Direct optimization across computer generated reaction networks balances materials use and feasibility of synthesis plans for molecule libraries

Gao, H, Pauphilet, J, Struble, T, Coley, C and Jensen, K F (2021) Direct optimization across computer generated reaction networks balances materials use and feasibility of synthesis plans for molecule libraries. Journal of Chemical Information and Modeling, 61 (1). pp. 493-504. ISSN 1549-9596

Abstract

The synthesis of thousands of candidate compounds in drug discovery and development offers opportunities for computer-aided synthesis planning to simplify the synthesis of molecule libraries by leveraging common starting materials and reaction conditions. We develop an optimization-based method to analyze large organic chemical reaction networks and design overlapping synthesis plans for entire molecule libraries so as to minimize the overall number of unique chemical compounds needed as either starting materials or reaction conditions. We consider multiple objectives, including the number of starting materials, the number of catalysts/solvents/reagents, and the likelihood of success of the overall syntheses plan, to select an optimal reaction network to access the target molecules. The library synthesis planning task was formulated as a network flow optimization problem, and we design an efficient decomposition scheme that reduces solution time by a factor of 5 and scales to instance with 48 target molecules and nearly 8000 intermediate reactions within hours. In four case studies of pharmaceutical compounds, the approach reduces the number of starting materials and catalysts/solvents/reagents needed by 32.2 and 66.0% on average and up to 63.2 and 80.0% in the best cases. The code implementation can be found at https://github.com/Coughy1991/Molecule_library_synthesis

Supporting information: https://pubs.acs.org/doi/10.1021/acs.jcim.0c01032?goto=supporting-info

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Item Type: Article
Subject Areas: Management Science and Operations
Additional Information:

© 2020 American Chemical Society

Date Deposited: 08 Jan 2021 10:51
Date of first compliant deposit: 08 Jan 2021
Subjects: P > Pharmaceutical industry
S > Simulation models
C > Computer software
Last Modified: 07 Sep 2021 00:22
URI: https://lbsresearch.london.edu/id/eprint/1592
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