McAllister Scott R, Feng Xiao-Jiang, DiMaggio Peter A, Floudas Christodoulos A, Rabinowitz Joshua D, Rabitz Herschel
Department of Chemical Engineering, Princeton University, Princeton, NJ 08544, USA.
Bioorg Med Chem Lett. 2008 Nov 15;18(22):5967-70. doi: 10.1016/j.bmcl.2008.09.068. Epub 2008 Sep 21.
Molecular discovery often involves identification of the best functional groups (substituents) on a scaffold. When multiple substitution sites are present, the number of possible substituent combinations can be very large. This article introduces a strategy for efficiently optimizing the substituent combinations by iterative rounds of compound sampling, substituent reordering to produce the most regular property landscape, and property estimation over the landscape. Application of this approach to a large pharmaceutical compound library demonstrates its ability to find active compounds with a threefold reduction in synthetic and assaying effort, even without knowing the molecular identity of any compound.
分子发现通常涉及确定支架上最佳的官能团（取代基）。当存在多个取代位点时，可能的取代基组合数量会非常大。本文介绍了一种策略，通过多轮迭代的化合物采样、取代基重新排序以生成最规则的性质图谱，以及在该图谱上进行性质估计，来高效优化取代基组合。将这种方法应用于一个大型药物化合物库，证明了其能够在合成和测定工作量减少三分之二的情况下找到活性化合物，甚至无需知道任何化合物的分子身份。
