AI-based identification of therapeutic agents targeting GPCRs: introducing ligand type classifiers and systems biology-Reference-Cited by-同舟云学术

AI-based identification of therapeutic agents targeting GPCRs: introducing ligand type classifiers and systems biology

Published:2023 Issue:32 Volume:14 Page:8651-8661
ISSN:2041-6520
Container-title:Chemical Science
language:en
Short-container-title:Chem. Sci.

Author:

Goßen Jonas¹²^ORCID,Ribeiro Rui Pedro¹,Bier Dirk³,Neumaier Bernd³⁴^ORCID,Carloni Paolo¹²⁵^ORCID,Giorgetti Alejandro¹⁶,Rossetti Giulia¹⁷⁸^ORCID

Affiliation:

1. Institute for Computational Biomedicine (INM-9/IAS-5) Forschungszentrum Jülich, Wilhelm-Johnen-Straße, 52428 Jülich, Germany

2. Faculty of Mathematics, Computer Science and Natural Sciences RWTH Aachen University, Aachen, Germany

3. Institute of Neuroscience and Medicine, Nuclear Chemistry (INM-5), Forschungszentrum Jülich GmbH, Wilhelm-Johnen-Straße, 52428 Jülich, Germany

4. Institute of Radiochemistry and Experimental Molecular Imaging, University of Cologne, Faculty of Medicine and University Hospital Cologne, Kerpener Straße 62, 50937 Cologne, Germany

5. JARA-Institut Molecular Neuroscience and Neuroimaging (INM-11) Forschungszentrum Jülich, Wilhelm-Johnen-Straße, 52428 Jülich, Germany

6. Department of Biotechnology University of Verona, Verona, Italy

7. Jülich Supercomputing Centre (JSC) Forschungszentrum Jülich, Jülich, Germany

8. Department of Neurology University Hospital Aachen (UKA), RWTH Aachen University, Aachen, Germany

Abstract

By merging structural macromolecular data with systems biology simulations and AI-based classifier of chemical space, we developed a framework to identify therapeutic agents against GPCRs with novel chemotypes other than the physiological ligands.

Publisher

Royal Society of Chemistry (RSC)

Subject

General Chemistry

Link

http://pubs.rsc.org/en/content/articlepdf/2023/SC/D3SC02352D

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