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arXiv · 2502.12219

Towards Efficient Molecular Property Optimization with Graph Energy Based Models

Luca Miglior·Lorenzo Simone·Marco Podda·Davide Bacciu
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Abstract

Optimizing chemical properties is a challenging task due to the vastness and complexity of chemical space. Here, we present a generative energy-based architecture for implicit chemical property optimization, designed to efficiently generate molecules that satisfy target properties without explicit conditional generation. We use Graph Energy Based Models and a training approach that does not require property labels. We validated our approach on well-established chemical benchmarks, showing superior results to state-of-the-art methods and demonstrating robustness and efficiency towards de novo drug design.

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Luca Miglior, Lorenzo Simone, Marco Podda, Davide Bacciu. 2025-02-17. Towards Efficient Molecular Property Optimization with Graph Energy Based Models. https://doi.org/10.14428/esann%2F2025.es2025-120

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