利用 GFlowNets 生成平衡分子构象

IF 6.2 Q1 CHEMISTRY, MULTIDISCIPLINARY
Alexandra Volokhova, Michał Koziarski, Alex Hernández-García, Cheng-Hao Liu, Santiago Miret, Pablo Lemos, Luca Thiede, Zichao Yan, Alán Aspuru-Guzik and Yoshua Bengio
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引用次数: 0

摘要

对各种热力学上可行的分子构象进行采样在预测分子性质方面起着至关重要的作用。在本文中,我们建议使用 GFlowNets 从波尔兹曼分布(由分子能量决定)中对小分子构象进行采样。所提出的方法可与不同保真度的能量估算方法结合使用,并为类药物分子发现多种低能构象。我们证明了 GFlowNets 可以通过按波尔兹曼分布比例采样来再现分子势能面。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Towards equilibrium molecular conformation generation with GFlowNets†

Towards equilibrium molecular conformation generation with GFlowNets†

Towards equilibrium molecular conformation generation with GFlowNets†

Sampling diverse, thermodynamically feasible molecular conformations plays a crucial role in predicting properties of a molecule. In this paper we propose to use GFlowNets 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 drug-like molecules. We demonstrate that GFlowNets can reproduce molecular potential energy surfaces by sampling proportionally to the Boltzmann distribution.

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