论文标题
分子特性景观的粗糙度及其对可调节性的影响
Roughness of molecular property landscapes and its impact on modellability
论文作者
论文摘要
在分子发现和药物设计中，通常对结构 - 特性关系和活动景观进行定性或定量分析，以指导化学空间的导航。这些分子特性景观的粗糙度（或平滑度）是它们研究最多的几何属性之一，因为它可以表征活动悬崖的存在，而通常预计更粗糙的景观会带来更严格的优化挑战。在这里，我们引入了一种一般的定量措施，以描述分子特性景观的粗糙度。所提出的粗糙度指数（ROGI）是受分形维概念的启发，并与机器学习模型在众多回归任务上实现的样本外错误密切相关。
In molecular discovery and drug design, structure-property relationships and activity landscapes are often qualitatively or quantitatively analyzed to guide the navigation of chemical space. The roughness (or smoothness) of these molecular property landscapes is one of their most studied geometric attributes, as it can characterize the presence of activity cliffs, with rougher landscapes generally expected to pose tougher optimization challenges. Here, we introduce a general, quantitative measure for describing the roughness of molecular property landscapes. The proposed roughness index (ROGI) is loosely inspired by the concept of fractal dimension and strongly correlates with the out-of-sample error achieved by machine learning models on numerous regression tasks.
