Auto-Encoding Molecular Conformations

• URL: http://arxiv.org/abs/2101.01618v1
• Date: Tue, 5 Jan 2021 16:09:10 GMT
• Title: Auto-Encoding Molecular Conformations
• Authors: Robin Winter, Frank No\'e, Djork-Arn\'e Clevert
• Abstract summary: We show that our proposed model converts the discrete spatial arrangements of atoms in a given molecular graph into a continuous fixed-sized latent representation. We also demonstrate how our model can be used to generate diverse sets of energetically favorable conformations for a given molecule.
• Score: 0.0
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: In this work we introduce an Autoencoder for molecular conformations. Our proposed model converts the discrete spatial arrangements of atoms in a given molecular graph (conformation) into and from a continuous fixed-sized latent representation. We demonstrate that in this latent representation, similar conformations cluster together while distinct conformations split apart. Moreover, by training a probabilistic model on a large dataset of molecular conformations, we demonstrate how our model can be used to generate diverse sets of energetically favorable conformations for a given molecule. Finally, we show that the continuous representation allows us to utilize optimization methods to find molecules that have conformations with favourable spatial properties.

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