Structure-based drug design with geometric deep learning. (arXiv:2210.11250v1 [physics.chem-ph])

Structure-based drug design uses three-dimensional geometric information of
macromolecules, such as proteins or nucleic acids, to identify suitable
ligands. Geometric deep learning, an emerging concept of neural-network-based
machine learning, has been applied to macromolecular structures. This review
provides an overview of the recent applications of geometric deep learning in
bioorganic and medicinal chemistry, highlighting its potential for
structure-based drug discovery and design. Emphasis is placed on molecular
property prediction, ligand binding site and pose prediction, and
structure-based de novo molecular …

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