Chemoton 2.0: Autonomous Exploration of Chemical Reaction Networks

计算机科学 化学空间 集合(抽象数据类型) 路径(计算) 钥匙(锁) 多样性(控制论) 回顾性分析 软件 理论计算机科学 人工智能 化学 药物发现 生物化学 有机化学 程序设计语言 计算机安全 全合成
作者
Jan P. Unsleber,S. Grimmel,Markus Reiher
出处
期刊:Journal of Chemical Theory and Computation [American Chemical Society]
卷期号:18 (9): 5393-5409 被引量:11
标识
DOI:10.1021/acs.jctc.2c00193
摘要

Fueled by advances in hardware and algorithm design, large-scale automated explorations of chemical reaction space have become possible. Here, we present our approach to an open-source, extensible framework for explorations of chemical reaction mechanisms based on the first-principles of quantum mechanics. It is intended to facilitate reaction network explorations for diverse chemical problems with a wide range of goals such as mechanism elucidation, reaction path optimization, retrosynthetic path validation, reagent design, and microkinetic modeling. The stringent first-principles basis of all algorithms in our framework is key for the general applicability that avoids any restrictions to specific chemical systems. Such an agile framework requires multiple specialized software components of which we present three modules in this work. The key module, Chemoton, drives the exploration of reaction networks. For the exploration itself, we introduce two new algorithms for elementary-step searches that are based on Newton trajectories. The performance of these algorithms is assessed for a variety of reactions characterized by a broad chemical diversity in terms of bonding patterns and chemical elements. Chemoton successfully recovers the vast majority of these. We provide the resulting data, including large numbers of reactions that were not included in our reference set, to be used as a starting point for further explorations and for future reference.
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