Projects per year
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.
Original language | English |
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Pages (from-to) | 4574−4585 |
Journal | Journal of Chemical Theory and Computation |
Volume | 18 |
Issue number | 7 |
DOIs | |
Publication status | Published - 12 Jul 2022 |
MoE publication type | A1 Journal article-refereed |
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Dive into the research topics of 'Molecular Conformer Search with Low-Energy Latent Space'. Together they form a unique fingerprint.Projects
- 4 Finished
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Computational study of fluorescent silver clusters with implications for biosensing and bioimaging applications
Chen, X., Kang, J., Pršlja, P., Härkönen, V. & Fang, L.
01/09/2020 → 31/08/2022
Project: Academy of Finland: Other research funding
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Artificial Intelligence for Microscopic Structure Search
Rinke, P., Lehto, E., Geurts, A., Ghosh, K., Himanen, L., Li, J., Todorovic, M. & Homm, H.
01/01/2018 → 31/12/2021
Project: Academy of Finland: Other research funding
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Computational study of fluorescent silver clusters with implications for biosensing and bioimaging applications
01/09/2017 → 31/08/2022
Project: Academy of Finland: Other research funding
Equipment
Press/Media
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New machine-learning approach facilitates molecular conformer search in complex molecules
25/08/2022
2 items of Media coverage
Press/Media: Media appearance