比较逆合成问题的搜索算法。

IF 2.8 4区医学 Q3 CHEMISTRY, MEDICINAL

Molecular Informatics Pub Date : 2024-07-01 Epub Date: 2024-06-12 DOI:10.1002/minf.202300259

Milo Roucairol, Tristan Cazenave

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引用次数: 0

摘要

在本文中，我们在 AstraZeneca 的开源逆合成工具 AiZynthFinder 上尝试了不同的算法，即嵌套蒙特卡罗搜索和贪婪最佳优先搜索。我们将这些算法与 AiZynthFinder 的基本蒙特卡洛树搜索进行了比较，比较的基准是从 PubChem 数据库和拜耳的化学家那里挑选出来的。我们的结果表明，嵌套蒙特卡罗搜索和贪婪最佳优先搜索都优于 AstraZeneca 的蒙特卡罗树形搜索，而嵌套蒙特卡罗搜索在实验中采用了启发式，略胜一筹。我们还展示了搜索算法如何受到策略网络质量的限制，为了改进我们的结果，下一步就是改进策略网络。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Comparing search algorithms on the retrosynthesis problem.

In this article we try different algorithms, namely Nested Monte Carlo Search and Greedy Best First Search, on AstraZeneca's open source retrosynthetic tool : AiZynthFinder. We compare these algorithms to AiZynthFinder's base Monte Carlo Tree Search on a benchmark selected from the PubChem database and by Bayer's chemists. We show that both Nested Monte Carlo Search and Greedy Best First Search outperform AstraZeneca's Monte Carlo Tree Search, with a slight advantage for Nested Monte Carlo Search while experimenting on a playout heuristic. We also show how the search algorithms are bounded by the quality of the policy network, in order to improve our results the next step is to improve the policy network.

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来源期刊

Molecular Informatics CHEMISTRY, MEDICINAL-MATHEMATICAL & COMPUTATIONAL BIOLOGY

CiteScore

7.30

自引率

2.80%

发文量

审稿时长

3 months

期刊介绍： Molecular Informatics is a peer-reviewed, international forum for publication of high-quality, interdisciplinary research on all molecular aspects of bio/cheminformatics and computer-assisted molecular design. Molecular Informatics succeeded QSAR & Combinatorial Science in 2010. Molecular Informatics presents methodological innovations that will lead to a deeper understanding of ligand-receptor interactions, macromolecular complexes, molecular networks, design concepts and processes that demonstrate how ideas and design concepts lead to molecules with a desired structure or function, preferably including experimental validation. The journal''s scope includes but is not limited to the fields of drug discovery and chemical biology, protein and nucleic acid engineering and design, the design of nanomolecular structures, strategies for modeling of macromolecular assemblies, molecular networks and systems, pharmaco- and chemogenomics, computer-assisted screening strategies, as well as novel technologies for the de novo design of biologically active molecules. As a unique feature Molecular Informatics publishes so-called "Methods Corner" review-type articles which feature important technological concepts and advances within the scope of the journal.