Molecular Conformation Generation via Shifting Scores

• URL: http://arxiv.org/abs/2309.09985v1
• Date: Tue, 12 Sep 2023 07:39:43 GMT
• Title: Molecular Conformation Generation via Shifting Scores
• Authors: Zihan Zhou, Ruiying Liu, Chaolong Ying, Ruimao Zhang and Tianshu Yu
• Abstract summary: We propose a novel molecular conformation generation approach driven by the observation that the disintegration of a molecule can be viewed as casting increasing force fields to its composing atoms. The corresponding generative modeling ensures a feasible inter-atomic distance geometry and exhibits time reversibility.
• Score: 21.986775283620883
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Molecular conformation generation, a critical aspect of computational chemistry, involves producing the three-dimensional conformer geometry for a given molecule. Generating molecular conformation via diffusion requires learning to reverse a noising process. Diffusion on inter-atomic distances instead of conformation preserves SE(3)-equivalence and shows superior performance compared to alternative techniques, whereas related generative modelings are predominantly based upon heuristical assumptions. In response to this, we propose a novel molecular conformation generation approach driven by the observation that the disintegration of a molecule can be viewed as casting increasing force fields to its composing atoms, such that the distribution of the change of inter-atomic distance shifts from Gaussian to Maxwell-Boltzmann distribution. The corresponding generative modeling ensures a feasible inter-atomic distance geometry and exhibits time reversibility. Experimental results on molecular datasets demonstrate the advantages of the proposed shifting distribution compared to the state-of-the-art.

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