ASKCOS: Open-Source, Data-Driven Synthesis Planning

IF 16.4 1区 化学 Q1 CHEMISTRY, MULTIDISCIPLINARY
Zhengkai Tu, Sourabh J. Choure, Mun Hong Fong, Jihye Roh, Itai Levin, Kevin Yu, Joonyoung F. Joung, Nathan Morgan, Shih-Cheng Li, Xiaoqi Sun, Huiqian Lin, Mark Murnin, Jordan P. Liles, Thomas J. Struble, Michael E. Fortunato, Mengjie Liu, William H. Green, Klavs F. Jensen and Connor W. Coley*, 
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引用次数: 0

Abstract

The advancement of machine learning and the availability of large-scale reaction datasets have accelerated the development of data-driven models for computer-aided synthesis planning (CASP) in the past decade. In this Account, we describe the range of data-driven methods and models that have been incorporated into the newest version of ASKCOS, an open-source software suite for synthesis planning that we have been developing since 2016. This ongoing effort has been driven by the importance of bridging the gap between research and development, making research advances available through a freely available practical tool. ASKCOS integrates modules for retrosynthetic planning, modules for complementary capabilities of condition prediction and reaction product prediction, and several supplementary modules and utilities with various roles in synthesis planning. For retrosynthetic planning, we have developed an Interactive Path Planner (IPP) for user-guided search as well as a Tree Builder for automatic planning with two well-known tree search algorithms, Monte Carlo Tree Search (MCTS) and Retro*. Four one-step retrosynthesis models covering template-based and template-free strategies form the basis of retrosynthetic predictions and can be used simultaneously to combine their advantages and propose diverse suggestions. Strategies for assessing the feasibility of proposed reaction steps and evaluating the full pathways are built on top of several pioneering efforts that we have made in the subtasks of reaction condition recommendation, pathway scoring and clustering, and the prediction of reaction outcomes including the major product, impurities, site selectivity, and regioselectivity. In addition, we have also developed auxiliary capabilities in ASKCOS based on our past and ongoing work for solubility prediction and quantum mechanical descriptor prediction, which can provide more insight into the suitability of proposed reaction solvents or the hypothetical selectivity of desired transformations. For each of these capabilities, we highlight its relevance in the context of synthesis planning and present a comprehensive overview of how it is built on top of not only our work but also of other recent advancements in the field. We also describe in detail how chemists can easily interact with these capabilities via user-friendly interfaces. ASKCOS has assisted hundreds of medicinal, synthetic, and process chemists in their day-to-day tasks by complementing expert decision making and route ideation. It is our belief that CASP tools are an important part of modern chemistry research and offer ever-increasing utility and accessibility.

ASKCOS:开源,数据驱动的综合规划
在过去十年中,机器学习的进步和大规模反应数据集的可用性加速了计算机辅助综合规划(CASP)数据驱动模型的发展。在本帐户中,我们描述了已纳入最新版本ASKCOS的数据驱动方法和模型的范围,ASKCOS是我们自2016年以来一直在开发的用于综合规划的开源软件套件。这一正在进行的努力是由缩小研究与开发之间差距的重要性推动的,通过一个免费的实用工具使研究进展可获得。ASKCOS集成了反合成规划模块、状态预测和反应产物预测互补功能模块,以及几个在综合规划中发挥不同作用的补充模块和实用程序。对于逆合成规划,我们开发了一个交互式路径规划器(IPP)用于用户引导搜索,以及一个树生成器用于自动规划,其中包含两个著名的树搜索算法,蒙特卡罗树搜索(MCTS)和Retro*。基于模板和无模板策略的四种一步反合成模型构成了反合成预测的基础,可以同时使用,结合它们的优势,提出不同的建议。我们在反应条件推荐、途径评分和聚类、反应结果预测(包括主要产物、杂质、位点选择性和区域选择性)等子任务中所做的开创性工作,为评估所提出的反应步骤的可行性和评估完整途径建立了策略。此外,基于我们过去和正在进行的溶解度预测和量子力学描述子预测工作,我们还在ASKCOS中开发了辅助功能,这可以更深入地了解所提出的反应溶剂的适用性或期望转化的假设选择性。对于这些能力中的每一个,我们都强调了它在综合规划背景下的相关性,并全面概述了它是如何建立在我们的工作以及该领域其他最新进展的基础上的。我们还详细描述了化学家如何通过用户友好的界面轻松地与这些功能进行交互。ASKCOS通过补充专家决策和路线构想,帮助数百名药物、合成和工艺化学家完成日常任务。我们相信CASP工具是现代化学研究的重要组成部分,并提供不断增加的实用性和可及性。
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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来源期刊
Accounts of Chemical Research
Accounts of Chemical Research 化学-化学综合
CiteScore
31.40
自引率
1.10%
发文量
312
审稿时长
2 months
期刊介绍: Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance. Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.
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