Enhancing hERG Risk Assessment with Interpretable Classificatory and Regression Models-Reference-Cited by-同舟云学术

Enhancing hERG Risk Assessment with Interpretable Classificatory and Regression Models

Published:2024-05-23 Issue:6 Volume:37 Page:910-922
ISSN:0893-228X
Container-title:Chemical Research in Toxicology
language:en
Short-container-title:Chem. Res. Toxicol.

Author:

Sanches Igor H.¹²³^ORCID,Braga Rodolpho C.⁴^ORCID,Alves Vinicius M.⁵^ORCID,Andrade Carolina Horta¹²³^ORCID

Affiliation:

1. Laboratory for Molecular Modeling and Drug Design (LabMol), Faculty of Pharmacy, Universidade Federal de Goiás, Goiânia, GO 74690-900, Brazil

2. Center for Excellence in Artificial Intelligence (CEIA), Institute of Informatics, Universidade Federal de Goiás, Goiânia, GO 74690-900, Brazil

3. Center for the Research and Advancement in Fragments and Molecular Targets (CRAFT), School of Pharmaceutical Sciences at Ribeirao Preto, University of São Paulo, Ribeirão Preto, SP 05508-220, Brazil

4. InsilicAll Inc., São Paulo, SP 04571-010, Brazil

5. University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, United States

Funder

Funda??o de Amparo ? Pesquisa do Estado de Goi?s

Conselho Nacional de Desenvolvimento Cient?fico e Tecnol?gico

Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior

Publisher

American Chemical Society (ACS)

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.chemrestox.3c00400

Reference55 articles.

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2. Cryo-EM Structure of K+-Bound hERG Channel Complexed with the Blocker Astemizole

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4. Post-marketing withdrawal of 462 medicinal products because of adverse drug reactions: a systematic review of the world literature

5. Drug Withdrawal Due to Safety: A Review of the Data Supporting Withdrawal Decision