BEGAN: Boltzmann-Reweighted Data Augmentation for Enhanced GAN-Based Molecule Design in Insect Pheromone Receptors DOI

Jialei Dai,

Yutong Zhang, C. H. Shi

et al.

The Journal of Physical Chemistry B, Journal Year: 2024, Volume and Issue: 128(47), P. 11666 - 11675

Published: Nov. 14, 2024

Identifying small molecules that bind strongly to target proteins in rational molecular design is crucial. Machine learning techniques, such as generative adversarial networks (GAN), are now essential tools for generating molecules. In this study, we present an enhanced method molecule generation using objective-reinforced GANs. Specifically, introduce BEGAN (Boltzmann-enhanced GAN), a novel approach adjusts occurrence frequencies during training based on the Boltzmann distribution exp(-Δ

Language: Английский

BEGAN: Boltzmann-Reweighted Data Augmentation for Enhanced GAN-Based Molecule Design in Insect Pheromone Receptors DOI

Jialei Dai,

Yutong Zhang, C. H. Shi

et al.

The Journal of Physical Chemistry B, Journal Year: 2024, Volume and Issue: 128(47), P. 11666 - 11675

Published: Nov. 14, 2024

Identifying small molecules that bind strongly to target proteins in rational molecular design is crucial. Machine learning techniques, such as generative adversarial networks (GAN), are now essential tools for generating molecules. In this study, we present an enhanced method molecule generation using objective-reinforced GANs. Specifically, introduce BEGAN (Boltzmann-enhanced GAN), a novel approach adjusts occurrence frequencies during training based on the Boltzmann distribution exp(-Δ

Language: Английский

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