3D Conformational Generative Models for Biological Structures Using Graph Information-Embedded Relative Coordinates.

ABSTRACT: Developing molecular generative models for directly generating 3D conformation has recently become a hot research area. Here, an autoencoder based generative model was proposed for molecular conformation generation. A unique feature of our method is that the graph information embedded relative coordinate (GIE-RC), satisfying translation and rotation invariance, was proposed as a novel way for encoding molecular three-dimensional structure. Compared with commonly used Cartesian coordinate and internal coordinate, GIE-RC is less sensitive on errors when decoding latent variables to 3D coordinates. By using this method, a complex 3D generation task can be turned into a graph node feature generation problem. Examples were shown that the GIE-RC based autoencoder model can be used for both ligan

SUBMITTER: Xu M 

PROVIDER: S-EPMC9823299 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature