Bartosz A. Grzybowski, Tomasz Badowski, Karol Molga, Sara Szymku?
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引用次数: 5
Abstract
In 2020, a “hybrid” expert-AI computer program called Chematica (a.k.a. Synthia) was shown to autonomously plan multistep syntheses of complex natural products, which remain outside the reach of purely data-driven AI programs. The ability to plan at this level of chemical sophistication has been attributed mainly to the superior quality of Chematica's reactions rules. However, rules alone are not sufficient for advanced synthetic planning which also requires appropriately crafted algorithms with which to intelligently navigate the enormous networks of synthetic possibilities, score the synthetic positions encountered, and rank the pathways identified. Chematica's algorithms are distinct from prêt-à-porter algorithmic solutions and are product of multiple rounds of improvements, against target structures of increasing complexity. Since descriptions of these improvements have been scattered among several of our prior publications, the aim of the current Review is to narrate the development process in a more comprehensive manner.
期刊介绍：
Computational molecular sciences harness the power of rigorous chemical and physical theories, employing computer-based modeling, specialized hardware, software development, algorithm design, and database management to explore and illuminate every facet of molecular sciences. These interdisciplinary approaches form a bridge between chemistry, biology, and materials sciences, establishing connections with adjacent application-driven fields in both chemistry and biology. WIREs Computational Molecular Science stands as a platform to comprehensively review and spotlight research from these dynamic and interconnected fields.
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