SynthLens:促进多步骤合成路线设计的可视化分析。

Qipeng Wang, Rui Sheng, Shaolun Ruan, Xiaofu Jin, Chuhan Shi, Min Zhu
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引用次数: 0

摘要

设计新分子的合成路线在医学和化学等各个领域都至关重要。在这个过程中,研究人员需要探索一组合成反应,将起始分子逐步转化为中间体,直到获得新的目标分子。然而,设计合成路线给研究人员带来了挑战。首先,研究人员需要在每个步骤的众多可能的合成反应中做出决策,考虑各种标准(如产率、实验持续时间、实验步骤数)来构建合成路线。其次,他们必须考虑每个步骤中一个选择对整个合成路线的潜在影响。为了解决这些挑战,我们提出了SynthLens,这是一个可视化分析系统,通过在构建的每个步骤探索合成反应的多种可能性来促进合成路线的迭代构建。具体来说,我们在SynthLens中引入了一种树形可视化,可以在考虑探索步骤和多个标准的情况下,对不同探索步骤下的所有探索路线进行比较和评估。我们的系统使研究人员能够全面考虑他们的构建过程,引导他们走向有前途的探索方向,完成合成路线。我们通过定量评估和专家访谈验证了SynthLens的可用性和有效性,强调了它在促进合成路线设计过程中的作用。最后,我们讨论了SynthLens的见解,以启发其他多标准决策场景与视觉分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
SynthLens: Visual Analytics for Facilitating Multi-step Synthetic Route Design.

Designing synthetic routes for novel molecules is pivotal in various fields like medicine and chemistry. In this process, researchers need to explore a set of synthetic reactions to transform starting molecules into intermediates step by step until the target novel molecule is obtained. However, designing synthetic routes presents challenges for researchers. First, researchers need to make decisions among numerous possible synthetic reactions at each step, considering various criteria (e.g., yield, experimental duration, and the count of experimental steps) to construct the synthetic route. Second, they must consider the potential impact of one choice at each step on the overall synthetic route. To address these challenges, we proposed SynthLens, a visual analytics system to facilitate the iterative construction of synthetic routes by exploring multiple possibilities for synthetic reactions at each step of construction. Specifically, we have introduced a tree-form visualization in SynthLens to compare and evaluate all the explored routes at various exploration steps, considering both the exploration step and multiple criteria. Our system empowers researchers to consider their construction process comprehensively, guiding them toward promising exploration directions to complete the synthetic route. We validated the usability and effectiveness of SynthLens through a quantitative evaluation and expert interviews, highlighting its role in facilitating the design process of synthetic routes. Finally, we discussed the insights of SynthLens to inspire other multi-criteria decision-making scenarios with visual analytics.

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