Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada.
Nat Chem Biol. 2010 Jul;6(7):549-57. doi: 10.1038/nchembio.380. Epub 2010 May 30.
The resistance of Caenorhabditis elegans to pharmacological perturbation limits its use as a screening tool for novel small bioactive molecules. One strategy to improve the hit rate of small-molecule screens is to preselect molecules that have an increased likelihood of reaching their target in the worm. To learn which structures evade the worm's defenses, we performed the first survey of the accumulation and metabolism of over 1,000 commercially available drug-like small molecules in the worm. We discovered that fewer than 10% of these molecules accumulate to concentrations greater than 50% of that present in the worm's environment. Using our dataset, we developed a structure-based accumulation model that identifies compounds with an increased likelihood of bioavailability and bioactivity, and we describe structural features that facilitate small-molecule accumulation in the worm. Preselecting molecules that are more likely to reach a target by first applying our model to the tens of millions of commercially available compounds will undoubtedly increase the success of future small-molecule screens with C. elegans.
秀丽隐杆线虫对药理学干扰的抗性限制了其作为新型小分子生物活性物质筛选工具的应用。提高小分子筛选命中率的一种策略是预先选择更有可能到达线虫靶标的分子。为了了解哪些结构可以逃避线虫的防御，我们首次对 1000 多种市售类药性小分子在线虫中的积累和代谢进行了调查。我们发现，这些分子中只有不到 10%的分子积累到的浓度大于线虫环境中存在的浓度的 50%。利用我们的数据集，我们开发了一种基于结构的积累模型，可以识别具有更高生物利用度和生物活性的化合物，并描述了促进小分子在线虫中积累的结构特征。通过首先将我们的模型应用于数千万种市售化合物，预先选择更有可能到达靶点的分子，无疑将提高未来使用秀丽隐杆线虫进行小分子筛选的成功率。
