Towards equilibrium molecular conformation generation with GFlowNets
Alexandra Volokhova Michał Koziarski Alex Hernández-García Cheng-Hao Liu Santiago Miret Pablo Lemos Luca Thiede Zichao Yan Alán Aspuru-Guzik Yoshua Bengio
Sampling diverse, thermodynamically feasible molecular conformations plays a
crucial role in predicting properties of a molecule. In this paper we propose
to use GFlowNet for sampling conformations of small molecules from the
Boltzmann distribution, as determined by the molecule's energy. The proposed
approach can be used in combination with energy estimation methods of different
fidelity and discovers a diverse set of low-energy conformations for highly
flexible drug-like molecules. We demonstrate that GFlowNet can reproduce
molecular potential energy surfaces by sampling proportionally to the Boltzmann
distribution.