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通过伊辛计算加速的原子到原子映射的枚举方法。

Enumeration Approach to Atom-to-Atom Mapping Accelerated by Ising Computing.

作者信息

Ali Mohammad, Mizuno Yuta, Akiyama Seiji, Nagata Yuuya, Komatsuzaki Tamiki

机构信息

Graduate School of Chemical Sciences and Engineering, Hokkaido University, Kita 13, Nishi 8, Kita-ku, Sapporo 060-8628, Hokkaido, Japan.

Statistics Discipline, Khulna University, Sher-E-Bangla Road, Khulna 9208, Bangladesh.

出版信息

J Chem Inf Model. 2025 Feb 24;65(4):1901-1910. doi: 10.1021/acs.jcim.4c01871. Epub 2025 Feb 2.

Abstract

Chemical reactions are regarded as transformations of chemical structures, and the question of which atoms in the reactants correspond to which atoms in the products has attracted chemists for a long time. Atom-to-atom mapping (AAM) is a procedure that establishes such correspondence(s) between the atoms of reactants and products in a chemical reaction. Currently, automatic AAM tools play a pivotal role in various chemoinformatics tasks. However, achieving accurate automatic AAM for complex or unknown reactions within a reasonable computation time remains a significant challenge due to the combinatorial nature of the problem and the difficulty in applying appropriate reaction rules. In this study, we propose a rule-free AAM algorithm, which enumerates all atom-to-atom correspondences that minimize the number of bond cleavages and formations during the reaction. To reduce the computational burden associated with the combinatorial optimization (i.e., minimizing bond changes), we introduce Ising computing, a computing paradigm that has gained significant attention for its efficiency in solving hard combinatorial optimization problems. We found that our Ising computing framework outperforms conventional combinatorial optimization algorithms in terms of computation times, making it feasible to solve the AAM problem without reaction rules in an acceptable time. Furthermore, our AAM algorithm successfully found the correct AAM solution for all problems in a benchmark data set. In contrast, conventional AAM algorithms based on chemical heuristics failed for several problems. Specifically, these algorithms either failed to find the optimal solution in terms of bond changes, or they identified only one optimal solution, which was incorrect when multiple optimal solutions exist. These results emphasize the importance of enumerating all optimal correspondences that minimize bond changes, which is effectively achieved by our Ising-computing framework.

摘要

化学反应被视为化学结构的转变,反应物中的哪些原子对应于产物中的哪些原子这一问题长期以来一直吸引着化学家。原子到原子映射(AAM)是一种在化学反应中建立反应物和产物原子之间这种对应关系的过程。目前,自动AAM工具在各种化学信息学任务中起着关键作用。然而,由于问题的组合性质以及应用适当反应规则的困难,在合理的计算时间内为复杂或未知反应实现准确的自动AAM仍然是一项重大挑战。在本研究中,我们提出了一种无规则AAM算法,该算法枚举了所有能使反应过程中键断裂和形成的数量最小化的原子到原子对应关系。为了减轻与组合优化相关的计算负担(即最小化键变化),我们引入了伊辛计算,这是一种因其在解决硬组合优化问题方面的效率而备受关注的计算范式。我们发现,我们的伊辛计算框架在计算时间方面优于传统的组合优化算法,使得在可接受的时间内无反应规则地解决AAM问题成为可能。此外,我们的AAM算法成功地为基准数据集中的所有问题找到了正确的AAM解决方案。相比之下,基于化学启发式的传统AAM算法在几个问题上失败了。具体来说,这些算法要么未能在键变化方面找到最优解,要么只识别出一个最优解,而当存在多个最优解时这个解是不正确的。这些结果强调了枚举所有能使键变化最小化的最优对应关系的重要性,而我们的伊辛计算框架有效地实现了这一点。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/936b/11863377/4a6c2182bcdb/ci4c01871_0001.jpg

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