Molformer: Motif-based Transformer on 3D Heterogeneous Molecular Graphs. (arXiv:2110.01191v5 [q-bio.QM] UPDATED)

Procuring expressive molecular representations underpins AI-driven molecule
design and scientific discovery. The research to date mainly focuses on
atom-level homogeneous molecular graphs, ignoring the rich information in
subgraphs or motifs. However, it has been widely accepted that substructures
play a dominant role in the identification and determination of molecular
properties. To address such issues, we formulate heterogeneous molecular graphs
(HMGs), and introduce Molformer to exploit both molecular motifs and 3D
geometry. Specifically, we extract functional groups as motifs for small …

3d arxiv bio graphs transformer