MCNN_MC: Computational Prediction of Mitochondrial Carriers and Investigation of Bongkrekic Acid Toxicity Using Protein Language Models and Convolutional Neural Networks-Reference-Cited by-同舟云学术

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MCNN_MC: Computational Prediction of Mitochondrial Carriers and Investigation of Bongkrekic Acid Toxicity Using Protein Language Models and Convolutional Neural Networks

Published:2024-08-12 Issue: Volume: Page:
ISSN:1549-9596
Container-title:Journal of Chemical Information and Modeling
language:en
Short-container-title:J. Chem. Inf. Model.

Author:

Malik Muhammad Shahid¹²^ORCID,Chang Yan-Yun¹,Liu Yu-Chen¹,Le Van The¹,Ou Yu-Yen¹³

Affiliation:

1. Department of Computer Science and Engineering, Yuan Ze University, Chung-Li 32003, Taiwan

2. Department of Computer Sciences, Karakoram International University, Gilgit-Baltistan 15100, Pakistan

3. Graduate Program in Biomedical Informatics, Yuan Ze University, Chung-Li 32003, Taiwan

Funder

National Science and Technology Council

Publisher

American Chemical Society (ACS)

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.jcim.4c00961

Reference33 articles.

1. Bongkrekic Acid Analogue, Lacking One of the Carboxylic Groups of its Parent Compound, Shows Moderate but pH-insensitive Inhibitory Effects on the Mitochondrial ADP/ATP Carrier

2. ANT1 Activation and Inhibition Patterns Support the Fatty Acid Cycling Mechanism for Proton Transport

3. Structural Approaches of the Mitochondrial Carrier Family

4. The ADP and ATP transport in mitochondria and its carrier

5. Molecular Design, Synthesis, and Evaluation of Novel Potent Apoptosis Inhibitors Inspired from Bongkrekic Acid

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