Generating 3D molecules conditional on receptor binding sites with deep generative models-Reference-Cited by-同舟云学术

Generating 3D molecules conditional on receptor binding sites with deep generative models

Published:2022 Issue:9 Volume:13 Page:2701-2713
ISSN:2041-6520
Container-title:Chemical Science
language:en
Short-container-title:Chem. Sci.

Author:

Ragoza Matthew¹^ORCID,Masuda Tomohide²,Koes David Ryan²

Affiliation:

1. Intelligent Systems Program, University of Pittsburgh, Pittsburgh, PA, 15213, USA

2. Department of Computational and Systems Biology, University of Pittsburgh, Pittsburgh, PA, 15213, USA

Abstract

We generate 3D molecules conditioned on receptor binding sites by training a deep generative model on protein–ligand complexes. Our model uses the conditional receptor information to make chemically relevant changes to the generated molecules.

Funder

National Institute of General Medical Sciences

National Science Foundation

Center for Research Computing, University of Pittsburgh

Publisher

Royal Society of Chemistry (RSC)

Subject

General Chemistry

Link

http://pubs.rsc.org/en/content/articlepdf/2022/SC/D1SC05976A

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