VisMole: a molecular representation based on voxel for molecular property prediction

Qiang Tong; Jiahao Shen; Xiulei Liu

doi:10.1117/12.2667694

28 March 2023 VisMole: a molecular representation based on voxel for molecular property prediction

Qiang Tong, Jiahao Shen, Xiulei Liu

Proceedings Volume 12566, Fifth International Conference on Computer Information Science and Artificial Intelligence (CISAI 2022); 1256628 (2023) https://doi.org/10.1117/12.2667694
Event: Fifth International Conference on Computer Information Science and Artificial Intelligence (CISAI 2022), 2022, Chongqing, China

Abstract

To make computers understand the molecules, the first and important thing is to represent molecules in a proper way, which will affect the efficiency of chemistry tasks like property prediction and molecular design. In this work, we introduce a molecular representation for noncrystalline small molecules based on the theory of quantum physics. This representation captures the microscopic spatial structure of the molecule, which ensures it reflects more visual perception information about the molecule. We use Drug3DNet as our baseline and test the efficiency of our representation. By comparing with several other representations, we prove that our representation performs better on most of the properties.

Citation Download Citation

Qiang Tong, Jiahao Shen, and Xiulei Liu "VisMole: a molecular representation based on voxel for molecular property prediction", Proc. SPIE 12566, Fifth International Conference on Computer Information Science and Artificial Intelligence (CISAI 2022), 1256628 (28 March 2023); https://doi.org/10.1117/12.2667694

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