过（a）平均分数、（b）分数范围和（c）分数敏感性值进行参数化。第一个参数代表了一种非常简单的方法，用于解释经常被忽视的替代结合模式所做出的贡献，而最后两个描述符则编码了给定配体在结合腔中保持的移动程度（分数范围）以及配体探索这种移动性的容易程度（分数敏感性）。在此，结合空间的概念被应用于通过协同考虑多个构象和多个蛋白质结构来预测BChE的水解活性。获得的结果揭示了结合空间概念的显著潜力，其参数能够显著提高对接结果的可预测性，这一点通过扩展相关性分析得到了证实。平均分数是提供最大统计改进的参数，所有在此提出的基于对接的描述符均显示出在开发预测模型中的增强效果。最后，该研究描述了一种新的评分函数（接触评分），该函数仅基于周围残基的数量，在结合空间框架下似乎特别有效。