以合成电位评分为指导的化学酶合成计划

IF 6.2 Q1 CHEMISTRY, MULTIDISCIPLINARY
Xuan Liu, Hongxiang Li and Huimin Zhao
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引用次数: 0

摘要

计算机辅助化学酶合成计划综合了酶和有机反应的优点,为目标分子设计高效的杂化合成路线。现有的工具要么依赖于一步一步的策略,要么依赖于绕过策略。在这里,我们引入一个综合潜能评分(SPScore)来统一这两种策略。这个分数是通过在现有的反应数据库上训练多层感知器来评估酶或有机反应合成分子的潜力。我们系统地评估了SPScore在单步和多步杂交反合成中的有效性,证明了它有很强的能力来优先考虑有希望的反应类型。在SPScore指导下对各种化学酶反合成算法进行基准测试时,我们发现,与使用由1001个分子组成的测试数据集的最先进工具相比,名为ACERetro的异步搜索算法具有更高的效率和鲁棒性,可以多找到46%的分子混合合成路线。然后,我们应用ACERetro为4种fda批准的药物设计有效的化学酶合成路线。我们预计SPScore的应用将为计算机辅助化学酶合成规划提供新的途径,从而推动功能分子的合成。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Chemoenzymatic synthesis planning guided by synthetic potential scores

Chemoenzymatic synthesis planning guided by synthetic potential scores

Computer-aided chemoenzymatic synthesis planning integrates the advantages of enzymatic and organic reactions to design efficient hybrid synthesis routes for a target molecule. Existing tools rely on either a step-by-step strategy or a bypass strategy. Here we introduce a synthetic potential score (SPScore) to unify these two strategies. This score is developed by training a multilayer perceptron on existing reaction databases to evaluate the potential of enzymatic or organic reactions for synthesis of a molecule. We systematically evaluate the effectiveness of the SPScore in both single-step and multi-step hybrid retrosynthesis, demonstrating its strong ability to prioritize promising reaction types. In benchmarking various chemoenzymatic retrosynthesis algorithms guided by the SPScore, we find that an asynchronous search algorithm named ACERetro yields higher efficiency and robustness that can find hybrid synthesis routes to 46% more molecules compared with the state-of-the-art tool using a test dataset consisting of 1001 molecules. We then apply ACERetro to design efficient chemoenzymatic synthesis routes for 4 FDA-approved drugs. We anticipate that the application of the SPScore will provide a new avenue for computer-aided chemoenzymatic synthesis planning, thereby advancing the synthesis of functional molecules.

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CiteScore
2.80
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