Rarey M, Kramer B, Lengauer T
German National Research Center for Information Technology (GMD), Institute for Algorithms and Scientific Computing (SCAI), Sankt Augustin, Germany.
J Comput Aided Mol Des. 1997 Jul;11(4):369-84. doi: 10.1023/a:1007913026166.
A possible way of tackling the molecular docking problem arising in computer-aided drug design is the use of the incremental construction method. This method consists of three steps: the selection of a part of a molecule, a so-called base fragment, the placement of the base fragment into the active site of a protein, and the subsequent reconstruction of the complete drug molecule. Assuming that a part of a drug molecule is known, which is specific enough to be a good base fragment, the method is proven to be successful for a large set of docking examples. In addition, it leads to the fastest algorithms for flexible docking published so far. In most real-world applications of docking, large sets of ligands have to be tested for affinity to a given protein. Thus, manual selection of a base fragment is not practical. On the other hand, the selection of a base fragment is critical in that only few selections lead to a low-energy structure. We overcome this limitation by selecting a representative set of base fragments instead of a single one. In this paper, we present a set of rules and algorithms to automate this selection. In addition, we extend the incremental construction method to deal with multiple fragmentations of the drug molecule. Our results show that with multiple automated base selection, the quality of the docking predictions is almost as good as with one manually preselected base fragment. In addition, the set of solutions is more diverse and alternative binding modes with low scores are found. Although the run time of the overall algorithm increases, the method remains fast enough to search through large ligand data sets.
解决计算机辅助药物设计中出现的分子对接问题的一种可能方法是使用增量构建方法。该方法包括三个步骤:选择分子的一部分,即所谓的基础片段;将基础片段放置到蛋白质的活性位点;以及随后重建完整的药物分子。假设已知药物分子的一部分,且该部分足够特异可作为良好的基础片段,那么该方法已被证明在大量对接实例中是成功的。此外,它还产生了迄今为止已发表的用于柔性对接的最快算法。在对接的大多数实际应用中,必须测试大量配体与给定蛋白质的亲和力。因此,手动选择基础片段并不实际。另一方面,基础片段的选择至关重要,因为只有少数选择会导致低能量结构。我们通过选择一组代表性的基础片段而非单个片段来克服这一限制。在本文中,我们提出了一组规则和算法来自动进行这种选择。此外,我们扩展了增量构建方法以处理药物分子的多个片段化。我们的结果表明,通过多次自动基础选择,对接预测的质量几乎与使用一个手动预先选择的基础片段一样好。此外,解决方案集更加多样,并且发现了得分较低的替代结合模式。虽然整个算法的运行时间增加了,但该方法仍然足够快,可以搜索大型配体数据集。