Molecular conformation generation aims to generate three-dimensional coordinates of all
\nthe atoms in a molecule and is an important task in bioinformatics and pharmacology. Previous methods usually first predict the interatomic distances, the gradients of interatomic
\ndistances or the local structures (e.g., torsion angles) of a molecule, and then reconstruct its
\n3D conformation. How to directly generate the conformation without the above intermediate values is not fully explored. In this work, we propose a method that directly predicts
\nthe coordinates of atoms: (1) the loss function is invariant to roto-translation of coordinates
\nand permutation of symmetric atoms; (2) the newly proposed model adaptively aggregates
\nthe bond and atom information and iteratively refines the coordinates of the generated
\nconformation. Our method achieves the best results on GEOM-QM9 and GEOM-Drugs
\ndatasets. Further analysis shows that our generated conformations have closer properties
\n(e.g., HOMO-LUMO gap) with the groundtruth conformations. In addition, our method
\nimproves molecular docking by providing better initial conformations. All the results demonstrate the effectiveness of our method and the great potential of the direct approach. The
\ncode is released at https:\/\/github.com\/DirectMolecularConfGen\/DMCG.<\/p>\n","protected":false},"excerpt":{"rendered":"
Molecular conformation generation aims to generate three-dimensional coordinates of all the atoms in a molecule and is an important task in bioinformatics and pharmacology. Previous methods usually first predict the interatomic distances, the gradients of interatomic distances or the local structures (e.g., torsion angles) of a molecule, and then reconstruct its 3D conformation. How to 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