Using a Graph Convolutional Neural Network Model to Identify Bile Salt Export Pump Inhibitors-Reference-Cited by-同舟云学术

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Using a Graph Convolutional Neural Network Model to Identify Bile Salt Export Pump Inhibitors

Published:2023-06-06 Issue:24 Volume:8 Page:21853-21861
ISSN:2470-1343
Container-title:ACS Omega
language:en
Short-container-title:ACS Omega

Author:

AbdulHameed Mohamed Diwan M.¹²^ORCID,Liu Ruifeng¹²^ORCID,Wallqvist Anders¹

Affiliation:

1. Department of Defense Biotechnology High Performance Computing Software Applications Institute, Telemedicine and Advanced Technology Research Center, U.S. Army Medical Research and Development Command, Fort Detrick 21702, Maryland, United States

2. The Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., Bethesda 20817, Maryland, United States

Funder

Medical Research and Materiel Command

Defense Threat Reduction Agency

Publisher

American Chemical Society (ACS)

Subject

General Chemical Engineering,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acsomega.3c01583

Reference56 articles.

1. The Bile Salt Export Pump: Molecular Structure, Study Models and Small-Molecule Drugs for the Treatment of Inherited BSEP Deficiencies

2. Targeting the Four Pillars of Enterohepatic Bile Salt Cycling; Lessons From Genetics and Pharmacology

3. Structural basis of sodium-dependent bile salt uptake into the liver

4. Can Bile Salt Export Pump Inhibition Testing in Drug Discovery and Development Reduce Liver Injury Risk? An International Transporter Consortium Perspective

5. Development of an Adverse Outcome Pathway From Drug-Mediated Bile Salt Export Pump Inhibition to Cholestatic Liver Injury

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