Pärn Juri, Degen Jörg, Rarey Matthias
Center for Bioinformatics, Hamburg, Germany.
J Comput Aided Mol Des. 2007 Jun;21(6):327-40. doi: 10.1007/s10822-007-9121-3. Epub 2007 Jun 28.
We present a new algorithm for the enumeration of chemical fragment spaces under constraints. Fragment spaces consist of a set of molecular fragments and a set of rules that specifies how fragments can be combined. Although fragment spaces typically cover an infinite number of molecules, they can be enumerated in case that a physicochemical profile of the requested compounds is given. By using min-max ranges for a number of corresponding properties, our algorithm is able to enumerate all molecules which obey these properties. To speed up the calculation, the given ranges are used directly during the build-up process to guide the selection of fragments. Furthermore, a topology based fragment filter is used to skip most of the redundant fragment combinations. We applied the algorithm to 40 different target classes. For each of these, we generated tailored fragment spaces from sets of known inhibitors and additionally derived ranges for several physicochemical properties. We characterized the target-specific fragment spaces and were able to enumerate the complete chemical subspaces for most of the targets.
我们提出了一种用于在约束条件下枚举化学片段空间的新算法。片段空间由一组分子片段和一组指定片段如何组合的规则组成。尽管片段空间通常涵盖无限数量的分子，但在给出所需化合物的物理化学概况的情况下，可以对其进行枚举。通过使用多个相应属性的最小-最大范围，我们的算法能够枚举所有符合这些属性的分子。为了加快计算速度，在构建过程中直接使用给定范围来指导片段的选择。此外，使用基于拓扑的片段过滤器来跳过大多数冗余的片段组合。我们将该算法应用于40个不同的目标类别。对于其中每一个类别，我们从已知抑制剂集合中生成定制的片段空间，并另外推导了几种物理化学属性的范围。我们对目标特异性片段空间进行了表征，并能够枚举大多数目标的完整化学子空间。
