ArticleJournal of chemical theory and computation2022
Molecular Conformer Search with Low-Energy Latent Space.
Article in Journal of chemical theory and computation, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- AI-Driven Design Platforms of Next-Generation Antibody Therapeutics.Topics in current chemistry (Cham) · 2026Review
- Active Learning-Assisted Exploration of [POAdvanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Targeted discovery of polyketides with antioxidant activity through integrated omics and cocultivation strategies.Applied and environmental microbiology · 2024Article
- Exploring the Conformers of an Organic Molecule on a Metal Cluster with Bayesian Optimization.Journal of chemical information and modeling · 2023Article
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Authors and funding
7 authors.
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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.
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