Molecular Conformer Search with Low-Energy Latent Space

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Journal Title
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Volume Title
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
Date
2022-07-12
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Language
en
Pages
4574−4585
Series
Journal of Chemical Theory and Computation, Volume 18, issue 7
Abstract
Identifying low-energy conformers with quantum mechanical accuracy for molecules with many degrees of freedom is challenging. In this work, we use the molecular dihedral angles as features and explore the possibility of performing molecular conformer search in a latent space with a generative model named variational auto-encoder (VAE). We bias the VAE towards low-energy molecular configurations to generate more informative data. In this way, we can effectively build a reliable energy model for the low-energy potential energy surface. After the energy model has been built, we extract local-minimum conformations and refine them with structure optimization. We have tested and benchmarked our low-energy latent-space (LOLS) structure search method on organic molecules with 5-9 searching dimensions. Our results agree with previous studies.
Description
Funding Information: X.G., L.F. and X.C. acknowledge the financial support from the Academy of Finland (project numbers 308647, 314298, 335571). X.G, Y.X. and W.D. acknowledge the financial support from the Basic Science Center Project of NSFC (grant no. 51788104), the National Science Fund for Distinguished Young Scholars (grant no. 12025405), the National Natural Science Foundation of China (grant no. 11874035), and the Beijing Advanced Innovation Center for Future Chip (ICFC), M.T. and P.R. have received funding from the Academy of Finland via the Artificial Intelligence for Microscopic Structure Search (AIMSS) project no. 316601 and the Flagship programme: Finnish Center for Artificial Intelligence FCAI. X.G. and X.C. Generous computational resources were provided by CSC – IT Center for Science, Finland, and the Aalto Science-IT project. L.F. also acknowledges financial support from the Chinese Scholarship Council (grant no. [2017]3109). Publisher Copyright: © 2022 The Authors. Published by American Chemical Society.
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Citation
Guo , X , Fang , L , Xu , Y , Duan , W , Rinke , P , Todorović , M & Chen , X 2022 , ' Molecular Conformer Search with Low-Energy Latent Space ' , Journal of Chemical Theory and Computation , vol. 18 , no. 7 , pp. 4574−4585 . https://doi.org/10.1021/acs.jctc.2c00290