Multi-Instance Learning Approach to the Modeling of Enantioselectivity of Conformationally Flexible Organic Catalysts

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989592%3A15110%2F23%3A73622001" target="_blank" >RIV/61989592:15110/23:73622001 - isvavai.cz</a>
Result on the web
<a href="https://pubs.acs.org/doi/10.1021/acs.jcim.3c00393" target="_blank" >https://pubs.acs.org/doi/10.1021/acs.jcim.3c00393</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1021/acs.jcim.3c00393" target="_blank" >10.1021/acs.jcim.3c00393</a>

Result language
angličtina
Original language name
Multi-Instance Learning Approach to the Modeling of Enantioselectivity of Conformationally Flexible Organic Catalysts
Original language description
Computational design of chiral organic catalysts for asymmetric synthesis is a promising technology that can significantly reduce the material and human resources required for the preparation of enantiopure compounds. Herein, for the modeling of catalysts' enantioselectivity, we propose to use the multi-instance learning approach accounting for multiple catalyst conformers and requiring neither conformer selection nor their spatial alignment. A catalyst was represented by an ensemble of conformers, each encoded by three-dimesinonal (3D) pmapper descriptors. A catalyzed reactant transformation was converted into a single molecular graph, a condensed graph of reaction, encoded by 2D fragment descriptors. A whole chemical reaction was finally encoded by concatenated 3D catalyst and 2D transformation descriptors. The performance of the proposed method was demonstrated in the modeling of the enantioselectivity of homogeneous and phase-transfer reactions and compared with the state-of-the-art approaches.
Czech name
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Czech description
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Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10406 - Analytical chemistry

Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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