Fischer B, Merlitz H, Wenzel W
Institut für Nanotechnologie, Forschungszentrum Karlsruhe, Karlsruhe, Germany.
Methods Mol Biol. 2008;443:353-64. doi: 10.1007/978-1-59745-177-2_18.
An important contribution to today's computer-aided drug design is the automated screening of large compound databases against structurally resolved protein receptors targets. The introduction of ligand flexibility has, by now, become a standardized procedure. In contrast, a general approach to treat target degrees of freedom is still to be found, a consequence of the extreme increase of computational complexity, which comes along with the relaxation of protein degrees of freedom. In this chapter, we discuss in some detail both benefits and present limitations of target flexibility for high-throughput in silico database screens. Among the benefits are an improved diversity of binding modes, which allows one to identify a wider class of drug candidates. The limitations are related to a diminishing docking accuracy and an increased number of false hits. Using the thymidine kinase receptor and ten known inhibitors as an example, we describe in detail how target flexibility was implemented and how it affected the screening performance.
对当今计算机辅助药物设计的一项重要贡献是针对结构解析的蛋白质受体靶点对大型化合物数据库进行自动筛选。到目前为止,引入配体灵活性已成为一种标准化程序。相比之下,由于蛋白质自由度的松弛带来计算复杂性的极端增加,处理靶点自由度的通用方法仍有待探索。在本章中,我们将详细讨论靶点灵活性在高通量虚拟数据库筛选中的优点和当前的局限性。优点包括结合模式的多样性提高,这使得能够识别更广泛类别的候选药物。局限性则与对接准确性的降低和错误命中数量的增加有关。以胸苷激酶受体和十种已知抑制剂为例,我们详细描述了靶点灵活性是如何实现的以及它如何影响筛选性能。